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Predicting the future velocity of vehicles is essential for the safety of autonomous driving and the Intelligent Transport System. This study investigates how the surrounding vehicles influence a driving vehicle. Based on the HighD dataset, a scenario that considers the current lane and the neighboring lanes is selected while the drivers' visual angles and visual gap angles along with other parameters in the dataset are characterized as features. To predict the velocity of a driving vehicle and calibrate the influence of surrounding vehicles, a Transformer-based model integrating the features of multiple vehicles is proposed, and different features are added to the layers while constructing the model. Moreover, the information from previous timestamps of the vehicle state is integrated to estimate the duration of the influences, since the influence of an incident is not instantaneous. In our experiments, we find that the duration of the influence on the driving state perfectly fits the driver's reaction time when maneuvers occur in the surrounding vehicles. In addition, we further quantify the importance of the influence on the vehicle velocity prediction based on the Random Forest and obtain some practical conclusions, for instance, the velocity of a vehicle is more influenced by the front vehicle in the left lane than that in the right lane, but is still mainly influenced by the front vehicle in the current lane. [ABSTRACT FROM AUTHOR]

Identification of vehicles violating a certain speed by measuring the speed of vehicles in a nonintrusive manner with low cost and good results is very important, as it directly contributes to helping the traffic police instead of using radar, lidar or other expensive devices, the use of video analysis to estimate the speed of vehicles involved in traffic accidents is becoming increasingly common. In most cases, the estimate is based on in situ reference measurements or data derived using photogrammetry techniques. In this research, the suggested method estimates the average vehicle speed via computing the distance between consecutive tires using the "Pixel Image Scale Coefficient" and converts the results to accurate measurements. Using an installed camera or a mobile phone device at video frames per second (fps of 30 frames per second, a mathematical function to identify the speed of a passing vehicle predicated on its motion pattern vector and transform that speed from measurements of pixels in succeeding frames to realistic measurements is presented. Three steps were used in this work to implement the technique: In the first stage, a vehicle is distinguished from other objects utilizing artificial intelligence, particularly the Aggregated Channel Features(ACF) vehicle detectors algorithm. In the second step, automobiles are monitored by tracking successive video frames and then the third step, which is the working core of this The research, is to calculate the speed of the detected vehicles in successive video frames through the proposed mathematical equation that mainly depends on the product of the obtained Euclidean distance, and then convert this result to what is proportional to the realistic measurements of speed, which really is km/h. The project work was produced on a 64-bit system with an Intel Core i7 processor using Matlab R2021a. The software was used to analyze a series of locally captured movies that were used as the data source for a data set used to calculate the average vehicle speed. The proposed program's results were compared with the established driving velocity in order to verify the findings. A simulation of a vehicle moving at a known speed was employed. The mistake rate as a result of the vehicle speeds varied from 1 to 5 km/h. [ABSTRACT FROM AUTHOR]

Definition: A modern roundabout is an intersection with a circulatory roadway at which the vehicle speed is low, and the traffic is continuous and circulating in one direction around the central island towards the exits at the approach legs. Modern roundabout design is an iterative process that is composed of the following steps: (1) the identification of the roundabout as the optimal traffic solution; (2) the definition of the number of lanes at the intersection based on the required capacity and the level of service; (3) the initial design of the roundabout geometry; (4) design vehicle swept path, the fastest path analysis, and visibility performance checks; and (5) detailed roundabout design if the results of the performance checks are in line with the design recommendations. Initial roundabout geometry design elements are not independent of each other; therefore, care must be taken to provide compatibility between them. An overview and a comparative analysis of the initial geometric design elements for suburban single-lane roundabouts defined in roundabout design guidelines and norms used in Croatia, Austria, France, the Netherlands, Germany, Serbia, and Switzerland is given in this entry. [ABSTRACT FROM AUTHOR]

The need to accurately estimate the speed of road vehicles is becoming increasingly important for at least two main reasons. First, the number of speed cameras installed worldwide has been growing in recent years, as the introduction and enforcement of appropriate speed limits are considered one of the most effective means to increase the road safety. Second, traffic monitoring and forecasting in road networks plays a fundamental role to enhance traffic, emissions and energy consumption in smart cities, being the speed of the vehicles one of the most relevant parameters of the traffic state. Among the technologies available for the accurate detection of vehicle speed, the use of vision‐based systems brings great challenges to be solved, but also great potential advantages, such as the drastic reduction of costs due to the absence of expensive range sensors, and the possibility of identifying vehicles accurately. This paper provides a review of vision‐based vehicle speed estimation. The terminology and the application domains are described and a complete taxonomy of a large selection of works that categorizes all stages involved is proposed. An overview of performance evaluation metrics and available datasets is provided. Finally, current limitations and future directions are discussed. [ABSTRACT FROM AUTHOR]

Due to the emergence of new technologies over the past decade, vehicle speed assistance systems in intelligent transportation systems have frequently been discussed. Up to now, a systematic literature review has not been presented to discover and evaluate the different vehicle speed assistance approaches for on‐road vehicles in intelligent transportation systems. To overcome this issue, this research identified peer‐reviewed articles published in the most well‐known libraries from 2011 to 2020. 79 primary studies were then projected and a systematic analysis of the selected literature was conducted. The findings show different driving goals, namely eco‐driving, safety, comfort, travel time improvement as well as the high‐level objectives addressed by vehicle speed assistance systems. The analytical discussions are provided to show different perspectives, properties and limitations of the existing solutions. This analysis allows to provide future challenges and directions in this field of research. [ABSTRACT FROM AUTHOR]

This paper presents a method based on Artificial Neural Networks for estimation of the vehicle speed. The technique exploits the combination of two tasks: a) speed estimation by means of regression neural networks dedicated to different road conditions (dry, wet and icy); b) identification of the road condition with a pattern recognition neural network. The training of the networks is conducted with experimental datasets recorded during the driving sessions performed with a vehicle on different tracks. The effectiveness of the proposed approach is validated experimentally on the same car by deploying the algorithm on a dSPACE computing platform. The estimation accuracy is evaluated by comparing the obtained results to the measurement of an optical sensor installed on the vehicle and to the output of another estimation method, based on the mean value of velocity of the four wheels. [ABSTRACT FROM AUTHOR]

