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The rapid global expansion of the taxi industry has brought significant safety concerns regarding taxi trips, particularly related to the frequency of taxi crashes and their potential impact on road safety. To address this issue, the present study focuses on investigating the impact of time pressure on the driving speed of male taxi drivers through the use of driving simulator experiment. The aim of this study was to understand how time pressure influences driving speed at speed violation camera locations. A total of 56 taxi drivers participated in the study, with five drivers excluded due to simulation sickness. The findings revealed a significance of time pressure as a critical factor influencing driving speed among taxi drivers. Specifically, the study results showed that under time pressure situation, taxi drivers displayed significantly higher speeds, particularly in proximity to speed camera locations. To improve road safety, policymakers should focus on addressing time pressure concerns among taxi drivers. Implementing strategies to alleviate time constraints and optimize trip schedules can lead to safer driving practices, benefiting both drivers and passengers. [ABSTRACT FROM AUTHOR]

• Driver compliance in car-following tasks was measured and analysed. • V2V information reduces driver response time to lead car's speed change. • Multimodal information presentation improves driver compliance. • Driver compliance to lead car deceleration was higher than that for acceleration. The success of vehicle-to-vehicle (V2V) communication in improving the driving safety and efficiency primarily depends on driver compliance with the transmitted information. In this study, driver compliance with V2V information in simulated car-following tasks was measured and analyzed under different information display settings, such as baseline without information, visual information only, and multimodal information. Car-following data were collected from 30 participants in a driving simulation environment. The results revealed that V2V information could significantly reduce the driver's response time to the lead car's speed change, resulting in an increase in the minimum time-to-collision when the lead car slowed down. Driver compliance was significantly higher under multimodal information settings than when using visual information alone. Moreover, driver compliance was higher when facing a decelerating lead car than when facing an accelerating lead car. No significant differences in driver compliance between the deceleration levels was observed; however, differences existed among different car-following preference groups. The findings of this study can be applied to V2V car-following models to improve the simulation accuracy for connected-vehicle traffic. Additionally, multimodal information presentation can provide a reference for V2V communication design. [ABSTRACT FROM AUTHOR]

• The probability of traffic conflicts was studied for the lane-shifting sections during the highway reconstruction and expansion activities. To accurately identify the traffic conflict in this complex road section, this study adopted the indicator pair of TTC and TDTC instead of TTC alone. • The correlations between the road and traffic factors and the vehicle collision risk were evaluated via machine learning. The influencing factors were found to be the curve radius, the standard deviation of single-vehicle speed, the cumulative angle in unit length, the vehicle type, the average speed, and the standard deviation of traffic flow speed in decreasing order of their influence on the probability of traffic conflicts. • Based on the conclusions, pertinent measures can be taken to reduce the collision risk of vehicles in the lane-shifting sections. Specific proposals are: diversion of large vehicles; restriction of the vehicle speed in the lane-shifting sections; increase of the curved section radius in line with the specifications; decrease of the cumulative turning angle per unit length i.e. the average turning curvature per unit length. Introduction: There are designated sections for lane-shifting in several highway reconstruction and expansion zones. Similar to the bottleneck sections of highways, these sections are characterized by poor pavement surface conditions, disorderly traffic flow, and high safety risk. This study examined the continuous track data of 1,297 vehicles collected using an area tracking radar. Method: The data from the lane shifting sections were analyzed in contrast with the regular section data. Further, the single-vehicle attributes, traffic flow factors, and the respective road characteristics in the lane-shifting sections were also taken into account. In addition, the Bayesian network model was established to analyze the uncertain interaction between the various other influencing factors. The K-Fold cross validation method was used to evaluate the model. Results: The results showed that the model has a high reliability. The analysis of the model revealed that the significant influencing factors in decreasing order of their influence on the traffic conflict are: the curve radius, cumulative turning angle per unit length, standard deviation of the single-vehicle speed, vehicle type, average speed, and the standard deviation of the traffic flow speed. The probability of traffic conflicts is estimated to be 44.05% when large vehicles pass through the lane- shifting section while it is 30.85% for small vehicles. The probabilities of traffic conflict are 19.95%, 34.88%, and 54.79% when the turning angles per unit length are 0.20 °/m, 0.37 °/m, and 0.63 °/m, respectively. Practical Applications: The results support the view that the highway authorities help reduce traffic risks on lane change sections by diverting large vehicles, implementing speed limits on road sections, and increasing the turning angle per unit length of vehicles. [ABSTRACT FROM AUTHOR]

• Variable message signs displaying anti-speeding messages influenced drivers to reduce speed. • Speed reductions were partially sustained in the week after signage removal. • Different speed change effects were found for school hours, weekdays, and weekend days. • All three anti-speeding messages demonstrated effectiveness. • The three messages performed differentially in daytime and night-time driving. Determine whether anti-speeding messages displayed on roadside variable message signage (VMS) influence drivers' speed choice selections. Speed detection tubes were installed across a single carriageway 60 km/h limit road section at positions prior to, immediately after, and at a longer distance from VMS display of anti-speeding messages during study Week2. Bi-directional vehicle speed data were collected continuously during the week prior to VMS installation (Week1), throughout the week that the anti-speeding messages were displayed (Week2), and a post-display week (Week3). Of six separately measured locations, Week2 southbound mean speeds (facing signage) and percent of drivers/riders exceeding the signed speed limit were consistently below those recorded during Week1 for all time periods. Aggregated Week3 (post-VMS) southbound data for all time periods, showed consistent patterns for mean speed and percent of drivers exceeding the signed speed limit, being higher than in Week2 (VMS displayed) but lower than during Week1 (pre-VMS). Compared with Week1, messages influenced aggregate driver speed selection during Week2, with a residual positive effect (slower speeds) in Week3. While all three messages had positive effects, differences occurred in relative effectiveness between daytime (school and non-school hours) and night-time periods. Separately disaggregated data revealed differential effects for the three messages. Findings demonstrated the value of implementing theoretically informed message content and provided evidence for the impact that roadside road safety messaging can have on driver speed selection. [ABSTRACT FROM AUTHOR]

• Repeated measures of the overtaking maneuver on a two-lane highway within varied traffic environments using driving simulation. • Revealing of the spatial characteristics of micro-decisions (MDs) in overtaking trajectories K-means clustering. • Comprehensively evaluating the overtaking performances focusing on safety, comfort, and efficiency via Data Envelopment Analysis (DEA). • Validating the mediating role of MDs between external factors and overtaking performances and further developing the optimized overtaking trajectory strategies. An unreasonable overtaking attempt on two-lane highways could cause drivers to suffer in terms of driving safety, comfort, and efficiency. Several external factors related to the traffic environment (e.g., speed and car type of surrounding vehicles), were found to be the significant factors in drivers' overtaking performance in the previous studies. However, the microscopic decision-making (e.g., the moments of the occupation of the opposite lane) mechanisms during overtaking, by means of which drivers react to changes in the external traffic environment and adjust their overtaking trajectories, are still need to be explored. Hence, this study had three goals: (i) To explore the spatial characteristics of micro-decisions (MDs) (such as the start and end point) in overtaking trajectories; (ii) To measure three types of performance indicators (i.e., safety, comfort, and efficiency) for the execution of overtaking maneuvers; (iii) To quantitatively explain the microscopic decision-making mechanism in overtaking. Data for overtaking trajectories were collected from driving a simulation experiment where 52 Chinese student drivers completed a series of overtaking maneuvers on a typical two-lane highway under different traffic conditions. Two analyses were conducted: firstly, the distributions of the relative distance between the ego and surrounding vehicles at four key points (i.e., the start, entry, back, and end) in the overtaking trajectory were investigated and clustered to uncover the spatial characteristics of the MDs. Secondly, the safety, comfort, and efficiency of the overtaking were measured by the aggregations of multi-targets collision risks, triaxial acceleration variances, and spatial consumptions respectively based on the Data Envelopment Analysis (DEA), which were further applied in a two-stage SEM model to reveal the quantitative interrelationships among the external factors, microscope decisions and performances in overtaking. We confirmed that the MDs could be considered as the mediating variables between the external factors and overtaking performances. In the presence of the more hazardous traffic environment (e.g., faster traffic flow and impeded by a truck), the safety, comfort and efficiency of overtaking would be deteriorated inevitably. But drivers would execute the overtaking under the longer passing sight distance, migrate their trajectories forward, and shorten the spatial duration to significantly improve the overtaking performances. Based on this mechanism, a overtaking trajectory optimization strategy for the advanced or automatic driving system, was confirmed and concluded that 1) the passing gap should be firstly planned according to the sight distance acceptance of different drivers, which directly determine the upper limit of the safety performance in the overtaking; 2) the trajectory forward migration and shortening the whole duration in overtaking could be effective to enhance the overtaking performances of the overtaking on the two-lane highway; 3) the guidance of the stable control of the steering wheel and gas/brake pedals is essential in the overtaking. [ABSTRACT FROM AUTHOR]

