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Considering the influence of slope sections and random degradation of the communication function of cooperative adaptive cruise control vehicles and the effect of the cooperative adaptive cruise control vehicle group driving, a linear stability criterion for heterogeneous traffic flow composed of cooperative adaptive cruise control vehicles and humanly-driven vehicles on slopes is derived, and a parameter sensitivity analysis is carried out. On this foundation, the safety of traffic flow on two-lane roads up and down hills is simulated while considering the lane-changing behavior of automobiles. The stability study shows increased cooperative adaptive cruise control vehicle penetration and uphill gradient will help improve traffic flow stability. In contrast, the increase in the downhill slope will intensify the transmission amplitude of the disturbance. When vehicle starting sensitivity is 2.5, and the gradient is 60, the minimum cooperative adaptive cruise control vehicle penetration required for mixed traffic flow to maintain stability on a downhill at any initial equilibrium speed is 85%, and the minimum penetration required on an uphill is 73%, and this proportion decreases with the increase in the uphill gradient and increases with the rise in the downhill slope. According to the safety study, increasing cooperative adaptive cruise control vehicle penetration and implementing lane-changing rules will improve traffic flow safety. Compared with the straight section, under the same conditions, the traffic flow safety of the uphill section is the best, and the safety of the downhill section is poor, which is consistent with the stability analysis results. This study is of great significance for future traffic control strategies for mountain roads. [ABSTRACT FROM AUTHOR]

Perception response time (PRT), the time required for drivers to respond to roadway events, is a concept that is derived from scientific psychology. The concept is now fundamental to human factors and ergonomics (HFE), to the design of transportation systems, and is often called upon in forensic analyses of traffic crashes. Yet the application of PRT is neither simple nor straightforward, especially when evaluating human performance under difficult conditions, which is typically the situation in forensic analysis of traffic crashes. This article revisits these fundamental limitations by reviewing the scientific history of PRT, highlighting its utility and evolution as well as important constraints on its application. Common violations of these constraints and their ramifications for providing accurate and defensible information in forensic practice are discussed. We conclude that driving behavior is both complex and variable, and no single PRT value, adjusted or not, will ever be universally applicable. [ABSTRACT FROM AUTHOR]

The complex environment at grade crossings and the severe collision consequences give rise to the concern of safety condition at crossings among traffic control authorities. Optimizing conventional devices and applying emerging technologies are worthwhile measures to improve the safety conditions at grade crossings. In this study, a flashing-light running (FLR) warning system was proposed to reduce crossing violation and improve performances of drivers at flashing-light-controlled grade crossings (FLCGCs). Forty-four fully licensed drivers aged between 30 and 48 years participated in a driving simulator study to investigate the efficacy of two countermeasures of the system: proposed design of signs and pavement markings (PSM) for grade crossing, and two-stage in-vehicle audio warning (IVAW) technology. A range of flashing light trigger timing and two foggy conditions were designed in this experiment to test the system applicability. Drivers' gender and vocation were considered as well to examine drivers' adaptation to the new proposed system. Five variables were collected and analyzed in this study to investigate the effectiveness of the system, i.e., drivers' compliance, approaching mean speed, brake reaction time, deceleration, and red-to-crossing time. Results showed that drivers' driving performances were improved in both PSM only condition and PSM + W condition. The FLR warning system could eliminate the negative effects of foggy weather and reduce gender differences in driver behaviors to some extent. These findings suggested that the FLR warning system has a potential to reduce the probability of grade crossing collisions. [ABSTRACT FROM AUTHOR]

In research on traffic injury prevention, young male drivers willing to take risks are known as "young problem drivers" and have been identified as the greatest road safety challenge. This intersectional study draws on interviews and participant observation, and employs a masculinity perspective to explore how 12 young, male drivers who were injured in severe accidents assess driving after their accidents and ways in which they construct their identities as disabled men. While the participants cited their accidents as a turning point that prompted a change in their attitudes and practices regarding driving, they often continued to engage in deviant driving practices, especially speeding. In addition, the men tended to distance themselves from the social category of disability. We propose that the field of traffic injury prevention would benefit from supplementing the biological approach in the research literature with cultural perspectives on the internal logics and prevailing masculinity discourses that guide the choices of young, male drivers. Also, we argue that the men's negotiation of disability illustrates the stigma still attached to the social category of disability. [ABSTRACT FROM AUTHOR]

Realistic microscopic traffic simulation is essential for prospective evaluation of the potential impacts of new traffic control strategies. Freeway corridors with interacting bottlenecks and dedicated lanes generate complex traffic flow phenomena and congestion patterns, which are difficult to reproduce with existing microscopic simulation models. This paper discusses two alternative driving behavior models that are capable of modeling freeways with multiple bottlenecks and dedicated lanes over an extended period with varying demand levels. The models have been calibrated using archived data from a complicated 13-mile long section of the northbound SR99 freeway near Sacramento, California, for an 8-hour time period in which the traffic fluctuated from free-flow to congested conditions. The corridor includes multiple bottlenecks, multiple entry and exit ramps, and an HOV lane. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. The main behavior that should be captured for successful modeling of such a complex corridor includes the anticipative and cooperative driver behavior near merges, lane preference in presence of dedicated lanes, and variations in desired headway along the corridor. [ABSTRACT FROM AUTHOR]

