Examining driver behavior using data gathered from red light photo enforcement cameras

INTRODUCTION: To develop an effective driver assistance system that can prevent red light violations, it is important to have a thorough understanding of contributing factors and circumstances surrounding such violations. METHODS: Red light violation behavior was examined using about 47,000 violation records that were captured by photo enforcement cameras from 11 signalized intersections in the city of Sacramento, California, over a four-year period. This examination identified factors with strong correlation to red light running behavior. RESULTS: Key findings based on Sacramento's red light violation records include: (a) younger drivers showed a higher tendency of running the red light and were more likely to commit such a violation at speeds above the posted speed limit; (b) off-peak time period between 8 p.m. to 5 a.m. had lower violation counts, but red light violators in this time frame had a higher propensity of racing through intersections at high speeds; (c) also during the time period between 8 p.m. to 5 a.m., violators showed a higher probability of entering intersections two or more seconds after the onset of red light; and (d) violators were less likely to cross high traffic-volume intersections with speeds greater than the posted speed limit. DISCUSSION: Sacramento's data suggest that some red light violators might have committed such an offense unintentionally. The top three violation speeds were all below 20 mph and more than 94% of red light runners crossed intersections within 2 seconds after the onset of the red light. IMPACT ON INDUSTRY: In the next several years, studies will be executed to assess whether a red light violation warning system can reduce "unintentional red light running" such as drivers who made incorrect judgment regarding the adequate time to clear the intersection and inattentive motorists who fail to observe the presence and status of the red light.     

Using European naturalistic driving data to assess secondary task engagement when stopped at a red light

Problem: Some evidence exists that drivers choose to engage in secondary tasks when the driving demand is low (e.g., when the car is stopped). While such a behavior might generally be considered as rather safe, it could be argued that the associated diversion of attention away from the road still leads to a reduction of situational awareness, which might increase collision risk once the car regains motion. This is especially relevant for texting, which is associated with considerable eyes-off-the-road-time. Nonetheless, it seems that previous research has barely addressed the actual engagement in secondary tasks while waiting at a red light (as compared to just addressing the tasks’ mere prevalence). Objective: The present study investigated secondary task engagement while stopped at a red light using European naturalistic driving data collected through the UDRIVE project. Attention was given to the whole engagement process, including simple prevalence and the tasks’ relation (in terms of start/end) to the red light period. Moreover, given that texting is one of the most problematic forms of distraction, it was characterized in more detail regarding glance behavior. Method: Videos of 804 red light episodes from 159 drivers were annotated. Glance behavior was also coded for a sub-set of 75 texting events and their matched baselines. Results, conclusions and practical applications: Drivers engaged in at least one secondary task across almost half of the annotated red light episodes. Drivers who texted while stopped spent most of the time looking at their cell phone. Consequently, drivers might not have been prepared for potentially unexpected events once the light turned green. Further, drivers concluded texting a considerable number of times well after the red light period, which has potential implications for traffic safety.     

Sight obstruction at at-grade pedestrian crossings: A review of the understanding of the meaning of zigzag lines

Parked and stopped vehicles in the vicinity of an at-grade pedestrian crossing obstruct visibility between pedestrians crossing the roadway and approaching vehicles, leading into vehicle–pedestrian crashes. Pavement zigzag line markings at at-grade pedestrian crossings, mostly at mid-block locations are used to restrict parking, stopping, and overtaking within the crossing, to enhance driver–pedestrian visibility. Yet, in some countries zigzag lines are used as advance markings to the crossing. Like any other traffic control device, zigzag lines’ effectiveness hinges on road user’s understanding of their meanings.This paper reviews the literature on the applications and understanding of these lines at pedestrian crossings. The meaning of zigzag line pavement markings at pedestrian crossings has not been well understood to some road users and road safety stakeholders worldwide. This dilemma may suggest that educating road users, especially drivers, may be necessary in order to improve pedestrian safety. Documented literature such as this one may also improve the understanding of these lines to road safety stakeholders. Despite of the importance of unobstructed sight between the pedestrian and the driver, treatments in the forms of signs and pavement markings require continuous education and enforcement. Practicing traffic engineers may want to place more emphasis on engineering treatments that are more effective in improving pedestrian safety, such as those that manages vehicle speeds, than relying heavily on traffic control devices that are often misunderstood and lesser effective such as zigzag lines.     

