Using SHRP2 naturalistic driving data to examine driver speeding behavior

Problem: Speeding-related crashes continue to be a serious problem in the United States. According to the National Highway Traffic Safety Administration, 26% of all fatal crashes in 2017 had speeding as a contributing factor. Method: Vehicle speed data recorded during the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study were analyzed to identify the frequency of speeding episodes. Up to 100 trips were sampled from 2,910 individual drivers aged 16–64. Vehicle speed data from individual trips were parsed into continuous speeding episodes (SEs) and Free-Flow Episodes (FFEs), which approximated opportunities to speed. Results & Discussion: Driving 10 mph above the posted speed limit (PSL) was common, and 99.8% of drivers had at least one occurrence SE within their trip sample, yielding an average of 2.75 SEs per trip (623,202 SEs in total). The analysis focused on a subset of higher-speed SEs in which the vehicle reached speeds of at least 15 mph above the PSL during the SE (71,113 SEs in total). Average maximum speeds for most higher-speed SEs ranged between 12 mph to 15 mph above the PSL, and most also lasted less than 2 min. Most drivers spent less than 5% of the FFE time speeding, and only a small number of drivers spent more than 10% of the time speeding. There was also a clear trend towards the younger group having higher overall percentages of SE time relative to FFE time. Practical Applications: The methods and measures developed in this study provide the foundation for future analyses to determine if there are different types of speeding that vary in terms of risky characteristics, and further, if certain drivers are more likely to engage in riskier speeding behavior. Identifying higher-risk speeders is an important step for developing countermeasures and strategies targeting drivers that are at greatest risk of speed-related crashes.     

Effects of vehicle power on passenger vehicle speeds

Objectives: During the past 2 decades, there have been large increases in mean horsepower and the mean horsepower-to–vehicle weight ratio for all types of new passenger vehicles in the United States. This study examined the relationship between travel speeds and vehicle power, defined as horsepower per 100 pounds of vehicle weight.

Methods: Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit.

Results: After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant.

Conclusions: Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash risk and crash severity, this is cause for concern.     

Women drivers' behavior in well-known versus less familiar locations

INTRODUCTION: Through observations this study sought to examine the effects of road familiarity on driving performance. METHOD: Severe and minor traffic violations, dangerous behaviors, and speeding were assessed in well known and in less familiar locations. RESULTS: As compared to less known locations, drivers in well known locations performed more severe and minor violations, more dangerous behaviors, and they drove above the speed limit more often. DISCUSSION: The results are discussed in the context of Theory of Risk Homeostasis (later re-labeled as Target Risk Theory), the psychological effect of familiarity on driving performance, and the phenomenon of automatic driving. Presenting the risk of driving in familiar locations would assist to elevate safe driving.     

Do speeding tickets reduce the likelihood of receiving subsequent speeding tickets? A longitudinal study of speeding violators in Maryland

OBJECTIVE: Speeding tickets are the most commonly used tool to deter speeders, yet little is known about how speeding citations affect individual drivers' behavior over time. This study examined the effects of being cited for speeding and types of legal consequences on drivers' subsequent speeding citations, which are an indicator of speeding behavior. METHODS: A cohort of 3,739,951 Maryland licensed drivers were identified and followed for one year. Drivers were categorized by whether or not they received a speeding citation in May 2002. Among those cited for speeding in May 2002, drivers were grouped by type of penalty (fines and points; probation before judgment [PBJ, which results in fines but no points]; or no legal consequences). The relative risks (RR) and 95 percent confidence intervals (CI) of receiving a speeding citation during follow-up were compared between drivers ticketed and not ticketed in May 2002, as well as among different penalty groups. Cox proportional hazards regression modeling was used to adjust for potential confounders, including age, gender, alcohol-impaired driving, and residence. Kaplan-Meier survival functions were used to examine timing of violations. RESULTS: Young drivers and male drivers were more likely to receive a speeding citation. Drivers who received a speeding citation in May 2002 had almost twice the risk of receiving a speeding citation during follow-up, compared with those not cited for speeding that month (RR 1.6, 95% CI 1.52-1.68). Overall legal consequences had no significant effect on the risk of receiving a repeat speeding citation relative to ticketed drivers who escaped those consequences (RR 0.98, 95% CI 0.84-1.15); however, stratified analyses showed a significant decrease in repeat citations among females (RR 0.75, 95% CI 0.63-0.90) and drivers who received PBJ (RR 0.81, 95% CI 0.67-0.96). Kaplan-Meier curves showed that the study group of speeders had a significantly shorter time between May 2002 until receipt of a speeding citation than controls. Among penalty groups, significantly shorter times until receipt of another citation were observed among drivers escaping consequences or receiving fines/points compared with drivers receiving fines/PBJ. CONCLUSIONS: Drivers who receive speeding citations are at increased risk of receiving subsequent speeding citations, suggesting that speeding citations have limited effects on deterrence in the context of the current traffic enforcement system. When comparing different penalties, PBJ is associated with a reduced rate of recidivism more than stronger penalties; however, it is unclear whether the reduction primarily is attributable to the penalty itself or to characteristics of drivers receiving PBJ. Increasing drivers' perceptions that they are at risk of being caught speeding may improve the effectiveness of speeding law enforcement.     