This article presents an innovative method of diagnostics of rolling bearings used in the bearing nodes of motor vehicles, with the use of a prototype specialist stand. The tests were carried out based on a developed research plan, which included the impact of damage to the bearing and tyre of the vehicle, as well as the vehicle speed. Vibration accelerations were recorded in three measurement axes. Signal spectra were created based on the time courses of the vibration signals and were further analysed. The presented method is aimed at detecting excessive wear of rolling bearings in wheels from its early period. [ABSTRACT FROM AUTHOR]

The article presents research on the methods of crash velocity determination based on the Compact car class. The database used in the research is provided by the NHTSA (National Highway Traffic Safety Administration) and includes numerous frontal crash tests, which allowed the determination of the mathematical model parameters. Two methods are presented that enable the determination of vehicle velocity before the collision. The first researched method is the so-called inversed system method and is based on the assumption that the relationship between bk coefficient Cs is an inverse function. The second line of research focuses on the tensor product method, which is grounded in the Legendre polynomials, orthogonal on the interval [-1, 1] (Axler, 1997; Cheney and Kincaid, 2002). The article presents the calculation algorithm for both cases and the results with reference to the NHTSA database (Sharma et al., 2007; Siddall and Day, 1996). The application of the least square method provides more precise results in both cases than in previously researched solutions, with a slight advantage of the tensor product method. The obtained mean relative error of the velocity determination using the inverse system method is approximately 16,22% for the linear model and 10,58% for the nonlinear model. In the case of the tensor product method the errors for linear and nonlinear models are respectively 6,74% and 6,3%. [ABSTRACT FROM AUTHOR]

Highlights • Identifies causes of performance deterioration due to rough terrain. • Effects of fluctuations in the angular wheel speeds. • Effects of variations in vertical loading conditions. • Experimental and simulation results. • Good correlation between measured and simulated tyre force using FTire. Abstract The performance of Anti-lock Brake Systems (ABS) for vehicles deteriorate on rough terrains, due to fluctuations in the angular wheel speeds and in the vertical loading conditions of the tyre caused by the terrain inputs. In this paper, ABS braking performance on non-deformable rough terrain is investigated by performing experiments and simulations using a testing trailer and a validated multi-body dynamics model. The trailer was constructed using a Land Rover Defender chassis and installed with standard Land Rover braking components including an ABS modulator. It was found in the ABS tests performed, while using a standard Bosch ABS algorithm, that the ABS algorithm failed to perform optimally due to oscillations and irregularities that were present in the measurement of angular wheel speeds. Good correlation is found between the tyre forces measured and the forces simulated using an FTire model in MSC ADAMS software. A powerful platform was created for future off-road ABS investigation and development using both experiments and a simulation platform. [ABSTRACT FROM AUTHOR]

Sites with varying geometric features were analyzed to develop the 85th percentile speed prediction models for car and sports utility vehicle (SUV) at 50 m prior to the point of curvature (PC), PC, midpoint of a curve (MC), point of tangent (PT) and 50 m beyond PT on four-lane median divided rural highways. The car and SUV speed data were combined in the analysis as they were found to be normally distributed and not significantly different. Independent parameters representing geometric features and speed at the preceding section were logically selected in stepwise regression analyses to develop the models. Speeds at various locations were found to be dependent on some combinations of curve length, curvature and speed in the immediately preceding section of the highway. Curve length had a significant effect on the speed at locations 50 m prior to PC, PC and MC. The effect of curvature on speed was observed only at MC. The curve geometry did not have a significant effect on speed from PT onwards. The speed at 50 m prior to PC and curvature is the most significant parameter that affects the speed at PC and MC, respectively. Before entering a horizontal curve, drivers possibly perceive the curve based on its length. Longer curve encourages drivers to maintain higher speed in the preceding tangent section. Further, drivers start experiencing the effect of curvature only after entering the curve and adjust speed accordingly. Practitioners can use these findings in designing consistent horizontal curve for vehicle speed harmony. [ABSTRACT FROM AUTHOR]

Estimating longitudinal vehicle speed is required in a wide range of applications from road safety to vehicular emissions modelling. Each vehicle speed estimation method has specific challenges including the high cost of measurement equipment, the small range of vehicle models accessible for performing tests and the low resolution of data in time and space. Thus, the goals of this study are (a) to investigate the use of smartphones' integrated sensors as a convenient, reliable and powerful means of vehicle speed data collection which would mitigate the issues observed in previous methods, and (b) to propose a post-processing pipeline for generating vehicles' speed profiles based on the raw data captured by the proposed data collection method. Accordingly, a smartphone application is developed to facilitate the collection of vehicles' movement data, particularly inside tunnels and high-density urban areas, where state-of-the-art global positioning system (GPS) applications fail to record the desired data. Moreover, a post-processing pipeline is proposed for calculating vehicles' speed profiles and emissions from the raw smartphone acceleration data, and the full system is evaluated through a series of controlled experiments as well as simulations. [ABSTRACT FROM AUTHOR]

Rear-end collisions represent a quarter to one-third of the total number of collisions occurring on North American roads. While there are several methods to mitigate rear-end collision effects, one way is to warn drivers about impending events using forward collision warning (FCW) systems. At the core of any FCW algorithm is a trigger distance at which a message is relayed to the driver to avoid rear-end collisions. The main goal of this paper is to propose a warning distance model based on naturalistic driver following behavior. This was achieved by investigating car-following events within a critical time-to-collision range. A total of 5785 candidate car-following events were identified for the model development from 2 months of naturalistic driving study data of 63 drivers. Using regression analysis, the minimum warning distance was linked to several performance measures. It was found that the relative speed, the host vehicle speed, and the host vehicle acceleration can significantly affect the minimum warning distance. To assess the performance of the developed algorithm, it was compared to six of the existing FCW algorithms in terms of warning distances. The results of the developed algorithm were consistent with the other perceptual FCW algorithms. However, the warning distances of the proposed algorithm were less than the distances produced by the kinematic algorithms. The proposed algorithm could be used as a minimum threshold to trigger an alert for an FCW algorithm. Since the proposed algorithm is developed based on actual driving data, it is expected to be more acceptable by drivers. However, the algorithm needs further testing in real-life to validate this expectation. [ABSTRACT FROM AUTHOR]