Red light violations at rural and suburban signalized intersections in Jordan

This case study investigated red light violations at rural and suburban signalized intersections in Jordan. Field observations were conducted at 15 signalized intersections located in different Jordanian regions: Amman, Irbid, and Zarqa. The results showed that, out of a total of 1,190 drivers who had a chance for violation, 153 (12.9%) drivers ran red lights. It was found that older drivers have less tendency for running red lights. Based on vehicle type, the analysis showed that truck drivers had the highest violation rate followed by small vehicles and then buses. The Y-shaped intersection had a higher percentage of violations as compared to the T- and cruciform-shaped intersections. The percentage of red light violations was found to be directly proportional to the subjects approach speed and inversely proportional to the conflicting traffic volumes.     

Evaluation of countermeasures for red light running by traffic simulator–based surrogate safety measures

Objective: The conflicts among motorists entering a signalized intersection with the red light indication have become a national safety issue. Because of its sensitivity, efforts have been made to investigate the possible causes and effectiveness of countermeasures using comparison sites and/or before-and-after studies. Nevertheless, these approaches are ineffective when comparison sites cannot be found, or crash data sets are not readily available or not reliable for statistical analysis. Considering the random nature of red light running (RLR) crashes, an inventive approach regardless of data availability is necessary to evaluate the effectiveness of each countermeasure face to face.

Method: The aims of this research are to (1) review erstwhile literature related to red light running and traffic safety models; (2) propose a practical methodology for evaluation of RLR countermeasures with a microscopic traffic simulation model and surrogate safety assessment model (SSAM); (3) apply the proposed methodology to actual signalized intersection in Virginia, with the most prevalent scenarios—increasing the yellow signal interval duration, installing an advance warning sign, and an RLR camera; and (4) analyze the relative effectiveness by RLR frequency and the number of conflicts (rear-end and crossing).

Results: All scenarios show a reduction in RLR frequency (?7.8, ?45.5, and ?52.4%, respectively), but only increasing the yellow signal interval duration results in a reduced total number of conflicts (?11.3%; a surrogate safety measure of possible RLR-related crashes). An RLR camera makes the greatest reduction (?60.9%) in crossing conflicts (a surrogate safety measure of possible angle crashes), whereas increasing the yellow signal interval duration results in only a 12.8% reduction of rear-end conflicts (a surrogate safety measure of possible rear-end crash).

Conclusions: Although increasing the yellow signal interval duration is advantageous because this reduces the total conflicts (a possibility of total RLR-related crashes), each countermeasure shows different effects by RLR-related conflict types that can be referred to when making a decision. Given that each intersection has different RLR crash issues, evaluated countermeasures are directly applicable to enhance the cost and time effectiveness, according to the situation of the target intersection. In addition, the proposed methodology is replicable at any site that has a dearth of crash data and/or comparison sites in order to test any other countermeasures (both engineering and enforcement countermeasures) for RLR crashes.     

Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Analysis of motor-vehicle crashes at stop signs in four US cities

Problem: Nearly 700,000 police-reported motor vehicle crashes occur annually at stop signs, and approximately one-third of these crashes involve injuries. The purpose of this study was to develop a better understanding of the crashes that occur at stop signs and to identify potential countermeasures. Method: Police reports of crashes at stop sign-controlled intersections during 1996–2000 in four U.S. cities were examined in detail. At total of 1,788 crash reports for intersections with two-way stop signs were included in the study. Results: Stop sign violations accounted for about 70% of all crashes. Typically these crashes were angular collisions. Among crashes not involving stop violations, rear-end crashes were most common, accounting for about 12% of all crashes. Stop sign violation crashes were classified into several subtypes — driver stopped, driver did not stop, snow/wet/ice, and other/unknown. In about two-thirds of stop sign violation crashes, drivers said they had first come to a stop. In these cases, inability or failure to see approaching traffic often was cited as the cause of the crash. Drivers younger than 18 as well as drivers 65 and older were disproportionately found to be at fault in crashes at stop signs. Impact on industry: Potential countermeasures include changing traffic control and intersection design, improving intersection sight distance, and increasing conspicuity of stop signs through supplemental pavement markings and other devices.     

