Near crash characteristics among risky drivers using the SHRP2 naturalistic driving study

Problem: Previous research have focused extensively on crashes, however near crashes provide additional data on driver errors leading to critical events as well as evasive maneuvers employed to avoid crashes. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive data on real world driving and offers a reliable methodology to study near crashes. The current study utilized the SHRP2 database to compare the rate and characteristics associated with near crashes among risky drivers. Methods: A subset from the SHRP2 database consisting of 4,818 near crashes for teen (16–19 yrs), young adult (20–24 yrs), adult (35–54 yrs), and older (70+ yrs) drivers was used. Near crashes were classified into seven incident types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups. For rear-end near crashes, near crash severity, max deceleration, and time-to-collision at braking were compared across age. Results: Near crash rates significantly decreased with increasing age (p < 0.05). Young drivers exhibited greater rear-end (p < 0.05) and road departure (p < 0.05) near crashes compared to adult and older drivers. Intersection near crashes were the most common incident type among older drivers. Evasive maneuver type did not significantly vary across age groups. Near crashes exhibited a longer time-to-collision at braking (p < 0.01) compared to crashes. Summary: These data demonstrate increased total near crash rates among young drivers relative to adult and older drivers. Prevalence of specific near crash types also differed across age groups. Timely execution of evasive maneuvers was a distinguishing factor between crashes or near crashes. Practical Applications: These data can be used to develop more targeted driver training programs and help OEMs optimize ADAS to address the most common errors exhibited by risky drivers.     

Driver behavior analysis for right-turn drivers at signalized intersections using SHRP 2 naturalistic driving study data

IntroductionUnderstanding driver behavior is important for traffic safety and operation, especially at intersections where different traffic movements conflict. While most driver-behavior studies are based on simulation, this paper documents the analysis of driver-behavior at signalized intersections with the SHRP 2 Naturalistic Driving Study (NDS) data. This study analyzes the different influencing factors on the operation (speed control) and observation of right-turn drivers.MethodA total of 300 NDS trips at six signalized intersections were used, including the NDS time-series sensor data, the forward videos and driver face videos. Different factors of drivers, vehicles, roads and environments were studied for their influence on driver behavior. An influencing index function was developed and the index was calculated for each influencing factor to quantitatively describe its influencing level. The influencing index was applied to prioritize the factors, which facilitates development and selection of safety countermeasures to improve intersection safety. Drivers' speed control was analyzed under different conditions with consideration of the prioritized influencing factors.ResultsVehicle type, traffic signal status, conflicting traffic, conflicting pedestrian and driver age group were identified as the five major influencing factors on driver observation.ConclusionsThis research revealed that drivers have high acceleration and low observation frequency under Right-Turn-On-Red (RTOR), which constituted potential danger for other roadway users, especially for pedestrians.Practical applicationsAs speed has a direct influence on crash rates and severities, the revealed speed patterns of the different situations also benefit selection of safety countermeasures at signalized intersections.     

Driver speed selection on high-speed two-lane highways: Comparing speed profiles between uniform and differential speed limits

Objective: Although a considerable amount of prior research has investigated the impacts of speed limits on traffic safety and operations, much of this research, and nearly all of the research related to differential speed limits, has been specific to limited access freeways. The unique safety and operational issues on highways without access control create difficulty relating the conclusions from prior freeway-related speed limit research to 2-lane highways, particularly research on differential limits due to passing limitations and subsequent queuing. Therefore, the objective of this study was to assess differences in driver speed selection with respect to the posted speed limit on rural 2-lane highways, with a particular emphasis on the differences between uniform and differential speed limits.

Methods: Data were collected from nearly 59,000 vehicles across 320 sites in Montana and 4 neighboring states. Differences in mean speeds, 85th percentile speeds, and the standard deviation in speeds for free-flowing vehicles were examined across these sites using ordinary least squares regression models.

Results: Ultimately, the results of the analysis show that the mean speed, 85th percentile speed, and variability in travel speeds for free-flowing vehicles on 2-lane highways are generally lower at locations with uniform 65 mph speed limits, compared to locations with differential limits of 70 mph for cars and 60 mph for trucks.

Conclusions: In addition to posted speed limits, several site characteristics were shown to influence speed selection including shoulder widths, frequency of horizontal curves, percentage of the segment that included no passing zones, and hourly volumes. Differences in vehicle speed characteristics were also observed between states, indicating that speed selection may also be influenced by local factors, such as driver population or enforcement.     