• Explores the empirical evidence for existence of "social effect" in driving behavior. • Focuses on the imitating behavior of drivers who were passed by the fast-moving vehicles. • Uses naturalistic driving data and rigorous modeling to explore the social effect. • Finds that in 16% of passing events, subject vehicle drivers mimicked passing vehicles by accelerating. Models for describing the microscopic driving behavior rarely consider the "social effects" on drivers' driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers' driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers' instantaneous behavior and shift the individuals' driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver's acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers' social interactions can change traffic flow and implications of the study results are discussed. [ABSTRACT FROM AUTHOR]

• EVA-PZT-PANI composite based TENG, was fabricated. • A voltage and current of 17.8 V, 190nA output was achieved. • TENG help to power capacitors and harnesses human motion. • Demonstration of self-powered traffic counter, advancing intelligent transportation. This work aims to create energy-harvesting composites using poly(ethylene-co-vinyl acetate) EVA, lead zirconate titanate (PZT) and polyaniline (PANI) composites. The novelty lies in the fabrication of a triboelectric nanogenerator (TENG) using EVA-PZT-PANI composites. These composites combine the flexibility of EVA polymer with the electricity-generating power of PZT ceramic and the conductivity of PANI. Systematic investigation of the structural, electrical, and microstructural properties of these composites is carried out to optimize their energy-harvesting performance. Among various compositions, the EVP3 device demonstrates exceptional output, generating a peak voltage of 17.8 V and a current of 190 nA at 2 Hz and 5 N applied force. The TENG demonstrates its versatility in harvesting energy from various sources by powering capacitors and collecting energy from human motions. Moreover, we show the potential application of the TENG for real-time traffic monitoring. By embedding the TENG into roads, we can measure car speeds and serve as a traffic management counter, opening up new possibilities for self-powered intelligent transportation systems. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the effect of posted speed limit change on travel speeds. To do this, we use the National Performance Management Research Data Set (NPMRDS), which is a unique and rich dataset provided via the Federal Highway Administration (FHWA). Particularly, we focus on the impact of increased posted speed limit, implemented during June 2015, on interstate highways in Wisconsin including urban and rural areas between 2014 and 2016 by employing a quasi-experimental model with a panel dataset. Our findings clearly demonstrate that the posted speed limit change from 65 to 70 increases travel speed by 1.7 mph after controlling for location and time specific fixed-effects. Specifically, the posted speed limit change on Wisconsin interstate highways increases average travel speed of passenger and freight vehicles by 1.87 and 1.16 mph, respectively. Findings also show that speed variations have increased after the speed limit change, and higher variations do not occur in freight travel speeds, but in passenger vehicle travel speeds. These variations differently exist between urban and rural areas. We suggest that transportation agencies should consider these variations by vehicle types and places when they increase posted speed limit. • Explored effects of the posted speed limit change on the speed and speed variation. • Employed a quasi-experimental model with a panel dataset from NPMRDS. • The PSL change increases average travel speed by 1.7mph. • Speed variations has increased after the PSL change. [ABSTRACT FROM AUTHOR]

• Heterogeneity in means and variances is explored. • Temporal stability of injury severity determinants is examined. • Head-on collisions are pronounced at RTU horizontal curves. • Elderly drivers are prone to severe injuries in horizontal crashes. • Presence of curve signing can reduce severe injuries. Introduction: Safety of horizontal curves on rural two-lane, two-way undivided roadways is not fully explored. This study investigates factors that impact injury severity of such crashes. Method: To achieve the aim of this paper, issues associated with police-reported crash data such as unobserved heterogeneity and temporal stability need to be accounted for. Hence, a mixed logit model was estimated, while heterogeneity in means and variances is investigated by considering four injury severity outcomes for drivers: severe injury, moderate injury, possible injury, and no injury. Crash data for the period between 2011 and 2016 for crashes that occurred in the state of Oregon was analyzed. Temporal stability in factors determining the injury severity was investigated by identifying three time periods through splitting crash data into 2011–2012, 2013–2014, and 2015–2016. Results: Despite some factors affecting injuries in all specified time periods, the values of the marginal effects showed relative differences. The estimation results revealed that some factors increased the risk of being involved in severe injury crashes, including head-on collisions, drunk drivers, failure to negotiate curves, older drivers, and exceeding the speed limits. Conclusions: The hypothesis that attributes of injury severity are temporally stable is rejected. For example, young drivers (30 years old and younger) and middle-aged drivers were found to be temporally instable over time. Practical applications: The findings could help transportation authorities and safety professionals to enhance the safety of horizontal curves through appropriate and effective countermeasures. [ABSTRACT FROM AUTHOR]

Removing bus stops is often a prerequisite for introducing faster, more reliable, and more frequent rail or coach services in rural areas. Despite the potentially higher quality of service through trains or coaches, however, the bus-stop removals often become stumbling blocks. It is sometimes feared that the alterations to the public transport network will pose a threat to the possibilities of living in rural areas outside villages. In this study, we investigate how travel by public transport is affected in areas where bus services are substantially reduced in connection with the introduction of rail services with fewer stops. Through an analysis of access trips from rural areas surrounding the train stations, we are able to study the development of public transport patronage in these areas in comparison with a control group with retained rural bus services. A total of 28 villages with surrounding rural areas in southern Sweden are included in the study. Our results reveal a significantly larger patronage increase around new train stations compared to areas where regional bus services are kept, and importantly, the patronage increase does not only occur in the immediate surroundings of the stations. Outside the villages, in the rural areas where public transport services have been cut, the increase is of equal magnitude. Hence, our results oppose the idea of distortion between the villages and their surrounding rural areas, at least in terms of net effect on public transport usage. • A study into effects of longer stop distances in rural areas. • Large increase of patronage around new stations compared to former bus services. • Longer stop distances are compensated by more bicycle and car access trips. • No signs of distortion between the villages and their surrounding rural areas. [ABSTRACT FROM AUTHOR]

• Understanding power structures is critical for sustainable future planning. • Engaging strategic partners facilitates a sustainable adaptation pathways process. • Context-specific nature of adaptation pathways makes it difficult to replicate them. • Sustainable adaptation pathways processes require time to materialize. Adaptation Pathways have emerged as promising approaches for exploring sequences of actions to address challenges in uncertain conditions. This study elaborates on how pathway approaches operate in practice by applying a learning framework that identifies guiding propositions for successful adaptation pathways. The framework is used to analyze a transformative scenario planning case study from rural Mali. Findings confirm that adaptation pathways are highly context-specific, grounded in local institutions. The study also emphasizes that the adaptation pathways process requires a sufficient timeframe to allow for cross-level interactions and institutional changes to unfold as needed. The case demonstrates that the framework can be a useful tool for reflexive learning and identifying gaps in a structured way during pathway development. However, it needs to be adjusted to specific contexts to better capture the influence of and implications for power relations and social inequality in future adaptation plans. [ABSTRACT FROM AUTHOR]

Rural regions in industrialised countries are facing problems in public transport (PT) provision against the backdrop of demographic change, urbanisation and austerity policies. However, innovative mobility concepts evolve under technological developments. Demand responsive transport (DRT) has been identified in research to meet the challenges and efficiently improve mobility through the concept of ride-pooling. Still, most of these DRT services are being investigated in urban settings with high mobility demand and population density. Research on low-demand regions, such as the Oberharz in Germany, is rarely considered. Moreover, the applied DRT services come with several restrictions regarding stop locations, customer target groups or spatial restrictions. Therefore, this paper fills this gap through spatial and temporal analysis of a real-life, fully flexible and true door-to-door DRT experiment. Over a 6-months period around 38,000 trips took place in the Oberharz. The analysis of these trips shows that an unrestricted DRT service between three main centres (Goslar, Clausthal-Zellerfeld and Osterode) results in main travel axes between these cities while the more remote areas forfeit mobility to these centres of public service provision. Consequently, a feeder-trunk system should be favoured for future DRT services in low-demand areas to sustainably improve mobility in remote regions. The complementary extension of the existing PT through such a DRT service should then meet mobility needs of rural areas to redeem car dependency and improve mobility for all population groups. • Under a fully flexible, door-to-door DRT service in a rural area travel axes form between larger cities in the area. • A feeder-trunk concept or a demand responsive connector may increase viability of DRT services even in rural areas. • Temporal and spatial booking constraints are suitable to improve overall DRT system performance. • Rural population accepts innovative DRT service and prefers using the smartphone app for bookings. [ABSTRACT FROM AUTHOR]