Purpose: Glaucoma affects different aspects of vision including visual field. This prospective observational study aims to collect details of driving license (DL) renewal procedure (in an urban metro in India) among patients with diagnosed glaucoma and the method of reporting of vision-related requirements during renewal.Methods: One-hundred patients with diagnosed glaucoma above 40 years, having valid DL (with at least one renewal cycle), were included. Patients with other ocular comorbidities were excluded. Driving Habits Questionnaire and a questionnaire about license renewal were administered. Driving eligibility was compared to international guidelines.Results: Study population included patients with 69% early, 29% moderate, and 2% advanced glaucoma. Sixteen percent of patients had stopped driving. Legal license renewal procedure was bypassed by 45%. Form-1 was not submitted by 43% and 49% did not submit Form-1A at the time of renewal. Only 7.01% mentioned about glaucoma in the self-declaration form. None were asked about their visual field during renewal. Among 61 patients who submitted a medical certificate, the undersigning doctor was an ophthalmologist in only six patients. Thirty percent patients with valid Indian DL would not have satisfied International College of Ophthalmologists guidelines. Driving difficulties were experienced by 44%, more so in advanced glaucoma (F (1, 82) = 22.12, P < 0.001).Conclusion: Vision-related testing at the time of renewal of DL is inadequate in India. Chronic eye diseases such as glaucoma are commonly not self-declared or detected at pre-renewal testing. Clear-cut guidelines about visual requirements and implementation are required to prevent road traffic events because of vision-related errors. [ABSTRACT FROM AUTHOR]

Highlights • Trajectories play a critical role in CF model calibration and validation. • Developed a pattern recognition algorithm to differentiate driving regimes. • Developed a method to distinguish between free flow and CF sections. • Applied the algorithm to US-101 and reconstructed I-80 data. • Most trajectories in these datasets belong to acceleration, deceleration, and following. Abstract Vehicular trajectories are widely used for car-following (CF) model calibration and validation, as they embody characteristics of individual driving behaviour (each trajectory reflects an individual driver). Previous studies have highlighted that the trajectories should contain all the major vehicular interactions (driving regimes) between the leader and the follower for reliable CF model calibration and validation. Based on Dynamic Time Warping and Bottom-Up algorithms, this paper develops a pattern recognition algorithm for vehicle trajectories (PRAVT) to objectively, accurately, and automatically differentiate different driving regimes in a trajectory and then select the most complete trajectories (i.e. trajectories containing a maximum number of regimes). PRAVT is rigorously tested using synthetic data and then applied to the NGSIM data. We have observed that the NGSIM data are dominated by the trajectories which contain only three regimes, namely acceleration, deceleration, and following, 77% of the trajectories lack the standstill regime, and no trajectory in the NGSIM data is complete. These findings' impact on how to properly utilize NGSIM data can be profound. Given the extensive use of the NGSIM data in the traffic flow community, this paper also provides insights about the types of regimes contained in each trajectory of the NGSIM data. [ABSTRACT FROM AUTHOR]

This driving simulator study investigated the impact of perceptual countermeasures on driving behavior by creating perceptual effects via pavement markings. Two different marking schemes (i.e. Optical Circles and Optical Bars) were tested separately for road transitions between rural and urban areas where the speed limit reduces from 70 kph to 50 kph. The tested treatments were intended to achieve combined perceptual effects (i.e. increase drivers' attention, perceptual speed and perceptual road narrowing effect) independently. Data were analyzed for 44 participants (30 men and 14 female). The study results showed that the speed was reduced significantly for both road marking treatments, however, the Optical Circle scenario in which circles with increasing size were implemented was the most effective solution. Moreover, standard deviation of acceleration/deceleration and lateral position were not found to be significant due to the treatments. This indicates that drivers did not decelerate or evade vehicles unsafely when confronting the road markings. The obtained results recommend Optical Circles to policy makers for further evaluation as a low-cost speed management tool. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate about the driving style in different types of roads, with the final aim to establish some domains of road safety based on speeds and accelerations. We identify a tool that can provide an objective indicator of driving behaviour, represented by the percentage of points outside the domain: the more the percentage of points outside the domain is, the more the driving risk is. The proposed work is supported by an experimental survey consisting in the monitoring of real paths ran by drivers. For each path, the instantaneous speed and acceleration along the pattern were registered by means of GPS-enabled smartphones. Three different roads placed in the South of Italy were analysed, and specifically, a minor rural arterial road, a principal rural arterial road, and a freeway. The registered parameters were used for defining a safety domain which establishes if the driver had a safe behaviour or an unsafe one. The proposed methodology starts from the dynamic equilibrium of the vehicle, and arrives to establish a curve expressing the relationship between the speed and the acceleration vectors, which represent the domain within which the driver behaviour can be considered as safe. Having different formulations concerning the friction factor for the three different kinds of road, we obtained three different curves, or domains. Interesting findings were obtained by comparing the results from the proposed methodology for the different types of roads. As expected, the limits of the domain are quite different among the roads, because each road has its own characteristics. [ABSTRACT FROM AUTHOR]

When driving a vehicle, the driver must allocate adequate attention to the demands of driving in order to be safe. Based on analyses of vehicle data, driving environment data, and videos of the road ahead, a driving task demand prediction model based on real-time road traffic data was established in this study. Assessments of driving task demands allowed for the validation of this model. In addition, intervention strategies were proposed for distractions from in-vehicle secondary tasks at different levels of demand. The analysis showed that at a high driving task demand, the control of all in-vehicle information systems (IVIS), except for the playing of radio or CD, should be warned against or forbidden. Meanwhile, distractions from secondary tasks originated from 91% of the in-vehicle foreign objects, and 67% of the in-vehicle facilities can be avoided by formulating precaution strategies. This study provides methods and technical support for the management of driver distraction precaution. [ABSTRACT FROM AUTHOR]

In traffic systems, cooperative driving has attracted the researchers’ attention. A lot of works attempt to understand the effects of cooperative driving behavior and/or time delays on traffic flow dynamics for specific traffic flow models. This paper is a new attempt to investigate analyses of linear stability and weak nonlinearity for the general car-following model with consideration of cooperation and time delays. We derive linear stability condition and study how the combinations of cooperation and time delays affect the stability of traffic flow. Burgers’ equation and Korteweg de Vries’ (KdV) equation for car-following model considering cooperation and time delays are derived. Their solitary wave solutions and constraint conditions are concluded. We investigate the property of cooperative optimal velocity (OV) model which estimates the combinations of cooperation and time delays about the evolution of traffic waves using both analytic and numerical methods. The results indicate that delays and cooperation are model-dependent, and cooperative behavior could inhibit the stabilization of traffic flow. Moreover, delays of sensing relative motion are easy to trigger the traffic waves; delays of sensing host vehicle are beneficial to relieve the instability effect to a certain extent. [ABSTRACT FROM AUTHOR]

