A rear-end collision risk assessment model based on drivers’ collision avoidance process under influences of cell phone use and gender—A driving simulator based study

Driver’s collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver’s performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver’s gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle’s sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver’s gender. The cell phone use and driver’s gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in critical situation, they were more quickly in braking with larger maximum deceleration rate, and they tended to keep a larger safety margin with the leading vehicle compared to male drivers. The findings shed some light on the further development of advanced collision avoidance technologies and the targeted intervention strategies about cell phone use while driving.     

Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model

Multi-vehicle rear-end accidents constitute a substantial portion of the accidents occurring at signalized intersections. To examine the accident characteristics, this study utilized the 2001 Florida traffic accident data to investigate the accident propensity for different vehicle roles (striking or struck) that are involved in the accidents and identify the significant risk factors related to the traffic environment, the driver characteristics, and the vehicle types. The Quasi-induced exposure concept and the multiple logistic regression technique are used to perform this analysis. The results showed that seven road environment factors (number of lanes, divided/undivided highway, accident time, road surface condition, highway character, urban/rural, and speed limit), five factors related to striking role (vehicle type, driver age, alcohol/drug use, driver residence, and gender), and four factors related to struck role (vehicle type, driver age, driver residence, and gender) are significantly associated with the risk of rear-end accidents. Furthermore, the logistic regression technique confirmed several significant interaction effects between those risk factors.     

Young driver accidents in the UK: the influence of age, experience, and time of day

Young drivers, especially males, have relatively more accidents than other drivers. Young driver accidents also have somewhat different characteristics to those of other drivers; they include single vehicle accidents involving loss of control; excess speed for conditions; accidents during darkness; accidents on single carriageway rural roads; and accidents while making cross-flow turns (i.e. turning right in the UK, equivalent to a left turn in the US and continental Europe). A sample of over 3000 accident cases was considered from midland British police forces, involving drivers aged 17-25 years, and covering a two year period. Four types of accident were analysed: right-turns; rear-end shunts; loss of control on curves; and accidents in darkness. Loss of control on curves and accidents in darkness were found to be a particular problem for younger drivers. It was found that cross-flow turn accidents showed the quickest improvement with increasing driver experience, whereas accidents occurring in darkness with no street lighting showed the slowest rate of improvement. 'Time of day' analyses suggested that the problems of accidents in darkness are not a matter of visibility, but a consequence of the way young drivers use the roads at night. There appears to be a large number of accidents associated with voluntary risk-taking behaviours of young drivers in 'recreational' driving.     

Risky driving related to driver and vehicle characteristics

This investigation was performed to determine relationships between driver and vehicle characteristics and risk taking in everyday driving, as measured by close following in freeway traffic. A total of 12,000 observations were made of headways (time intervals between successive vehicles) in high flow freely moving freeway traffic at two sites, one in Michigan, the other in Toronto, Canada. The headways were measured using a photographic technique which allowed vehicle and occupant characteristics to be recorded, including type of vehicle and sex and seat belt use. For the Michigan observations, the vehicle license number was recorded, from which additional information on the vehicle and owner (usually the driver) was obtained from state files, including the vehicle mass and model year and the owner's age. sex and history of recorded accidents and traffic violations. Shorter headways, corresponding to higher risk, were found for drivers with prior accidents or violations, young drivers, male drivers, drivers with no passengers. and drivers who did not wear a seat belt. Vehicles associated with shorter headways included newer cars and cars of intermediate mass (1600–1900 kg).     

Speed as a measure of driver risk: Observed speeds versus driver and vehicle characteristics

This investigation was performed to determine relationships between driver and vehicle characteristics and freely chosen speeds of cars on a two lane road with little commercial or residential development. Speed is taken as a measure of a driver's willingness to expose himself to risk of accident, in the same way that short freeway headways were interpreted in an earlier study. A total of 6638 passenger car speeds were measured by radar while each oncoming vehicle was simultaneously photographed. Driver and vehicle characteristics were derived from the photographs, both by direct observation (vehicle type, driver sex, presence of front seat passengers, seat belt use) and from the car license plate through the use of State vehicle registration and driver licensing files. The State files provided the car mass and model year and the owner (usually driver) age, sex, and recorded accidents and violations. Higher speeds were observed for younger drivers, drivers with prior accidents and convictions, newer cars, heavier cars and cars with no passengers.     

