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In order to reveal the driving psychological characteristics and influencing factors of drivers under the hairpin curve section, 11 continuous hairpin curves on mountain roads were selected for natural driving test, and the on-board instruments were used to collect the driver’s ElectroCardioGraphy (ECG) under the natural driving habits. Analyse the overall heart rate characteristics, Heart Rate Increase (HRI), Heart Rate Variability (HRV) characteristics of drivers, as well as the relationship between heart rate change and the visual performance of curve corner and slop and curve environment. And compared with the general curve. The results show that: with 180° as the limit, the curve angle of the hairpin curve was divided into 3 types: greater, less or approximate. The 3 types of curve angle have different effects on the driver’s heart rate fluctuations. The overall heart rate distribution can be divided into 2 regions, in which the average heart rate of each driver at the curve, which curve angle ≈ 180°, was higher than the other 2 types of curves. The overall fluctuation range of heart rate in the middle of the curve is at the lowest level in the 3-stage curve segment area. Through the eigenvalue analysis of HRI, it can be seen that the drivers were more susceptible to the external environment when going downhill. When going uphill, the distribution range of the heart rate abnormality value was stable, but the sudden change was obvious. However, during the downhill direction, the overall adjacent heart rate varies greatly, but the abrupt change was small. Take the change trend of the HRI in the curve segment as an indicator, heart rate types were divided into 4 categories, continuous tension, relax gradually, relaxation-tension, and tension-relaxation. The 4 modes have a significant relationship with the difference of curve entrance environment. Compared with the modes shown in general curves, they focus on the modes with greater volatility, while the general curves focus on a more single growth trend.

The widely held thesis is that the profession of pilot is one of the most difficult jobs to do. The task of the article was to analyse whether and how the difficulty of the performed task affects the pilot's workload during the flight. The research was carried out using a flight simulator. During the simulator tests, the cognitive load measurements represented by the change in pilot pulse and concentration were used. A finger pulse oximeter was used for the first purpose. The second device was Mindwave Mobile which allows to measure level of pilot's concentration and relaxation. The NASA-TLX questionnaire is used as a subjective method of operator's workload assessment. The examined person assesses the level of his/ her load, using six dimensions: mental demand, physical demand, temporal demand, performance, effort, and frustration level. Five research hypotheses were put forward and verified by the Friedman test. It has been shown that the level of difficulty of individual stages of the study is appropriately differentiated by pulse, concentration, relaxation, and subjective assessment of the respondents' workload. It has been proved that pulse measurement, concentration, and relaxation levels, as well as subjective assessment of load levels, can be successfully used to assess the psychophysical condition of the operator. [ABSTRACT FROM AUTHOR]

Control delay is an important parameter that is used in the optimization of traffic signal timings and the estimation of the level of service at signalized intersection. However, it is also a parameter that is very difficult to estimate. In recent years, floating car data has emerged as an important data source for traffic state monitoring as a result of high accuracy, wide coverage and availability regardless of meteorological conditions, but has done little for control delay estimation. This article proposes a vehicle trajectory based control delay estimation method using low-frequency floating car data. Considering the sparseness and randomness of low-frequency floating car data, we use historical data to capture the deceleration and acceleration patterns. Combined with the low-frequency samples, the spatial and temporal ranges where a vehicle starts to decelerate and stop accelerating are calculated. These are used together with the control delay probability distribution function obtained based on the geometric probability model, to calculate the expected value of the control delay for each vehicle. The proposed method and a reference method are compared with the truth. The results show that the proposed method has a root mean square error of 11.8 s compared to 13.7 s for the reference method for the peak period. The corresponding values for the off-peak period are 9.3 s and 12.5 s. In addition to better accuracy, the mean and standard deviation statistics show that the proposed method outperforms the reference method and is therefore, more reliable. This successful estimation of control delay from sparse data paves the way for a more widespread use of floating car data for monitoring the state of intersections in road networks. First published online 5 February 2020

This study analysed unbalanced traffic distribution on Triple Left-Turn Lanes (TLTLs) at signalized intersections that is caused by left-turn drivers' unequal lane preferences. To develop statistical bonding between the multilane traffic flow and individual lane choices, the lane volumes are formatted as compositional data to subject the sum-constant constraint. One-way and two-way Compositional ANalysis Of VAriance (CANOVA) models were formulated respectively to estimate the independent effect of one factor and its joint effects with other factors on the multilane traffic distribution. TLTL volume composition was the dependent variable of the models, while the factors of geometric design and traffic control that could affect left-turn drivers' lane choice were the independent variables. Results indicate that variance of vehicle turning curve, length of the upstream segment, the location of triple left-turn sign, signal phase / cycle length, could affect the traffic distribution, and its balance could be achieved at specific levels of a factor. The joint effects of some factor couples could improve the unbalanced traffic distribution while others could not work. [ABSTRACT FROM AUTHOR]

