Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data

Identification and screening of key traffic violations: based on the perspective of expressing driver's accident risk

Drawing on the core idea of Propensity Score Matching, this study proposes a new concept named Historical Traffic Violation Propensity to describe the driver's historical traffic violations, and combines the new concept with an improved mutual information-based feature selection algorithm to construct a method for screening key traffic violations from the perspective of expressing driver's accident risk. The validation analysis based on the real data collected in Shenzhen demonstrated that drivers' state of Historical Traffic Violation Propensity on 19 key traffic violations screened have a stronger predictive ability of their subsequent accidents compared to the level in existing research. The positive state of Historical Traffic Violation Propensity on 'Drinking', 'Parking in dangerous areas', 'Wrong use of turn lights', 'Violating prohibited and restricted traffic regulations', and 'Disobeying prohibition sign' will increase the probability of a driver's subsequent accident by more than 1.7 times. The research provides directions to more efficiently and accurately capture the driver's accident risk through historical traffic violations, which is valuable for identifying high-risk drivers as well as the key psychological or physical risk factors that manifest in daily driving activities and lead to subsequent accidents.

Do crashed drivers need more drug testing? A retrospective analysis of blood samples from hospitalised post-crash drivers in New Zealand

Driving under the influence of alcohol and other drugs is a prominent safety concern in New Zealand and across the world. While alcohol testing is routinely performed for drivers involved in hospitalisation crashes, testing for other drugs is often not undertaken. The present study refers to 530 traffic crashes that occurred from October 2019 to January 2020 on New Zealand roads. The blood samples from 550 drivers who were injured in a crash and were admitted to a hospital (66% of all drivers involved in these crashes), previously tested for drugs and/or alcohol, were retested for a wider range of drugs. Alcohol above the applicable limit was found to be present in 38% of hospitalised drivers, while other drugs of interest were found in 47% of hospitalised drivers. Binary logistic regression was used to predict the presence of drugs of interest for a crashed driver using previous offence data. A driver having at least one prior drink and drug driving offence is 61% more likely to be positive for a drug of interest when involved in a crash. Similarly, a driver having at least one prior non-traffic drug offence is 4.7 times more likely to be positive for at least a drug of interest when involved in a crash. While the presence of a drug or drugs cannot be presumed to have played a role in the occurrence of the crash, this study has provided a unique and comprehensive picture of the presence of various drugs present in New Zealand drivers' blood. It is recommended to consider standardising drug testing on all blood specimens taken in relation to a serious injury or fatal crash. This procedure is not only of interest for information purposes but may importantly inform appropriate charging decisions.

Associations of cannabis use with motor vehicle crashes and traffic stops among older drivers: AAA LongROAD study

BACKGROUND

Acute cannabis use is associated with a higher risk of motor vehicle crashes (MVC). This study aimed to determine if self-reported past-year cannabis use is associated with MVC or traffic stops among older drivers.

METHODS

This cross-sectional analysis used data from a multi-center study enrolling active drivers aged 65-79 years. Data regarding cannabis use, MVC, and traffic stops (i.e., being pulled over by police, whether ticketed or not) within the previous 12 months were collected through participant interviews. Log-binomial regression models examined associations of past-year cannabis use with MVC and traffic stops, adjusting for site and sociodemographic and mental health characteristics.

RESULTS

Of 2,095 participating older drivers, 186 (8.88%) used cannabis in the past year but only 10 (<0.5%) within an hour before driving in the last 30 days; 11.41% reported an MVC and 9.45% reported a traffic stop. Past-year cannabis users had a higher prevalence of MVC (adjusted prevalence ratio [aPR] = 1.38; 95%CI: 0.96, 2.00; p = 0.086) and traffic stops (aPR = 1.58; 1.06, 2.35; p = 0.024).

CONCLUSIONS

Past-year cannabis use was associated with increased traffic stops, which are correlated modestly with increased MVC in past studies and may indicate impaired driving performance. We did not find a statistically significant association of past-year cannabis use with MVC, which may indicate limited sustained effects on driving performance from periodic use among older adults, who report rarely driving immediately after use.