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions. [ABSTRACT FROM AUTHOR]

An extensive body of research has found that angry and aggressive driving are both significantly related to crash involvement. There has also been a large body of research investigating the situational factors related to angry and aggressive driving, but one interesting question that has not yet been answered is whether the enforcement of traffic laws causes or reduces angry and aggressive driving. The independent region of Northern Kosovo represents a unique opportunity to investigate the impact of a lack of traffic enforcement on driving behaviour. Therefore, the present study set out to investigate whether the presence of traffic enforcement has a significant impact on the level of driver anger and aggressive driving. Registered owners of motor vehicles in Northern Kosovo and Serbia were both sent a questionnaire which contained the 28-item Dula Dangerous Driving Index (DDDI) and the 21-item UK Driving Anger Scale (UKDAS). This found that anger was higher in two of the four driving anger factors (direct hostility and progress impeded) and two of the three DDDI factors (risky driving & aggressive driving). Furthermore, the present study found that the lack of police enforcement was a significant predictor of both aggressive and risky driving, even after the driving anger and demographic variables had been partialled out. Therefore, it appears that introducing or increasing traffic enforcement may be one method of reducing aggressive and risky driving behaviour. [ABSTRACT FROM AUTHOR]

The design of a mountain expressway includes many special road sections, such as the combination of sharp bends and curved slopes, which may easily cause traffic accidents. Speed limit is an effective means of ensuring the safety of travellers. A novel speed limit formulation method was proposed in this study to improve the scientific level of the speed limit standard of a mountain expressway. First, the model of vehicle driving stability in the critical state of side rollover and sideslip was established. Second, the stabilities of vehicle side rollover and sideslip on the horizontal curve and slope curve were analyzed by considering the influence of vehicle dynamic characteristics. Finally, a specific speed limit implementation scheme for a multi-curve road section was proposed with an example. Results demonstrate that when the curvature radius of the road is large, the critical speed of vehicle side rollover and sideslip is high. In particular, the critical speed of vehicle side rollover is high when the gradient value of the transverse slope of the road section is considerable within a limited range. Meanwhile, the critical speed of vehicle sideslip is high when the frictional resistance coefficient of the pavement is high. The gradient value of the longitudinal slope of the curved slope section slightly affects the critical speed of vehicle rollover and sideslip. This study provides a strong theoretical basis for setting a safe driving speed limit in curve road sections. [ABSTRACT FROM AUTHOR]

Trust in automation is a key determinant for the adoption of automated systems and their appropriate use. Therefore, it constitutes an essential research area for the introduction of automated vehicles to road traffic. In this study, we investigated the influence of trust promoting (Trust promoted group) and trust lowering (Trust lowered group) introductory information on reported trust, reliance behavior and take-over performance. Forty participants encountered three situations in a 17-min highway drive in a conditionally automated vehicle (SAE Level 3). Situation 1 and Situation 3 were non-critical situations where a take-over was optional. Situation 2 represented a critical situation where a take-over was necessary to avoid a collision. A non-driving-related task (NDRT) was presented between the situations to record the allocation of visual attention. Participants reporting a higher trust level spent less time looking at the road or instrument cluster and more time looking at the NDRT. The manipulation of introductory information resulted in medium differences in reported trust and influenced participants' reliance behavior. Participants of the Trust promoted group looked less at the road or instrument cluster and more at the NDRT. The odds of participants of the Trust promoted group to overrule the automated driving system in the non-critical situations were 3.65 times (Situation 1) to 5 times (Situation 3) higher. In Situation 2, the Trust promoted group's mean take-over time was extended by 1154 ms and the mean minimum time-to-collision was 933 ms shorter. Six participants from the Trust promoted group compared to no participant of the Trust lowered group collided with the obstacle. The results demonstrate that the individual trust level influences how much drivers monitor the environment while performing an NDRT. Introductory information influences this trust level, reliance on an automated driving system, and if a critical take-over situation can be successfully solved. [ABSTRACT FROM AUTHOR]

Issues addressed Cyclists' perceptions of harassment from motorists discourages cycling. This study examined changes in cyclists' reporting of harassment pre- to post-introduction of the Queensland trial of the minimum passing distance road rule amendment (MPD-RRA). Methods Cross-sectional online surveys of cyclists in Queensland, Australia were conducted in 2009 (pre-trial; n=1758) and 2015 (post-trial commencement; n=1997). Cyclists were asked about their experiences of harassment from motorists while cycling. Logistic regression modelling was used to examine differences in the reporting of harassment between these time periods, after adjustments for demographic characteristics and cycling behaviour. Results At both time periods, the most reported types of harassment were deliberately driving too close (causing fear or anxiety), shouting abuse and making obscene gestures or engaging in sexual harassment. The percentage of cyclists who reported tailgating by motorists increased between 2009 and 2015 (15.1% to 19.5%; P<0.001). The percentage of cyclists reporting other types of harassment did not change significantly. Conclusions Cyclists in Queensland continue to perceive harassment while cycling on the road. The amendment to the minimum passing distance rule in Queensland appears to be having a negative effect on one type of harassment but no significant effects on others. So what? Minimum passing distance rules may not be improving cyclists' perceptions of motorists' behaviours. Additional strategies are required to create a supportive environment for cycling. [ABSTRACT FROM AUTHOR]

The present paper proposes a conceptual framework for the driver’s visual–spatial perceptual processes. Based on a theoretical analysis of driving proposed by Gibson and Crooks [(1938). A theoretical field-analysis of automobile-driving.The American Journal of Psychology,51, 453–471. doi:10.2307/1416145], the developed field of safe travel (FoST) framework suggests that at any moment the driver constructs a “field” by integrating two perceptual entities: (i) the possible available spatial fields for locomotion and (ii) the driver’s mental image of ego-vehicle outer-line and motion dynamics. This framework is used to reinterpret in a unified way a number of disparate research findings reported in the literature concerning specific driving sub-tasks (e.g. lane keeping and car following). It is argued that the FoST framework may be used to predict drivers’ behaviour in various traffic/situation environments based on their prioritisation between the above two perceptual entities. Implications of the proposed framework at a theoretical and practical level, in view of the future of driving with multiple levels of automation, are also discussed. [ABSTRACT FROM AUTHOR]