Comparative judgements of crash risk and driving ability for speeding behaviours

Introduction: Preliminary research has indicated that numerous drivers perceive their risk of traffic crash to be less than other drivers, while perceiving their driving ability to be better. This phenomenon is referred to as ‘comparative optimism’ (CO) and may prove to inhibit the safe adoption of driving behaviors and/or dilute perceptions of negative outcomes. The objective of this study was to investigate comparative judgments regarding crash risk and driving ability, and how these judgments relate to self-reported speeding. Method: There were 760 Queensland motorists comprised of 51.6% males and 48.2% females, aged 16–85 (M = 39.60). Participants completed either a paper or online version of a survey. Judgments of crash risk and driving ability were compared to two referents: the average same-age, same-sex driver, and the average same-age, same-sex V8 supercar champion. Results: Drivers displayed greater optimism when comparing their crash risk and driving ability to the average same-age, same- sex driver (respectively, 72%, 72.4%), than when comparing to a V8 supercar champion (respectively, 60%, 32.9%). When comparing judgements of crash risk and driving ability to a similar driver, it appears that participants in the present study are just about as optimistic about their risk of crash (i.e. 72%) as they are optimistic about their driving ability (i.e. 74.2%).     

Evaluation of left-turn lane offset using the naturalistic driving study data

IntroductionThe Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS) data were used to evaluate gap acceptance behavior of drivers at left-turn lanes with negative, zero, or positive offsets ranging from − 29 ft to + 6 ft. The objectives of the study were to develop guidance for the design of offset left-turn lanes used as a safety countermeasure, and to provide insight regarding the use of the NDS data to future users.MethodThe study included 3350 gaps in opposing traffic evaluated by 145 NDS volunteer drivers and 275 non-NDS drivers at 14 two-way stop-controlled intersections and 44 signalized opposing left-turn pairs. Logistic regression was used to model the critical gap length for drivers as a function of offset, under conditions when their view was either blocked or not by an opposing left-turning driver.ResultsThe analysis found that the critical gap was longer at left-turn lanes with negative offsets than at those with zero or positive offsets, and was also longer when sight distance was blocked by an opposing left-turning vehicle. Sight distance was much more likely to be restricted by an opposing left-turning vehicle at negative-offset and drivers at those intersections were less likely to accept a gap when an opposing left-turn driver was present.ConclusionsLonger gap lengths could potentially result in decreased operational efficiency of an intersection. In addition, drivers making left-turns at negative-offset left-turn lanes are, on average, more likely to leave the shortest amount of time between their turn and the arrival of the next opposing through-vehicle, which may present a potential safety concern.Practical applicationsThe findings provide guidance for highway designers considering using offset left-turn lanes as a crash countermeasure. This research also highlights the benefits and limitations of using the SHRP 2 NDS data to answer similar research questions.     

A validation of the low mileage bias using naturalistic driving study data

IntroductionThis paper evaluated the low mileage bias (LMB) phenomenon for senior drivers using data mined from the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study. Supporters of the LMB construct postulate that it is only those seniors who drive the lowest annual mileage who are primarily responsible for the increased crash rates traditionally attributed to this population in general.MethodThe current analysis included 802 participants, all aged 65 or older who were involved in 163 property damage and injury crashes, and deemed to be at-fault in 123 (75%) of those instances. Poisson regression models were used to evaluate the association between annualized mileage driven and crash risk.ResultsResults show that the crash rate for drivers with lower annualized mileage (i.e., especially for those driving fewer than approximately 3000 miles per year) was significantly higher than that of drivers with higher annualized mileage, and that 25% of the overall sample were low- mileage drivers according to this criterion. Data were also evaluated by gender and meta-age group (i.e., younger-old: 65–74 and older-old: 75–99), and the results were consistent across these sub-groups.ConclusionsThis study provides strong support for the existence of the LMB.Practical applicationsThese results can help to reshape how transportation safety stakeholders view senior drivers in general and help them to focus their efforts on those seniors most in need of either risk-reducing countermeasures or alternative means of transportation.     

Identification of aggressive driving from naturalistic data in car-following situations

Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.     