• Using a multi-user driving simulator to conduct experiments. • Exploring the patterns of FRECs occurrence under foggy conditions and speed limits. • Safety margin in fleet were reduced in heavy fog led to high frequency of FRECs. • Lower speed limits satisfy drivers' visual and psychological requirements in fog. • Vehicles at the front positions of a fleet were more likely to have collisions. Vehicle fleet rear-end collisions (FRECs) are an extremely fatal type of traffic collisions on freeway and they usually occur in foggy weather. This study aimed to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits on freeway. A multi-user driving simulator system was used to conduct the experiment and the driving behavior data were collected from eight participants. The experimental results showed that as the fog density increased, the length of vehicle fleet decreased significantly, and drivers tended to keep a more stable car-following distance. The fog weather and short vehicle gap prompted drivers to react faster and brake harder in respond to the leading vehicle's brake. In spite of the compensational behaviors, more FRECs were observed under heavy fog condition. Lowering speed limit can significantly reduce the FRECs under foggy conditions. As the speed limits reduced, drivers' brake response time and speed variance significantly reduced. The study also found that drivers' brake response time was negatively correlated with their positions in the fleet. Drivers in the front positions of the fleet had a longer response time than drivers in the back positions and thus were more likely to encounter collisions. The study generated a better understanding of drivers' behavioral pattern in a vehicle fleet and the patterns of vehicle fleet rear-end collisions occurrence. The findings also shed lights on the design of driver assistance system for complex driving situations such as freeway driving under adverse weather. [ABSTRACT FROM AUTHOR]

• An investigation of speeding behaviour of drivers in their work and personal vehicles. • Underpinned on the TPB and objective data collection through on-road driving. • TPB variables were compared between work and private driving settings. • The strongest determinant of speed limit compliance was drivers Attitudes. • Higher Intention to comply with speed limits in a work than private vehicle. • High intenders drove for longer distance without exceeding the speed limits. Existing evidence suggests that drivers, particularly those who work in companies with strong road safety cultures exhibit different sets of speeding attitudes and behaviours in work and private driving. Using Ajzen and Fishbein's (1980) Theory of Planned behaviour (TPB) and on-road driving experiments, this study examined the self-reported and objective behaviour of driving within posted speed limits for a sample of fleet drivers. The findings show that the TPB explained up to 24% of the variance in intention to comply with speed limits. Drivers' attitude emerged as the most significant predictor and strongest correlate with intentions to comply with the speed limit in both work and private vehicle. Further analysis revealed participants had a higher intention to comply with speed limits in their work than private vehicle. Also, investigation of the relationship between TPB variables and observed speeding behaviour suggests that participants with higher intention to comply with the speed limit or high perceived behavioural control (PBC), exceeded the speed limit less often than those with lower intention to comply with the speed limit or low PBC. The findings have important theoretical and applied implications for development of better speed limit compliance interventions to improve driving behaviour, and road safety in general. [ABSTRACT FROM AUTHOR]

• Speed externalities are usually quoted to justify highway speed limits but they could already be internalized if a pre-existing policy were in place that is related to speed. • We develop an economic equilibrium model of highway speed choice accounting for speed externalities, a speed related behavioral anomaly, and a pre-existing fuel tax. • In Germany where fuel taxes are relatively high, speed externalities are largely internalized and the externality rationale in favor of speed regulation does not apply to the majority of drivers. • Nevertheless, a moderate speed limit on German highways of 130 km/h would probably not compromise economic efficiency, at least as long as the share of diesel cars is significant. • Lack of rationality always justifies speed regulation unless appropriate "nudges" are available. Speed externalities – the impacts that a driver's speed choice imposes on others – are usually quoted to justify highway speed regulation in the form of maximum speed limits. However, speed externalities could already be internalized if a pre-existing policy were in place that is related to speed, questioning the traditional rationale supporting speed limits. Given the relationship between speed and fuel consumption and the omnipresence of fuel taxes around the world, it comes as a surprise that pre-existing taxes on motor fuel are completely missing in the debate on the general appropriateness of speed regulation. In this paper we develop an economic equilibrium model of highway speed choice accounting for (i) a market failure – speeding externalities capturing the fact that drivers do not internalize the adverse consequences of speeding on other highway users and the society as a whole; (ii) a famous speed related behavioral anomaly – causing adverse effects drivers impose on themselves by falsely predicting the time saving potential of speed; (iii) a pre-existing fuel tax – closing the wedge between the privately and socially optimal speed. The latter creates a 'government feedback effect' reflecting the positive feedback effect of speed on fuel tax revenue and so the broader beneficial fiscal impacts of speed choice ignored by drivers. Numerical computations for Germany indicate a dominant 'government feedback effect' ((iii) outweighs (i)) for mean speeds up to around 120 km/h presuming fully variable travel time budgets and beyond that speed level when drivers put (some of the) travel time savings from speeding into more highway traveling. This implies that speed externalities are largely internalized and that the externality rationale in favor of speed regulation does not apply to the majority of drivers. Nevertheless, a moderate speed limit on German highways of 130 km/h would probably not compromise economic efficiency, at least as long as the share of diesel cars is significant. Generally, when drivers are subject to lack of rationality leading to excess speeding, (iii) is not able to outweigh (i). Then, speed limits remain highly warranted provided that appropriate "nudging" is not available. The numerical finding is likely to hold for a large number of European countries too but probably not for North American countries where fuel taxes are considerably lower. [ABSTRACT FROM AUTHOR]

The estimation of the free flow speed (FFS) distribution is important for capacity analysis, determination of the level-of-service, and setting speed limits. Subjective time headway thresholds have been commonly used to identify vehicles travelling under free flow speed conditions i.e., vehicles whose speeds are not influenced by the vehicle in front. Since, the headway a driver operates under the free flow state is subjective and varies from driver to driver, such approaches can introduce biases in the FFS estimation. Therefore, in this paper a parametric probabilistic latent approach is proposed based on discrete choice utility theory to estimate the FFS distribution on urban roads and simultaneously the probability that drivers perceive their state as constrained by the vehicle in front. This methodology is used to estimate the impacts of road characteristics and Posted Speed Limit (PSL) changes on the FFS distribution using an extensive dataset of speed observations from urban roads with varying characteristics. The results show that the simultaneous estimation of the free flow speed distribution and the state the driver is in (e.g., free or constrained) is feasible. The analysis indicates that the FFS is influenced by several road characteristics such as land use, on-street parking and the presence of sidewalks. The PSL change impacts not only the distribution of the free flow vehicles but also the speed distribution of the constrained vehicles. The constrained probabilities vary depending on the PSL change with higher probabilities for lower speed limits. [ABSTRACT FROM AUTHOR]

Conventional public transportation (CPT) services in rural areas are among others confronted with the accessibility problem and low traveler quantities. Demand responsive transportation (DRT) is an emerging mainstream concept, which aims to offer flexible mobility services to customers and also to solve the aforementioned problems of CPT providers. Studies and simulations about the comparison of CPT and DRT mostly focus on urban areas. Therefore, this paper is a case study of CPT vs. DRT services in the rural town of Colditz: A stop-based and a door-to-door DRT service is analyzed along with a CPT bus line. [ABSTRACT FROM AUTHOR]

Long queues at signals cause fuel-consuming stop-and-go traffic. In this work we use a complete microscopic spatiotemporal measurement of congested city traffic at a signal to i) calibrate a both longitudinal and latitudinal driving model and then to ii) examine how changes in single vehicle's driving behaviour could improve the situation. The model calibration is realized using a genetic algorithm. In this way, a realistic heterogeneous traffic scenario that has similar properties as empirical traffic could be simulated. We then show that already changing the behaviour of a single vehicle per traffic light cycle can significantly reduce the number of vehicles waiting in queues. [ABSTRACT FROM AUTHOR]

• A novel microscopic modelling framework for area based (non-lane based) heterogeneous traffic flow. • MNL model for the area selection of the vehicle movement. • Modified IDM model for the movement of the vehicle. • Model is throughly tested and applied on real trajectory data from India. The area-based (i.e., non-lane based) heterogeneous traffic (as in developing countries) has significant differences from the lane-based homogeneous traffic (as in developed countries). In area-based traffic, drivers generally ignore the lane markings and perceive the entire road space while progressing longitudinally. The traditional car-following and lane changing models are not directly applicable to model such driving behaviour. This research aims to microscopically model the dynamics of the subject vehicle in area-based traffic flow. The modelling is conducted in two steps: area selection , and vehicle movement. In step-1, a multinomial logit (MNL) model is considered for selecting the area-based movement direction of the subject vehicle. The choice space of the subject vehicle is divided into numbers of realistic radial cones considering the possible moving directions of the subject vehicle in the next simulation time step. These radial cones form the alternatives for the decision of the subject vehicle. The attributes of the alternatives are defined in terms of angular deviation from the direction of the flow, spacing and relative speed. This model is calibrated and validated for both cars and motorcycles using real trajectory data, and the results demonstrate the good performance of the model. In step-2, a modified intelligent driving model (MIDM) is proposed to simulate the next position of the subject vehicle (along the selected direction as the outcome of the model in step-1). The parameters of the MIDM model are calibrated using real data for cars and motorcycles. The deterministic parameters for MNL model and the empirical distribution of the MIDM model parameters are utilized to stochastically simulate vehicle trajectories with the initial and boundary conditions determined by the real dataset. The comparison of the macroscopic properties between the simulated and real datasets provides promising results for the simulation applicability of the proposed modelling framework. [ABSTRACT FROM AUTHOR]