Congestion is a kind of expression of instability of traffic network. Traffic signal control keeping traffic network stable can reduce the congestion of urban traffic. In order to improve the efficiency of urban traffic network, this study proposes a decentralized traffic signal control strategy based on backpressure algorithm used in Wi-Fi mesh networks for packets routing. Backpressure based traffic signal control algorithm can stabilize urban traffic network and achieve maximum throughput. Based on original backpressure algorithm, the variant parameter and penalty function are considered to balance the queue differential and capacity of downstream links in urban traffic network. For each traffic phase of intersections, phase weight is computed using queue differential and capacity of downstream links, which fixed the deficiency of infinite queue capacity in original backpressure algorithm. It is proved that the extended backpressure traffic signal control algorithm can maintain stability of urban traffic network, and also can prevent queue spillback, so as to improve performance of whole traffic network. Simulations are carried out in Vissim using Vissim COM programming interface and Visual Studio development tools. Evaluation results illuminate that it can get better performance than the backpressure algorithm just based on queue length differential in average queue length and delay of traffic network. [ABSTRACT FROM AUTHOR]

The Origin-Destination (O-D) matrix, is an important information in transportation planning and traffic control. Rapid changes in land use, particularly in developing countries, have been and are on an increase, which makes the estimation and observation of this matrix more significant. The objective of this paper is to observe O-D matrix under two scenarios. In the first scenario, it is assumed that the traffic network is equipped with path-ID sensors. In this situation, the goal is to determine the optimal number and location of these sensors in the network, where by applying collected information through these sensors, the O-D matrix is observed. Because path-ID sensors are not available in many cities, in the second scenario the interview alternative is proposed in order to observe O-D matrix. The interview method has encountered some restrictions. Several mathematical programming models have been developed to overcome these restrictions. To illustrate these proposed methodologies, they are applied in the Nguyen-Dupuis transportation network and the results are analysed. By applying the model on the intercity road network in the Province of Isfahan (Iran), a large network, the efficiency of these proposed models is demonstrated. Finally, some conclusions and final recommendations are included. [ABSTRACT FROM AUTHOR]

An efficient and intelligent road traffic management system is the corner stone for every smart cities. Vehicular Ad-hoc NETworks (VANETs) applies the principles of mobile ad hoc networks in a wireless network for Vehicle-to-vehicle data exchange communication. VANETs supports in providing an efficient Intelligent Transportation System (ITS) for smart cities. Road traffic congestion is a most common problem faced by many of the metropolitan cities all over the world. Traffic on the road networks are widely increasing at a larger rate and the current traffic management systems is unable to tackle this impediment. In this paper, we propose an Efficient Intelligent Traffic Light Control and Deviation (EITLCD) system, which is based on multi-agent system. This proposed system overcomes the difficulties of the existing traffic management systems and avoids the traffic congestion problem compare to the prior scenario. The proposed system is composed of two systems: Traffic Light Controller (TLC) system and Traffic Light Deviation (TLD) system. The TLC system uses three agents to supervise and control the traffic parameters. TLD system deviate the vehicles before entering into congested road. Traffic and travel related information from several sensors are collected through a VANET environment to be processed by the proposed technique. The proposed structure comprises of TLC system and makes use of vehicle measurement, which is feed as input to the TLD system in a wireless network. For route pattern identification, any traditional city map can be converted to planar graph using Euler's path approach. The proposed system is validated using Nagel-Schreckenberg model and the performance of the proposed system is proved to be better than the existing systems in terms of its time, cost, expense, maintenance and performance. [ABSTRACT FROM AUTHOR]