In recent years, many schemes have been proposed to disseminate Emergency Warning Messages (EWMs) in VANETs. However, various problems such as broadcast storm, hidden terminal and connectivity issues still persist to reduce the efficacy of these systems. In this paper, we propose a novel Social Utility-based Dissemination Scheme (SUDS) for Emergency Warning Messages in Vehicular Social Networks (VSNs). We utilize social properties of nodes such as centrality, interests and friendships to mitigate broadcast storm and hidden terminal problems. Furthermore, we employ the hybrid architecture of VSNs to solve connectivity and contact duration-related issues in sparse and high mobility environments. For this purpose, we devise a dual-strategy-based mechanism, where vehicles communicate with each other in a distributed or centralized manner according to the required situation. In order to evaluate the performance of proposed scheme, we have conducted extensive experiments for a highway scenario under varying vehicular density, vehicular speed and distance, in comparison with the state-of-the-art dissemination schemes. Simulation results have demonstrated the superiority of SUDS over the compared protocols in terms of delivery ratio, transmission delay and total number of transmissions. We have also demonstrated the positive effects of hybrid architecture of VSNs on various network parameters. [ABSTRACT FROM AUTHOR]

The objective of this research study was to investigate and analyze the acoustical characteristics of asphalt concrete and cement concrete surface types by two noise measurement techniques: statistical pass-by (SPB) and Close Proximity (CPX) methods. A noise trailer was devised and manufactured as part of the CPX methodology to evaluate tyre/pavement noise interaction at source. Two national highway test sections covering over 11 km of asphalt and cement concrete surfaces were selected to carry out the noise measurements, and the effects of vehicle speeds and/or sizes on the overall noise profiles were investigated. The major contribution of this first of its kind study in India was the utilization of sophisticated tools and techniques to measure the tyre/pavement interaction noise at source through CPX, which helped correlate the influence of road surfaces on the generation of overall road traffic noise using SPB technique. The SPB method noise profiles revealed that the noise pressure levels increased with increasing vehicle speeds and weights. The noise trailer CPX findings corroborated the results obtained from the SPB method in that cement concrete surface produced a higher noise at source than that of the asphalt concrete surface by about 5 dBA. Further, there was about 5 dBA differential in noise between SPB and CPX methods for cement concrete pavement sections; also, there was about 10 dBA differential in noise between the two methods for asphalt concrete pavement stretches. [ABSTRACT FROM AUTHOR]

In this paper we address drivers’ actions prior to mandatory lane changes of long combination vehicles in dense highway traffic. The studied driver actions were: turn indicator activation, speed reduction and lateral intrusion. We categorised and compared the drivers’ actions with respect to the surrounding traffic cooperation and the level of urgency. Urgency here was based on the remaining distance to a targeted exit ramp. The results show that when the subject vehicle is close to the exit ramp, drivers used speed reduction significantly more than when the vehicle is further away. No significant difference was found for the use of lateral intrusion considering the distance to the exit ramp. As regards traffic cooperation, significant differences were found for both speed reduction and lateral intrusion. The drivers’ speed reduction and lateral intrusion were significantly greater when the surrounding traffic cooperation was low. [ABSTRACT FROM AUTHOR]

The fine-scale behavior of wildlife when crossing roads and interacting with traffic is likely to mirror natural responses to predation risk including not responding, pausing, avoiding, or increasing speed during crossing. We generated coarse-scale behavioral predictions based on these expectations that could be assessed with GPS radiotelemetry. We evaluated our predictions using an integrated stepselection analysis of wolverine (Gulo gulo luscus) space use in relation to spatially and temporally dynamic vehicle traffic on industrial roads in northern Alberta. We compared support for alternative models of road avoidance, increased speed near roads, and road avoidance and increased speed near roads. We predicted that wolverines would avoid roads and increase their speed near roads and that these behaviors would increase with traffic volume. We found that vehicle traffic was relatively low (0-30 vehicles/12 h) but important for explaining wolverine space use. Top winter and summer models indicated that wolverines avoided and increased speed near roads. Wolverine movement, but not avoidance, increased with traffic volume. We suggest that movement is a fine-scaled response that is more responsive to vehicle traffic than habitat selection. We show that roads, regardless of traffic volume, reduce the quality of wolverine habitats and that higher-traffic roads might be most deleterious. We suggest that wildlife behavior near roads should be viewed as a continuum and that accurate modeling of behavior when near roads requires quantification of both movement and habitat selection. Mitigating the effects of roads on wolverines would require clustering roads, road closures, or access management. [ABSTRACT FROM AUTHOR]

Most of the existing operating speed statistical models are applicable to individual design elements, particularly horizontal curves and tangents. A segment approach to operating speed has rarely been followed, with a few exceptions mainly related to the performance assessment of urban and freeway corridors, or design consistency studies using speed profiles built from successive design elements. This study introduces a new model to predict operating speeds in segments of two-lane highways. The maximum operating speed is given by a stochastic frontier function of the average daily traffic and road geometrics; the asymmetric disturbance accounts for the diversity in drivers’ behaviour and vehicle characteristics, allowing estimating any percentile speed. The model was calibrated using probe vehicle data from noncongested roads. The accuracy of the average daily traffic in representing the actual driving conditions was further validated using simultaneous speed-traffic measurements. The new model aims to assist practitioners in the evaluation of design consistency from a macroscopic perspective since the early stages of road planning and design, as well as to support the definition of speed limits at new or existing infrastructures. [ABSTRACT FROM AUTHOR]