• Controlling a portion of cooperative AVs to achieve system optimum. • A linear program is formulated to find the minimum control ratio. • Numerical examples show the ratio is typically below 23%. • Combining path-based pricing significantly reduces the ratio without collecting much toll. In the future, when traffic streams comprise a mix of conventional and automated vehicles (AVs), AVs may be employed as mobile actuators to regulate or manage traffic flow across an urban road network to enhance its performance. This paper develops a path-control scheme to achieve the system optimum (SO) of the network by controlling a portion of cooperative AVs (CAVs) as per the SO routing principle. A linear program is formulated to delineate the scheme and determine the minimum control ratio (MCR) of CAVs to achieve SO. The properties of the MCR are mathematically and numerically investigated. Numerical examples based on real-world networks reveal that the SO of most of the tested networks can be achieved with an MCR below 23%. Considering the low market penetration of AVs at early stages of their deployment, we further investigate a joint path-based control and pricing scheme to replicate SO. Numerical examples demonstrate the remarkable synergy of these combined instruments on reducing the MCR with little collected tolling revenue. [ABSTRACT FROM AUTHOR]

• A reconstruction model aims to reconstruct unmeasurable parameters from measurable ones. • Previous model's parameters are migrated to the next to achieve faster convergence. • Auto-correlation and sequential reconstruction can improve reconstruction accuracy. Due to the complex internal structure of aeroengine and the constraints of sensor installation, it is often impractical to deploy many sensors inside the aeroengine to monitor the key internal parameters. As a result, it is impossible to realize the goal of module performance evaluation. Relevant learning strategies for parameter reconstruction using limited measurement parameters have been studied to solve this problem. Firstly, because the measurable data is time series data containing noise, an attention mechanism about sequence correlation is adopted. This mechanism can gradually decompose complex time series. At the subsequence level, sequence information aggregation is carried out to improve information utilization. Due to the inclusion of attention in this mechanism, it can adaptively identify and reduce the impact of noise while retaining true signals related to aeroengine performance. Secondly, measurable parameter and reconstructed parameter as inputs to the model helps the model learn and consider the relationship between the two simultaneously, thereby better capturing the details and integrity of the aeroengine system, which can provide more comprehensive and rich information. Thirdly, due to the trained parameters already containing some level of knowledge, the parameters of the previously trained model are used as the initial parameters for the next to accelerate the convergence speed. Finally, three datasets are used for experimental verification to assess the effectiveness of the proposed method. The experimental results demonstrate that the proposed method exhibits good reconstruction performance. The relative error mean on aeroengine dataset is below 1.10%. The maximum relative error is below 5.44%. [ABSTRACT FROM AUTHOR]

Decarbonizing the passenger transportation sector is critical for climate change mitigation. Existing studies on net-zero scenarios using Energy System Optimization Models (ESOM) often overlook non-monetary aspects of consumers' mobility choices but primarily focus on cost aspects. This study incorporates consumers' travel time duration and valuation, and an endogenous modal shift option into the Swiss TIMES Energy system Model (STEM). STEM is applied in a multi-objective optimization framework to quantify the impacts of faster Public Transport (PT) and slower car speeds on modal shifts in the transport sector's transformation. Similarly, we assess scenarios where consumers weigh travel time less, reflecting improved travel productivity. The results show that speed variations on medium- and long-distance trips, which can be interpreted as policies for highway speed limits and more efficient PT, can induce modal shifts towards 5–10% higher PT demand. Its implied secondary effects across the energy system include a reduced need for electrification of heavy-duty trucks by 11% and a decrease in hydrogen demand in road transportation by 34% by 2050. If travelers weigh costs over travel time, PT becomes less competitive against cars. Thus, electric vehicles (EVs) need to play a more dominant role in decarbonization, with a demand increase of 13% in 2040 (+9.2 billion passenger kilometer (bpkm)) and 6% in 2050 (+5.0 bpkm), along with the need for additional 45,000 public chargers of 22 kW size. Policy implications include the emphasis on improved PT speeds, speed limits on highways, needs to achieve more widespread EV adoption, and the need for balancing travelers' decision factors when aiming for reduced transport CO 2 emissions. • Non-monetary aspects relevant for modal shift incorporated in the Swiss TIMES model. • Multi-objective optimization to quantify net-zero impacts of non-monetary aspects. • Travel speed measures induce a 5–10% demand uptake of public transport. • Weighing travel time less makes electric cars more critical for decarbonization. • Secondary energy system effects are quantified & policy implications are drawn. [ABSTRACT FROM AUTHOR]

Rollovers can cause many hazards to the passengers in the car. The main cause of this problem is the driver's sudden steering at high speed to avoid an obstacle or enter a roundabout. To limit this phenomenon, it is necessary to equip the car with an active stabilizer bar. In this article, we use a new fuzzy control method to direct an active stabilizer bar. This method is established based on five points of view regarding the stability and responsiveness of the system, so it is called the novel adaptive fuzzy algorithm (NAFC). This is a completely new point in the article compared to previous studies. A combined dynamics model that is a fusion of the seven DOFs spatial dynamics model and the three DOFs motion model. The simulation and calculation occur in the Simulink® interface, with two cases representing the steering angles J-turn and Fish-hook. The speed of the car is changed according to three specific values. According to the calculation results, the vehicle body roll angle is greatly reduced when using active stabilizer bars controlled by the novel adaptive fuzzy algorithm. Besides, the minimum dynamic force value at the rear wheel is better guaranteed. The car's roll index is also sharply reduced when applying this algorithm to the hydraulic stabilizer bar model. In addition, rollover occurs when the car steers the J-turn at v 3 and the fish hook at v 2 and v 3 (if stabilizer bars are unavailable). Meanwhile, car's stability is always guaranteed in the case of a car with a stabilizer bar using the NAFC algorithm. The article's achievements can be used as a basis for developing more complex control algorithms in the future. [ABSTRACT FROM AUTHOR]

• Vehicle speed computation designed to give driver indications based on target speed. • Target speed calculation based on Predictive Cruise Control for energy reduction. • Speed computation algorithm valid to any vehicle type and powertrain architecture. • Simulated energy reduction achieved on real scenarios between 3% and 11%. • Algorithm suitable for on board implementation and real time use on vehicles. Energy reduction in automotive applications is addressed since many years by both academia and vehicle manufactures. Recently, the introduction of innovative technical solutions, based, for instance, on internet connectivity and Advanced Driver-Assistance Systems (ADAS), allowed the on-board implementation of complex Energy Management Strategies (EMS) based on advanced optimization algorithms. However, these solutions require, in most cases, high computational capabilities and are generally customized on vehicle type and addressed to hybrid powertrain configurations. In this regard, this paper presents a vehicle speed management algorithm that suggests in real time to the driver the speed that shall be followed to achieve fuel consumption reduction. The algorithm requires road information, such as speed limits and slope variation, but it can be applied to any vehicle (e.g., light-weight cars, busses, trucks, etc.) and powertrain configuration (conventional, hybrid, pure electric, etc.). The basic structure relies on Predictive Cruise Control (PCC) approach, without introducing any complex mathematical optimization algorithm. The algorithm performance is here investigated in simulated environment by analyzing different vehicle types and routes. Under all the addressed scenarios, the algorithm can allow fulfilling energy consumption reduction (within the range of 3%-11% for real scenarios) with respect to a given reference speed profile under the same travel time. [ABSTRACT FROM AUTHOR]

his paper begins with the assumption that a mobile phone is placed in the right trouser pocket. Its primary objective is to ascertain whether the mobile phone belongs to the driver or the passenger. To achieve this goal, the paper conducts an analysis of raw data collected from phone sensors, specifically the accelerometer, gyroscope, orientation, and GPS, in order to identify and detect movement in the right leg. Based on this analysis, the application makes the decision to disconnect the signal and Internet access on the driver's phone if the car's speed exceeds 60 miles per hour, while maintaining these services for passengers. Subsequently, relevant features are extracted from the data, and a variety of machine learning algorithms are evaluated to determine the most suitable model for the task. The results demonstrate promising performance, suggesting that the proposed method could serve as an effective tool for detecting distracted driving. [ABSTRACT FROM AUTHOR]