Fundamental diagram, a graphical representation of the relationship among traffic flow, speed, and density, has been the foundation of traffic flow theory and transportation engineering for many years. Underlying a fundamental diagram is the relation between traffic speed and density, which serves as the basis to understand system dynamics. Empirical observations of the traffic speed versus traffic density show a wide-scattering of traffic speeds over a certain level of density, which would form a speed distribution over a certain level of density. The main aim of the current research is to study on the distribution of traffic speed in different traffic conditions in the urban roads since the distribution of traffic speed is necessary for many traffic engineering applications including generating traffic in micro-simulation systems. To do so, the traffic stream is videotaped at various locations in the city of Budapest (Hungary). The recorded videos were analysed by traffic engineering experts and different traffic conditions were extracted from these recorded videos based on the predefined scenarios. Then their relevant speeds in that time interval were estimated with the so-called "g-estimator method" using the outputs of the available loop detectors among the videotaped locations. Then different parametric candidate distributions have been fitted to the speeds by Maximum Likelihood Estimation (MLE) method. Having fitted different parametric distributions to speed data, they were compared by three goodness-of-fit tests along with two penalized criteria (Akaike Information Criterion - AIC and Bayesian Information Criterion - BIC) in order to overcome the over-fitting problems. The results showed that the speed of traffic flow follows exponential, normal, lognormal, gamma, beta and chisquare distribution in the condition that traffic flow followed over-saturated congestion, under saturated flow, free flow, congestion, accelerated flow and decelerated flow respectively. [ABSTRACT FROM AUTHOR]

A large number of transport infrastructure equipment are located along the driving lanes of roadways, which must be secured by restraint systems. Among others, the different road lanes must be adequately separated from each other. The investigations reported herein aim to provide a probabilistic approach for the departure of motor vehicles from their intended lane and iimpact on restraint systems. Currently, evaluations of the road infrastructure against possible accidents are mostly focused on the resistance side. This contribution, however, intends to address the action side, focusing in particular on the probability of impact of vehicles on the road furniture. The main parameters taken into account are the geometry of the road and the traffic composition and characteristics. The objective of this research is to develop an analysis tool for the probability-based assessment of vehicles departing from their driving lane. The analysis tool for the determination of the likelihood of impact events in transport networks, requires to define (a) of the alignment (longitudinal inclination, transverse inclination, and curvature of the lanes), (b) of the pavement conditions (lane grooves, road grip, and pavement cracks etc.), and (c) of the traffic composition as significant input parameters. These were investigated together with the road infrastructure operators. A newly introduced methodology is presented herein taking into account the above mentioned parameters and factoring in characteristic properties in order to assess the fragility of the infrastructure subsystem. The evaluation is based on either road engineering physics or expert judgements. The method is incorporated in a spreadsheet tool, which is also presented, the feasibility of this tool is demonstrated, and sensitivities of the assessment process are evaluated and discussed. [ABSTRACT FROM AUTHOR]

The recent European debt crisis has led many governments to impose strict measures to alleviate public expenditure and increase revenue, especially in the southern countries. Many public services and infrastructures became more costly for users due to the increase of existing fees or the implementation of new ones. In Portugal, one of the measures adopted by the government consisted in the removal of shadow tolls and the application of the user-pays principle to the entire network of rural motorways. To rapidly implement, this measure, in the context of financial constraints, the Electronic Toll Collection (ETC), materialized by the installation of gantries in selected motorway segments, was the preferred solution over the more time and resource consuming construction of toll plazas. Toll revenue is directly collected by the state, which intends to cover, at least partially, the expenses associated with the contractual payments to private concessionaires for the traffic using these roads. The main objective of this research is to provide a new optimization tool to allocate toll gantries to the segments of an existing motorway with the aim of maximizing toll revenue, based on the case study of Portuguese motorways. A macroscopic decision model that predicts drivers' decision on using a tolled segment or the fastest alternative route and an optimization model that sets the price and location of toll gantries along a given motorway work together to provide a valuable tool to maximize the revenue. A special focus has been placed on scenarios of economic downturn, characterized by a negative growth of the Gross Domestic Product (GDP); however, the new tool allows making explanatory analyses for situations of economic growth. The results show that the optimal configuration for ETC vary with the macroeconomic scenario, with the number of tolled segments and price per kilometre inducing relevant variations on the revenue and traffic volume. The proposed methodology may be applied in other countries to assist decision makers in the implementation of ETC in motorways under different conditions. The required data is easy to collect from sources at the disposal of the practitioners.. [ABSTRACT FROM AUTHOR]

Road markings are an important component of delineation, intended to provide guidance and warning, to manage and regulate road traffic. In order to properly fulfil their function, road markings must be visible and it is precisely the visibility, in terms of road safety, that presents their most important characteristic. Practical tests showed that the marking visibility, or retroreflectivity, changes depending on directionality, showing higher values in the direction the marking is applied than in the opposite direction. This paper addressed the impact of road markings directionality on their retroreflectivity using the dynamic method for testing retroreflectivity. The research considered paint, thermoplastic and structural markings made of cold plastic. The results showed that the impact of directionality of paint and flat thermoplastic markings on their retroreflectivity is negligible. The average difference in retroreflectivity of renewed paint markings is 13.1 mcd/m²·lx and 11.85 mcd/m²·lx for existing paint markings, while the respective difference concerning flat thermoplastic markings is 9.60 mcd/m²·lx for renewed markings and 9.20 mcd/m²·lx for existing markings. A more significant difference was noted with structural markings made of cold plastic, namely 62.80 mcd/m²·lx for renewed markings and 49.60 mcd/m²·lx for existing markings. The results for paint and thermoplastic markings show that directionality should not be taken into consideration when evaluating their quality, which greatly facilitates and simplifies the process of testing the markings retroreflectivity. The stated results are of great importance for traffic safety and markings maintenance system. [ABSTRACT FROM AUTHOR]