Dangerous driving behavior detection can be used in video surveillance systems to identify dangerous patterns, such as Abrupt Double Lane Change (ALC), Retrograde Driving (RD), and Illegal U-Turn (IT), for traffic design, traffic management, and law enforcement. The purpose of this study is to develop a detection method of dangerous driving behavior based on video surveillance. First, a novel method named trajectory histogram is proposed. A set of trajectory histograms (e.g., control points histogram and velocity histogram) is constructed to represent vehicle motion. Then, a frequently used feature selection method named Minimum Redundancy and Maximum Relevance (mRMR) is introduced to evaluate the most representative trajectory histograms for dangerous driving behavior detection. In addition, a hybrid algorithm, Particle Swarm Optimization-Support Vector Machine (PSO_SVM), is then developed to identify dangerous driving behavior. To validate the performance and effectiveness of the proposed method, several experiments are conducted. The results show that mRMR is better than other representative methods, namely Conditional Mutual Information Maximization (CMIM), Mutual Information Maximization (MIM), and ReliefF, for evaluating the most representative trajectory histograms. Based on the most representative trajectory histograms, the detection accuracy rate of dangerous driving behavior using PSO_SVM is superior to those of the most frequently used classifiers—Naïve Bayesian Classifier (NBC), k-Nearest Neighbor (kNN), and C4.5 decision tree. In addition, we find that the proposed method outperforms the two common approaches for dangerous driving behavior detection in video surveillance systems. Therefore, the proposed method can be widely applied to detect dangerous driving behavior in video surveillance systems. [ABSTRACT FROM PUBLISHER]

In rapidly developing economies, like urban India, where road traffic injury rates are among the world's highest, the corporate workplace offers a non-traditional venue for road safety interventions. In partnership with a major multinational corporation (MNC) with a large Indian workforce, this study aimed to elicit local employee perspectives on road safety to inform a global corporate health platform. The safety attitudes and behaviours of 75 employees were collected through self-report survey and focus groups in the MNC offices in Bangalore and Pune. Analysis of these data uncovered incongruity between employee knowledge of safety strategies and their enacted safety behaviours and identified local preference for interventions and policy-level actions. The methods modelled by this study offer a straightforward approach for eliciting employee perspective for local road safety interventions that fit within a global strategy to improve employee health. Study findings suggest that MNCs can employ a range of strategies to improve the road traffic safety of their employees in settings like urban India including: implementing corporate traffic safety policy, making local infrastructure changes to improve road and traffic conditions, advocating for road safety with government partners and providing employees with education and access to safety equipment and safe transportation options. [ABSTRACT FROM AUTHOR]

Conclusive evidence has justified great importance of energy management strategies in the performance and economy of plug-in hybrid electric vehicles (PHEVs). This article pays attention to improve adaptive equivalent consumption minimization strategy (A-ECMS) for parallel PHEV based on driving behavior recognition and real time traffic information prediction. Three main efforts have been made to distinguish our work from exiting research. Firstly, a hierarchical driving behavior model is constructed, providing in-depth knowledge about behavior generation, transmission, and consequence. Secondly, an online driving behavior classification method is designed. The proposed method is the coefficient result of offline driving behavior study based on self-report driving behavior questionnaire (DBQ) and online driving behavior discrimination by BP neural network. Thirdly, an improved adaptive equivalent consumption minimization strategy (IA-ECMS) is formulated based on identified driving behavior and predicted real time traffic information. The IA-ECMS can realize equivalent factor tuning instantaneously and reasonably. The simulation results indicate the proposed energy management strategy holds potential in fuel economy improvement than A-ECMS. [ABSTRACT FROM AUTHOR]

Under the traffic environment of the Internet of Vehicles, especially with the development of vehicle-to-vehicle technologies (i.e., V2V), drivers not only frequently perceive the vehicle information for preceding vehicles but also can actively check the real-time information of following vehicles with the assistance of V2V technologies. However, those traditional traffic flow models where driving behaviors are driven only by the preceding vehicle information are no longer suited to describing this situation. Therefore, a bidirectional cellular automaton model is proposed under active bidirectional looking (ABDL) context, which involves the actively obtained succeeding vehicle information and includes two special cases (i.e., the forward-looking only (FLO) and backward-looking only (BLO)). Meanwhile, a methodology of giving the sensitivity coefficients in the randomization probability of braking is introduced, which helps categorize drivers into three different sensitivity types (i.e., aggressive, normal, and conservative). Subsequently, various kinds of homogeneous and heterogeneous vehicle fleets are generated depending on the combinations of stimulation type (i.e., ABDL, FLO, and BLO) and the sensitivity types, whose safety performance can be evaluated by the average danger coefficients. Finally, through numerical experiments, it is concluded that considering both the preceding and succeeding vehicle information under V2V while driving is conducive to improving the safety performance, and the vehicular flow state, stimulation type, sensitivity type, and orders between different stimulation or sensitivity types have an important effect on the safety performance. [ABSTRACT FROM AUTHOR]

Measures of traffic organization and traffic management in school zones, key protection areas for traffic safety, have been increasingly discussed by government administrations at all levels and researchers as well. Juveniles' trips occur frequently near school areas, especially in primary and secondary school zones. The sensitive topic of these vulnerable road users encountering traffic accidents tends to draw the whole society's attention. In this regard, the paper analyzed different traffic characteristics of 20 primary school zones in Beijing. With the starting point of traffic safety in the area, the paper divided these school zones by type, which was then verified preliminarily reliable and proper, by means of field measurement and driving simulation test, with speed characteristics as the major basis for judgment. By doing this, the authors look forward to providing a theoretical basis for carrying out measures of traffic organization and traffic management. [ABSTRACT FROM AUTHOR]

