Crash risk by driver age,gender, and time of day using a new exposure methodology

Introduction: Concerns have been raised that the nonlinear relation between crashes and travel exposure invalidates the conventional use of crash rates to control for exposure. A new metric of exposure that bears a linear association to crashes was used as basis for calculating unbiased crash risks. This study compared the two methods – conventional crash rates and new adjusted crash risk – for assessing the effect of driver age, gender, and time of day on the risk of crash involvement and crash fatality. Method: We used police reports of single-car and multi-car crashes with fatal and nonfatal driver injuries that occurred during 2002–2012 in Great Britain. Results: Conventional crash rates were highest in the youngest age group and declined steeply until age 60–69 years. The adjusted crash risk instead peaked at age 21–29 years and reduced gradually with age. The risk of nighttime driving, especially among teenage drivers, was much smaller when based on adjusted crash risks. Finally, the adjusted fatality risk incurred by elderly drivers remained constant across time of day, suggesting that their risk of sustaining a fatal injury due to a crash is more attributable to excess fragility than to crash seriousness. Conclusions: Our findings demonstrate a biasing effect of low travel exposure on conventional crash rates. This implies that conventional methods do not yield meaningful comparisons of crash risk between driver groups and driving conditions of varying exposure to risk. The excess crash rates typically associated with teenage and elderly drivers as well as nighttime driving are attributed in part to overestimation of risk at low travel exposure. Practical Applications: Greater attention should be directed toward crash involvement among drivers in their 20s and 30s as well as younger drivers. Countermeasures should focus on the role of physical vulnerability in fatality risk of elderly drivers.     

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers

Introduction: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. Method: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ‘‘middle-aged and elderly drivers with low risk of driving violations and high historical crash records,” ‘‘drivers with high risk of driving violations and high historical crash records,” and ‘‘middle-aged drivers with no driving violations and conviction records.” Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.     

Causal attribution in explanations of near-crash events behind the wheel,and its relationship to comparative judgments

IntroductionThe development of skills essential for avoiding crashes depends, in particular, on how drivers explain the causes of dangerous driving behaviors that resulted in a near crash. Here, we analyze causes attributed to such behaviors by car drivers in a self-report study. We explore the relationships between the dimensions of causal attribution, attribution of responsibility for the near crash, and drivers' comparative judgments.MethodFor approximately two months, drivers used logbooks to document the near crashes that occurred during their trips. The causes attributed in those reports to driving behaviors resulting in near crashes were then coded by two judges on the basis of several causal dimensions. Drivers also estimated their own and an average driver's skill levels, and their risk of being involved, as a driver, in a crash.ResultsWe distinguished main types of causes of the near crashes reported. Drivers had a tendency to more often attribute external causes to their own behaviors resulting in near crashes than to those of others. The probability of attributing a controllable cause increased with overestimation of one's own skills and decreased with underestimation of one's own risk in comparison to other drivers. The probability of attributing a stable cause increased with underestimation of one's own risk.ConclusionsWhen they explained their own behaviors resulting in near crashes, drivers mentioned different causes than when they explained those of others. Overestimation of one's own skills as compared to other drivers could be beneficial for developing crash-avoiding skills, insofar as it seems to foster attribution of controllable causes. By contrast, underestimation of one's own risk could have the opposite effect.Practical applicationsVulnerability to road risks should be stressed in driver’s training and risk communication campaigns. However, self-confidence with respect to one's skills should not always be targeted as a safety problem.     

Driver licensing,motor-vehicle crashes,and moving violations among older adults

IntroductionDriving is important for well-being among older adults, but age-related conditions are associated with driving reduction or cessation and increased crash risk for older drivers. Our objectives were to describe population-based rates of older drivers’ licensing and per-driver rates of crashes and moving violations.Methods: We examined individual-level statewide driver licensing, crash, and traffic citation data among all New Jersey drivers aged ≥ 65 and a 35- to 54-year-old comparison group during 2010–2014. Rate ratios (RR) of crashes and moving violations were estimated using Poisson regression.Results: Overall, 86% of males and 71% of females aged ≥ 65 held a valid driver’s license. Older drivers had 27% lower per-driver crash rates than middle-aged drivers (RR: 0.73, 95% CI: 0.73, 0.74)—with appreciable differences by sex—but 40% higher fatal crash rates (RR: 1.40 [1.24, 1.58]). Moving violation rates among older drivers were 72% lower than middle-aged drivers (RR: 0.28 [0.28, 0.28]).Conclusion: The majority of older adults are licensed, with substantial variation by age and sex. Older drivers have higher rates of fatal crashes but lower rates of moving violations compared with middle-aged drivers.Practical applications: Future research is needed to understand the extent to which older adults drive and to identify opportunities to further reduce risk of crashes and resultant injuries among older adults.     