The concept of Shared Space Street (SSS) has the potential to bring many benefits to a city. Those include promotion of social interaction, the connectivity within the city for both vehicles and pedestrians, active engagement of the people with the space, walkability, vitality and street livability, better economic wealth and alike. These factors work together to improve livability, vitality of street and indirectly bring economic wealth to municipalities through increasing the footfall to shops, enhancing the health and safety of the locality and increasing the property values. Hence, this clearly is a consideration for strategic property management and relevant professionals. This concept has also been criticized for its practical issues when implemented in some parts of the world. Such issues include difficulties faced by aged people and people with disabilities, harassments faced by the cyclists, etc. This paper explores the methods and approaches that can be used to harness potential advantages of the SSS concept and to overcome its practical issues and criticisms through a detail evaluation of design driven use of space in three case studies within United Kingdom. Finally, this paper proposes a set of design factors which can be applied to a SSS design in order to ensure a successful implementation. [ABSTRACT FROM AUTHOR]

The paper deals with studying the relationships between the motorcyclists' thinking about proper behaviour and their actual behaviour in the traffic. The impact of some control variables, such as riders' age, experience, driving history, and engine cubature, on actual behaviour, is also addressed here. For the purpose of research, two additional questionnaires were applied besides the well-known Motorcycle Rider Behaviour Questionnaire (MRBQ). To examine the causal relations between all-important latent factors present in this study, the structural equation model was designed. Exploratory and confirmatory factor analyses were also engaged in the analysis and the statistical modelling process. The results show that the higher awareness about alcohol danger and benefits of protective equipment and helmet can noticeably contribute to the bigger traffic safety. Besides, from the results is evident that the control variables are in most cases also significantly interrelated with the actual behaviour factors. The findings of this research could be important for the planning of better traffic safety strategies for the motorcyclists to decrease the fatalities and related costs and traumas. [ABSTRACT FROM AUTHOR]

Many congestion charging projects charge traffic only within part of a day with predetermined congestion tolls. Demand peaks have been witnessed just around the time when the charge jumps up or down. Such peaks may not be desirable, in particular (a) when the resulting peaks are much higher than available capacities; (b) traffic speeding up to get into the charging zone causes more incidents just before the toll rises up to a higher level; or (c) traffic slowing down or parking on the roadside decreases road traffic throughput just before the toll falls sharply. We term these types of demand peaks 'boundary effects' of congestion charging. This paper investigates these effects in a bottleneck scenario and aims to design charging schemes that reduce undesired demand peaks. For this purpose, we observe and analyse the boundary effects utilising a bottleneck model under three types of toll profiles that are indicative of real charging schemes. The first type maintains a constant toll across the charging period, the second type allows the toll to increase from zero to a given maximum level and then decrease back to zero and the third type allows the toll to rise from zero to a given maximum level, remain at this level for a fixed period and then fall down to zero. This investigation shows that all three types of toll profiles can produce greater boundary peak demands than the bottleneck capacity. A significant contribution of this work is that instead of designing an optimal traffic congestion pricing scheme we analyse how existing sub-optimal congestion pricing schemes could be improved and suggest how observed problems may be overcome. Hence, we propose a set of extra requirements to supplement existing principles or requirements for design and implementation of congestion charging, which aim to reduce the adverse consequences of boundary effects. Concluding remarks are made on implications of this investigation for the improvement of existing congestion charging projects and for future research. [ABSTRACT FROM AUTHOR]

Road traffic accident is an accident on a public road in which at least one moving vehicle has been involved and material damage or injury or death has occurred. Traffic accidents occur for various reasons, with one of them being the transport infrastructure and next the condition of traffic environment. Motorways are considered to be the safest roads, which have initially been planned as dedicated roads intended to be travelled only by personal cars, but the evolution of modal split of freight transport in Europe is causing the heterogeneity of traffic flows on these roads, which consequently affects the traffic safety. The aim of this paper is to explore the effects of changing volume and structure of traffic flows on road safety on Slovenian motorways. After the exhaustive analysis of past data, the paper provides different models for forecasting traffic safety on Slovenian motorways. [ABSTRACT FROM AUTHOR]