The control of the environmental impacts is a considerable challenge to the daily operations of modern logistics companies, especially under the current trend of increasing carbon dioxide emission. This paper focusses on freight distribution, introduces a transportation resource sharing strategy to address the multi-depot green vehicle routing problem, and incorporates the time-dependency of speed as well as piecewise penalty costs for earliness and tardiness of deliveries. Transportation resource sharing is proposed to eliminate long and empty-vehicle trips, improve the network's fluidity and the efficiency of resource management. A bi-objective model is proposed to minimize total carbon emission and operating cost, while enforcing piecewise penalty costs on earliness and tardiness to reduce waiting time and improve customer satisfaction. Further, we combine the Clarke and Wright Savings Heuristic Algorithm (CWSHA), the Sweep Algorithm (SwA) and the Multi-Objective Particle Swarm Optimization algorithm (MOPSO) to design a hybrid heuristic algorithm for the vehicle routing optimization. CWSHA and SwA are consecutively used to generate the initial population, and MOPSO is employed for local and global solution search. Computational experiments reveal that sharing transportation resource reduces the total travelled distance, the number of vehicles, and facilitates a cost effective and environment-friendly distribution network. In addition, we also observe that the shortest path sometimes undermines minimum cost and carbon emission objectives. Moreover, sensitivity analyses reveal that vehicle routes are less influenced by piecewise penalty costs under unimodal traffic flows, while bimodal traffic flows would require more investment to reduce carbon emission. • Time-dependent speed and piecewise penalty cost are integrated to optimize MDGVRP. • A method combining bi-objective mathematical model and hybrid heuristic is designed. • Transportation resource sharing reduces travelled distance and carbon emission. • Vehicle routes are less influenced by piecewise penalty cost under unimodal traffic. • The shortest path sometimes undermines minimum cost and carbon emission objectives. [ABSTRACT FROM AUTHOR]

• A system is designed based on electromagnetic energy-harvesting for pavement. • The system performance is studied by laboratory testing and numerical simulations. • The prototype generated maximum 3 mW electrical power over each axle passage. • Steel and Aluminum are the best materials for top plate based on FE analysis. • The technology can be used for low-powered applications in roadways. Roadway pavements are repeatedly subjected to two different types of energy sources—solar radiation and kinetic energy from passing vehicles. Therefore, they have great potential to be utilized as sustainable energy sources. In this study, an electromagnetic speed bump energy harvester (ESE) prototype was developed to harvest energy from the kinetic energy of passing vehicles and to simultaneously control vehicles' speed. The ESE absorbs the deflection generated by a passing vehicle and converts it to a rotating shaft that triggers an embedded generator. A set of laboratory tests were conducted to simulate traffic conditions and evaluate the performance of the prototype in generating electrical power. These tests investigated the effect of load magnitude, time of loading, time of unloading, and ratio of loading time to unloading time on the power output generated by the ESE. The experimental results had a maximum average power of 3.21 mW, which shows that the proposed prototype promises to generate substantial power under actual traffic loading conditions. The effect of load magnitude was negligible, while a shorter time of loading led to a higher power output, implying that the optimum vehicle speed for maximizing the power output is the speed limit in the ESE location. Four sets of linear static analyses were performed in order to evaluate the response of the prototype fabrication. The top component of the ESE was modeled using material properties of steel, aluminum, or composites of heavy-duty rubber, and the bottom frames were given steel or aluminum properties. [ABSTRACT FROM AUTHOR]

• Middle age men and older women had the highest and lowest recorded mean speed, respectively, both in warning and non-warning states at black spots. • Young male drivers had the highest speed variations in the warning state middle age male drivers recorded the lowest variations in the non-warning state. • Elderly women were found to be the most cautious group both in warning and non-warning states. A high percentage of crashes occur at black spots of rural highways, and it is of paramount importance to employ strategies that can significantly reduce these crashes. The use of warning systems is one of the different methods of achieving this goal, and this study evaluates the effectiveness of these systems in different classes of drivers. To analyze the effects of warning systems on driver performance, three speed measures (mean speed, speed variation and speed limit violation) were applied. Forty-eight male and female drivers were categorized into three age groups, namely young (18–35 years old), middle age (36–55 years old) and elderly (above 55 years old), and they were asked to drive on a rural two-lane two-way highway in the north-west of Iran to conduct the experiment. The results indicate that middle-aged men and elderly women had the highest and lowest recorded mean speeds at black spots respectively both in the warning and non-warning states. On the other hand, young male drivers had the highest speed variations in the warning state, and middle-aged male drivers recorded the lowest variations in the non-warning state. Concerning the violation of speed limit at the black spots, young and middle-aged men had the highest number of violations in the warning and non-warning states respectively. Elderly women were found to be the most cautious group both in the warning and non-warning states. Conclusively, strategies such as changing the type and number of warnings are proposed to improve the effectiveness of the warning systems in special groups of drivers. [ABSTRACT FROM AUTHOR]

• A speeding prediction model is established based on quantifying the visual road environment to improve pre-waring systems. • A visual road environment model consists of two parts, including the visual road geometry and visual roadside environment. • Random Forests were then applied to build the speeding prediction model and variable importance was calculated. • Under both levels of the speeding criterion, the speeding prediction model performed well with high out-of-bag accuracy. • This model could predict drivers' speeding behavior at the future position located a sighting distance away. Speeding is one of the major contributors to traffic crashes. To solve this problem, speeding prediction is recognized as a critical step in a pre-warning system. While previous studies have shown that speeding is affected by road environmental design, research in predicting speeding behavior through road environment features has not yet been conducted. Furthermore, there is a large discrepancy between actual and perceived road environmental information given that a driver's visual perception plays a crucial role as the dominant source of information in determining driver's behavior. Thus, this paper aims to establish a speeding prediction model based on quantifying the visual road environment to improve the design of pre-waring systems, which can predict whether drivers are going to speed and provide them with visual or/and audio warnings about their current driving speed and the speed limit prior to the occurrence of speeding behavior. Twenty input variables derived from three categories including visual road environment parameters, vehicle kinematic features, and driver characteristics were considered in the proposed speeding prediction model. Especially, the road environmental design factors consisting of the visual road geometry and visual roadside environment as perceived by the driver's eyes were quantified using a visual road environment model. Field experiments were conducted to collect naturalistic driving data concerning speeding behavior on the typical two-lane mountainous rural highways in five provinces of China. Random Forests, an ensemble learning method for regression and classification, were applied to build the speeding prediction model and variable importance was calculated. Additionally, logistic regression was used as a supplement to further investigate factors impacting on speeding behavior. A speeding criterion was defined with two levels in this study: a lower level (exceeding the posted speed limit) and a higher level (10% above the posted speed limit). Under both levels of the speeding criterion, the speeding prediction model performed well with high accuracy (over 85%). This model could use the value of the variables obtained from the current position to predict drivers' speeding behavior at the future position located a sighting distance away. This interval was sufficient for a pre-warning system to give a speeding warning that a driver with normal perception-reaction time (around 2.5 s) could respond to. Findings in this study can be used to effectively predict speeding in advance and help to reduce speeding-related traffic accidents. [ABSTRACT FROM AUTHOR]

• This study explores the applicability of univariate and two-stage approaches for estimating crash frequency by severity. • The prediction accuracies of univariate and two-stage severity distribution function (SDF) methods were found to be similar. • The results highlight the potential of the two-stage SDF approach at least for curved two-lane road sections. • The two-stage SDF approach can be especially a useful method for the all too frequent cases where samples are too small. The Highway Safety Manual (HSM) procedures apply specific safety performance functions (SPFs) and crash modification factors (CMFs) appropriate for estimating the safety effects of design and operational changes to a roadway. Although the applicability of the SPFs and CMFs may significantly vary by crash severity, they are mainly based on total crash counts, with different approaches for estimation of crashes by crash severity. The variety of approaches in the HSM and in the literature in general suggests that there may be no one best approach for all situations, and that there is a need to develop and compare alternative approaches for each potential application. This paper addresses this need by demonstrating the development and comparison of alternative approaches using horizontal curves on two-lane roads as a case study. This site type was chosen because of the high propensity for severe crashes and the potential for exploring a wide range of variables that affect this propensity. To facilitate this investigation, a two-stage modeling approach is developed whereby the proportion of crashes for each severity level is estimated as a function of roadway-specific factors and traffic attributes and then applied to an estimate of total crashes from an SPF. Using Highway Safety Information System (HSIS) curve data for Washington state, a heterogeneous negative binomial (HTNB) regression model is estimated for total crash counts and then applied with severity distribution functions (SDFs) developed by a generalized ordered probit model (GOP). To evaluate the performance of this two-stage approach, a comparison is made with predictions directly obtained from estimated univariate SPFs for crash frequency by severity and also from a fixed proportion method that has been suggested in the HSM. The results revealed that, while the two-stage SDF approach and univariate approach adopt different procedures for model estimation, their prediction accuracies are similar, and both are superior to the fixed proportion method. In short, this study highlights the potential of the two-stage SDF approach in accounting for crash frequency variations by severity levels, at least for curved two-lane road sections, and especially for the all too frequent cases where samples are too small to estimate viable univariate crash severity models. [ABSTRACT FROM AUTHOR]