Continued trends in older driver crash involvement rates in the United States: Data through 2017–2018

Introduction: With the growing older adult population due to the aging baby-boom cohort, there was concern that increases in fatal motor-vehicle crashes would follow. Yet, previous analyses showed this to be untrue. The purpose of this study was to examine current trends to determine if previous declines have persisted or risen with the recent increase in fatalities nationwide. Methods: Trends among drivers ages 70 and older were compared with drivers 35–54 for U.S. passenger vehicle fatal crash involvements per 100,000 licensed drivers from 1997 to 2018, fatal and all police-reported crash involvements per vehicle miles traveled using the 1995, 2001, 2009, and 2017 National Household Travel Surveys, and driver deaths per 1,000 crashes. Results: Since the mid-1990s, fatal crashes per licensed driver trended downward, with greater declines for drivers ages 70 and older than for middle-aged drivers (43% vs. 21%). Fatal crash rates per 100,000 licensed drivers and police-reported crash rates per mile traveled for drivers ages 70–79 are now less than those for drivers ages 35–54, but their fatal crash rates per mile traveled and risk of dying in a crash remain higher as they drive fewer miles. As the economy improved over the past decade, fatal crash rates increased substantially for middle-aged drivers but decreased or remained stable among older driver age groups. Conclusions: Fatal crash involvements for adults ages 70 and older has recently increased, but they remain down from their 1997 peak, even as the number of licensed older drivers and the miles they drive have increased. Health improvements likely contributed to long-term reductions in fatal crash rates. As older drivers adopt vehicles with improved crashworthiness and safety features, crash survivability will improve. Practical Application: Older adults should feel confident that their independent mobility needs pose less risk than previously expected.     

Assessing driver behavior using shrp2 adverse weather data

IntroductionThis study explored how drivers adapt to inclement weather in terms of driving speed, situational awareness, and visibility as road surface conditions change from dry to slippery and visibility decreases. The proposed work mined existing data from the SHRP 2 NDS for drivers who were involved in weather-related crash and near-crash events. Baseline events were also mined to create related metadata necessary for behavioral comparisons. Methods: Researchers attempted, to the greatest extent possible, to match non-adverse-weather driving scenarios that are similar to the crash and near-crash event for each driver. The ideal match scenario would be at a day prior to the crash during non-adverse weather conditions having the same driver, at the same time of day, with the same traffic level on the same road on which the crash or near-crash occurred. Once the matched scenarios have been identified, a detailed analysis will be performed to determine how a driver’s behavior changed from normal driving to inclement-weather driving. Results: Data collected indicated that, irrespective of site location (i.e., state), most crashes and near-crashes occurred in rain, with only about 12% occurring in snowy conditions. Also, the number of near-crashes was almost double the number of crashes showing that many drivers were able to avoid a crash by executing an evasive maneuver such as braking or steering. Conclusions: Most types of near crashes were rear-end and sideswipe avoidance epochs, as the drivers may have had a difficult time merging or trying to change lanes due to low visibility or traffic. Hard braking combined with swerving were the most commonly used evasive maneuvers, occurring when drivers did not adjust their speeds accordingly for specific situations. Practical applications: Results from this study are expected to be utilized to educate and guide drivers toward more confident and strategic driving behavior in adverse weather.     

Socio-demographic and experience factors affecting drivers’ runoff risk along horizontal curves of two-lane rural highway