To understand the vibration characteristics of rubber track system in traveling, this research studied the small harvester installed with rubber track system and the dynamic model reflecting vibration characteristics of rubber track system on the ground was constructed. Comparing analysis results with measured experimental data obtained from vehicle test, it is proved that the dynamic model established by theoretical analysis can correctly and effectively predict actual movement condition and vibration characteristics of rubber track system, especially at low test vehicle speeds. The relative difference between measured data of vibration acceleration obtained from real vehicle tests and the theoretical value was in the range of -1.2%-+18.2%. The vibration prediction and analysis method of rubber tracked vehicle was discussed in this study, and important basic data were provided for the research of comfort evaluation of working posture and lightweight design of rubber tracked mechanism. [ABSTRACT FROM AUTHOR]

Carrier–vehicle systems generally consist of a slow carrier (e.g., a ship) with a long operational range and a faster vehicle (e.g., an aircraft) with a limited operational range. The carrier has the role of transporting the faster vehicle and of deploying, recovering, and servicing it. The goal of the carrier–vehicle traveling salesman problem (CVTSP) is to permit the faster vehicle to visit a given collection of targets in the shortest time while using the carrier as a base for possible multiple trips. As a consequence, the carrier and vehicle should be synchronized. The visiting sequence of the targets is not given a priori. We present a mixed-integer, second-order conic programming (MISOCP) formulation for the CVTSP. Computational results are shown for the resolution of the model with commercial solvers. The MISOCP structure and the relationship to the traveling salesman problem are exploited for developing a ranking-based solution algorithm that outperforms the commercial solvers. [ABSTRACT FROM AUTHOR]

Many traffic accidents are due to an incorrect assessment of the current situation by the driver of the vehicle. With correct assessment of the situation, the driver has also to take into account a number of other factors. This article focuses on some of these factors such as the vehicle load, vehicle speed and curve radius. The first part of the article deals with the position of the vehicle center of gravity (CG), which has a major impact on the driving characteritics of the vehicle. The paper demonstrates the calculation of the maximum speed of a car model and truck model (without load and with load) when cornering. The center of gravity has an effect on the vehicle axles load distribution, and thereby on braking forces. This issue is dealt with in the second part of the paper. In the last part the calculation of the braking force as a function of the adhesion coefficient of the tires depending on the road surface is mentioned. The importance of the contribution consists in quantifying the impact of vehicle load on its driving characteristics. [ABSTRACT FROM AUTHOR]

This paper presents longitudinal and lateral velocity estimators by considering the effect of the suspension compliance (SC) at each corner (tire) for ground vehicles. The estimators are developed to be resilient to sensor measurement inaccuracies, model and tire parameter uncertainties, switchings in observer gains, and measurement failures. More particularly, the stability of the observer is investigated, and its robustness to road condition uncertainties and sensor noises is analyzed. The sensitivity of the observers’ stability and performance to the model parameter changes is discussed. Moreover, the stability of the velocity observers for two cases of arbitrary and stochastic switching gains is investigated. The stochastic stability of the observer in the presence of faulty measurements is also studied, and it is shown that if the probability of a faulty measurement occurring is less than a certain threshold, the observer error dynamics will remain stochastically stable. The performance of the observer and the effect of the SC are validated via several road experiments. [ABSTRACT FROM PUBLISHER]

The dynamic responses and failure modes of reinforced concrete bridge columns under vehicle collision have been numerically investigated in this study by using a numerical model verified against some experimental testing data. The numerical results show that the Peak Impact Force (PIF) from the collision is governed by the vehicle engine and the vehicle velocity while the impulse of the impact force is influenced by the initial momentum of the total mass. It is, therefore, suggested that not only the total vehicle mass and the vehicle velocity but also the engine’s weight need to be considered to determine the impact force on structures under vehicle collision. The engine’s mass significantly affects the peak impact force, the moment, the shear force and thus the damage of the column. The lateral impact force considerably affects the column axial force and a relation between the PIF and the increase of the axial force is proposed for the design purpose. The numerical model is able to reproduce and provide an explanation of most of the common failure modes observed in real impact events including flexural failure, shear failure, and punching shear damage. In addition, the influences of four different methods of the superstructure modelling, i.e. uniformly distributed load, lumped mass, simplified beam model, and 3D detailed model on the behaviour of the bridge column under vehicle impact are also investigated. [ABSTRACT FROM AUTHOR]

Several algorithms have already made to estimate vehicle’s speed using single camera. The main problem is the efficiency of these systems: processing is done on the whole image while moving objects occupy only a specific part. This work aims to present a technique of speed estimation based on one pixel’s width line processing. This line image can be extracted from a full size image or from a line camera in order to apply some processing like background subtraction, morphological operations, binarization and finally blob detection to allow tracking. This new approach enables implementation on low-cost platforms with low computing power. The size of data to process can almost be divided by the width’s image of a standard resolution camera, allowing a low data rate from acquisition. [ABSTRACT FROM AUTHOR]

Purpose: Speed estimation of drivers’ own vehicles and other vehicles on the road is an important task for drivers and is also crucial to the roadway safety. The objective of the study was to examine the effects of multiple factors such as image scale, speed, road type, driving experience, and gender on the speed perception of drivers’ own vehicles. Methods: Thirty participants consisted of 17 males and 13 females, including 13 without driving experience. All participants estimated the driving speed of 192 5-second video clips, which were selected from naturalistic driving recordings. The recorded driving speeds were evenly distributed across the entire range from 5mph to 65mph. Half of the selected video clips were recorded on wide roads and another half were recorded on comparatively narrow roads. Video clips were played on a large screen, with each clip shown in one of 4 image scales (100%, 75%, 50%, and 38% of the actual field of view in the real world). Results: Speed estimates were most accurate for the smallest image size (38% of the actual field of view). As the image size increased, the driving speed was increasingly underestimated. Participants with driving experience accurately estimated the driving speed on both wide and narrow roads whereas those without driving experience had greater underestimates on wider roads. Speeds were most accurately estimated within the range 25-35mph, but the speeds slower than the range tend to be overestimated and the speeds faster than the range are more likely to be underestimated. While males and females showed the same pattern across speed groups, females have greater estimation errors at the highest and lowest speed groups. Participants without driving experience showed increasing underestimation of speed as driving speed increased whereas participants with driving experience primarily underestimated the highest speeds. Conclusions: The present study shows the effect of multidimensional influential factors on perceived vehicle speed from drivers’ perspective. The results also have implications for driving simulation scenario design, driving simulator setup, and the assessment of speed control in simulated and naturalistic environments. [ABSTRACT FROM AUTHOR]