A data-driven Bayesian network for probabilistic crash risk assessment of individual driver with traffic violation and crash records

In recent years, individual drivers' crash risk assessments have received much attention for identifying high-risk drivers. To this end, we propose a probabilistic assessment method of crash risks with a reproducible long-term dataset (i.e., traffic violations, license, and crash records). In developing this method, we used 7.75 million violations and crashes of 5.5 million individual drivers in Seoul, South Korea, from June 2013 to June 2017 (four years). The stochastic process of the Bayesian network (BN), whose structure is optimized by tabu-search, successfully evaluates individual drivers' crash and violation probability. In addition, the cluster analysis classifies drivers into five distinctive groups according to their estimated violation and crash probabilities. As a result, this study found that the estimated average crash rate within a cluster converges with the actual crash rate by the proposed framework without privacy issues. We also confirm that violation records and expected crash probability are strongly correlated, and there is a direct relationship between a driver's previous violations and crash record and the future at-fault crash. The proposed assessment method is valuable in developing proactive driver education programs and safety countermeasures, including adjusting the penalty system and developing user-based insurance by recognizing dangerous drivers and identifying their properties.

Convergent validity of vision based technology (VBT) among professional bus drivers

INTRODUCTION

Due to the relative rarity of crashes, researchers use traffic offenses, police records, public complaints, and In-Vehicle Data Recorder (IVDR) data as proxies for assessing crash risk. In this study, a unique IVDR system, called Vision-Based Technology [(VBT), (Mobileye Inc.)] was used to monitor perilous naturalistic driving events, such as insufficient distance from other vehicles and pedestrian or bicycle rider near-misses. The study aimed to test the convergent validity of VBT as an indicator of crash involvement risk.

METHODS

Data from 61 professional drivers working for a large bus company were analyzed (16 of 77 in the original data cohort were excluded for insufficient VBT data). Data included: recorded VBT data, objective data collected from official records (crash records provided by the bus company, and public complaints of reckless driving), self-report data regarding crash involvement, and police tickets. The correlation between VBT, objective and self-reported data was analyzed. Binary-logistic regression modeling (BLM) was used to calculate the odds ratio (OR) for participants involved in a car crash.

RESULTS

Correlations were found between the total VBT risk score and official crash records, public complaints, and self-reports of crash involvement. The BLM correctly classified 90% of those who were involved in a crash (sensitivity) and 60% of those who were "crash-free" (specificity). The VBT total risk score was the only significant contributing factor to crash risk, and for each point of increase, the odds of being involved in a crash increased by a factor of 1.55.

CONCLUSIONS

It is the first study to provide empirical evidence validating the VBT as an indicator of crash involvement and driver safety among professional bus drivers.

PRACTICAL APPLICATIONS

VBT technology can provide researchers and clinicians a better understanding of bus drivers' risky driving behaviors- a valuable contribution to road safety interventions for this target group.

Does past offending behaviors catch up with you? A study examining the relationship between traffic offending history and fatal crash involvement

OBJECTIVE

The aim of the current study was to compare the traffic histories of drivers fatally injured in a road traffic crash, to alive drivers of the same age and gender in order to determine if key markers of increased fatality-risk could be identified.

METHODS

The case sample comprised 1,139 (82% male) deceased drivers, while the control sample consisted of 1,139 registered Queensland drivers (who were individually matched to the case sample on age and gender).

RESULTS

Using a logistic regression model, and adjusting for age and gender, it was found that a greater number of offenses predicted greater odds of fatal crash involvement, with each increase in offense frequency category increasing ones' odds by 1.98 (95% CI: 1.8, 2.18). When each offense type was considered individually, dangerous driving offenses were most influential, predicting a 3.44 (95% CI: 2, 5.93) increased odds of being in the case group, followed by the following offense types: learner/provisional (2.88, 95% CI: 1.75, 4.74), drink and drug driving (2.82, 95% CI: 1.97, 4.04), not wearing a seatbelt/helmet (2.63, 95% CI: 1.53, 4.51), licensing offenses (1.87, 95% CI: 1.41, 2.49), and speeding (1.48, 95% CI: 1.33, 1.66). In contrast, mobile phone and road rules offenses were not identified as significant predictors.