Evaluation of driver performance with a prototype cyber physical mid-block crossing advanced warning system

Introduction: Using connected vehicle technologies, pedestrian to vehicle (P2V) communication applications can be installed on smart devices allowing pedestrians to communicate with drivers by broadcasting discrete safety messages, received by drivers in-vehicle, as an alternative to expensive fixed-location physical safety infrastructure. Method: This study consists of designing, developing, and deploying an entirely cyber-physical P2V communication system within the cellular vehicle to everything (C-V2X) environment at a mid-block crosswalk to analyze drivers’ reactions to in-vehicle advanced warning messages, the impacts of the advanced warning messages on driver awareness, and drivers’ acceptance of this technology. Results: In testing human subjects with, and without, advanced warning messages upon approaching a mid-block crosswalk, driver reaction, acceptance, speed, eye tracking data, and demographic data were collected. Through an odds ratio comparison, it was found that drivers were at least 2.44 times more likely to stop for the pedestrian with the warning than without during the day, and at least 1.79 times more likely during the night. Furthermore, through binary logistic regression analysis, it was found that driver age, time of the day, and the presence of the advanced warning message all had strong, significant impacts with a confidence value of at least 98% (p < 0.02) on the rate at which drivers stopped for the pedestrian. Conclusions: The results from this study indicate that the advanced warning message sent within the C-V2X had a strong, positive impact on driver behavior and understanding of pedestrian intent. Practical Applications: Pedestrian crashes and fatality rates at mid-block crossings continue to increase over the years. Connected vehicle technology utilizing smart devices can be used as a means for communications between pedestrians and drivers to deliver safety messages. State and local city planners should consider geofencing designated mid-block crossings at which this technology operates to increase pedestrian safety and driver awareness.     

The effect of age and gender on motor vehicle driver injury severity at highway-rail grade crossings in the United States

IntroductionBased on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive database of highway-rail grade crossing accidents in the United States from 2002 to 2011, estimation results showed that there were substantial differences across age/gender groups for driver's injury severity.MethodThe study applied an ordered probit model to explore the determinants of driver injury severity for motor vehicle drivers at highway-rail grade crossings.ResultsThe analysis found that there are important behavioral and physical differences between male and female drivers given a highway-rail grade crossing accident happened.Practical applicationsOlder drivers have higher fatality probabilities when driving in open space under passive control especially during bad weather condition. Younger male drivers are found to be more likely to have severe injuries at rush hour with high vehicle speed passing unpaved highway-rail grade crossings under passive control. Synthesizing these results led to the conclusion that the primary problem with young is risk-taking and lack of vehicle handling skills. The strength of older drivers lies in their aversion to risk, but physical degradation issues which result in longer reaction/perception times and degradation in vision and hearing often counterbalance this attribute.     

上海市小学生交通行为观测与特征分析

为了有针对性地开展小学生交通安全教育,采用行为观测方法研究了上海市小学生的交通行为特征。采用视频观测小学生过街,对行为特征进行编码,利用数理统计分析方法研究行为特征规律。研究发现整体上小学生安全过街行为表现很差,在路边正确位置等待和正确左右观看两方面表现尤为欠缺。研究特别对小学生过街行人组合(一人、结伴、家长陪同)、路口过街方式(一次过街2、次过街)和性别对其交通行为的影响进行了分析,发现过街行人组合显著影响等待位置、是否闯红灯、是否正确左右观看,路口过街方式显著影响等待位置、是否闯红灯、是否正确左右观看、有无不良交通行为,小学生的性别对过街时的交通行为无显著影响。因此对小学生进行交通安全教育是十分必要的,需要针对小学生交通行为特征开展有针对性的安全教育。     

Evaluating safety-influencing factors at stop-controlled intersections using automated video analysis

Introduction: Although stop signs are popular in North America, they have become controversial in cities like Montreal, Canada where they are often installed to reduce vehicular speeds and improve pedestrian safety despite limited evidence demonstrating their effectiveness. The purpose of this study is to evaluate the impact of stop-control configuration (and other features) on safety using statistical models and surrogate measures of safety (SMoS), namely vehicle speed, time-to-collision (TTC), and post-encroachment time (PET), while controlling for features of traffic, geometry, and built environment. Methods: This project leverages high-resolution user trajectories extracted from video data collected for 100 intersections, 336 approaches, and 130,000 road users in Montreal to develop linear mixed-effects regression models to account for within-site and within-approach correlations. This research proposes the Intersection Exposure Group (IEG) indicator, an original method for classifying microscopic exposure of pedestrians and vehicles. Results: Stop signs were associated with an average decrease in approach speed of 17.2 km/h and 20.1 km/h, at partially and fully stop-controlled respectively. Cyclist or pedestrian presence also significantly lower vehicle speeds. The proposed IEG measure was shown to successfully distinguish various types of pedestrian-vehicle interactions, allowing for the effect of each interaction type to vary in the model. Conclusions: The presence of stop signs significantly reduced approach speeds compared to uncontrolled approaches. Though several covariates were significantly related to TTC and PET for vehicle pairs, the models were unable to demonstrate a significant relationship between stop signs and vehicle–pedestrian interactions. Therefore, drawing conclusions regarding pedestrian safety is difficult. Practical Applications: As pedestrian safety is frequently used to justify new stop sign installations, this result has important policy implications. Policies implementing stop signs to reduce pedestrian crashes may be less effective than other interventions. Enforcement and education efforts, along with geometric design considerations, should accompany any changes in traffic control.     