This study focuses on the comparison of operating mode distributions and other assumptions used in the estimation of transit bus emissions with the motor vehicle emission simulator (MOVES). The study area is the city of Montreal, Canada, where a single transit provider operates bus service along 220 routes. For this purpose, instantaneous speeds and passenger ridership data were collected onboard a total of 96 buses during the summer and fall of 2013. The data collection campaign covered eight bus routes in Montreal. The selected routes serve a range of corridor types capturing a variability in land use, road geometry, traffic flow, bus type, and transit service. Ultimately, the authors analyzed data from 3,702 road segments amounting to approximately 975.5 km (606 mi) with bus service. Significant differences between locally derived operating mode distributions and MOVES2014 default distributions were observed. The MOVES distributions assume a significantly larger portion of idling than that obtained from local data. The authors also investigated the drive cycle characteristics of different bus types and observed differences between standard and articulated buses, which are currently unaccounted for by MOVES. The findings illustrate the importance of collecting local bus data when estimating transit emissions. [ABSTRACT FROM AUTHOR]

In this paper, an integrated estimation and control system is developed for the stability and traction control of electric vehicles. A model predictive control technique is used to track the desired vehicle yaw rate while maintaining small lateral velocity and tire slip ratios. This paper proposes a new method to control the lateral stability of the vehicle. In this method, the lateral vehicle velocity is controlled indirectly by adjusting the reference yaw rate. This reduces the size of the prediction model and its computational complexity. The controller requires the vehicle’s lateral and longitudinal velocities as well as its tire forces for stability and traction control. This paper also proposes a novel velocity estimation scheme that uses the combined vehicle kinematics and tire model. The developed Kalman-based estimator provides velocities and lateral forces at each corner that are robust to changes in the road condition. The combined model-based and kinematic-based estimation structure mitigates some common problems of the widely used kinematic-based estimators such as the spikes and drifting issues. The stability of the proposed time-varying estimator is also investigated. The designed control and estimation scheme are experimentally validated on various driveline configurations and proven to provide reliable results. [ABSTRACT FROM AUTHOR]

Driving tests that have been performed for many years are not representative of actual vehicle operating conditions in terms of emissions and fuel consumption. This paper presents the research results of a new Worldwide harmonized Light duty Test Cycle (WLTC), that takes into account situations occurring in traffic inside and outside the city and on highways in Europe, India, Japan, Korea and USA. Conducted analysis demonstrated a multifractal nature of vehicle speed time signal, typical for he processes of asymmetric generalized multiplicative cascade. [ABSTRACT FROM AUTHOR]

In this paper, we focus on fully automatic traffic surveillance camera calibration, which we use for speed measurement of passing vehicles. We improve over a recent state-of-the-art camera calibration method for traffic surveillance based on two detected vanishing points. More importantly, we propose a novel automatic scene scale inference method. The method is based on matching bounding boxes of rendered 3D models of vehicles with detected bounding boxes in the image. The proposed method can be used from arbitrary viewpoints, since it has no constraints on camera placement. We evaluate our method on the recent comprehensive dataset for speed measurement BrnoCompSpeed. Experiments show that our automatic camera calibration method by detection of two vanishing points reduces error by 50% (mean distance ratio error reduced from 0.18 to 0.09) compared to the previous state-of-the-art method. We also show that our scene scale inference method is more precise, outperforming both state-of-the-art automatic calibration method for speed measurement (error reduction by 86 % – 7.98 km/h to 1.10 km/h) and manual calibration (error reduction by 19 % – 1.35 km/h to 1.10 km/h). We also present qualitative results of the proposed automatic camera calibration method on video sequences obtained from real surveillance cameras in various places, and under different lighting conditions (night, dawn, day). [ABSTRACT FROM AUTHOR]

The four-wheel independent drive electric vehicle (4WID EV) has some advantages, such as independent control of torque, easy measurement of torque, and multiple drive modes, the most significant of which are four-wheel drive and two-wheel drive modes. However, there is a problem with the switched drive mode, which would have an adverse effect on the precision of vehicle velocity estimation, the vehicle stability and comfort. In order to solve the problem, a control strategy with a switched drive mode is proposed. The control strategy is based on two vehicle velocity estimation algorithms. Between the two vehicle velocity estimation algorithms, the vehicle velocity estimation algorithm based on an unscented Kalman filter is designed in a four-wheel drive mode condition, whereas the vehicle velocity estimation algorithm based on the wheel rotational speed is designed in a two-wheel drive mode condition. Switchover of the two vehicle velocity estimation algorithms would cause a vehicle velocity saltus step, which has an adverse effect on vehicle control, so a vehicle velocity smoothing algorithm is proposed. Simulation results show that the control strategy not only reaches a high vehicle velocity control accuracy, it also improves the vehicle stability as well as the comfort. Furthermore, the results show that the proposed strategy can achieve stabilization with disturbance. [ABSTRACT FROM AUTHOR]

