Lane Change Crash Research Articles

A surrogate safety analysis at sharp gore areas of diverging freeway ramps using micro simulation under congested traffic conditions

Safety at the gore areas near diverging ramps is very crucial during planning and implementation of highway safety improvement programs. Limited research has been conducted on safety at the gore areas on arterial roads. This study aims at investigating the impact of improving a sharp gore area in Lincoln, Nebraska by performing a micro simulation before-and-after study with respect to its underlying state of safety and congestion. Data on travel times and traffic volumes for peak hours are incorporated after successful calibration to find out how a geometric intervention can decrease mobility issues as well as the likelihood of crash involvement. This study has utilized VISSIM software package to run the simulation however, to perform safety analysis, Surrogate Safety Assessment Model (SSAM) is used which is developed by the Federal Highway Administration (FHWA). During the model calibration, custom driving behaviors are created to represent driving tendencies of familiar drivers. The simulation results indicated that by adding an auxiliary lane near the gore area, the mobility issues such as bottle necks, lane changing dilemmas and queue lengths are substantially decreased. However, geometric interventions such as provision of a separate lane, increasing ramp spacing, nose spacing, deceleration area and queue storage area considerably reduced the likelihood of rear-end and lane changing crashes. Surrogate safety assessment in diverging ramps, particularly for sharp gores, has not previously been studied, and this study can serve as a primary footmark for future research on ramp-gores safety.

Analysis of pre-crash scenarios and contributing factors for autonomous vehicle crashes at intersections

Intersections are high-risk locations for autonomous vehicles (AVs). Crash causation analysis based on pre-crash scenarios can provide new insight into these crashes that can lead to effective countermeasures, but there are significant differences in pre-crash scenarios between autonomous and conventional vehicles, and inadequate AV data has put limits on research. The association rule method, however, can yield useful results despite these limits. This study therefore aims to use the method with pre-crash scenarios to understand the characteristics and contributing factors of AV crashes at intersections from the latest 5-year AV crash data. Analysis of 197 AV crashes at intersections revealed 30 types of pre-crash scenarios. The rear-end crash (58.88%) and lane change crash (16.24%) were the most frequently occurring scenarios for AVs. The proportion of AVs being rear-ended by conventional vehicles was 58.38%. The main contributing factors of these two most common AV scenarios were identified by association rules and crash causes were analyzed from the perspective of AV decision-making. The main factors contributing to the AV rear-end scenario were location outside the intersection in the intersection-related area, traffic signal control, autonomous engaged mode, mixed-use or public land, and weekdays, while those for lane change scenarios were on-street parking and the time of 8:00 a.m. Important causes of rear-end crashes attributable to the AV were inadequate stop and deceleration decisions by the AV’s automated driving system (ADS) and insufficient collision avoidance decisions in lane change crashes. Identification of the pre-crash characteristics and contributing factors provide new insight into AV crash causation and can be used in the determination of the AV’s operational design domain and the development and optimization of the AV’s ADS at intersections. These findings can also play a role in guiding traffic safety agencies to discover AV hotspots and propose AV management regulations.

Field effectiveness of general motors advanced driver assistance and headlighting systems

This study examined the field effectiveness of General Motors advanced driver assistance and headlighting systems. A total of 8,311,707 Model Year 2013–2019 vehicles were matched to police-reported crashes from 12 states. The quasi-induced exposure method was used to compare system-relevant and system-irrelevant (control) crash counts for equipped and unequipped vehicles. Logistic regression was used to adjust for ten covariates. Results indicated fusion/radar Automatic Emergency Braking, camera Automatic Emergency Braking, and Forward Collision Alert systems reduced rear-end striking crashes by 45%, 38%, and 20%, respectively. When restricting data to crashes in which someone in the General Motors striking vehicle was injured, these reductions were elevated to 59%, 54%, and 31%, respectively, providing evidence of additional crash mitigation benefits. Similarly, the Lane Keep Assist with Lane Departure Warning and Lane Departure Warning (alone) systems provided 12% and 10% reductions in lane departure crashes, respectively, with corresponding benefits in the injury analysis increasing to 19% and 18%, respectively. The Lane Change Alert with Side Blind Zone Alert system reduced lane change crashes by 16%. Reverse Automatic Braking, Rear Cross Traffic Alert, Rear Park Assist, and Rear Vision Camera (where each of these systems generally included all of the preceding systems) produced, respectively, an 82%, 55%, 36%, and 24% reduction in backing crashes. For Front Pedestrian Braking, a non-significant 14% reduction was observed for the limited set of available pedestrian crash cases. Intellibeam (auto high beam headlighting), High-Intensity Discharge headlights, and the combination of these two systems provided 26%, 11%, and 32% reductions (relative to halogen headlights) in a combined set of (unlighted) nighttime animal, pedestrian, and bicyclist crashes, respectively. These results provide widespread evidence of the substantial crash avoidance and injury reduction opportunities afforded by the production systems evaluated, as well as identify untapped system opportunities for moving toward a zero crashes vision.