Large numbers of traffic accidents were experienced on the road networks of Arab Gulf Countries including United Arab Emirates (UAE). This had resulted in enormous loss of lives and economy. This article through using Abu Dhabi city, UAE capital as a case study is aiming to understand the reasons behind such safety problem through analysing a large accidents data-set extending over the period from 2008 to 2013. The traffic accidents data-set was obtained from Abu Dhabi traffic police department records and covers wide range of accident's attributes. A wide spectrum of accident attributes was analysed in the paper including but not limited to the time of accident, accident location, type of accident, reasons behind the accident, driver characteristics, road conditions, and many other accident attributes. A specific reasoning for each of these attributes was given by authors. Furthermore, recommendations to enhance the safety levels were introduced. [ABSTRACT FROM AUTHOR]

This study aim to determine the proportion of traffic rule infractions in Cali, Colombia, in places where a road traffic injury (RTI) occurred. Description of videotaping of sites where a person was injured in an RTI in 2009. Counts of road users and infractions were established for each road user group and were compared using a Z-test. They were found 13,491 users, distributed as follow: 8.9% were pedestrians, 4.6% cyclists, 24.6% motorcyclists, and 61.8% were automobile drivers. The most frequent traffic violation among motorcyclists was transiting on lines designated for other vehicles (55.2%). Among cyclists, the most frequent violations were transiting without a helmet (99.2%) and not wearing the designated vest (100%). Among pedestrians, crossing streets at prohibited places (77.3%), even at sites where a pedestrian bridge was present (72.7%), represented two common violations. Vulnerable road users committed more traffic infractions than automobile drivers (p < 0.001). High rates of traffic rule infractions among vulnerable road users were observed. Studies to better understand the occurrence of these behaviours and the promotion of effective interventions are warranted. [ABSTRACT FROM AUTHOR]

Under certain circumstances, drivers fail to notice changes in electronic speed limits. A video-based study was performed to reveal which countermeasures would improve drivers' ability to detect changes in electronic speed limits. Countermeasures included leaving electronic signs blank prior to a speed limit change and adding motion signals by means of flashing amber lights or a wave. A video representing a motorway was shown repeatedly to 255 participants. They were instructed to press the space bar when detecting a change. The video was viewed 13 times before the speed limit changed. Results showed that leaving signs blank prior to the change instead of displaying speed limits continuously did not alter change detection, whereas flashers and waves eroded detection of the changed speed limit. This suggests that using flashers and waves to attract attention to electronic signs in fact decreases people's ability to process the information contained in the signs. [ABSTRACT FROM AUTHOR]

A driver receives most of environmental information through his vision. The distribution of drivers' visual attention in different driving environment has an important effect on driving workload and traffic safety. The study on the distribution of drivers' visual attention may result in a more realistic, objective and reliable assessment of traffic safety. Based on various curve radii in mountain expressway, real vehicle experiments are carried out in this study and the fixation duration percentage, fixation number percentage, average fixation duration in the X and Y visual angles are recorded and analysed. The results show that smaller curve radius result in larger mental workload of drivers and more visual attention to the interior side of the expressway when turning. The mental workload is more significant when turning left than right. With the increase of curve radius, the range of visual angle becomes bigger. [ABSTRACT FROM AUTHOR]

To connect microscopic driving behaviors with the macro-correspondence (i.e., the fundamental diagram), this study proposes a flexible traffic stream model, which is derived from a novel car-following model under steady-state conditions. Its four driving behavior-related parameters, i.e., reaction time, calmness parameter, speed- and spacing-related sensitivities, have an apparent effect in shaping the fundamental diagram. Its boundary conditions and homogenous case are also analyzed in detail and compared with other two models (i.e., Longitudinal Control Model and Intelligent Driver Model). Especially, these model formulations and properties under Lagrangian coordinates provide a new perspective to revisit the traffic flow and complement with those under Eulerian coordinate. One calibration methodology that incorporates the monkey algorithm with dynamic adaptation is employed to calibrate this model, based on real-field data from a wide range of locations. Results show that this model exhibits the well flexibility to fit these traffic data and performs better than other nine models. Finally, a concrete example of transportation application is designed, in which the impact of three critical parameters on vehicle trajectories and shock waves with three representations (i.e., respectively defined in x - t , n - t and x - n coordinates) is tested, and macro- and micro-solutions on shock waves well agree with each other. In summary, this traffic stream model with the advantages of flexibility and efficiency has the good potential in level of service analysis and transportation planning. [ABSTRACT FROM AUTHOR]

Problem, research strategy, and findings: Planners commonly recommend compact development in part as a way of getting people to drive less, with the idea that less driving will lead to more sustainable communities. Planners base their recommendations on a substantial body of research that examines the impact of compact development on driving. Different studies, however, have found different outcomes: Some studies find that compact development causes people to drive less, while other studies do not. I use meta-regression analysis to a) explain why different studies on driving and compact development yield different results, and b) combine different findings from many studies into reliable statistics that can better inform planning practice. I address the following questions: Does compact development make people drive less, and if so, how much less? I find that compact development does make people drive less, because most of the compact development features I study have a statistically significant negative influence on driving. The impact, however, is fairly small: Compact development features do not appear to have much influence on driving. My findings are limited to some extent because they are derived from small sample sizes. Takeaway for practice: Planners should not rely on compact development as their only strategy for reducing driving unless their goals for reduced driving are very modest and can be achieved at a low cost. [ABSTRACT FROM PUBLISHER]

Because the stability of the automatic driving system can be guaranteed by only using the single information of the location of vehicle. So the traditional design of sliding mode lane keeping controller seldom use both the information of position and angular speed. But in aircraft control, the signal of angular speed was widely used to increase the damping ration and stability of the system, so a kind of sliding mode with the hybrid information of location and angular speed was designed to solve the lane keeping problem based on the simplified model of automatic driving system. Because of the introducing of angular speed, so the stability and safety were greatly improved. And considering the uncertainty of the system model, the adaptive control strategy was designed and the stability was proved by constructing a Lyapunov function method. Finally, detailed simulation analysis with random perturbation was done, and the method with both information of location and angular speed and the method with only information of location was compared and analyzed to testify the rightness and effectiveness of the proposed hybrid method. [ABSTRACT FROM AUTHOR]