CONCLUSION

The findings indicate that engagement in a range of aberrant driving behaviors may result in an increased odds of future fatal crash involvement, which has multiple implications for the sanctioning and management of apprehended offenders.

Versatile, but not focused, traffic offenders are more likely to be at fault for a fatal crash

INTRODUCTION

The aim of this study was to determine whether drivers who had received more traffic infringements were more likely to be at fault for the crash in which they were killed.

METHOD

The current dataset was derived from the crash and traffic history records provided by the Queensland Department of Transport and Main Roads and Coroner's Court for every driver, with available records, who was killed in a crash in Queensland, Australia, between 2011 and 2019 (N = 1,136). The most common traffic offenses in the current sample were speeding, disobeying road rules, driving under the influence of drugs and alcohol, and unlicensed driving. Logistic regression models were used to compute odds ratios for the number of overall offenses, the number of specific offense types, and for specific offending profiles that were derived from the literature. Age, gender, and crash type were each controlled for by entering them into the initial blocks of the regression models.

RESULTS

After accounting for the variance associated with age, gender, and crash type, only the overall number of offenses and the number of unlicensed driving offenses predicted a significant change in a drivers' likelihood of being at fault for the crash that killed them. Furthermore, drivers who were identified as having versatile (i.e., multiple offenses from different categories) or criminal-type offense profiles (i.e., offenses that were considered to approximate criminal offenses) were each significantly more likely to be at fault for a fatal crash.

PRACTICAL APPLICATIONS

This study provided an important contribution by demonstrating how a more nuanced approach to understanding how a driver's traffic history might be used to identify drivers who are more at risk of being involved in a crash (i.e., for which they were at fault). The implications of these findings are discussed with recommendations and consideration for future research.

A proportional odds model of risk behaviors associated with recurrent road traffic crashes among young adults in Kuwait

Background

The aims of this cross-sectional study were to i) assess one-year period prevalence of one, two, three or more road traffic crashes (RTCs) as an ordinal outcome and ii) identify the drivers’ characteristics associated with this ordinal outcome among young adult drivers with propensity to recurrent RTCs in Kuwait.

Methods

During December 2016, 1465 students, 17 years old or older from 15 colleges of Kuwait University participated in this cross-sectional study. A self-administered questionnaire was used for data collection. One-year period prevalence (95% confidence interval (CI)) of one, two, three or more RTCs was computed. Multivariable proportional odds model was used to identify the drivers’ attributes associated with the ordinal outcome.

Results

One-year period prevalence (%) of one, two and three or more RTCs respectively was 23.1 (95% CI: 21.2, 25.6), 10.9 (95% CI: 9.4, 12.6), and 4.6 (95% CI: 3.6, 5.9). Participants were significantly (p < 0.05) more likely to be in higher RTCs count category than their current or lower RCTs count, if they habitually violated speed limit (adjusted proportional odds ratio (pOR_adjusted) = 1.40; 95% Cl: 1.13, 1.75), ran through red lights (pOR_adjusted = 1.64; 95%CI: 1.30, 2.06), frequently (≥ 3) received multiple (> 3) speeding tickets (pOR_adjusted = 1.63; 95% CI: 1.12, 2.38), frequently (> 10 times) violated no-parking zone during the past year (pOR_adjusted = 1.64; 95% CI: 1.06, 2.54) or being a patient with epilepsy (pOR_adjusted = 4.37; 95% CI: 1.63, 11.70).

Conclusion

High one-year period prevalence of one, two and three or more RTCs was recorded. Targeted education based on identified drivers’ attributes and stern enforcement of traffic laws may reduce the recurrent RTCs incidence in this and other similar populations in the region.

The role of perceived legitimacy in understanding traffic rule compliance: A scoping review

BACKGROUND

Perceived legitimacy associated with rules and authorities is an important element for understanding and encouraging compliance with rules in the field of road safety, often more so than with a deterrence approach. Despite a growing interest in legitimacy in recent decades and in the psychological field in particular, its definitions and measurements appear to be heterogeneous, subject to debate and in need of a common theoretical framework. Therefore, one can expect these limitations to also concern the definitions and measurements of legitimacy in the field of road safety. However, no literature review related to this issue is currently available. This contribution therefore aims to fill this void by proposing a scoping review investigating, in the field of road safety, how legitimacy is defined, measured, related to compliance and what are its main determinants.