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. These results pave the way for future design of secure systems from a monitoring perspective.

Injury-severity analysis of lane change crashes involving commercial motor vehicles on interstate highways

Introduction: One of the challenging tasks for drivers is the ability to change lanes around large commercial motor vehicles. Lane changing is often characterized by speed, and crashes that occur due to unsafe lane changes can have serious consequences. Considering the economic importance of commercial trucks, ensuring the safety, security, and resilience of freight transportation is of paramount concern to the United States Department of Transportation and other stakeholders. Method: In this study, a mixed (random parameters) logit model was developed to better understand the relationship between crash factors and associated injury severities of commercial vehicle crashes involving lane change on interstate highways. The study was based on 2009–2016 crash data from Alabama. Results: Preliminary data analysis showed that about 4% of the observed crashes were major injury crashes and drivers of commercial motor vehicles were at-fault in more than half of the crashes. Acknowledging potential crash data limitations, the model estimation results reveal that there is increased probability of major injury when lane change crashes occurred on dark unlit portions of interstates and involve older drivers, at-fault commercial vehicle drivers, and female drivers. The results further show that lane change crashes that occurred on interstates with higher number of travel lanes were less likely to have major injury outcomes. Practical Applications: These findings can help policy makers and state transportation agencies increase awareness on the hazards of changing lanes in the immediate vicinity and driving in the blind spots of large commercial motor vehicles. Additionally, law enforcement efforts may be intensified during times and locations of increased unsafe lane changing activities. These findings may also be useful in commercial vehicle driver training and driver licensing programs.

Factors associated with driver injury severity of lane changing crashes involving younger and older drivers

Lane change maneuvers can be a difficult driving task for many drivers, particularly, younger and inexperienced drivers and older drivers. Frequent and improper lane changing has a substantial effect on both traffic operations and safety. This study investigates the factors that contribute to the injury severity of crashes resulting from improper lane change maneuvers involving younger and older drivers in Alabama. Crash data for the study was obtained from the Critical Analysis Reporting Environment (CARE) system developed by the Center for Advanced Public Safety at the University of Alabama. Preliminary data analysis showed that younger drivers were responsible for about 63.1 % of the crashes. Random logit with heterogeneity in means models were developed to identify significant crash factors that were associated with the crash outcomes. The results show that younger male drivers were more likely to be severely injured in lane changing crashes whereas older male drivers were less likely to be severely injured. The results further show that younger drivers were more likely to sustain a major injury on six-lane highways whereas older drivers sustained major injuries from overtaking maneuvers on two-lane highways. It was further found that while younger drivers got into major injury crashes under daylight conditions, older drivers were more likely to be involved in major injury crashes under dark/unlit lighting conditions. Improper lane changing constitutes some form of aggressive driving which needs to be addressed considering that many lives are lost annually from the practice. The findings from this study may be used by road safety advocates and practitioners to identify what and how to target crash countermeasures to the younger and older driver population groups in the state.

Nonparametric Multivariate Adaptive Regression Splines Models for Investigating Lane-Changing Gap Acceptance Behavior Utilizing Strategic Highway Research Program 2 Naturalistic Driving Data