This research proposes a fuzzy model built to predict the track paths of a motor vehicle on a two-lane road and two-way traffic. The purpose of this study stems from the awareness that the position of the vehicle within the cross-section hardly coincides with the axis of the lane but deviates from this one because of some conditions generally not provided in the road standards. To solve this problem, the authors prepared an instrumented vehicle, measuring many variables during some trials in a rural road located in Sicily, Italy. The resulting database was treated at first with subtractive clustering techniques to correctly size the membership functions and rules without the subjective help of an analyst. Therefore, the fuzzy model was built only on the basis of the measured data, and the result was the position of the vehicle within the cross-section of the examined road. This research can help the analyst to look for the real cause of user's misbehavior even when the variables involved are fully respectful with the road standard to modify or eliminate disturbing elements in the understanding of the road by the users. [ABSTRACT FROM AUTHOR]

This study illustrates the ways to make driving behaviors, i.e. the experiential prevention and intervention in defensive driving, more efficient. The exercises chosen in the prevention phase prepare the drivers for the examination situation, and also for the preventive driving of the vehicle, while the experiential training optimizes their reactions in case of a side-slip. The results thus obtained underline the importance of these two types of interventions in the change of the manner in which drivers react in traffic. [ABSTRACT FROM AUTHOR]

This paper firstly show that 2 Dimensional Intelligent Driver Model (Jiang et al., 2014) is not able to replicate the synchronized traffic flow. Then we propose an improved model by considering the difference between the driving behaviors at high speeds and that at low speeds, which is in the framework of three-phase traffic theory. Simulations show that the improved model can reproduce the phase transition from synchronized flow to wide moving jams, the spatiotemporal patterns of traffic flow induced by traffic bottleneck, and the concave growth pattern of traffic oscillations (i.e. the standard deviation of the velocities of vehicles increases in a concave/linear way along the platoon). Validating results show that the empirical time series of traffic speed obtained from Floating Car Data can be well simulated as well. [ABSTRACT FROM AUTHOR]

The traditional vehicle mobility is restricted to the driver habits and the line-of-sight. The new-emerging connected vehicles enable information exchange with each other at vicinity, which will undoubtedly bring a greatly positive effect on the vehicle mobility pattern. In this paper, we propose to modeling and analyzing the vehicle mobility patterns respectively driven by traditional drivers and connected drivers. We perform the extensive simulations to explore the statistical differences between two mobility patterns and the underlying reasons through comparing to the real vehicle trace datasets. The results show that they behave quite diversely at the concerned aspects, e.g. degree distribution, clustering coefficient, topological shortest path, topological coefficient, and vehicle density, and also we find that the connected vehicles are well distributed and contribute a relieved traffic congestion situation. [ABSTRACT FROM AUTHOR]

The approach to spot speed prediction in two-lane highways followed in this study aims to evaluate the effects of a comprehensive set of speed factors, with a special focus on the geometric characteristics of the road segment to which the element belongs. Two flexible models were developed for different types of roads based on a stochastic frontier formulation in which the maximum operating speed is estimated as a function of road geometrics, and the one-sided disturbance accounts for diversity in driving behavior and vehicle characteristics, allowing the estimation of any percentile speed. The models are applicable to horizontal curves and tangents and consider both on-site characteristics and aggregated variables characterizing the road segment. The results show a clear influence of segment features on different percentile spot speeds, revealing that recent driving experience and expectations about the quality of the geometric design influence the way a driver approaches a specific road element. Additionally, this study contributes to addressing some of the limitations of existing speed models identified in the literature. [ABSTRACT FROM AUTHOR]

Driving behavior from vehicle interactions, such as acceleration, deceleration, and stop-and-go, is highly associated with traffic environment and safety conditions. This study is intended to investigate the connection between traffic environment and safety, more specifically, vehicle emissions and crash potential occurring in freeway traffic. Individual vehicle trajectory data collected from the US-101 freeway are used to investigate the relationship. Vehicle emission and crash potential indices are derived to characterize traffic environment and safety conditions, respectively, and relate those indices using correlation and regression. The resultant findings reveal that vehicle emissions are positively correlated with crash potentials in a statistically significant relationship. The methodological process for vehicle emissions and crash potential estimation developed in this study is expected to be used to monitor vehicle emissions from traffic conflict potential. Correspondingly, the methodological process is also to evaluate traffic control technology and policy implementation for improvement of transportation system efficiency with the goal of transportation emissions reduction. [ABSTRACT FROM AUTHOR]

Simulating driving behavior in high accuracy allows short-term prediction of traffic parameters, such as speeds and travel times, which are basic components of Advanced Traveler Information Systems (ATIS). Models with static parameters are often unable to respond to varying traffic conditions and simulate effectively the corresponding driving behavior. It has therefore been widely accepted that the model parameters vary in multiple dimensions, including across individual drivers, but also spatially across the network and temporally. While typically on-line, predictive models are macroscopic or mesoscopic, due to computational and data considerations, nowadays microscopic models are becoming increasingly practical for dynamic applications. In this research, we develop a methodology for online calibration of microscopic traffic simulation models for dynamic multi-step prediction of traffic measures, and apply it to car-following models, one of the key models in microscopic traffic simulation models. The methodology is illustrated using real trajectory data available from an experiment conducted in Naples, using a well-established car-following model. The performance of the application with the dynamic model parameters consistently outperforms the corresponding static calibrated model in all cases, and leads to less than 10% error in speed prediction even for ten steps into the future, in all considered data-sets. [ABSTRACT FROM AUTHOR]

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]