• This study aims to quantify the effectiveness of the CV-VSL application by exploring drivers' reactions to warnings (e.g., recommended travel speeds). • In order to analyze the effectiveness of the CV-VSL application, a connected vehicle testing platform was established based on a driving simulator, and characteristics of the drivers' speed adjustments after receiving warnings were analyzed with respect to different levels of visibility (i.e., no fog, slight fog, and heavy fog). • This study also examined the effect of warnings on drivers in different impact zones (i.e., clear zone, transition zone, and fog zone). • Three indicators were identified: 1) speed at the end of the clear zone, 2) maximum deceleration rate in the transition zone, and 3) average speed reduction in the fog zone. • Throughout the experiment, the relationship between speed adjustments and the level of visibility was explored. • The findings of this research can be used to support decision-making for implementing the CV-VSL application, and the connected vehicle testing platform based on a simulator provides a new method for evaluating the effectiveness of connected vehicles in adverse weather and roadway conditions. In response to developing and/or diminishing foggy conditions, the variable speed limit application in a connected vehicle environment (CV-VSL) can estimate and deliver recommended travel speeds to individual drivers, which can help to reduce crashes when visibility conditions change. This study aims to quantify the effectiveness of the CV-VSL application by exploring drivers' reactions to warnings (e.g., recommended travel speeds). In order to analyze the effectiveness of the CV-VSL application, a connected vehicle testing platform was established based on a driving simulator, and characteristics of the drivers' speed adjustments after receiving warnings were analyzed with respect to different levels of visibility (i.e., no fog, slight fog, and heavy fog). This study also examined the effect of warnings on drivers in different impact zones (i.e., clear zone, transition zone, and fog zone). Three indicators were identified: 1) speed at the end of the clear zone, 2) maximum deceleration rate in the transition zone, and 3) average speed reduction in the fog zone. Throughout the experiment, the relationship between speed adjustments and the level of visibility was explored. The results indicated that the CV-VSL application is effective in making drivers reduce travel speeds in all three types of zones. Furthermore, it appeared that the CV-VSL application could help manage travel speeds prior to vehicles entering the transition zone, and influence drivers' braking decisions upon encountering reduced visibility. It was also found that the CV-VSL application was more effective in heavy fog conditions than in light fog conditions. The connected vehicle testing platform based on the driving simulator provided a new method for evaluating the effectiveness of in-vehicle messaging generated by connected vehicle applications. [ABSTRACT FROM AUTHOR]

• A novel vehicle speed management strategy is proposed for preventing crashes. • Vehicle interactions are evaluated in terms of comprehensive crash risks. • VISSIM simulation experiments are conducted to investigate the feasibility of the proposed methodology. • The outcome will be valuable for supporting the management of individual vehicle speeds in automated driving environments. Recent technological advancements have facilitated the implementation of speed harmonization based on connected and automated vehicles (CAV) to prevent crashes on the road. In addition, trajectory-level vehicle controls are receiving substantial attention as sensors, wireless communications, and control systems are rapidly advancing. This study proposes a novel vehicle speed control strategy to minimize inter-vehicle crash risks in automated driving environments. The proposed methodology consists of the following three components: a risk estimation module, a risk map construction module, and a vehicle speed control module. The essence of the proposed strategy is to adjust the subject vehicle speed based on an analysis of the interactions among a subject vehicle and the surrounding vehicles. Crash risks are quantified by a fault tree analysis (FTA) method to integrate the crash occurrence potential and crash severity at every time step. A crash risk map is then constructed by projecting the integrated risk of the subject vehicle into a two-dimensional space composed of relative speed and relative spacing data. Next, the vehicle speed is continuously controlled to reach the target speed using risk map analysis to prevent a crash. The performance of the proposed methodology is evaluated by a VISSIM simulator with various traffic congestion levels and market penetration rates (MPR) of controlled vehicles. For example, an approximate 50% reduction rate of the crash potential was achievable without a loss of the operational performance of the traffic stream when all vehicles were controlled by the proposed methodology under the level of service (LOS) C conditions. This study is meaningful in that vehicle speed control is performed for the purpose of speed harmonization in a traffic stream based on a comprehensive analysis of inter-vehicle risks. It is expected that the outcome of this study will be valuable for supporting the development of vehicle control systems for preventing crashes in automated driving environments. [ABSTRACT FROM AUTHOR]

• This study introduced the probable hot zone terminology in road safety research. • Road safety risk index assessed hotspots and hot zones mapping techniques. • Hot zones and probable hot zones exhibited different regional and temporal patterns. • Hot zones and probable hot zones predominantly occurred along rural highways. • Spatial autocorrelation indices provided useful insights on Tunisia's safety policies. Focusing on how hot zones mapping can predict spatial patterns of crashes and how different mapping approaches compare can help to better inform their application in practice. This study examines the stability of the performance of two spatial autocorrelation measures on the basis of a Road Safety Risk Index (RSRI) through the comparison of the results for three regions (North-West, Center-East, and Center-West) and for three time periods (2002–2005, 2006–2009 and 2010–2013) in Tunisia. Our study differs from others in that it discusses the identification of probable hot zones and enhances the capability to examine a given highway by determining "dangerous probable lengths", which aims to anticipate the traffic crashes in the future. The identified hot zones and probable hot zones exhibit different regional and temporal characteristics. There are clearly some outstanding spatial clusters of crashes covering specific locations. In both Northwest and Center-West regions, the majority of the identified hot zones and probable hot zones predominantly occur along mainly highways characterized by a dominant rural character. In the Center-East region, both hot zones and probable hot zones are mostly spread northeast and south-west more precisely in NH1 and NH2 where many urban activities are taking place. Spatial autocorrelation indices per region address the diversity within the regions and provide us with useful insights that can be translated into safety policies in Tunisia. [ABSTRACT FROM AUTHOR]

• Evaluates suitability of negative binomial models when applied to rural local roads with a low sample mean of crashes. • Bivariate negative binomial and ordered probit models are estimated across two severity levels for rural local intersections. • Models are investigated for prediction biases under the presence of the low sample mean. • No obvious biases detected; moreover, the negative binomial model seems to slightly outperform the ordered probit model. • Several influential road and roadside features identified, many prompting practical safety improvements. Count models, such as negative binomial regression, are well-established statistical methods for analyzing road safety. Although count models are widely used for arterial roads, their application to rural local roads is sparse, partly due to the concern of possible estimation bias caused by low crash counts. This paper revisits the matter to further evaluate the suitability of negative binomial models for rural local roads with low crash frequencies, comparing the performance of the model to probabilistic regression (ordered probit) proposed in the past. The negative binomial model was estimated to predict crashes for rural local intersections and compared to predictions obtained from the ordered probit model. Bivariate versions of both models were applied to improve model efficiency by incorporating correlation between two severity outcomes, fatal/injury (FI) and property damage only (PDO) crashes. The estimated models included several significant variables with intuitive signs. These results are discussed in the paper to support the claim that both models are adequate. Furthermore, the cumulative sums of the model-predicted and observed crashes conditioned on the estimated effects were compared to detect any systematic bias in the results. Although both models showed similar performance and no obvious biases could be detected, the negative binomial model seemed to behave slightly better than the ordered probit model, demonstrating the model's suitability in the analyzed case. The results point to the possibility of applying the Highway Safety Manual methodology to lower-volume county roads with focus shifted from individual high-crash locations to safety-deficient road features present at multiple locations. [ABSTRACT FROM AUTHOR]

Rural and peripheral areas with low population density and long travel distances challenge the supply of public transport service. The objective of this paper is to analyze which type of public transport service best fit the periphery and compare alternative services based on a set of quantities and qualitative measures with emphasize on equity considerations. We applied for the first time the Potential Mobility Index (PMI) developed by Martens (2016) to analyze the equity implications of the alternatives. We applied it in a new and unique way with two measures of travel time: in-vehicle travel time and door to door travel time. The research applies the methodology to a case study of Israel's peripheral cities. Two different alternative services were analyzed: high-speed rail to the Northern and Southern peripheral cities, and a fix schedule regional BRT shuttle service with a timed transfer to rail hubs near the periphery. The accessibility measures show that the rail service to the periphery provides high accessibility, however, the demand analysis suggests that the demand would be low to justify high-speed rail service. The analysis of the in-vehicle time PMI shows an advantage to the high-speed rail alternative, however, the door to door calculation of PMI shows that the BRT service gives better PMI scores to all the peripheral cities that we examined and can be effective in providing a high quality of service to the periphery. The results provide some insights for research and service planning in rural areas and found some generalization to equity aspects in the periphery dilemma. [ABSTRACT FROM AUTHOR]