A bus may be blocked from entering and exiting a stop by other buses and traffic lights. The objective of this paper is to model each type of delay under these phenomena and the overall delay a bus experiences at a stop. Occupy-based delay, transfer block-based delay and block-based delay are defined and modelled. Bus delay at stop is just the sum of these three types of delay. Bus arrival rate, bus service rate, berth number and traffic lights are taken into consideration when modelling delay. Occupy-based delay is modelled with mean waiting time in Queueing theory. Transfer block-based delay and block-based delay are modelled based on standard deviation of waiting time and the probabilities of their occurrences. Two stops in Vancouver, Canada are selected for parameter estimation and model validation. The unknown parameter is estimated as 0.4230 using Ordinary Least Squares (OLS), which indicates that 42.3% of waiting time variation can be attributed to buses being blocked by the buses in front and red light for the selected stops. Model validation shows the average accuracy rate of the proposed model is 75.07% for the selected stops. Bus delay at stop evidently increases when arrival rate is more than 85 buses per hour for the given service time (50 s), ratio of red time to cycle length (0.65) and berth number (2). We also figure out that bus delay at stop evidently increases when service time is more than 60 s for the given arrival rate (54 buses per hour), ratio of red time to cycle length (0.65) and berth number (2). The proposed model can provide a tool for bus stop design and offer the foundation for service quality evaluation of transit. [ABSTRACT FROM AUTHOR]

Predicting the duration time of incidents is important for effective real-time Traffic Incident Management (TIM). In the current study, the k-Nearest Neighbor (kNN) algorithm is employed as a nonparametric regression approach to develop a traffic incident duration prediction model. Incident data from 2008 on the third ring expressway mainline in Beijing are collected from the local Incident Reporting and Dispatching System. The incident sites are randomly distributed along the mainline, which is 48.3 km long and has six two-way lanes with a single-lane daily volume of more than 10000 veh. The main incident type used is sideswipe and the average incident duration time is 32.69 min. The most recent one-fourth of the incident records are selected as testing set. Vivatrat method is employed to filter anomalous data for the training set. Incident duration time is set as the dependent variable in Kruskal-Wallis test, and six attributes are identified as the main factors that affect the length of duration time, which are 'day first shift', 'weekday', 'incident type', 'congestion', 'incident grade' and 'distance'. Based on the characteristics of duration time distribution, log transformation of original data is tested and proven to improve model performance. Different distance metrics and prediction algorithms are carefully investigated. Results demonstrate that the kNN model has better prediction accuracy using weighted distance metric based on decision tree and weighted prediction algorithm. The developed prediction model is further compared with other models based on the same dataset. Results show that the developed model can obtain reasonable prediction results, except for samples with extremely short or long duration. Such a prediction model can help TIM teams estimate the incident duration and implement real-time incident management strategies. [ABSTRACT FROM AUTHOR]

A Hook Turn (HT) traffic control scheme has been successfully implemented in urban Melbourne (Australia) ever since 1950s, for the regulation of right-turning vehicles at the intersections (in traffic system where driving is on the left). This paper addresses the optimal signal-timing of the HT scheme, which is still an open question in the literature. Under the HT scheme, right-turning vehicles should enter the intersection and stop at a waiting area. Hence, it is common to have a spillback from these vehicles if the right-turning volume is high. This paper provides an in-depth analysis of the spillback phenomenon on the traffic movements and the average delays, and proposes the models for the calculation of average delay in different cases. With the aim of minimizing the average delay of all the vehicles, a nonlinear integer-programming model is proposed for the optimal signal-timing problem of HT scheme. A Genetic Algorithm (GA) is used to solve this model, considering the complexity of its objective function. A realistic example developed based on one intersection with HT in urban Melbourne is adopted to assess the proposed methodology. Based on real survey data in morning peak and nonpeak hours, we compare the existing signal plan and optimal plan. The numerical test shows that compared with the existing plan, the optimal plan can reduce the average delay for 12.05% in peak hour and 19.96% in nonpeak hour. Sensitive analysis is also conducted to investigate the variation of right-turning ratio on the intersection operational performance. [ABSTRACT FROM AUTHOR]