Objective: The aim of this study was to quantify the impact of traffic density and verbal tasks on takeover performance in highly automated driving.Background: In highly automated vehicles, the driver has to occasionally take over vehicle control when approaching system limits. To ensure safety, the ability of the driver to regain control of the driving task under various driving situations and different driver states needs to be quantified.Methods: Seventy-two participants experienced takeover situations requiring an evasive maneuver on a three-lane highway with varying traffic density (zero, 10, and 20 vehicles per kilometer). In a between-subjects design, half of the participants were engaged in a verbal 20-Questions Task, representing speaking on the phone while driving in a highly automated vehicle.Results: The presence of traffic in takeover situations led to longer takeover times and worse takeover quality in the form of shorter time to collision and more collisions. The 20-Questions Task did not influence takeover time but seemed to have minor effects on the takeover quality.Conclusions: For the design and evaluation of human-machine interaction in takeover situations of highly automated vehicles, the traffic state seems to play a major role, compared to the driver state, manipulated by the 20-Questions Task.Application: The present results can be used by developers of highly automated systems to appropriately design human-machine interfaces and to assess the driver's time budget for regaining control. [ABSTRACT FROM AUTHOR]

In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions. [ABSTRACT FROM AUTHOR]

The growing proportion of older drivers in the population plays an increasingly relevant role in road traffic that is currently awaiting the introduction of automated vehicles. In this study, it was investigated how older drivers (⩾60 years) compared to younger drivers (⩽28 years) perform in a critical traffic event when driving highly automated. Conditions of the take-over situation were manipulated by adding a verbal non-driving task (20 questions task) and by variation of traffic density. Two age groups consisting of 36 younger and 36 older drivers drove either with or without a non-driving task on a six-lane highway. They encountered three situations with either no, medium or high traffic density where they had to regain vehicle control and evade an obstacle on the road. Older drivers reacted as fast as younger drivers, however, they differed in their modus operandi as they braked more often and more strongly and maintained a higher time-to-collision (TTC). Deterioration of take-over time and quality caused by increased traffic density and engagement in a non-driving task was on the same level for both age groups. Independent of the traffic density, there was a learning effect for both younger and older drivers in a way that the take-over time decreased, minimum TTC increased and maximum lateral acceleration decreased between the first and the last situation of the experiment. Results highlight that older drivers are able to solve critical traffic events as well as younger drivers, yet their modus operandi differs. Nevertheless, both age groups adapt to the experience of take-over situations in the same way. [ABSTRACT FROM AUTHOR]

Variable speed limits (VSL) are used more commonly around the globe lately. Although on a macroscopic level positive effects of VSLs have been reported, the caveat is that the impact of VSLs is very sensitive to the level of driver compliance. Thus far it is unknown whether all individual drivers are actually able to notice when a speed limit changes into another speed limit; a prerequisite for purposeful speed limit compliance in the first place. To simulate regular driving conditions, twenty-four participants were familiarised with a particular route by driving the same route in a driving simulator nineteen times on five separate days. Part of the route consisted of a motorway where VSL signs were regularly displayed above every driving lane. At drive nineteen, speed limits changed from 80 km/h to 100 km/h on four out of eight consecutive signs. After passing all signs, one expects 6.25% of the participants still to be unaware that the speed limit had increased (based on chance), while the results showed most participants had failed to notice the speed limit change (58.3%). Instead, they saw what they expected to see: a speed limit of 80 km/h. If the speed change had been vice versa, in other words from 100 km/h to 80 km/h, this would immediately result in speed offences, though not deliberately at all. [ABSTRACT FROM AUTHOR]

The effects of imagery-induced distraction on hazard perception and eye movements were investigated in 2 simulated driving experiments. Experiment 1: sixty participants viewed and responded to 2 driving films containing hazards. Group 1 completed the task without distraction; group 2 completed a concurrent imagery inducing telephone task; group 3 completed a non imagery inducing telephone task. Experiment 2: eye-tracking data were collected from forty-six participants while they reacted to hazards presented in 16 films of driving scenes. 8 films contained hazards presented in either central or peripheral vision and 8 contained no hazards. Half of the participants performed a concurrent imagery-inducing task. Compared to undistracted participants, dual-taskers were slower to respond to hazards; detected fewer hazards; committed more “looked but failed to see” errors; and demonstrated “visual tunnelling”. Telephone conversations may interfere with driving performance because the two tasks compete for similar processing resources, due to the imagery-evoking aspects of phone use. [ABSTRACT FROM AUTHOR]

The level of road safety of an entity (country, region, road etc.) is estimated using the number of accidents, as well as the rates that take into account the amount of exposure. Despite the interest in studying the relationship between economy and road safety, the lack of data regarding traffic volume or vehicle kilometers traveled (VKT) leads the researchers to use, as risk factors, other values which have an indirect association with traffic, like fuel consumption, GDP, household expenditure and number of vehicles. In Greece, the lack of traffic data, as a reliable and comparable exposure measure relevant to road safety, is a significant problem for researchers, as well as for decision-makers, when they try to estimate the road safety level in the country. This paper correlates economic conditions and road accident facts in the recession period of 2010 to 2013 and uses economic factors as an indicator of exposure, in order to evaluate the road safety level in the country during these years. A comparison between changes in the absolute number of accidents and rates produced from economic factors shows significant differences in the degree of improvement of road safety level in recent years. Specifically, the absolute numbers show a reduction of 31.4% in fatal accidents and 20.2% in total accidents (fatal, serious/light injuries) from 2010 to 2013, but the rates related to economic factors and consumer behavior give a less optimistic view of improvement, with a 2.1 to 3.2 times smaller reduction in fatal accidents and, in some cases, an increase of the rate of total accidents. According to these, the conclusion is that single indicators (and especially the number of accidents) have limited reliability, while the reduction is mainly an effect of traffic volume reduction or other circumstances and not a result of road safety measures. Also, a future development of the economy may lead to a significant deterioration of road safety level. This can serve as a warning message to policy makers, so as to prepare and implement an effective cost action plan to prevent a backward in road safety level. [ABSTRACT FROM AUTHOR]