The number of electric vehicles in service throughout the world has increased from a few thousand in 2009 to some 740,000 in December 2014. These vehicles are often seen as a means of reducing climate and health damaging emissions, and their development is directly supported by some countries and endorsed by the EU. Aside from questions of rebound effects, embedded emissions and cleanness of electricity generation, there are unanswered questions about the energy performance of such cars under a range of driving conditions, and the results of existing studies are not easily interpretable by policymakers and drivers. This study uses the results of extensive dynamometer tests on eight commonly sold electric vehicles. It develops a multivariate model, with regression coefficients around 0.97, to map power demand and energy consumption for all likely combinations of speed and acceleration, producing accessible, easily interpretable displays. While electric vehicles are frequently marketed on the basis of their high acceleration, an important finding is that episodes of modest to high acceleration severely compromise their range and energy efficiency, regardless of speed. This also raises questions as to how well such vehicles perform in the erratic driving conditions of urban traffic. [ABSTRACT FROM AUTHOR]

Background Vehicle speed is a major contributor to road trauma, both in terms of increased crash risk and injury severity. In Australia, approximately one third of fatal crashes occur in speed zones of 100 km/h. This proportion has remained the same, despite the reduction in the number of road fatalities over the past decade. To drive further reductions in speed-related crashes, an improved understanding of the underlying determinants of speed choice is required. Method A community attitude survey designed to understand speed behaviour and attitudes towards speeding was distributed to a large (N = 5179) representative sample of drivers in Australia. Participants provided information regarding their normal speed choices across four different speed zones (40, 50, 60 and 100 km/h), beliefs about the risks and enforcement of speeding behaviour as well as technology to reduce speeding. Results Almost half of the sample (47%) reported exceeding the speed limit in 100 km/h zones, although only a small number of these drivers (<0.5%) did so by 11 km/h or more. Age and sex were related to speed limit non-compliance. Males were more likely to be classified as mid-level speeders, defined as being up to 10 km/h over the limit, and excessive speeders (11 + km/h over the limit). Younger drivers were also more likely to be non-compliant. When compared to compliant drivers, non-compliers perceived less risk of a serious crash, reported greater likelihood of exceeding the speed limit when they believed they would not be detected, and reported a higher level of social acceptability of speeding. Only one-third of the sample reported prior knowledge of intelligent speed assist (ISA) technology, however, once explained, the majority agreed it would be personally useful (64%). Speed non-compliers were somewhat less likely to support the usefulness of ISA than speed limit compliant drivers. Conclusion These findings can be used to target appropriate interventions and road safety messages, aimed at reducing speeding behaviour. Measures designed to address perceived social acceptability of speed behaviour, the increased crash risk associated with speeding, and the threat of detection are recommended. [ABSTRACT FROM AUTHOR]

Vehicle to vulnerable road user (VRU) crash is a large portion of traffic crashes in China Crash data from Beijing, China from the year 2009 to 2012 are used to identify the factors associated with the likelihood of vehicle to VRU crashes. 180 passenger-vehicles to VRU crashes are collected including 60 vehicle to pedestrian, 60 vehicle to bicycle and 60 vehicle to electric-bicycle cases. Then the statistics of the crash data are carried out, and the variables of human, vehicle, road, environment are investigated. Further, a logic regression model is established to analyse the significance of main contributing factors of these crashes. This paper describes the sample data, which includes time of incident, road user's age and gender, impact speed, crash pattern and VRU's head impact position. Also a comparative research among the three crash types is performed. According to the results, some characteristics of three crash types are different, such as the occurrence time, road position, impact speed and the impact position of VRU's head on the passenger-car. Moreover, chi-square test reveals that night-time travelling, crash type involving pedestrian and speeding of vehicle are significant related to non-fatal/fatal crashes. The logic regression model shows that night-time, intersection, older age of VRU and higher speed of vehicle increased the crash severity. [ABSTRACT FROM PUBLISHER]

One approach to motion control of autonomous vehicles is to divide control between path planning and path tracking. This paper introduces an alternative control framework that integrates local path planning and path tracking using model predictive control (MPC). The controller plans trajectories, consisting of position and velocity states, that best follow a desired path while remaining within two safe envelopes. One envelope corresponds to conditions for stability and the other to obstacle avoidance. This enables the controller to safely and minimally deviate from a nominal path if necessary to avoid spinning out or colliding with an obstacle. A long prediction horizon allows action in the present to avoid a dangerous situation in the future. This motivates the use of a first-order hold discretization method that maintains model fidelity and computational feasibility. The controller is implemented in real-time on an experimental vehicle for several driving scenarios. [ABSTRACT FROM AUTHOR]

This article represents an area closely connected to the analysis of road accidents. When the act of accident is being considered by an expert, it often happens that one participant of the accident causes that the other participant has to change suddenly the speed or direction of his/her drive to prevent possible collision. For a proper consideration of the driving manoeuvres we need to know the limit of a sudden change of speed or a sudden change of direction of drive. The limit of suddenness can be taken as the limit between a safe and already unsafe driving manoeuvre (braking, transverse motion) of the vehicle. The author tried to settle this limit by measurements with respondents who were asked to subjectively classify particular driving manoeuvres. For classification of the sudden change of speed, the intensity of deceleration was altered (3 m/s2, 5 m/s2, 7 m/s2, and maximum attainable deceleration amax m/s2). At classifying a sudden change of direction, we changed the trajectory of the vehicle's motion with transverse motion in one curve. As a result in the change of trajectory, the magnitude of side acceleration changed (values of side acceleration 2 m/s2, 3 m/s2, 4 m/s2 and 6 m/s2). From the results achieved it can be settled that the limit of a sudden change of vehicle's speed went round a half of maximally achievable braking deceleration of personal vehicles, at approximately 3,8 to 4,8 m/s2. The limit of a sudden change of direction of drive went between 2,7 and 3,5 m/s2.of vehicles' side acceleration. Achieved knowledge can be used in the sphere of road accident analysis when classifying driving manoeuvres of individual participants of the scene of accident. All measurements were taken with personal vehicles, thus it is possible to pay further attention to setting the limit of a sudden change of speed and direction of drive with utility vehicles, lorries and trucks, respectively. [ABSTRACT FROM AUTHOR]