Taxi driver speeding: Who,when, where and how? A comparative study between Shanghai and New York City

Objective: The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?)

Methods: This study proposes a driver–road–environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC.

Results: The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0–1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities.

Conclusions: Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.     

Measures of speeding from a GPS-based travel behavior survey

Objective: Lacking information about actual driving speed on most roads in the Minneapolis–St. Paul region, we determine car speeds using observations from a Global Positioning System (GPS)-based travel survey. Speed of travel determines the likelihood and consequences of collisions. We identify the road segments where speeding occurs. This article then analyzes the relationship between link length, traveler characteristics, and speeding using GPS data collected from 152 individuals over a 7-day period as part of the Minneapolis–St. Paul Travel Behavior Inventory.

Methods: To investigate the relationship, we employed an algorithm and process to accurately match the GPS data with geographic information system (GIS) databases. Comparing actual travel speed from GPS data with posted speed limits, we measure where and when speeding occurs and by whom. We posit that link length and demographics shape the decision to speed.

Results: Speeding is widespread under both high speed limits (e.g., 60?mph [97?km/h]) and low speed limits (less than 25?mph [40?km/h]); in contrast, speeding is less common at 30–35?mph (48–56?km/h). The results suggest that driving patterns depend on the road type. We also find that when there are many intersections, the average link speed (and speeding) drops. Long links are conducive to speeding. Younger drivers and more educated drivers also speed more, and speeding occurs more often in the evening.

Conclusions: Road design and link length (or its converse, frequency of intersections) affect the likelihood of speeding. Use of increasingly available GPS data allows more systematic empirical analysis of designs and topologies that are conducive to road safety.     

Analyses of rear-end crashes based on classification tree models

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

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.     

Reliability of police-reported information for determining crash and injury severity

Posted speed limit and police-reported injury codes are commonly used by researchers to approximate vehicle impact and occupant injury severity. In-depth crash investigations, however, produce more precise measures of crash and injury severity: change in velocity (delta-V) for crash severity and Abbreviated Injury Scale (AIS) scores for injury severity. A comparison of data from police crash reports with that gathered by National Automotive Sampling System (NASS) investigators highlighted the inadequacy of speed limit and police injury codes as proxies for delta-V and AIS injury severity. In general, delta-V increased with speed limit and higher values of AIS were associated with higher police-coded injury severity, but there were a number of anomalies. In particular, 49% of the drivers coded by police as having incapacitating injuries actually had sustained no more than minor injuries. This overstatement of injury severity was less frequent among male (44%) and elderly (37%) drivers than among female (53%) and nonelderly (50%) drivers. Also, 79% of the investigated vehicles that crashed on roads posted at 60 mph (96 km/h) or higher experienced a delta-V less than 25 mph (40 km/h). Safety studies depending on data from only police reports to establish injury or crash severity therefore could produce erroneous results.     