Automatic imitation of risky behavior: a study of simulated driving in china

Objective: Imitation of risky behaviors among drivers is a potentially dangerous threat to driving safety but is infrequently discussed in the existing literature. To enrich the understanding of drivers' imitation behaviors on the road, 2 experiments were designed for a simulated traffic environment. Methods: Safe and risky behaviors were demonstrated by model vehicles separately in the 2 experiments, and imitation behaviors of the participants were observed and analyzed. Results: From experiment 1 it was found that the following distance of participants (measured in time headway) was affected by the distance demonstrated by other vehicles on the road. The influence was stronger when the speed was low, and the participants imitated both risky and safe behavior models. When the speed was high, the participants tended to only learn safe behaviors. In experiment 2, when approaching yellow lights, it was examined whether a driver's decision (pass or stop) would be affected by the behavior of another vehicle (the model vehicle), which was designed to either pass through or stop at the intersection. When the model vehicle ran the yellow light, 65 percent of the participants did the same, even though they were 30?m behind the model vehicle. In contrast, if the model vehicle stopped at the intersection, only 25 percent of the participants decided to pass. Conclusions: It was found that both novice and experienced participants had the tendency to imitate what they saw but were rarely aware of the influence by other drivers in both scenarios.     

A pedestrian's smile and drivers' behavior: When a smile increases careful driving

IntroductionResearch has reported that smiles facilitate social relationships. However, the effect of a smile on driving behavior has received less interest.MethodThis study attempts to evaluate how a pedestrian's smile influences an oncoming driver's behavior. In the first part of our study, male and female research assistants waiting at several pedestrian crossings were asked to smile or not at oncoming drivers.ResultsIt was found that a smile increases the number of drivers who stop. The same effect was observed when the pedestrian tries to cross outside the pedestrian crossing. Finally, this study shows that motorists drive slower after they see a pedestrian smile, suggesting that a smile can induce a positive mood.Practical ApplicationsThis leads to motorists stopping more readily and driving more carefully. These results also suggest that pedestrians may increase their own safety by using appropriate nonverbal signals toward drivers.     

Assessing the impacts of signal coordination on the crash risks of various driving cohorts

Introduction: Signal coordination has been wildly implemented on urban arterials to improve traffic efficiency. The impacts of signal coordination on traffic safety, however, are largely overlooked, particularly on crash propensities of driver–vehicle cohorts, which will vary due to changing traffic flow patterns. Method: The paper aims to compare crash risks of various driving cohorts (measured by relative crash involvement ratio) on arterials with and without signal coordination with quasi-induced exposure technique, which has been well developed in estimating crash risks for driver–vehicle characteristics (i.e., driver age, gender, and vehicle type). Michigan traffic crash data (2000–2014) are retrieved for the case study. Results: The results indicate that: (a) when signal coordination is implemented, young, male drivers, and pickups are associated with more crash responsibilities; (b) crash propensities vary for different disaggregated situations, e.g., young drivers may experience the rapid increase in crash risks during the peak hours; and (c) more hazardous actions (e.g., failing to stop in assured clear distance) are witnessed for the high-risk driving cohorts on the coordinated arterials than non-coordinated ones. Conclusions and practical applications: The findings highlight the importance of safety impact analysis of signal coordination, and serve to guide the potential improvements of safety operation and management of signal coordinated arterials.     