The sensor location problem is of particular importance when planning the allocation of limited field equipment intended to be used for advanced traffic management systems and traveller information services. The locations within a network that satisfy specific goals need to be carefully selected, based on predefined goals related to the effective collection of data and the subsequent estimation of traffic related information. The detection of traffic volumes is mainly associated with two purposes, the travel time and the Origin–Destination (O–D) trip matrix estimation. In this context, this paper presents a quadratic programing model, able to determine the optimal location of tracking sensors. The model is implemented in the urban road network of the city of Thessaloniki (Greece) in which specific number of sensors is installed and utilized for real-time travel time information provision. The proposed methodology models the sensor location problem under the general framework of a set covering problem, which is one of the most popular optimization problems and has been applied in many industrial problems. The results of the case study in Thessaloniki reveal that the proposed model defines the optimal location of the limited number of sensors in such a way that the network, which is created having all sensors as origin or destination of all possible paths, represents to great extent (87% of the traffic flow along the major paths) the traffic volumes of the whole road network of the city. [ABSTRACT FROM AUTHOR]

Speed has been identified for a long time as a key risk factor in road traffic. Inappropriate speeds contribute to a relevant part of road crashes, and then to the mortality and disabilities resulting from them. Starting from this consideration this paper investigates road safety by analysing operating speed, which is the 85th percentile speed. Particularly, two regression models are proposed to predict operating speeds for different road elements related to specific road conditions. The case study is represented by a two-lane rural highway. Smartphone-equipped vehicles were used to evaluate the operating speed for each element of the analysed road segment. Continuous speed data were recorded by the vehicles driven by users with different driving behaviours. Since the lack of safety is often linked to an inconsistency roadway geometric design, we effected a preliminary quantitative design consistency evaluation that confirmed the need of having accurate experimental measures of operating speed or appropriate models for predicting it. We propose two types of operating speed models: one for estimating speed profiles for horizontal curves, and the other one for tangents. According to both models, operating speed is predicted by the combination of an independent variable representing a geometric characteristic (curve radius for the curves and length for the tangent elements) and an independent variable relating to the speed, and specifically the operating speed of the previous road element. The models show a good predictive capability, and can be considered as a useful tool for operators and technicians for road management. [ABSTRACT FROM AUTHOR]

This paper presents two redundancy indices for road traffic network junctions and also an aggregated network redundancy index. The proposed redundancy indices could be implemented to identify optimal design alternatives during the planning stage of the network junctions whereas the aggregated network redundancy index could assess the best control and management policies under disruptive events. Furthermore, effective measures of network redundancy are important to policy makers in understanding the current resilience and future planning to mitigate the impacts of greenhouse gases. The proposed junction indices cover the static aspect of redundancy, i.e. alternative paths, and the dynamic feature of redundancy reflected by the availability of spare capacity under different network loading and service level. The proposed redundancy indices are based on the entropy concept, due to its ability to measure the system configuration in addition to being able to model the inherent uncertainty in road transport network conditions. Various system parameters based on different combinations of link flow, relative link spare capacity and Relative Link Speed (RLS) were examined. However, the two redundancy indices developed from the combined RLS and relative link spare capacity showed strong correlation with junction delay and volume capacity ratio of a synthetic road transport network of Delft city. Furthermore, the developed redundancy indices responded well to demand variation under the same network conditions and supply variations. Another case study on Junction 3A in M42 motorway near Birmingham demonstrated that the developed redundancy index is able to reflect the impact of the Active Traffic Management (ATM) scheme introduced in 2006. [ABSTRACT FROM PUBLISHER]

At signalized intersections, short left-turn lanes are often installed to improve capacity and level of service. However, the blockage or overflow of short left-turn lane often occurs when signal phasing is not coordinated with lane configuration and traffic demands. On the basis of probability theory, the probability of no blockage and overflow of the short left-turn lane is formulated under the three common signal phase plans when the lane next to a short left-turn lane is a through lane. For this case, it is shown that the left-through phasing should be adopted for the study approach when the short left-turn lane is very short and the volume of left-turn vehicles is high enough, and the leading or lagging left-turn phasing should be adopted for the study approach when the short left-turn lane is long enough and the volume of left-turn vehicles is low enough. To optimally allocate the space for each short left-turn lane and the green time for each lane group, a new optimization model is put forward to maximize intersection capacity and guarantee an acceptable level of service for each movement for isolated signalized intersections with short left-turn lanes. The usage of this model is demonstrated by an illustrative example. The results indicate that the intersection capacity can be maximized under the same level of service by integrating the configuration of traffic lanes and the split of signal phases. Finally, the procedure for using the proposed model is given for practical applications. [ABSTRACT FROM PUBLISHER]