Conventional vehicle routing problems (VRP) always assume that the vehicle travel speed is fixed or time-dependent on arcs. However, due to the uncertainty of weather, traffic conditions, and other random factors, it is not appropriate to set travel speeds to fixed constants in advance. Consequently, we propose a mathematic model for calculating expected fuel consumption and fixed vehicle cost where average speed is assumed to obey normal distribution on each arc which is more realistic than the existing model. For small-scaled problems, we make a linear transformation and solve them by existing solver CPLEX, while, for large-scaled problems, an improved simulated annealing (ISA) algorithm is constructed. Finally, instances from real road networks of England are performed with the ISA algorithm. Computational results show that our ISA algorithm performs well in a reasonable amount of time. We also find that when taking stochastic speeds into consideration, the fuel consumption is always larger than that with fixed speed model. [ABSTRACT FROM AUTHOR]

The rapid population growth and increasing economic activities have resulted in tremendous growth of vehicles which is considered as one of the primary factors responsible for increasing the traffic volume in metropolitan cities of developing countries, including Tiruchirapalli in India. The first phase of the project was the determination of reduced percentile spaced between the places Uraiyur and Tennur. The second phase of the project was the determination of the design of National Highway-227 in the area of Tolgate to Lalgudi to analyse the traffic in that road and to design that road according to it. The road safety level in National Highway is majorly based on two parameters, namely reduced percentile speed and design of that road. Thus the study is primarily confined in obtaining the percentile speed and design of the road. The design of the road is majorly based on the Indian Road Congress (IRC). [ABSTRACT FROM AUTHOR]

At non-signalized mid-block street crossings in China's cities, pedestrians often weave between motor vehicle flows. This paper investigated the influence patterns of the gender and age of pedestrians, the presence of a pedestrian group, vehicles' interference and the crossing direction on the crossing time at non-signalized mid-block street crossings in Changsha, China. The results show that the crossing speed is approximately 1-1.1 m/s; the crossing time increases with increasing age, and the crossing speed of a pedestrian will be quicker when the time gap between the pedestrian and the oncoming vehicle is smaller if he/she decides to cross. This paper also analyzed the crossing time pattern when pedestrians cross lane by lane and found that pedestrians spend the most time crossing the first lane and the least time crossing the middle lane, regardless of whether they are crossing from the curb to the central island or from the central island to the curb. The crossing speed is an important input to the design of pedestrian facilities, so these findings can be applied to the assessment of pedestrian crossing safety in China's cities and can provide a basis for the design of pedestrian crossing facilities. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article offers information on the importance of cross-sectional study design in injury research. Topics discussed include information of cross-sectional study which describes burden of the outcome of interest and its association with other variables; advantages of cross-sectional designs which involve ability to study multiple outcomes from a single study and easily replicated in other contexts; and measurement of the association between the outcome of interest and exposure variable.

Walking is encouraged by many transportation agencies as a sustainable mode that contributes to livable downtowns. Since pedestrians are the most vulnerable road users, safe and comfortable crosswalks are essential to ensure that pedestrian travel becomes an appealing alternative. In this context, the goal of this research is to study the traffic and vehicle trajectory factors that affect crosswalk law compliance and stopping distance from the crosswalk. The results of this research provide new insights into the relationships between traffic conditions, vehicle trajectory, and compliance rates. Results indicate that vehicle origin, vehicle type, stopping at upstream traffic lights, and changes in vehicle speed and headways are key factors to predict pedestrian crosswalk law compliance and stopping behavior; changes in vehicle speed and headways have the highest explanatory power. [ABSTRACT FROM AUTHOR]

The impacts of autonomous vehicles, coupled with greater inter-vehicle and system connectivity, may be far-reaching on several levels. They entail changes to (1) the demand and behavior side, (2) the supply of mobility services, and (3) network and facility operational performance. We focus here on their impact on traffic flow and operations, especially in mixed traffic situations in which autonomous vehicles share the road with regular, human-driven vehicles, along with connected vehicles that may also have some automated functions. These mixed traffic situations correspond to likely deployment scenarios of the technologies, especially in the long transition towards 100% deployment. We explain using elementary traffic science concepts how autonomous vehicles and connected vehicles are expected to increase the throughput of highway facilities, as well as improve the stability of the traffic stream. A microsimulation framework featuring varying behavioral mechanisms for the three classes of vehicles is introduced. The framework is used to examine the throughput and stability questions through a series of experiments under varying market penetration rates of autonomous and/or connected vehicles; at low market shares, the impacts are relatively minor on either throughput or stability. However, as market shares increase, autonomous vehicles exert a greater influence on both dimensions compared to the same shares of connected vehicles. Applications of the framework to examine the effectiveness of selected traffic management approaches are discussed, including dedicated lanes for autonomous vehicles (good only if its use is optional and when the market share of autonomous vehicles is greater than the percentage of nominal capacity represented by that lane), and speed harmonization. [ABSTRACT FROM AUTHOR]

In recent years, cellular floating vehicle data (CFVD) has been a popular traffic information estimation technique to analyze cellular network data and to provide real-time traffic information with higher coverage and lower cost. Therefore, this study proposes vehicle positioning and speed estimation methods to capture CFVD and to track mobile stations (MS) for intelligent transportation systems (ITS). Three features of CFVD, which include the IDs, sequence, and cell dwell time of connected cells from the signals of MS communication, are extracted and analyzed. The feature of sequence can be used to judge urban road direction, and the feature of cell dwell time can be applied to discriminate proximal urban roads. The experiment results show the accuracy of the proposed vehicle positioning method, which is 100% better than other popular machine learning methods (e.g., naive Bayes classification, decision tree, support vector machine, and back-propagation neural network). Furthermore, the accuracy of the proposed method with all features (i.e., the IDs, sequence, and cell dwell time of connected cells) is 83.81% for speed estimation. Therefore, the proposed methods based on CFVD are suitable for detecting the status of urban road traffic. [ABSTRACT FROM AUTHOR]