Investigate moped-car conflicts in China using a naturalistic driving study approach

ProblemMopeds are a popular transportation mode in Europe and Asia. Moped-related traffic accidents account for a large proportion of crash fatalities. To develop moped-related crash countermeasures, it is important to understand the characteristics of moped-related conflicts.MethodNaturalistic driving study data were collected in Shanghai, China from 36 car drivers. The data included 2,878 h and 78,296 km driven from 13,149 trips. Moped-car conflicts were identified and examined from the passenger car driver's perspective using kinematic trigger algorithms and manual video reduction.ResultsA total of 119 moped-car conflicts were identified, including 74 high g-force conflicts and 45 low g-force events. These conflicts were classified into 22 on-road configurations where both similarities and differences were found as compared to Western Countries. The majority of the conflicts occurred on secondary main roads and branch roads. Hard braking was the primary response that the car drivers made to these conflicts rather than hard steering.DiscussionsThe identified on-road vehicle-moped conflict configurations in Shanghai, China may be attributed to the complicated traffic environment and risky behavior of moped riders. The lower prevalence of hard steering in Shanghai as compared to the United States may be due to the lower speeds at event onsets or less available steering space, e.g., less available shoulder area on Chinese urban roads.ConclusionsThe characteristics of moped-car conflicts may impact the design of active safety countermeasures on passenger cars. The pilot data from Shanghai urban areas suggest that countermeasures developed for China may require some modifications to those developed for the United States and European countries, although this recommendation may not be conclusive given the small sample size of the study. Future studies with large samples may help better understand the characteristics of moped-car conflicts.     

Determining the risk of driver-at-fault events associated with common distraction types using naturalistic driving data

Introduction: Studies thus far have focused on automobile accidents that involve driver distraction. However, it is hard to discern whether distraction played a role if fault designation is missing because an accident could be caused by an unexpected external event over which the driver has no control. This study seeks to determine the effect of distraction in driver-at-fault events. Method: Two generalized linear mixed models, one with at-fault safety critical events (SCE) and the other with all-cause SCEs as the outcomes, were developed to compare the odds associated with common distraction types using data from the SHRP2 naturalistic driving study. Results: Adjusting for environment and driver variation, 6 of 10 common distraction types significantly increased the risk of at-fault SCEs by 20-1330%. The three most hazardous sources of distraction were handling in-cabin objects (OR = 14.3), mobile device use (OR = 2.4), and external distraction (OR = 1.8). Mobile device use and external distraction were also among the most commonly occurring distraction types (10.1% and 11.0%, respectively). Conclusions: Focusing on at-fault events improves our understanding of the role of distraction in potentially avoidable automobile accidents. The in-cabin distraction that requires eye-hand coordination presents the most danger to drivers’ ability in maintaining fault-free, safe driving. Practical Applications: The high risk of at-fault SCEs associated with in-cabin distraction should motivate the smart design of the interior and in-vehicle information system that requires less visual attention and manual effort.     

Understanding crashes involving roadway objects with SHRP 2 naturalistic driving study data

Introduction: Crashes involving roadway objects and animals can cause severe injuries and property damages and are a major concern for the traveling public, state transportation agencies, and the automotive industry. This project involved an in-depth investigation of such crashes based on the second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study (NDS) data including detailed information and videos about 2,689 events. Methods: The research team conducted a variety of logistic regression analyses, complemented by Support Vector Machine (SVM) analyses and detailed case studies. Results: The logistic regression results indicated that driver behavior/errors, involvement of secondary tasks, roadway characteristics, lighting condition, and pavement surface condition are among the factors that contributed significantly to the occurrence and/or increased severity outcomes of crashes involving roadway objects and animals. Among these factors, improper turning movements (odds ratio = 88), avoiding animal or other vehicle (odds ratio = 38), and reaching/moving object in vehicle (odds ratio = 29) particularly increased the odds of crash occurrence. Factors such as open country roadways, sign/signal violation, unfamiliar with roadway, fatigue/drowsiness, and speeding significantly increased the severity outcomes when such crashes occurred. The sensitivity analysis of the three SVM classifiers confirmed that driver behavior/errors, critical speed, struck object type, and reaction time were major factors affecting the occurrence and severity outcomes of events involving roadway objects and animals. Practical Applications: The study provides insights on risk factors influencing safety events involving roadway objects, including their occurrence and the severity outcomes. The findings allow researchers and traffic engineers to better understand the causes of such crashes and therefore develop more effective roadway- and vehicle- based countermeasures.     

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.     