Driver Behavior During Overtaking Maneuvers from the 100-Car Naturalistic Driving Study

Objective: Lane changes with the intention to overtake the vehicle in front are especially challenging scenarios for forward collision warning (FCW) designs. These overtaking maneuvers can occur at high relative vehicle speeds and often involve no brake and/or turn signal application. Therefore, overtaking presents the potential of erroneously triggering the FCW. A better understanding of driver behavior during lane change events can improve designs of this human–machine interface and increase driver acceptance of FCW. The objective of this study was to aid FCW design by characterizing driver behavior during lane change events using naturalistic driving study data.

Methods: The analysis was based on data from the 100-Car Naturalistic Driving Study, collected by the Virginia Tech Transportation Institute. The 100-Car study contains approximately 1.2 million vehicle miles of driving and 43,000 h of data collected from 108 primary drivers. In order to identify overtaking maneuvers from a large sample of driving data, an algorithm to automatically identify overtaking events was developed. The lead vehicle and minimum time to collision (TTC) at the start of lane change events was identified using radar processing techniques developed in a previous study. The lane change identification algorithm was validated against video analysis, which manually identified 1,425 lane change events from approximately 126 full trips.

Results: Forty-five drivers with valid time series data were selected from the 100-Car study. From the sample of drivers, our algorithm identified 326,238 lane change events. A total of 90,639 lane change events were found to involve a closing lead vehicle. Lane change events were evenly distributed between left side and right side lane changes. The characterization of lane change frequency and minimum TTC was divided into 10 mph speed bins for vehicle travel speeds between 10 and 90 mph. For all lane change events with a closing lead vehicle, the results showed that drivers change lanes most frequently in the 40–50 mph speed range. Minimum TTC was found to increase with travel speed. The variability in minimum TTC between drivers also increased with travel speed.

Conclusions: This study developed and validated an algorithm to detect lane change events in the 100-Car Naturalistic Driving Study and characterized lane change events in the database. The characterization of driver behavior in lane change events showed that driver lane change frequency and minimum TTC vary with travel speed. The characterization of overtaking maneuvers from this study will aid in improving the overall effectiveness of FCW systems by providing active safety system designers with further understanding of driver action in overtaking maneuvers, thereby increasing system warning accuracy, reducing erroneous warnings, and improving driver acceptance.     

Peer influence predicts speeding prevalence among teenage drivers

Impact on IndustryPreventing speed-related crashes could reduce costs and improve efficiency in the transportation industry.ObjectiveThis research examined the psychosocial and personality predictors of observed speeding among young drivers.MethodSurvey and driving data were collected from 42 newly-licensed teenage drivers during the first 18 months of licensure. Speeding (i.e., driving 10 mph over the speed limit; about 16 km/h) was assessed by comparing speed data collected with recording systems installed in participants' vehicles with posted speed limits.ResultsSpeeding was correlated with elevated g-force event rates (r = 0.335, pb0.05), increased over time, and predicted by day vs. night trips, higher sensation seeking, substance use, tolerance of deviance, susceptibility to peer pressure, and number of risky friends. Perceived risk was a significant mediator of the association between speeding and risky friends.ConclusionThe findings support the contention that social norms may influence teenage speeding behavior and this relationship may operate through perceived risk.     

Raising the speed limit from 75 to 80 mph on Utah rural interstates: Effects on vehicle speeds and speed variance