The research aims to explore the effects of geometric road features on driver speed behaviour in order to identify unsafe road segments where high reductions in speed between successive road elements occur. The sample involves two-lane rural roads on flat terrain (vertical grade less than 5%) in Southern Italy, totalling 184 km without spiral transition curves between the tangent segments and circular elements. The testing was carried out on 567 study sites, of which 248 are on circular curves and 319 on tangents. Speed data collection was carried out in environmental and traffic conditions using a laser. The conditions were the following: dry roads, free flow conditions, daylight hours and good weather conditions. The main goal was to calibrate and validate different operating speed prediction models: a) one model on tangent segments; b) one model on circular curves; c) only one model to be used at the same time on tangents and circular curves. The validation process involved almost 10% of the total road network length, that was removed from the calibration phase. The speed measurements of each of the first two datasets (a,b) were grouped into ten homogeneous substrates while for the remaining dataset (c) sixteen substrates were defined by using a hardc-means algorithm. Two statistical criteria were used to remove anomalous operating speed values from each group of three datasets, namely, the Chauvenet criterion and the Vivatrat method. The first criterion was preferred in the final process of model selection. The results of the first filtering procedure showed more homogeneous samples that guaranteed a higher correlation coefficient and lower residuals of the predictive models during the validation phase than the Vivatrat method. The models were developed using an Ordinary Least Squares (OLS) method. The explanatory variables were total segment length, lane width, curvature of the road element, the curvature change rate on homogeneous road segments, and the number of residential driveways per km. ANOVA and additional synthetic statistical parameters were assessed to check the effectiveness of using a single general model to predict operating speeds at the same time on tangents and on circular curves alike. The results suggested the reliability of this hypothesis and its effectiveness in bringing advantages during the application phase. [ABSTRACT FROM AUTHOR]

Newly-constructed and reconstructed highway pavements under the effect of traffic loading and climatic severity deteriorate progressively and need preservation intervention after a certain number of years following their construction. In the literature, the term ‘rest period’ has been used to refer to the number of years that elapse between the construction completion to the application of first major repair activity. The rest period is a critical piece of information that agencies use to not only plan and budget for the first major repair activity but also to develop more confidently, their life-cycle activity schedules for life cycle costing, work programming, and long-term plans. However, the literature lacks established procedures for predicting rest periods on the basis of pavement performance thresholds. In the absence of such resources, highway agencies rely mostly on expert opinion for establishing the rest periods for their pavement sections. In addressing this issue, this paper presents a statistical methodology for establishing the rest periods for newly-constructed or reconstructed pavements. The methodology was demonstrated using empirical data from in-service pavements in a Midwestern State in the US. The paper’s results show that the rest periods of newlyconstructed and reconstructed highway pavements are significantly influenced by their functional class, surface material type, traffic loading level, and climate severity. [ABSTRACT FROM AUTHOR]

Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea to avoid traffic instabilities and to homogenize traffic flow in such a way that risk of accidents is minimized and traffic flow is maximized. There is a need to predict traffic flow data for advanced traffic management and traffic information systems, which aim to influence traveller behaviour, reducing traffic congestion and improving mobility. This study applies Artificial Neural Network for short term prediction of traffic volume using past traffic data. Besides traffic volume, speed and density, the model incorporates both time and the day of the week as input variables. Model has been validated using actual rural highway traffic flow data collected through field studies. Artificial Neural Network has produced good results in this study even though speeds of each category of vehicles were considered separately as input variables. [ABSTRACT FROM AUTHOR]

Impact of Information and Communications Technologies (ICTs) on sustainable transport development is indisputable. It can be tested through various methods. The identification and detailed analysis of specific types of ICT solutions, case studies approach or scenarios analysis are examples of perspectives for impact assessment that can lead to the proof that successful applications of ICT solutions entails optimised, more accessible, less resource consuming and less emission intensive transport. The impact of ICTs in travel induction and substitution and resulting decarbonisation effect is difficult to assess isolated from other social, economic and technologic drivers. Financial applicability reflects initial investment cost as well as operation maintenance costs. Organizational feasibility refers primarily to the necessary changes in organisation and conduct of operations created by introduction of ICTs. The social factor results from user and public acceptance or lack of it. User acceptance is combination of many sub factors of which most important are: D2D travel time, D2D travel costs, comfort and convenience, safety and security. The objective of the article is to present the applicability of ICT solutions in passenger transport from the perspective of transport users taking into consideration real case studies from different European background. These case studies were identified as a result of specific selection process in order to receive a complex and differentiated sample. The first element of the selection process was the identification of ICT solutions to be applied in case studies. The next element was the choice of regions corresponding to varied economic and geographic characteristics. In addition, cultural factors have a strong impact on the behaviour of users. The resulting multidimensional factor matrix allows for the selection of best fitting case studies, which have potential to cover most of the ICT applications. Five European settings are selected for in-depth research. Each case represents different geographic, social and economic area, which forms a good European sample across differentiated setups. Case studies are supported by user surveys. Surveys allow for direct answers regarding user attitudes towards proposed ICTs. Based on this approach findings could be reported. The main conclusion is that users in various regions with very different characteristics as to the wealth, GDP levels, geography, and cultural back-grounds represent surprisingly similar attitudes towards ICTs. Specific findings regarding different types of solutions and different type of users are presented in the article. The analysis of selected case studies shows also that they could offer solution to many of transport sector problems including key issues from transport policy agenda: environment, mobility or accessibility. The paper is based on the authors research conducted within COMPASS project (Optimised co-modal passenger transport for reducing carbon emissions, project co-funded by the European Commission within the Seventh Framework Programme). [ABSTRACT FROM PUBLISHER]