METHODS

A scoping review was conducted, based on research literature from eight databases and concerned with the perceived legitimacy of traffic rules or traffic enforcement and rule compliance or traffic violations. Twenty-six publications meeting inclusion criteria were retained. The characteristics and content of publications were analyzed to identify the relevant elements related to our research questions.

RESULTS AND CONCLUSION

The main results revealed that perceived legitimacy in the field of road safety can be related to different objects (i.e., traffic rules, traffic violations, traffic enforcement, institutions) that should be better delineated and differentiated in future research. While perceived legitimacy is generally associated with compliance with traffic rules, its theoretical definitions and measures in the field of road safety are heterogeneous and present validity issues which limit the comparability of studies and so the accumulation of knowledge for both theoretical research and road safety applications. No empirical study investigating the outcomes of perceived legitimacy beyond compliance was identified. Few empirical studies have investigated the determinants of perceived legitimacy. Most identified empirical studies were cross-sectional, which is a limitation to establishing causality in investigated relationships. Theoretical implications and research perspectives to improve studies on legitimacy in the field of road safety and develop a multidimensional model of the perceived legitimacy of traffic rules are therefore proposed and discussed.

The Effectiveness of Different Incentive Programs to Encourage Safe Driving

This study examined the effectiveness of various financial incentive schemes for improving drivers’ safety performance, specifically in regard to speeding, tailgating, and frequent lane changing without signaling. The study examined the hypothesis that, with regard to modifying unsafe driving behavior in a sample of professional bus drivers in Israel, small yet reliable rewards are more effective than rewards that are large but rarely obtained. While this hypothesis has been tested and partially supported in laboratory studies, the current study is the first to test it in real-world conditions. This study demonstrates that a combination of surveillance, rewards (monetary compensation), and informing the drivers about their driving performance in real time produces a lasting and significant decline in traffic violations. The results show that financial incentives are effective for encouraging safe driving behavior. Simultaneously, the results show some indications that small yet probable rewards may be more effective than large but uncertain ones. This study also demonstrates that the improvement in behavior continued during the period immediately after the experiment.

Study on the Relationship between Drivers' Personal Characters and Non-Standard Traffic Signs Comprehensibility

Drivers’ incorrect perception and interpretation of the road space are among reasons for human errors. Proper road markings are elements improving perception of road space. Their effectiveness relies on traffic participants receiving the provided information correctly. The range of signs used is constantly expanding and unusual situations in traffic require use of non-standard signs or an unusual combination of existing standard signs. The aim of this study was to explore the level of comprehensibility of four different types of non-standard signs. The relationship between the level of comprehensibility of these signs and personality traits of the drivers was also studied. A total of 369 drivers were tested using a questionnaire to analyze the traffic signs comprehensibility and Five Factor Inventory (NEO-FFI). The obtained results indicate that symbolic signs, unlike symbolic and text ones, are much better comprehended by drivers. Men comprehend the significance of non-standard symbolic regulatory signs better than women. Higher level of comprehensibility of symbolic and text regulatory signs is shown by older, better educated drivers and professional drivers. The study found there is a link between personality traits of the driver and the comprehensibility of symbolic regulatory signs.

Explaining the Association between Driver's Age and the Risk of Causing a Road Crash through Mediation Analysis