IntroductionIn November 2010 and October 2013, Utah increased speed limits on sections of rural interstates from 75 to 80 mph. Effects on vehicle speeds and speed variance were examined.MethodsSpeeds were measured in May 2010 and May 2014 within the new 80 mph zones, and at a nearby spillover site and at more distant control sites where speed limits remained 75 mph. Log-linear regression models estimated percentage changes in speed variance and mean speeds for passenger vehicles and large trucks associated with the speed limit increase. Logistic regression models estimated effects on the probability of passenger vehicles exceeding 80, 85, or 90 mph and large trucks exceeding 80 mph.ResultsWithin the 80 mph zones and at the spillover location in 2014, mean passenger vehicle speeds were significantly higher (4.1% and 3.5%, respectively), as were the probabilities that passenger vehicles exceeded 80 mph (122.3% and 88.5%, respectively), than would have been expected without the speed limit increase. Probabilities that passenger vehicles exceeded 85 and 90 mph were non-significantly higher than expected within the 80 mph zones. For large trucks, the mean speed and probability of exceeding 80 mph were higher than expected within the 80 mph zones. Only the increase in mean speed was significant. Raising the speed limit was associated with non-significant increases in speed variance.ConclusionsThe study adds to the wealth of evidence that increasing speed limits leads to higher travel speeds and an increased probability of exceeding the new speed limit. Results moreover contradict the claim that increasing speed limits reduces speed variance.Practical applicationsAlthough the estimated increases in mean vehicle speeds may appear modest, prior research suggests such increases would be associated with substantial increases in fatal or injury crashes. This should be considered by lawmakers considering increasing speed limits.     

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

Aims: Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

Methods: A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004–2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

Results: Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

Conclusions: Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.     

Distracting behaviors among teenagers and young,middle-aged,and older adult drivers when driving without and with warnings from an integrated vehicle safety system

IntroductionNegative reinforcement from crash warnings may reduce the likelihood that drivers engage in distracted driving. Alternatively, drivers may compensate for the perceived safety benefit of crash warnings by engaging in distractions more frequently, especially at higher speeds. The purpose of this study was to examine whether warning feedback from an integrated vehicle-based safety system affected the likelihood that various secondary behaviors were present among drivers ages 16–17, 20–30, 40–50, and 60–70.MethodParticipants drove an instrumented sedan with various collision warning systems for an extended period. Ten 5-second video clips were randomly sampled from driving periods at speeds above 25 mph and below 5 mph each week for each driver and coded for the presence of 11 secondary behaviors.ResultsAt least one secondary behavior was present in 46% of video clips; conversing with a passenger (17%), personal grooming (9%), and cellphone conversation (6%) were the most common. The likelihood that at least one secondary behavior was present was not significantly different during periods when drivers received warnings relative to periods without warnings. At least one secondary behavior was 21% more likely to be present at speeds below 5 mph relative to speeds above 25 mph; however, the effect of vehicle speed was not significantly affected by warning presence. Separate models for each of the five most common secondary behaviors also indicated that warnings had no significant effect on the likelihood that each behavior was present.ConclusionsCollision warnings were not associated with significant increases or decreases in the overall likelihood that teen and adult drivers engaged in secondary behaviors or the likelihood of the behaviors at speeds above 25 mph or below 5 mph.Practical applicationsThere was no evidence that forward collision warning and other technologies like those in this study will increase or decrease distracted driving.     

Traffic speeds associated with implementation of 80 mph speed limits on West Texas rural interstates

Problem

In 2006 Texas raised the daytime speed limit for passenger vehicles on segments of I-10 and I-20 from 75 to 80 mph. Methods: Traffic speeds were measured before and 3, 12, and 16 months after the limit was changed. Results: During the 16-month period following the speed limit increase, mean speeds of passenger vehicles on I-20 increased by 9 mph relative to the comparison road, where no speed limit change occurred and traffic speeds declined. On I-10 mean speeds increased by 4 mph relative to the comparison road. Limiting the analysis to the month before the speed limit change and 1 year later, the proportion of drivers exceeding 80 mph was 18 times higher on I-20 and 2 times higher on I-10. Discussion: The smaller speed increases on I-10 may be related to its proximity to the U.S. border with Mexico. Highly visible border patrol activity coincided with posting of the higher speed limit. Long-term monitoring in other states suggests that traffic speeds in Texas are likely to continue to increase. Impact on Industry: The present study adds to the wealth of evidence that increased speed limits lead to increased travel speeds. The primary countermeasures to reduce the risk of speed-related crashes include highly visible police traffic enforcement and the use of speed cameras accompanied by publicity.     