We present a novel approach to developing a vehicle communication platform consisting of a low-cost, open-source hardware for moving vehicle data to a secure server, a Web Application Programming Interface (API) for the provision of third-party services, and an intuitive user dashboard for access control and service distribution. The CloudThink infrastructure promotes the commoditization of vehicle telematics data by facilitating easier, flexible, and more secure access. It enables drivers to confidently share their vehicle information across multiple applications to improve the transportation experience for all stakeholders, as well as to potentially monetize their data. The foundations for an application ecosystem have been developed which, taken together with the fair value for driving data and low barriers to entry, will drive adoption of CloudThink as the standard method for projecting physical vehicles into the cloud. The application space initially consists of a few fundamental and important applications (vehicle tethering and remote diagnostics, road-safety monitoring, and fuel economy analysis) but as CloudThink begins to gain widespread adoption, the multiplexing of applications on the same data structure and set will accelerate its adoption. [ABSTRACT FROM PUBLISHER]

The information about the environment and the precise guidance of visually impaired people is the basis for their safe movement of the traffic network. Therefore, the information and communication services should be adapted to this group of users. The services based on the advanced information and communication technologies provide the visually impaired persons with information about the environment while moving along the traffic network. This paper analyses the currently available information systems of users when moving traffic network, and the currently most services based on new ICT (Information and Communications Technology). The analysis was carried on a representative sample of the City of Zagreb (Croatia) in involving all interest groups of visually impaired people. Based on defined user requirements is proposed a new services based on NFC (Near Field Communication) and RTLS (Real-Time Locating Systems). Testing and analysing the efficiency of single information and communication technologies have been performed on the actual traffic network system of the City of Zagreb. The users of the Croatian Society for Promotion and Development of Tiphlotechnology (Hrvatska Udruga za Promicanje i Razvoj Tiflotehnike–HUPRT,http://www.huprt.hr) participated in checking the efficiency of single technologies and services. [ABSTRACT FROM PUBLISHER]

This work suggests a framework for modeling the traffic emissions in urban road traffic networks that are described by the Network Fundamental Diagram (NFD) concept. Traffic emission is formalized in finite spatiotemporal windows as a function of aggregated traffic variables, i.e. Total Travel Distances (TTDs) in the network and network average speed. The framework is extended for the size of an urban network during a signal cycle – the size of a window in which the network aggregated parameters are modeled in the NFD concept. Simulations have been carried out for model accuracy analysis, using the microscopic Versit + Micro model as reference. By applying the macroscopic emission model function and the traffic modeling relationships, the control objective for pollution reduction has also been formalized. Basically, multi-criteria control design has been introduced for two criteria: maximization of the TTD and minimization of traffic emissions within the network. [ABSTRACT FROM AUTHOR]

The paper analyses the impact of the road micro-profile on the duration and the type of the vehicle wheel contact with the road surface driving at different speed. The selected vehicle bicycle model describes vertical displacements of front and rear wheels and their suspension as well as the impact of the vehicle body motion and longitudinal oscillation. International Roughness Index (IRI) and micro-profile irregularities of the road section analysed in the paper were identified using specialized road testing equipment. The experimental investigations measuring the vehicle suspension displacement and the body acceleration were carried out. Frequency characteristics of suspension motion and regularities of vertical movement of the wheel were identified after dividing the investigated road section according to driving modes. The analysis into the wheel contact with the road surface and identified correlations enable to determine the vehicle stability on selected quality roads. [ABSTRACT FROM AUTHOR]