The paper provides results for the stabilization of a spatially uniform equilibrium profile for a scalar conservation law that arises in the study of traffic dynamics under variable speed limit control. Two different control problems are studied: the problem with free speed limits at the inlet and the problem with no speed limits at the inlet. Explicit formulas are provided for respective feedback laws that guarantee stabilization of the desired equilibrium profile. For the first problem, global asymptotic stabilization is achieved; while for the second problem, regional exponential stabilization is achieved. Moreover, the solutions for the corresponding closed-loop systems are guaranteed to be classical solutions, i.e., there are no shocks. The obtained results are illustrated by means of a numerical example. [ABSTRACT FROM AUTHOR]

Advanced communications technology enables us to obtain the Headway Variation Tendency (HVT) of the next moment in a car following scenario. To maximize the benefits of the new technology, we developed a new traffic flow model that takes into consideration the effect of HVT. First, linear analysis method is used to derive the linear stability condition, that determines whether the HVT can improve traffic system stability. Then, using the reductive perturbation method, a modified KdV (mKdV) equation is obtained and the kink–antikink solutions are derived. The phase diagram of driver sensitivity against equilibrium headway is also plotted by using the neutral stability line, derived from linear analysis and the coexisting line, derived from nonlinear analysis. This diagram demonstrates that HVT does have the ability to improve the stability of traffic stream. Finally, the effect of HVT is validated through numerical simulations, where it is evident that the information of HVT can smooth the traffic stream and prevent the formation of traffic congestion. • An improved car-following model is proposed by considering the effect of Headway Variation Tendency (HVT). • The linear stability condition and the modified KdV equation are derived. • The numerical simulation is presented to verify the effect of the headway variation tendency on traffic flow. • Both the analytical and simulation results show that HVT can attenuate disturbance and avoid serious traffic jam effectively. [ABSTRACT FROM AUTHOR]

As we are approaching critical tipping point in greenhouse emissions, aligning the overall structure of energy sector will require major shift in both the approach and production portfolio. At the same time the Industry 4.0 transformation is gaining speed and its core technologies are developing in ever-increasing paste. The accelerated developments, especially in the domain of Artificial intelligence and industrial robotics, are already visible. Coupled with the energy demand in transportation sector, especially the electric vehicles impact on production patters and grid-balancing, the long-term energy production disbalance will create unprecedented challenges for ever-growing electricity needs. The environment friendly production and distribution of needed electricity is one the main ones. The Industry 4.0 changing demand will create excessive pressure on companies and governments to rethink their long-term production strategies. For most, this will be a paradigm shift in overall sectoral approach. Although, the wind and solar will be the two dominating renewable energy technologies in the upcoming decades, the "integration costs" of wind and solar energy: grid costs, balancing costs and cost effects on conventional power plants – varies tremendously depending on the specific power system. The daunting task of transformation and alignment of existing transmission grid, coupled with the need to build new grid capacity beyond 2020, are estimated to nearly double today's capacity just to facilitate today envisaged industrial automation and electric vehicles developments only. By all accounts, the majority of European countries are facing an unprecedented challenges in its electricity production portfolio. It's not only the nature of production or the power mix that is in question, but also balance-load, merit order principal as well as monumental challenge of new grid requirements. In this overview we provide an outlook at energy trends in EU by 2050, coupled with electric vehicles and core Industry 4.0 technologies impact on electricity demand, power-mix and grid capacity challenge. [ABSTRACT FROM AUTHOR]

A key objective of the land reforms in South Africa was for the process to lead to the emergence of a cohort of black small-scale commercial farmers who would realize substantive agricultural production levels through irrigation and actively contribute to the local and national agricultural value chains. The available evidence suggests that this objective has been difficult to attain and the contribution of land reform to livelihoods of the beneficiaries has been negligible in the Limpopo province. This study deployed qualitative research methodologies to gather both secondary and empirical data that enabled analysis of the extent to which the land reform program has contributed to the livelihoods of small-scale emerging farmers in the surroundings of Bela-Bela Municipal Area, Limpopo Province. The study found out that financial resources are a big challenge, with most of the farmers being unable to raise the capital needed to invest in the farming enterprise. In addition, most of the ' emerging farmers ' do not have the know-how and experience needed to run a commercial farm. Overall, the study enabled us to conclude that the land reform projects have not only had limited impact on the livelihoods of the majority of the beneficiaries, instead, the reforms have left the country-side facing a real risk of increasing food insecurity. This suggests that a wide-ranging programme of land reform is a necessary but not sufficient condition for meaningful transformation of the livelihoods of the households involved. More groundwork still needs to be done by government and other development agencies to ensure availability of proper post-land transfer support systems for the emerging farmers. • Key objectives of the Land reform in South Africa have not been attained. • The 'emerging' farmers lack knowledge and capital for commercial farming. • Post land transfer support from government has been inadequate. • The reforms have left the country-side facing a real risk of worsening food insecurity. • Targeted support is needed to capacitate the farmers financially and knowledge-wise. [ABSTRACT FROM AUTHOR]

Highlights • Inertial consistency models have been calibrated for American rural roads. • Safety Performance Functions are proposed to predict the number of crashes. • Thresholds are proposed to define the consistency level on horizontal curves. • Thresholds are proposed to define the consistency level on entire road segments. • New tools were developed to enhance the assessment of road safety. Abstract Road crash occurrence is closely related to the geometric design consistency, which can be defined as how drivers' expectancies and road behavior fit. To this regard, the crash rate on a road segment increases as its consistency level decreases. To assess this phenomenon, inertial consistency models were recently developed. These models are based on the difference between the inertial operating speed, which represents drivers' expectancies, and the operating speed, which represents road behavior. The higher the difference between both speeds, the higher the likelihood of crash occurrence. This research aims to validate and calibrate these consistency models on American two-lane rural roads. For this, a total of 194 homogeneous road segments and 977 horizontal curves along 665 km in North Carolina (US) were used. As a result, the geometric design consistency was identified as a major factor of crash occurrence. The higher the difference between drivers' expectancies and road behavior, the higher the crash rate. Likewise, the greater the consistency level, the greater the percentage of horizontal curves without reported crashes. A Safety Performance Function was also calibrated to estimate the number of crashes on a road segment. Consistency thresholds were defined and tested to identify where these crashes are more likely to take place. Finally, the results obtained in this study were compared with those obtained previously on Spanish highways. To this regard, the crash rate on an American highway was 1.85 times greater than those observed on a Spanish highway under the same risk exposure and consistency conditions. Therefore, different tools were developed to enhance the assessment of road safety to the geometric design of both new two-lane rural roads and improvements of existing highways. [ABSTRACT FROM AUTHOR]

Traffic congestion is the main problem faced by big cities, such as Jakarta. One approach to reduce congestion levels is to improve traffic management that regulates and controls the number of vehicles. To evaluate the impact of traffic management before direct implementation on the highway, traffic modeling can be carried out. Parameters in modeling traffic must be determined from a calibration process where the vehicle is accurately measured for its position and speed. This study aims to propose an efficient calibration procedure with accurate results, based on recorded vehicle movement in perspective view. First, the road image is projected using the Direct Linear Transformation (DLT) method, then the vehicle position is detected using the Background Subtraction and tracked using Mixture of Gaussian (MoG) to determine the vehicle speed. Finally, we develop a prototype of Automated Traffic Flow Monitoring based on Python programming. In the experiment results, the accuracy of vehicle position detection is evaluated based on the Euclidean distance. The average difference between the results of position detection with ground-truth is 12.07 pixels with a camera angle 40 °. The percentage of speed measurement accuracy using the DLT projection method is 96.14%. [ABSTRACT FROM AUTHOR]

• Road and roadside environment and risk perception are two factors affect speed limit credibility. • Credible speed limit can be set based on drivers' subjective and objective measurements. • A new five indicators can be used for deciding credible speed limit in a given road environment. • It provide a valid methodology to evaluate credibility which can be adopt for further research. • Curved road and road with cycle lane need lower speed limit because of potential risk presented. • Setting credible speed limit will help bring more compliance with speed limit. • Improving the credibility of the speed limit is better for speed management. There is now a body of literature on speed limit credibility, particularly in connection with speed management under the overall umbrella of "Safe Systems". However, there is rather little empirical work on the underlying factors that determine the credibility of speed limits and on how to enhance credibility for a given type of road. The study reported here aimed to investigate how factors such as road layout and the roadside environment together with drivers' perception of risk affect speed limit credibility. It also aimed to provide a measurement of speed limit credibility and how to set more credible speed limits to improve drivers' speed compliance. A picture questionnaire and a driving simulator in an automated condition in a simulator were adopted to obtain the measurements. The results suggest that certain road layout and environment features influence speed limit credibility. The research results show that five new indicators can be used as a reference for deciding on a credible speed limit in a given road environment: the most common choice of speed limit by drivers; the highest credible rating score value; indication of comfort with speed in automated driving; risk rating in the range from feeling safe to very safe; arousal indicated by skin conductance. Applying these indicators makes it possible to determine a limit that is credible for most motorists in a given road environment. Improving the credibility of a speed limit will lead to better speed management overall. [ABSTRACT FROM AUTHOR]