Effects of environment, vehicle and driver characteristics on risky driving behavior at work zones

This study aims to analyze the effects of environment, vehicle and driver characteristics on the risky driving behavior at work zones. A decision tree is developed using the classification and regression tree (CART) algorithm to graphically display the relationship between the risky driving behavior and its influencing factors. This approach could avoid the inherent problems occurred in the conventional logistic regression models and further improve the model prediction accuracy. Based on the Michigan M-94/I-94/I-94BL/I-94BR highway work zone driving behavior data, the decision tree comprising 33 leaf nodes is built. Bad weather, poor road and light conditions, partial/no access control, no traffic control devices, turning left/right and driving in an old vehicle are found to be associated with the risky driving behavior at work zones. The middle-aged drivers, who are going straight ahead in their vehicles with medium service time and equipped with an airbag system, are more likely to take risky behavior at lower work zone speed limits. Further, the middle-aged male drivers engage in risky driving behavior more frequently than the middle-aged female drivers. The number of lanes exhibits opposing effects on risky behavior under different traveling conditions. More specifically, the risky driving behavior is associated with the single-lane road under bad light or weather conditions while drivers are more likely to engage in risky behavior on the multi-lane road under good light conditions.     

Modeling drivers’ reaction when being tailgated: A Random Forests Method

Background: Tailgating is a common aggressive driving behavior that has been identified as one of the leading causes of rear-end crashes. Previous studies have explored the behavior of tailgating drivers and have reported effective solutions to decrease the amount or prevalence of tailgating. This paper tries to fill the research gap by focusing on understanding highway tailgating scenarios and examining the leading vehicles’ reaction using existing naturalistic driving data. Method: A total of 1,255 tailgating events were identified by using the one-second time headway threshold criterion. Four types of reactions from the leading vehicles were identified, including changing lanes, slowing down, speeding up, and making no response. A Random Forests algorithm was employed in this study to predict the leading vehicle’s reaction based on corresponding factors including driver, vehicle, and environmental variables. Results: The analysis of the tailgating scenarios and associated factors showed that male drivers were more frequently involved in tailgating events than female drivers and that tailgating was more prevalent under sunny weather and in daytime conditions. Changing lanes was the most prevalent reaction from the leading vehicle during tailgating, which accounted for more than half of the total events. The results of Random Forests showed that mean time headway, duration of tailgating, and minimum time headway were three main factors, which had the greatest impact on the leading vehicle drivers’ reaction. It was found that in 95% of the events, leading vehicles would change lanes when being tailgated for two minutes or longer. Practical Applications: Results of this study can help to better understand the behavior and decision making of drivers. This understanding can be used in designing countermeasures or assistance systems to reduce tailgating behavior and related negative safety consequences.     

Red light violations at rural and suburban signalized intersections in Jordan

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

Aggressive driving behaviour in young drivers (aged 16 through 25) involved in fatal crashes

IntroductionWe wished to determine the extent to which number of passengers, driver age, and sex were associated with aggressive driving actions (ADAs) in young drivers involved in a fatal crash.MethodsWe used U.S. fatal-crash data from Fatality Analysis Reporting System (FARS), 1991 –2008. Proxy measures of aggressive driving included ADA presence and speed differential (posted speed limit minus estimated travel speed). We examined the odds of an ADA and speed differential in young drivers (aged 16 to 25) by passenger status.ResultsCompared to driving alone young drivers (aged 16) had increased odds of an ADA between 14% (OR: 1.14; 95% CI: 1.07; 1.22) and 95% (OR: 1.95; 95% CI: 1.40; 2.74) when accompanied by one and five passengers, respectively. Further, carrying a higher number of passengers was a stronger predictor of speeding in younger drivers.ConclusionsThis study supports the use of graduated licensing approaches. Specifically, developing interventions to reduce aggressive driving appear imperative.Impact on IndustryWhile the results of our study support the use of graduated licensing approaches there is room for improvement. Our study indicates that tackling impaired driving is not sufficient to drastically reduce aggressive driving among the youngest drivers. Further research on young drivers is required to understand the influence of peers and the role of gender on driving behavior. Strategies to reduce aggressive driving behaviors among the youngest drivers may not only prevent crashes during their early driving careers but may also translate into a reduced crash risk over their lifetime.