Exploring precrash maneuvers using classification trees and random forests

Taking evasive actions vis-à-vis critical traffic situations impending to motor vehicle crashes endows drivers an opportunity to avoid the crash occurrence or at least diminish its severity. This study explores the drivers, vehicles, and environments’ characteristics associated with crash avoidance maneuvers (i.e., evasive actions or no evasive actions). Rear-end collisions, head-on collisions, and angle collisions are analyzed separately using decision trees and the significance of the variables on the binary response variable (evasive actions or no evasive actions) is determined. Moreover, the random forests method is employed to rank the importance of the drivers/vehicles/environments characteristics on crash avoidance maneuvers. According to the exploratory analyses’ results, drivers’ visibility obstruction, drivers’ physical impairment, drivers’ distraction are associated with crash avoidance maneuvers in all three types of accidents. Moreover, speed limit is associated with rear-end collisions’ avoidance maneuvers and vehicle type is correlated with head-on collisions and angle collisions’ avoidance maneuvers. It is recommended that future research investigates further the explored trends (e.g., physically impaired drivers, visibility obstruction) using driving simulators which may help in legislative initiatives and in-vehicle technology recommendations.     

Collective responsibility for freeway rear-ending accidents? An application of probabilistic casual models

Determining whether or not an event was a cause of a road accident often involves determining the truth of a counterfactual conditional, where what happened is compared to what would have happened had the supposed cause been absent. Using structural causal models, Pearl and his associates have recently developed a rigorous method for posing and answering causal questions, and this approach is especially well suited to the reconstruction and analysis of road accidents. Here, we applied these methods to three freeway rear-end collisions. Starting with video recordings of the accidents, trajectory information for a platoon of vehicles involved in and preceding the collision was extracted from the video record, and this information was used to estimate each driver's initial speed, following distance, reaction time, and braking rate. Using Brill's model of rear-end accidents, it was then possible to simulate what would have happened, other things being equal, had certain driver actions been other than they were. In each of the three accidents we found evidence that: (1) short following headways by the colliding drivers were probable causal factors for the collisions, (2) for each collision, at least one driver ahead of the colliding vehicles probably had a reaction time that was longer than his or her following headway, and (3) had that driver's reaction time been equal to his or her following headway, the rear-end collision probably would not have happened.     

The effect of distractions on the crash types of teenage drivers

Teenage drivers are overrepresented in crashes when compared to middle-aged drivers. Driver distraction is becoming a greater concern among this group as in-vehicle devices, opportunities for distractions, and teenage drivers' willingness to engage in these activities increase. The objective of this study was to determine how different distraction factors impact the crash types that are common among teenage drivers. A multinomial logit model was developed to predict the likelihood that a driver will be involved in one of three common crash types: an angular collision with a moving vehicle, a rear-end collision with a moving lead vehicle, and a collision with a fixed object. These crashes were evaluated in terms of four driver distraction categories: cognitive, cell phone related, in-vehicle, and passenger-related distractions. Different driver distractions have varying effects on teenage drivers' crash involvement. Teenage drivers that were distracted at an intersection by passengers or cognitively were more likely to be involved in rear-end and angular collisions when compared to fixed-object collisions. In-vehicle distractions resulted in a greater likelihood of a collision with a fixed object when compared to angular collisions. Cell phone distractions resulted in a higher likelihood of rear-end collision. The results from this study need to be evaluated with caution due to the limited number of distraction related cases available in the U.S. GES crash database. Implications for identifying and improving the reporting of driver distraction related factors are therefore discussed.     

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.     

Modeling rear-end collisions including the role of driver's visibility and light truck vehicles using a nested logit structure

This paper presents an analysis of the effect of the geometric incompatibility of light truck vehicles (LTV)--light-duty trucks, vans, and sport utility vehicles--on drivers' visibility of other passenger cars involved in rear-end collisions. The geometric incompatibility arises from the fact that most LTVs ride higher and are wider than regular passenger cars. The objective of this paper is to explore the effect of the lead vehicle's size on the rear-end crash configuration. Four rear-end crash configurations are defined based on the type of the two involved vehicles (lead and following vehicles). Nested logit models were calibrated to estimate the probabilities of the four rear-end crash configurations as a function of driver's age, gender, vehicle type, vehicle maneuver, light conditions, driver's visibility and speed. Results showed that driver's visibility and inattention in the following (striker) vehicle have the largest effect on being involved in a rear-end collision of configuration CarTrk (a regular passenger car striking an LTV). Possibly, indicating a sight distance problem. A driver of a smaller car following an LTV, have a problem seeing the roadway beyond the LTV, and therefore would not be able to adjust his/her speed accordingly, increasing the probability of a rear-end collision. Also, the probability of a CarTrk rear-end crash increases in the case that the lead vehicle stops suddenly.