The speed of modern vehicles becomes higher and higher along with the development in supersonic technology and this brings challenge to detection by conventional radars. This article studies the problems encountered in high-speed target detection by conventional radars. Firstly, it analyzes the factors affecting the range migration of high-speed target echo envelope and gives three algorithm structures for high-speed target range migration. Secondly, this article reviews the characteristics of the three algorithm structures and, based on coordinate transformation, proposes a high-speed target detection algorithm using frequency compensation structure; this algorithm is capable of accomplishing first-order and second-order term compensation of high-speed target range migration. Finally, the validity and advantage of this algorithm are verified by experiment data. [ABSTRACT FROM AUTHOR]

There is little objective evidence about the extent older drivers’ are involved in speeding or factors that may influence this behaviour. Particular concern exists for the increasing number of older drivers with poor or declining cognitive and visual function. This study investigates whether a reduction in speeding forms part of the self-restrictive driving behaviour evident when older drivers experience poor cognitive and visual function. Driving data over 12 months were collected from 182 volunteers aged 75–94 years. Driving speed was estimated using Global Positioning System location, and speed limit data was based on a service-provider database. Speed events were defined as driving 1 km/h or more, with 3% tolerance, above a single speed limit, averaged over 30 s. Almost all participants (99%) were involved in speed events. While, 16–31% of participants experienced a meaningful decline in cognitive or visual function during the 12-months, these declines were not predictive of a change in speed events. Our results indicate speeding behaviour in this age group was highly prevalent, but less so for the oldest drivers whereby the rate of speed events was 7% lower per year older (IRR = 0.93, 95%CI = 0.89–0.96). Older drivers with worse function were less involved in speed events (unadjusted for distance driven) during 12 months of observation. Weekly distance driven decreased over the year by approximately 0.45 km with every week of monitoring for these older drivers. When distance driven was taken into account, decreased function was not predictive of involvement in speed events, indicating the reduction in speed events may be achieved by older drivers with lower function reducing distance driven. These results are important for developing policy to address speeding behaviour of the growing population of older drivers to reduce the incidence of crashes and resulting casualties. [ABSTRACT FROM AUTHOR]

Road safety is influenced by many factors; these factors include characteristics of the road, climate, traffic and, most importantly, vehicle speeds. Previous research shows that increases in speed are typically associated with an increased collision risk. Moreover, previous studies have also found relationships between road and traffic characteristics and collisions. In addition, these features have also been found to affect speeds. This paper aims to model all the aforementioned relationships simultaneously using a Structural Equation Modelling approach. More specifically, the paper attempts to model the relationship between average speed and collision frequency, while taking into account the effects of factors that confound the relationship. Moreover, the analysis attempts to assess the mediated effects that some variables have on collisions through their effects on speed. The data used in this study originated from 353 two-lane urban roads in the city of Edmonton, Canada. The average speeds were obtained from 35 million speed survey observations collected over a five-year period. The speed data are linked to the crash frequency at each location during the same time frame, along with the other factors (road, traffic and climate). The results show that, among others, average speed, volume, segment length, medians and horizontal curves all have statistically significant effects on collisions. On the other hand, shoulders, speed limits and vehicle-lengths are some variables that significantly influence speeds. The results also show that the effects of some variables on safety are indeed mediated through speeds (both partial and full mediation is observed). These findings provide valuable insight that may assist decision makers in choosing and developing alternative speed management strategies, which, in turn, could help improve safety. [ABSTRACT FROM AUTHOR]

This paper describes a turbo roundabout design procedure based on the rules of design vehicle movement geometry. Previous studies carried out on various junction types have shown that this design approach ensures the usage of optimal roundabout element dimensions as well as safety and comfort during driving. A five-step design procedure is suggested, including a detailed description of relevant influential parameters. They are choosing a design vehicle, implementing the initial roundabout scheme on which the vehicle swept path is analyzed, choosing a method of assigning input parameters for swept path requirements testing procedure, choosing optimal design elements of a standard turbo roundabout, and fastest path vehicle speed analysis. [ABSTRACT FROM AUTHOR]

Road dust emissions in Nordic countries still remain a significant contributor to PM 10 concentrations mainly due to the use of studded tyres. A number of measures have been introduced in these countries in order to reduce road dust emissions. These include speed reductions, reductions in studded tyre use, dust binding and road cleaning. Implementation of such measures can be costly and some confidence in the impact of the measures is required to weigh the costs against the benefits. Modelling tools are thus required that can predict the impact of these measures. In this paper the NORTRIP road dust emission model is used to simulate real world abatement measures that have been carried out in Oslo and Stockholm. In Oslo both vehicle speed and studded tyre share reductions occurred over a period from 2004 to 2006 on a major arterial road, RV4. In Stockholm a studded tyre ban on Hornsgatan in 2010 saw a significant reduction in studded tyre share together with a reduction in traffic volume. The model is found to correctly simulate the impact of these measures on the PM 10 concentrations when compared to available kerbside measurement data. Importantly meteorology can have a significant impact on the concentrations through both surface and dispersion conditions. The first year after the implementation of the speed reduction on RV4 was much drier than the previous year, resulting in higher mean concentrations than expected. The following year was much wetter with significant rain and snow fall leading to wet or frozen road surfaces for 83% of the four month study period. This significantly reduced the net PM 10 concentrations, by 58%, compared to the expected values if meteorological conditions had been similar to the previous years. In the years following the studded tyre ban on Hornsgatan road wear production through studded tyres decreased by 72%, due to a combination of reduced traffic volume and reduced studded tyre share. However, after accounting for exhaust contributions and the impact of meteorological conditions in the model calculations then the net mean reduction in PM 10 concentrations was only ∼50%, in agreement with observations. The NORTRIP model is shown to be able to reproduce the impacts of both traffic measures and meteorology on traffic induced PM 10 concentrations, making it a unique and valuable tool for predicting the impact of measures for air quality management applications. [ABSTRACT FROM AUTHOR]