Introduction: An improper driving strategy is one of the causative factors for a high probability of runoff and overturning crashes along the horizontal curves of two-lane highways. The socio-demographic and driving experience factors of a driver do influence driving strategy. Hence, this paper explored the effect of these factors on the driver’s runoff risk along the horizontal curves. Method: The driving performance data of 48 drivers along 52 horizontal curves was recorded in a fixed-base driving simulator. The driving performance index was estimated from the weighted lateral acceleration profile of each driver along a horizontal curve. It was clustered and compared with the actual runoff events observed during the experiment. It yielded high, moderate, and low-risk clusters. Using cross-tabulation, each risk cluster was compared with the socio-demographic and experience factors. Further, generalized mixed logistic regression models were developed to predict the high-risk and high to moderate risk events. Results: The age and experience of drivers are the influencing factors for runoff crash. The high-risk event percentage for mid-age drivers decreases with an increase in driving experience. For younger drivers, it increases initially but decreases afterwards. The generalized mixed logistic regression models identified young drivers with mid and high experience and mid-age drivers with low-experience as the high-risk groups. Conclusions: The proposed index parameter is effective in identifying the risk associated with horizontal curves. Driver training program focusing on the horizontal curve negotiation skills and graduated driver licensing could help the high-risk groups. Practical applications: The proposed index parameter can evaluate driving behavior at the horizontal curves. Driving behavior of high-risk groups could be considered in highway geometric design. Motor-vehicle agencies, advanced driver assistance systems manufacturers, and insurance agencies can use proposed index parameter to identify the high-risk drivers for their perusal.     

Behavioral Factors as Predictors of Motor Vehicle Crashes in Young Drivers

Gains in reducing mortality and morbidity from motor vehicle crashes can be achieved by understanding the behavioral factors that contribute to the elevated risk of motor vehicle-related injury and death. This study investigates the incidence, along with the effect of driver and behavioral factors, on the likelihood of motor vehicle crashes. Seventeen year old newly licensed drivers (n = 1277) in Perth, Western Australia, were recruited and followed over the first 12 months of driving. Using Cox proportional hazard analysis, driver and behavioral factors were assessed to determine whether they predicted the likelihood of a crash in the first 12 months of driving. The crash incidence rate was higher for males (1R = 4.6/10,000 driving days) than females (IR = 3.9/10,000 driving days). Multivariate analysis indicated that drivers who reported to have driven daily prior to obtaining their learners permit (L-plates) were at an increased risk of motor vehicle crash. A twofold increase in motor vehicle crash was apparent among drivers considered to be confident-adventurous drivers compared to low to moderate levels of driver confidence-adventurousness (HR = 2.04, 95% CI = 1.29-3.21). The research indicates that a driver's perception of their confidence and adventurousness in the road environment plays a part in the causal pathway leading to a motor vehicle crash. This research points to the need for preventive strategies that focus not only on knowledge and skill acquisition, but also the driver's perception in preparing young people for our roads.     

Does longevity impact the severity of traffic crashes? A comparative study of young-older and old-older drivers

Introduction: This article analyzes the effect of driver’s age in crash severity with a particular focus on those over the age of 65. The greater frequency and longevity of older drivers around the world suggests the need to introduce a possible segmentation within this group at risk, thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector. Method: We investigate differences in the severity of traffic crashes among two subgroups of older drivers –young-older (65–75) and old-older (75+), and findings are compared with the age interval of drivers under 65. Here, we draw on data for 2016 provided by Spanish Traffic Authority. Parametric and semi-parametric regression models are applied. Results: We identified the factors related to the crash, vehicle, and driver that have a significant impact on the probability of the crash being slight, serious, or fatal for the different age groups. Conclusions: We found that crash severity and the expected costs of crashes significantly increase when the driver is over the age of 75. Practical Applications: Our results have obvious implications for regulators responsible for road safety policies – most specifically as they consider there should be specific driver licensing requirements and driving training for elderly – and for the automobile insurance industry, which to date has not examined the impact that the longevity of drivers is likely to have on their balance sheets.     

Association between older driver characteristics, on-road driving test performance, and crash liability

From May 1999, a new system for licensing older drivers was introduced in New Zealand. It included a practical on-road driving test with expanded scope, to be completed every two years from the time the driver turns 80. The relationship between crashes and test performance needed to be studied to inform the debate regarding the testing system. The population studied was all drivers who entered this licensing system during its first three years of operation. They were defined as crash involved if they were involved in an injury crash during the two years following their first licensure under the new system. Logistic regression was used to describe the risk of crash involvement in terms of driving test performance and other driver characteristics. Each driving test failure was associated with a 33% increase in the odds of crash involvement (95% CI 14% to 55%), controlling for age, gender, minor traffic violations, and whether the older driver lived with another licensed driver or not. Minor traffic violations in the two years following the driving test were associated with twice the odds of crash involvement. These results suggest that the new on-road driving test does identify older driver behaviors or limitations that are related to crash liability. It is anticipated that the results presented here will provide essential information for discussing older driver licensing systems, whose impact will grow in importance as the population of drivers ages.     