Crash rates over time among younger and older drivers in the SHRP 2 naturalistic driving study

Objective: To examine crash rates over time among 16–17-year-old drivers compared to older drivers. Methods: Data were from a random sample of 854 of the 3,500 study participants in SHRP 2, a U.S. national, naturalistic driving (instrumented vehicle) study. Crashes/10,000 miles by driver age group, 3-month period, and sex were examined within generalized linear mixed models. Results: Analyses of individual differences between age cohorts indicated higher incidence rates in the 16–17-year old cohort relative to older age groups each of the first four quarters (except the first quarter compared to 18–20 year old drivers) with incident rate ratios (IRR) ranging from 1.98 to 18.90, and for the full study period compared with drivers 18–20 (IRR = 1.69, CI = 1.00, 2.86), 21 to 25 (IRR = 2.27, CI = 1.31, 3.91), and 35 to 55 (IRR = 4.00, CI = 2.28, 7.03). Within the 16–17-year old cohort no differences were found in rates among males and females and the decline in rates over the 24-month study period was not significant. Conclusions: The prolonged period of elevated crash rates suggests the need to enhance novice young driver prevention approaches such as Graduated Driver’s Licensing limits, parent restrictions, and post-licensure supervision and monitoring. Practical Applications: Increases are needed in Graduated Driver’s Licensing limits, parent restrictions, and postlicensure supervision and monitoring.     

Using SHRP 2 naturalistic driving data to assess drivers' speed choice while being engaged in different secondary tasks

IntroductionThe engagement in secondary tasks while driving has been found to result in considerable impairments of driving performance. Texting has especially been suspected to be associated with an increased crash risk. At the same time, there is evidence that drivers use various self-regulating strategies to compensate for the increased demands caused by secondary task engagement. One of the findings reported from multiple studies is a reduction in driving speed. However, most of these studies are of experimental nature and do not let the drivers decide for themselves to (not) engage in the secondary task, and therefore, eliminate other strategies of self-regulation (e.g., postponing the task). The goal of the present analysis was to investigate if secondary task engagement results in speed adjustment also under naturalistic conditions.MethodOur analysis relied on data of the SHRP 2 naturalistic driving study. To minimize the influence of potentially confounding factors on drivers' speed choice, we focused on episodes of free flow driving on interstates/highways. Driving speed was analyzed before, during, and after texting, smoking, eating, and adjusting/monitoring radio or climate control; in a total of 403 episodes.ResultsData show some indication for speed adjustment for texting, especially when driving with high speed. However, the effect sizes were small and behavioral patterns varied considerably between drivers. The engagement in the other tasks did not influence drivers' speed behavior significantly.Conclusions and practical applicationsWhile drivers might indeed reduce speed slightly to accommodate for secondary task engagement, other forms of adaptation (e.g., strategic decisions) might play a more important role in a natural driving environment. The use of naturalistic driving data to study drivers' self-regulatory behavior at an operational level has proven to be promising. Still, in order to obtain a comprehensive understanding about drivers' self-regulatory behavior, a mixed-method approach is required.     

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.     

E-bikers’ braking behavior: Results from a naturalistic cycling study

Abstract

Objective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.

Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5?h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.

Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.

Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation.     

Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting

Introduction: COVID-19 has disrupted daily life and societal flow globally since December 2019; it introduced measures such as lockdown and suspension of all non-essential movements. As a result, driving activity was also significantly affected. Still, to-date, a quantitative assessment of the effect of COVID-19 on driving behavior during the lockdown is yet to be provided. This gap forms the motivation for this paper, which aims at comparing observed values concerning three indicators (average speed, speeding, and harsh braking), with forecasts based on their corresponding observations before the lockdown in Greece. Method: Time series of the three indicators were extracted using a specially developed smartphone application and transmitted to a back-end platform between 01/01/2020 and 09/05/2020, a time period containing normal operations, COVID-19 spreading, and the full lockdown period in Greece. Based on the collected data, XGBoost was employed to identify the most influential COVID-19 indicators, and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models were developed for obtaining forecasts on driving behavior. Results: Results revealed the intensity of the impact of COVID-19 on driving, especially on average speed, speeding, and harsh braking per 100 km. More specifically, speeds were found to increase by 2.27 km/h on average compared to the forecasted evolution, while harsh braking/100 km increased to almost 1.51 on average. On the bright side, road crashes in Greece were reduced by 49% during the months of COVID-19 compared to the non-COVID-19 period.     

Conscientious personality and young drivers' crash risk

Introduction: Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Method: Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18 months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate, and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants' KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Results: Conscientiousness was marginally negatively associated with CNC (path c = − 0.034, p = .09) and both potential mediators KRD (path a = − 0.040, p = .09) and secondary task engagement while driving (path a = − 0.053, p = .03). KRD, but not secondary task engagement, was found to mediate (path b = 0.376, p = .02) the relationship between conscientiousness and CNC (path c′ = − 0.025, p = .20). Conclusions: Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, and suffered fewer CNC. Practical Applications: Part of the variability in crash risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers' personality into account when providing guidance, and establishing norms and expectations about driving.