• 37 participants, each overtook 7 cyclists on two lane road in a driving simulator. • We used these data to model how/when drivers decide to overtake and lateral clearance. • Higher driving speeds increase the probability to perform flying overtaking manoeuvres. • The lateral clearance predictive model results were not found to be satisfactory. • These models can support development and evaluation of active safety and policy making. The involvement of cyclists in road crashes has not been decreasing with the same magnitude as the involvement of other road users. In particular, the interactions between cyclists and motorized traffic can lead to high-severity crashes. To improve the safety of these interactions, a thorough understanding of road user behaviour is first needed. In this study, we focused on drivers overtaking cyclists on rural roads. The two main objectives of this study were to develop models that predicted: (a) drivers' decisions to perform either a flying or an accelerative overtaking manoeuvre in the presence of oncoming traffic, and (b) the lateral comfort distance that drivers maintain from cyclists during the overtaking. A driving simulator study was designed to assess driver decision-making during the overtaking. The 37 drivers who participated in the study each performed seven overtaking manoeuvres with oncoming traffic. Out of the 259 overtaking manoeuvres, 168 were flying and 91 were accelerative. Binary logistic-regression models with mixed effects predicted the type of overtaking strategy (flying or accelerative). Driving speeds were found to significantly affect the strategy. The overall performance of the models predicting the strategy was 85–90%. Models were also developed for predicting the lateral comfort distance. The results show that the lateral comfort distance is mostly affected by the longitudinal distance between the subject vehicle and the oncoming vehicle, the longitudinal distance between the subject vehicle and the cyclist, and the presence of an oncoming vehicle—as well as by the drivers' characteristics (sensation seeking in flying overtaking manoeuvres and ordinary violations in accelerative manoeuvres). The root mean square error, which was used to assess the performance of the models, ranged from 0.56 to 0.62. In conclusion, the models predicting the overtaking strategy performed reasonably well, while the models predicting lateral distance did not provide accurate predictions. The models predicting overtaking strategy may support (1) the development and evaluation of active safety systems, (2) the design of automated driving, and (3) policy making. [ABSTRACT FROM AUTHOR]

Abstract Considering effect of driver's memory and average speed effect of preceding vehicles, an extended car-following model is proposed in this paper. The control signal including the velocity difference between the considered vehicle's velocity and its preceding cars' average speed is considered. The stability conditions of the model are derived by control theory method. The extended model is also analyzed from the perspective of energy consumption. Numerical simulation results show that driver's memory has negative impact on stability of traffic flow and increases the energy consumption. However, the control signal can enhance the stability of traffic system and depress the energy consumption. Highlights • A new model is presented considering driver's memory and average speed of preceding vehicles. • The stability condition of the new model is deduced by feedback control method. • The energy consumption for this extended model is explored. [ABSTRACT FROM AUTHOR]

• Greater feeling of risk at a given speed has an influence on feeling that speed limit is too high (less credible). • As drivers feel more risk in a given road environment, they might decrease their driving speed and obey the speed limit. • As the speed limit is more credible, drivers are more compliant with the speed limit. More credible speed limit can make speeding drivers slow down, especially extreme offenders. • For practical implications for road design, the research has provided advice to local highway authorities on matching credible speed limit to rural single carriageway infrastructure for potential safety improvement for road users. Driving speed is an important factor in road safety. Speed limit compliance is not only affected by the speed limit credibility, but is also related to driver's risk perception. This study investigates the relationship between the factors of risk perception, speed limit credibility and speed limit compliance for a given rural single carriageway road and roadside environment. Speed limit credibility, subjective risk perception and compliance with the speed limit were measured separately. To be specific, speed limit credibility was measured by speed limit rating score using a picture questionnaire. Subjective risk perception was measured by risk rating in an automated car driving simulator for a given speed and road environment. Speed limit compliance was measured by percentage of driving time spent below the speed limit in a simulated manual driving task with a given speed limit and road environment. Multilevel regression and logistic regression analysis demonstrate that risk perception has a positive influence on compliance with the speed limit. Credibility of speed limit has a positive influence on speed limit compliance. Risk perception has a negative influence on speed limit credibility. The research results can be used for guiding speed limit design and speed management. [ABSTRACT FROM AUTHOR]

• This study aimed at driver performance on combined crest curves after treatment application. • Treatments were proposed to improve driver performance with/without oncoming vehicle. • Treatments were compared based on design consistency criteria in both scenarios. • Comparison of treatments showed negotiating curves improved best with yellow signal. Combined horizontal and crest vertical curves are among the most hazardous road segments because of drivers' difficulties in perceiving early road geometry. This study evaluates new treatments to improve the safety of horizontal and crest vertical curves and compares their efficiency for driver performance based on design consistency criteria under free flow traffic and on-coming traffic. A combination of chevron signs with three promising treatments included herringbones, sealed shoulder and a yellow blinking signal was applied to hazardous curve sections in a driving simulator. Performance measures consisted of mean of speed and lateral position. The results indicated that combining chevrons and a warning blinking signal is the most appropriate treatment for horizontal and crest vertical curves, as this resulted in lower speed and lateral position. In addition, speed and lateral position variations along the curves were lower compared to other treatments specially, with an on-coming vehicle. Sealed shoulder makes drivers drive faster while entering a curve and brake suddenly while changing direction. Using herring bones is found to reduce speed and speed differential along the curve but not lateral position which was even higher in treated curves particularly, in presence of an on-coming vehicle. [ABSTRACT FROM AUTHOR]

Conventional public transportation (CPT) services in rural areas are among others confronted with the accessibility problem and low traveler quantities. Demand responsive transportation (DRT) is an emerging mainstream concept, which aims to offer flexible mobility services to customers and also to solve the aforementioned problems of CPT providers. Studies and simulations about the comparison of CPT and DRT mostly focus on urban areas. Therefore, this paper is a case study of CPT vs. DRT services in the rural town of Colditz: A stop-based and a door-to-door DRT service is analyzed along with a CPT bus line. [ABSTRACT FROM AUTHOR]

Highlights • Speed humps have widespread usage across the world. • Speed humps are one of the well-known traffic calming devices to prevent urban traffic accidents. • The ride comfort is directly proportional to the vertical acceleration when traversing speed humps. • Parabolic speed humps are not effective beyond the vehicle speed of 25 km/h. Abstract This study aims to investigate the effect of parabolic speed hump profiles on ride comfort and driving safety under variable vehicle speeds. To this end, in-situ and simulation tests were carried out in which root-mean-square values were evaluated. Field tests were performed on seven parabolic speed humps within the boundaries of Istanbul Technical University Ayazaga Campus Area. These tests were conducted twice with different loads. Five vehicle speeds were taken into account within the range of 15 km/h to 35 km/h with 5 km/h increments. As in-situ tests focused on the measurement of the vertical acceleration when crossing the speed humps, maximum vertical accelerations and root-mean-square values were recorded by means of an accelerometer and a software. Two sets of parabolic speed hump profiles were considered for the simulation stage and then the results of the field tests and the simulation tests were compared. The results have yielded vehicle speed and parabolic speed hump height as the most important parameters affecting ride comfort and driving safety. It has also been demonstrated that the weight of the vehicle is negatively associated with motorists' sense of discomfort and an increase in the length of speed humps results in slightly better ride comfort. [ABSTRACT FROM AUTHOR]

Highlights • Lane changing behaviors under differentiated per-lane speed limits were investigated. • Characteristic parameters of driving behavior and driving workload were collected. • Unique lane changing behaviors and increasing driving workload were found. • Differentiated per-lane speed limits have potential to raise freeway safety levels. Abstract Inappropriate lane changing behaviour increases a driver's risk of being involved in a crash and the injury severity levels. It is hypothesized in this study that differentiated per-lane speed limit freeways could reduce inappropriate lane changing behaviours. A driving simulator experiment was conducted to investigate drivers' lane changing behaviour and the corresponding workload levels when different speed limit values are assigned to different lanes. Participants (N = 36) experienced three different test scenarios with different speed limit configurations. Lane changing behaviours are compared in regards to five measures describing lane changing behaviour. Meanwhile, task workload indexes were developed to evaluate key aspects of drivers' subjective experience of the test. The results reveal that the speed limit configurations have a considerable impact on lane changing behaviour as well as on the corresponding driving workload levels. This applies especially to the scenario with both different maximum and minimum speed limits for adjacent lanes, with drivers behaving differently than they did in other situations. Lane changes were found to be less frequent and have shorter durations, and drivers tended to avoid the dangerous behaviour of "rolling on the lane edge", therefore these compensatory safety-prone driving strategies suggest an enhanced driving safety level in association with the differentiated per-lane speed limit scenarios. The findings could provide important references for traffic management of freeways. [ABSTRACT FROM AUTHOR]