Young drivers' perceptions of culpability of sleep-deprived versus drinking drivers

Introduction: Sleep-deprived driving can be as dangerous as alcohol-impaired driving, however, little is known about attitudes toward sleep-deprived drivers. This study examined the extent to which young drivers regard sleep-deprived compared to drinking drivers as culpable for a crash, and how their perceptions of driving while in these conditions differ. Method: University student participants (N = 295; M = 20.4 years, SD = 1.3; 81% women) were randomly assigned to read one of five fatal motor-vehicle crash scenarios, which differed by aspects of the driver's condition. Culpability ratings for the drinking driver were higher than those for the sleep-deprived driver. Results: Qualitative findings revealed that driving while sleep-deprived was viewed as understandable, and driving after drinking was viewed as definitely wrong. The dangers of sleep-deprived driving remain under-recognized.     

Characteristics and risks of drivers with low annual distance driven

OBJECTIVES: It has been noted by several authors that risk (defined only in terms of total expected numbers of crash involvements per total distance driven) paints a misleading picture of crash liability, particularly for the young and the old, as their high risk is associated with risky driving patterns typical of people who drive low annual kms. This article sets out to analyze these driving patterns of low-km drivers and to evaluate the risk of these patterns. As licensing programs tend to focus on young and old drivers, who tend to drive lower annual distances, income and employment data are also analyzed for low-km drivers. This is to provide a better picture for policy makers of the sort of people and the sorts of transportation requirements that their policies may affect. METHODS: Crash data and travel data were disaggregated by driver characteristics and by driving conditions (road type, day and night, weekend and weekday) and combined to form estimates of risk for typical driving patterns of driver groups. Characteristics of driving patterns and of the drivers themselves were derived for groups defined by age and by the amount of annual driving undertaken. RESULTS: Older drivers who drive less tend to have higher risk per km mainly due to their predominantly urban trips. Nevertheless, because older drivers on average manage to reduce their risk per distance driven by choosing driving patterns that are safer than the driving patterns of other age groups, the risk of older drivers as a group is not overestimated. CONCLUSION: Despite being quite different from one another, the low- and high-km driving patterns of younger drivers were found to impose identical risks.     

The effect of extending graduated driver licensing to older novice drivers in Indiana

Introduction: Graduated driver licensing (GDL) systems have been shown to reduce rates of crashes, injuries, and deaths of young novice drivers. However, approximately one in three new drivers in the United States obtain their first driver’s license at age 18 or older, and thus are exempt from most or all provisions of GDL in most states. Method: In July 2015, the state of Indiana updated its GDL program, extending its restrictions on driving at night and on carrying passengers during the first 6 months of independent driving, previously only applicable to new drivers younger than 18, to all newly-licensed drivers younger than 21 years of age. The current study examined monthly rates of crashes per licensed driver under the affected conditions (driving at night and driving with passengers) among Indiana drivers first licensed at ages 18, 19, and 20 under the updated GDL system compared with drivers licensed at the same ages under the previous GDL system. We used Poisson regression to estimate the association between the GDL system and crash rates, while attempting to control for other factors that might have also influenced crash rates. We used linear regression to estimate the association between the GDL system and the proportion of all crashes that occurred under conditions restricted by the GDL program. Results: Results showed, contrary to expectations, that rates of crashes during restricted nighttime hours and with passengers were higher among drivers licensed under the updated GDL system. This mirrored a statewide increase in crash rates among drivers of all ages over the study period and likely reflected increased overall driving exposure. The proportions of all crashes that were at night or with passengers did not change. Practical Applications: More research is needed to understand how older novice drivers respond when GDL systems originally designed for younger novice drivers are applied to them.     

Analysis of effects of driver’s evasive action time on rear-end collision risk using a driving simulator