二次过街路口行人违反交通法规规律的研究

为了解在不同类型二次过街路口行人违反交通法规闯红灯的违法率,找出二次过街路口不同参数对行人违法率的影响,从而找出降低路口行人违法率的对策,保障路口行人交通安全和人车流畅通,本文选取上海市5种类型的二次过街路口调查行人在路口的违法率.通过分析调查数据,行人在路口一次穿越车道数为2～7,两次穿越车道总数为6～12,违法率随车道数的增加而降低.在红灯等待时间90 s之内,行人违法率随等待时间的升高呈一定的下降趋势.红灯等待时间在90～150 s之间,行人违法率没有确定的规律.安全岛、引导护栏、中继信号灯等设施具有明显降低行人违法率的作用.根据二次过街路口设置安全岛、引导护栏、中继信号灯、车道数以及是否从路边穿越5个影响因素的安全评价系数之和建立综合安全评价系数,得到行人在二次过街路口违法率随综合安全评价系数的增大而降低.研究表明,完善和优化二次过街路口的设施参数可以降低路口行人违法率.     

斑马线“人-车”博弈仿真

我国自2017年开展“车让人”活动以来,斑马线事故得到有效控制。但本文经统计发现,近两年交通事故量并未明显降低,即“车让人”虽有效控制了斑马线事故,但并未明显影响整体交通安全形势。为此论文设计了3种人车博弈仿真实验,分析不同典型情况下的礼让司机心态:在没有规定车让人时,积极礼让率约20%;在规定车让人时,积极礼让率约50%;当给予司机正向反馈时,积极礼让率约70%,仿真结果验证了:如果没有很好地兼顾司机情绪,“车让人”并不能实现本质安全,即大量交通事故只不过是从斑马线推移到了公路的其他地方(事故外溢)。论文最后建议在斑马线处分别设计给司机和行人阅读的2套标语,综合调控司机心境,有效防控“斑马线事故外溢”。     

Cell phone users, reported crash risk, unsafe driving behaviors and dispositions: a survey of motorists in Maryland

INTRODUCTION: The purpose of this investigation was to identify risky driving behaviors and dispositions that distinguish drivers who use a cell phone while operating a motor vehicle from non-cell phone using drivers. METHOD: Annual telephone surveys were used to identify drivers who reported using a cell phone while driving in the last month (n=1803) and were compared to those who said they did not use cell phones while driving (n=1578). RESULTS: Cell phone using drivers were more likely to report driving while drowsy, going 20 mph over the speed limit, driving aggressively, running a stop sign or red light, and driving after having had several drinks. They were also more likely to have had a prior history of citation and crash involvement than non-cell phone using drivers. Cell phone using drivers also reported they were less careful and more in a hurry when they drive than non-cell phone using drivers. CONCLUSION: Cell phone using drivers report engaging in many behaviors that place them at risk for a traffic crash, independent of the specific driving impairments that cell phone usage may produce. Strategies that combine coordinated and sustained enforcement activities along with widespread public awareness campaigns hold promise as effective countermeasures for these drivers, who resemble aggressive drivers in many respects.     

Effects of red light camera enforcement on fatal crashes in large U.S. cities

Objective

To estimate the effects of red light camera enforcement on per capita fatal crash rates at intersections with signal lights.

Methods

From the 99 large U.S. cities with more than 200,000 residents in 2008, 14 cities were identified with red light camera enforcement programs for all of 2004-2008 but not at any time during 1992-1996, and 48 cities were identified without camera programs during either period. Analyses compared the citywide per capita rate of fatal red light running crashes and the citywide per capita rate of all fatal crashes at signalized intersections during the two study periods, and rate changes then were compared for cities with and without cameras programs. Poisson regression was used to model crash rates as a function of red light camera enforcement, land area, and population density.

Results

The average annual rate of fatal red light running crashes declined for both study groups, but the decline was larger for cities with red light camera enforcement programs than for cities without camera programs (35% vs. 14%). The average annual rate of all fatal crashes at signalized intersections decreased by 14% for cities with camera programs and increased slightly (2%) for cities without cameras. After controlling for population density and land area, the rate of fatal red light running crashes during 2004-2008 for cities with camera programs was an estimated 24% lower than what would have been expected without cameras. The rate of all fatal crashes at signalized intersections during 2004-2008 for cities with camera programs was an estimated 17% lower than what would have been expected without cameras.

Conclusions

Red light camera enforcement programs were associated with a statistically significant reduction in the citywide rate of fatal red light running crashes and a smaller but still significant reduction in the rate of all fatal crashes at signalized intersections.

Impact on Industry

The study adds to the large body of evidence that red light camera enforcement can prevent the most serious crashes. Communities seeking to reduce crashes at intersections should consider this evidence.