It has been widely reported that younger and older drivers have an excess risk of causing a road crash. Two casual hypotheses may coexist: the riskier driving behaviors and age-related mechanisms in extreme age groups (direct path) and the different environmental and vehicle circumstances (indirect path). Our aim was to quantify, through a mediation analysis, the percentage contribution of both paths. A case-control study was designed from the Spanish Register of Road Crashes with victims from 2014 to 2017. Assuming a quasi-induced exposure approach, controls were non-responsible drivers involved in clean collisions between two or more vehicles (n = 52,131). Responsible drivers for these collisions plus drivers involved in single crashes constituted the case group (n = 82,071). A logit model in which the outcome was the log (odds) of causing a road crash and the exposure was age groups was adjusted for driver, vehicle and environmental factors. The highest crash risk was observed in extreme age groups, compared to the 35-44 year old age group: the youngest (18-24 years old, odds ratio = 2.14, 95% confidence interval: 2.06-2.24) and the oldest drivers (>74 years old, odds ratio = 3.30, 95% confidence interval: 3.04-2.58). The mediation analysis identified the direct path as the main explanatory mechanism for these increases: 89% in the youngest and 93% in the oldest drivers. These data support the hypothesis that the excess crash risk observed for younger and older drivers is mainly related to their higher frequency of risky driving behaviors and age-related loss of capabilities. Preventive strategies in extreme-aged drivers should focus on decreasing these behaviors.

How You Deal with Your Emotions Is How You Drive. Emotion Regulation Strategies, Traffic Offenses, and the Mediating Role of Driving Styles

Past research indicated the importance of traffic safety and driving behaviors for the sustainability of the traffic system. The aim of this study was to examine the effect of emotion regulation on drivers’ tendency to obey or transgress traffic rules. A sample of 554 Romanian drivers completed a set of measures assessing their driving styles, traffic offenses, and their habitual use of three emotion regulation strategies. The results of the mediation analyses showed that two of these strategies, i.e., reappraisal and experiential avoidance, are associated with less traffic offenses, and that specific driving styles mediate these effects. While the behavioral effects of experiential avoidance were mixed in valence, reappraisal was found to diminish the use of maladaptive driving styles and to foster careful driving. Overall, this pattern of results indicates the potential benefits of future interventions aiming to develop drivers’ abilities to regulate their emotions, especially through reappraisal, for increasing traffic safety.

Experience as a Safety Factor in Driving; Methodological Considerations in a Sample of Bus Drivers

Experience is generally seen as an important factor for safe driving, but the exact size and details of this effect has never been meta-analytically described, despite a fair number of published results. However, the available data is heterogeneous concerning the methods used, which could lead to very different results. Such method effects can be difficult to identify in meta-analysis, and a within-study comparison might yield more reliable results. To test for the difference in effects between some different analytical methods, analyses of data on bus driver experience and crash involvement from a British company were conducted. Effects of within- and between-subjects analysis, non-linearity of effects, and direct and induced exposure methods were compared. Furthermore, changes in the environmental risk were investigated. Between-subject designs yielded smaller effects as compared to within-subjects designs, while non-linearity was not found. The type of exposure control applied had a strong influence on effects, as did differences in overall environmental risk between years. Apparently, “the effect of driving experience” means different things depending upon how calculations have been undertaken, at least for bus drivers. A full meta-analysis, taking several effects of methodology into account, is needed before it can be said that the effect of driving experience on crash involvement is well understood.

Regulatory focus, time perspective, locus of control and sensation seeking as predictors of risky driving behaviors

Empirical evidence shows that most of the road safety efforts fail to reach the most risk-prone drivers. In light of this issue, we have developed this study in order to distinguish between high-risk drivers and low-risk drivers based on variables that have already been shown to affect the effectiveness of preventive messages: regulatory focus orientation, time perspective, locus of control and sensation seeking. We sent paper and pencil questionnaires to five thousand low-risk drivers and five thousand high-risk drivers randomly selected based on their driving records. A driver who has been convicted of two or more traffic infractions with demerit points (e.g., exceeding speed limits, red light violation, no seatbelt, etc.) in the last two years was considered a high-risk driver whereas a low-risk driver had no traffic offense registered in his driving record in the last four years. We received two thousand and sixty-four completed questionnaires for a response rate of 20.6%. Seven hundred and ninety-eight belonged to the group of high-risk drivers and one thousand two hundred and sixty-six to the group of low-risk drivers. The results show that a promotion focused orientation, a present hedonistic perspective, an internal locus of control, and sensation seeking are associated with more risky driving behaviors and could therefore distinguish between high-risk and low-risk drivers. These results increase the understanding of risky drivers' personalities and motivations. The literature review provides insight into how these findings might be considered in developing more effective road safety programs and campaigns, and the conclusion encourages researchers to explore these new avenues in future research.