Introduction: Driver’s evasive action is closely associated with collision risk in a critical traffic event. To quantify collision risk, surrogate safety measures (SSMs) have been estimated using vehicle trajectories. However, vehicle trajectories cannot clearly capture presence and time of driver’s evasive action. Thus, this study determines the driver’s evasive action based on his/her use of accelerator and brake pedals, and analyzes the effects of the driver’s evasive action time (i.e., duration of evasive action) on rear-end collision risk. Method: Fifty drivers’ car-following behavior on a freeway was observed using a driving simulator. An SSM called “Deceleration Rate to Avoid Crash (DRAC)” and the evasive action time were determined for each driver using the data from the driving simulator. Each driver tested two traffic scenarios – Cars and Trucks scenarios where conflicting vehicles were cars and trucks, respectively. The factors related to DRAC were identified and their effects on DRAC were analyzed using the Generalized Linear Models and random effects models. Results: DRAC decreased with the evasive action time and DRAC was closely related to drivers’ gender and driving experience at the road sections where evasive action to avoid collision was required. DRAC was also significantly different between Cars and Trucks scenarios. The effect of the evasive action time on DRAC varied among different drivers, particularly in the Trucks scenario. Conclusions: Longer evasive action time can significantly reduce crash risk. Driver characteristics are more closely related to effective evasive action in complex driving conditions. Practical Applications: Based on the findings of this study, driver warning information can be developed to alert drivers to take specific evasive action that reduces collision risk in a critical traffic event. The information is likely to reduce the variability of the driver’s evasive action and the speed variations among different drivers.     

Are drivers' comparative risk judgments about speeding realistic?

Introduction

This study focused on comparative judgments about speeding risks among young drivers who have a high risk of being involved in a traffic accident.

Method

We examined (a) how these drivers assess their risk of sanctions and their risk of causing an automobile crash because of speeding in comparison to the estimated risks of other drivers, and (b) how realistic their comparative risk judgments are. We measured the relationship between the drivers' comparative risk judgments, self-reported speeding, and driving-related sensation-seeking. We hypothesized that (a) they would think they have less risk of sanctions and of causing a car accident than others, and (b) their comparative judgments of speeding risks would be linked to self-reported speeding and driving-related sensation-seeking. The study was based on a computerized questionnaire survey conducted with 3,002 young drivers (mean age = 22.3) administered by professional investigators.

Results

The results confirmed our hypotheses.

Impact on Industry

In order to improve the effectiveness of prevention measures and to evaluate the effect of them, road-safety interventions should take into account comparative risk judgments about the targeted risk behavior.     

Older driver crash rates in relation to type and quantity of travel

It is a well-established phenomenon that, notwithstanding their overall good crash record, older drivers have a higher than average rate of involvement in injury crashes when the rate is calculated by dividing crash numbers by distance driven. It has been hypothesised that at least some of this higher crash rate is an artefact of the different nature of driving undertaken by many older drivers. For example, driving in congested urban environments provides more opportunities for collisions than driving the same distance on a motorway. However, there have been few opportunities to investigate this theory, as relevant data are difficult to acquire. High-quality data from the New Zealand Travel Survey (1997/1998) were combined with crash data to enable a statistical model to estimate the risk of driver groups under various driving conditions characterised by the type of road used, time of day, day of week, and season of year. Despite elevated crash risks per distance driven compared with middle-aged drivers for most road types, older drivers were as safe as any other age group when driving on motorways. Accounting for the fragility of older drivers and their passengers in the risk estimates for other road types, older drivers appeared to have daytime risks comparable to 25-year-olds and night-time risks as low as any other age group. The driving patterns of older drivers (in terms of when and where they drive) were estimated to minimize their risks in comparison with the driving patterns of other age groups. These results are of interest to both policy makers and transportation planners working against the background of inevitable increases in the number of older drivers as the population ages.     

Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.     

Associations between driver training, determinants of risky driving behaviour and crash involvement

The core aim of the study is to examine associations between formal and informal practical driver training as well as driving experience on the one hand and young drivers’ safety attitudes, self-assessment of driving ability and self-reported driver behaviour on the other hand. An additional aim is to examine the associations between attitudes, self-assessment and behaviour on the one hand and crash involvement on the other hand. The results are based on a self-completion questionnaire survey conducted among a representative sample of Norwegian drivers aged 18–20 years (n = 1419). The results showed that there were small yet significant associations between driver training, on the one hand and traffic safety attitudes and risky driving behaviour on the other hand. The amount of formal driver training was negatively associated with the respondents’ evaluation of their driving skills; although the amount of lay instruction was positively associated with such self-evaluation. The results also showed that attitudes as well as self-assessment of driving ability were significantly associated with self-reported risk behaviour. This was especially true for attitudes related to rule violations. There was a strong association between crash involvement and exposure (measured as months holding a licence). Young novice drivers’ crash involvement seems stronger associated with driving skills (manifested as self-assessment of driving ability) than safety attitudes and self-reported driver behaviour. The consequences of the results for driver training and accident prevention are discussed.     

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.