Differences in driving behavior due to the presence of users familiar (or unfamiliar) with the road are considered in the road and traffic engineering. However, although considered, the matter is largely unexplored: there is a lack of theoretical foundations and data on determining the impact of route familiarity on accident rates, speed choice and risk perception. On the other hand, some literature studies confirm that route familiarity is influential on driving behavior, encouraging research in this sense. This paper reports the results of an on-road test carried out on a two lane rural road in the District of Bari in the Puglia Region (Italy) over six days of testing by following this time schedule: first four tests in four consecutive days, the fifth test in the ninth day after the first test and the sixth test in the twenty-sixth day after the first test. The main aim of the experiment was to find relationships between route familiarity and speed choice. In particular, speed data were analyzed by considering the influence of road geometry and human factors. The main finding is that speed choice seems to be affected by route familiarity: speed increases with the repetition of travels on the same route. The particular schedule used for the tests allows to consider the influence of memory on the speed behavior of the test drivers. Moreover, some relationships between changes in speed over days, road geometry and drivers’ attitudes were shown. [ABSTRACT FROM AUTHOR]

Car following modeling framework seeks for a more realistic representation of car following behavior in complex driving situations to improve traffic safety and to better understand several puzzling traffic flow phenomena, such as stop-and-go oscillations. Calibration and validation techniques pave the way towards the descriptive power of car-following models and their applicability for analyzing traffic flow. However, calibrating these models is never a trivial task. This is caused by the fact that some parameters, such as reaction time, are generally not directly observable from traffic data. On the other hand, traffic data might be subject to various errors and noises. This contribution puts forward a Cross-Entropy Method (CEM) based approach to identify parameters of deterministic car-following models under noisy data by formulating it as a stochastic optimization problem. This approach allows for statistical analysis of the parameter estimations. Another challenge arising in the calibration of car following models concerns the selection of the most important parameters. This paper introduces a relative entropy based Probabilistic Sensitivity Analysis (PSA) algorithm to identify the important parameters so as to reduce the complexity, data requirement and computational effort of the calibration process. Since the CEM and the PSA are based on the Kullback–Leibler ( K – L ) distance, they can be simultaneously integrated into a unified framework to further reduce the computational burden. The proposed framework is applied to calibrate the intelligent driving model using vehicle trajectories data from the NGSIM project. Results confirm the great potential of this approach. [ABSTRACT FROM AUTHOR]

Automated driving is gaining increasing amounts of attention from both industry and academic communities because it is regarded as the most promising technology for improving road safety in the future. The ability to make an automated lane change is one of the most important parts of automated driving. However, there has been little research into automated lane change maneuvers, and current research has not identified a way to avoid potential collisions during lane changes, which result from the state variations of the other vehicles. One important reason is that the lane change vehicle cannot acquire accurate information regarding the other vehicles, especially the vehicles in the adjacent lane. However, vehicle-to-vehicle communication has the advantage of providing more information, and this information is more accurate than that obtained from other sensors, such as radars and lasers. Therefore, we propose a dynamic automated lane change maneuver based on vehicle-to-vehicle communication to accomplish an automated lane change and eliminate potential collisions during the lane change process. The key technologies for this maneuver are trajectory planning and trajectory tracking. Trajectory planning calculates a reference trajectory satisfying the demands of safety, comfort and traffic efficiency and updates it to avoid potential collisions until the lane change is complete. The trajectory planning method converts the planning problem into a constrained optimization problem using the lane change time and distance. This method is capable of planning a reference trajectory for a normal lane change, an emergency lane change and a change back to the original lane. A trajectory-tracking controller based on sliding mode control calculates the control inputs to make the host vehicle travel along the reference trajectory. Finally, simulations and experiments using a driving simulator are conducted. They demonstrate that the proposed dynamic automated lane change maneuver can avoid potential collisions during the lane change process effectively. [ABSTRACT FROM AUTHOR]

This paper describes an equilibrium formulation for incorporating parking search into traffic network assignment models. The proposed model allows general network topologies and reflects uncertainty related to parking availability, including the possibility of cycling behavior as drivers search for parking. The equilibrium framework represents the mutual dependence between the probabilities of finding parking at different locations and the search processes employed by drivers to minimize total expected journey time (or cost). In this framework, network loading is represented by a system of nonlinear flow conservation networks, and feasibility and uniqueness issues are discussed. The equilibrium problem is formulated as a variational inequality and a convex combinations heuristic is proposed. Numerical results show that neglecting parking search can substantially underestimate network flows, and quantitatively demonstrate the relationship between parking duration effects and the cost of time spent walking relative to driving, and the expected driving and walking times. [ABSTRACT FROM AUTHOR]

Background: Most countries have detailed lists of traffic rules and elaborate legal regimes for penalizing drivers who break them. Previous research has suggested that drivers tend to drive more safely after receiving penalties for traffic infringements.Methods: We linked driver-level data on infringements and crashes in Queensland, Australia (1995-2010) with information on the licence histories of all drivers in the state. We used a case-crossover design to examine drivers' risk of crashing in the month following an infringement penalty. We also examined whether changes in crash risk following infringement penalties varied according to driver age and gender, type of infringement and whether the offender was at fault in a subsequent crash.Results: Drivers had higher risks of crashes following infringement penalties [odds ratio (OR) 1.32; 95% confidence interval (CI) 1.29-1.36], especially crashes in which the offender was at fault (1.41; 1.36-1.46). Crash risk relative to a comparable period was particularly high for teenage drivers (1.55; 1.34-1.78) and among drivers penalized for dangerous driving (3.19; 2.52-4.03) or driving under the influence of alcohol (1.99; 1.67-2.37). The risk remained relatively high for more than 6 months after the penalty, but declined steadily over this period.Conclusions: Crash risk among drivers in Queensland was higher, not lower, following receipt of penalties for traffic infringements. Penalties themselves are unlikely to increase crash risk. A more likely explanation is that penalties (or the corresponding infringements) mark episodes of risky driving. Our findings suggest that such episodes trounce any deterrent effect penalties may produce. [ABSTRACT FROM AUTHOR]