Gap acceptance is one of the crucial components of lane-changing analysis and an important parameter in microsimulation modeling. Drivers’ poor gap judgment, and failure to accept a necessary safety gap, make it one of the major causes of lane-changing crashes on roadways. Several studies have been conducted to investigate lane-changing gap acceptance behavior; however, very few studies examined the behavior in complex real-world situations, such as in naturalistic settings. This study examined lane-changing gap acceptance behavior from the big Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study (NDS) datasets using a nonparametric multivariate adaptive regression splines (MARS) approach to better understand the complex effects of different factors in gap acceptance behavior. The study developed a unique methodology to identify lane-changing events of the non-NDS-vehicles using the front-mounted radar data from NDS vehicles and extract necessary parameters for analyzing gap acceptance behavior. In addition, surrogate measures of safety, that is, time-to-collision (TTC), was utilized to understand the impact of lane-changing on the NDS following vehicle safety. Moreover, different distributions of gap acceptance were fitted to identify the trend of gap acceptance behavior. The results from the MARS model revealed that different factors including relative speed between lane-changing vehicle (LCV) and lead vehicle (LV)/following vehicle (FV), traffic conditions, acceleration of LCV and FV, and roadway geometric characteristics have significant effects on gap acceptance behavior. The results of this study have significant implications, which could be used in microsimulation model calibration and safety improvements in connected and autonomous vehicles (CAV).

Factors affecting lane change crashes

This study aims to investigate the contributing factors affecting the occurrence of crashes while lane-changing maneuvers of drivers. Two different data sets were used from the same drivers' population. The first data set was collected from the traffic police crash reports and the second data set was collected through a questionnaire survey that was conducted among 429 drivers. Two different logistic regression models were developed by employing the two sets of the collected data. The results of the crash occurrence model showed that the drivers' factors (gender, nationality and years of experience in driving), location and surrounding condition factors (non-junction locations, light and road surface conditions) and roads feature (road type, number of lanes and speed limit value) are the significant variables that affected the occurrence of lane-change crashes. About 57.2% of the survey responders committed that different sources of distractions were the main reason for their sudden or unsafe lane change including 21.2% was due to mobile usage. The drivers' behavior model results showed that drivers who did sudden lane change are more likely to be involved in traffic crashes with 2.53 times than others. The drivers who look towards the side mirrors and who look out the windows before lane-change intention have less probability to be involved in crashes by 4.61 and 3.85 times than others, respectively. Another interesting finding is that drivers who reported that they received enough training about safe lane change maneuvering during issuing the driving licenses are less likely to be involved in crashes by 2.06 times than other drivers.

Effects of blind spot monitoring systems on police-reported lane-change crashes

Objective: The objective of this study was to examine the effectiveness of blind spot monitoring systems in preventing police-reported lane-change crashes.Methods: Poisson regression was used to compare crash involvement rates per insured vehicle year in police-reported lane-change crashes in 26 U.S. states during 2009–2015 between vehicles with blind spot monitoring and the same vehicle models without the optional system, controlling for other factors that can affect crash risk.Results: Crash involvement rates in lane-change crashes were 14% lower (95% confidence limits −24% to −2%) among vehicles with blind spot monitoring than those without.Discussion: Blind spot monitoring systems are effective in preventing police-reported lane-change crashes when considering crashes of all severities. If every U.S. vehicle in 2015 were equipped with blind spot monitoring that performed like the study systems, it is estimated that about 50,000 crashes could have been prevented.

Modeling lane-change-related crashes with lane-specific real-time traffic and weather data

ABSTRACTThis study investigates the relationship between lane-change-related crashes and lane-specific, real-time traffic factors. It is anticipated that the real-time traffic data for the two lanes—the vehicle's lane (subject lane) and the lane to which that a vehicle intends to change (target lane)—are more closely related to lane-change-related crashes, as opposed to congregated traffic data for all lanes. Lane-change-related crash data were obtained from a 62-mile long freeway in Southeast Wisconsin in 2012 and 2013. One-minute traffic data from the 5- to 10-minute interval prior to the crashes were extracted from an immediately upstream detector station and two immediately downstream stations from the crash location. Weather information was collected from a major historical weather database. A matched case-control logistic regression was used for analysis. Results show that the following factors significantly affect the probability of a lane-change-related crash: average flow into the target lane at the first downstream station, the flow ratio at the second downstream station, and snow conditions. Additionally, the average speed in the target lane at the first downstream station contributes to the occurrence of lane-change crashes during snowy conditions. According to the model, the probability of a lane-change-related crash under real-time traffic conditions can aid in flagging potential crash-prone conditions. The identified contributing factors can help traffic operators select traffic control and management countermeasures to proactively mitigate lane-change-related crashes.

Using Traffic Micro-Simulation to Test Route Diversion as a Real-Time Crash Prevention Strategy on Freeways

The purpose of this study is to examine the potential of route diversion for reducing the real-time crash risk along a typical urban freeway. The PARAMICS micro-simulation software package was used to simulate the Interstate-4 corridor in Florida. The crash risk along the freeway was determined using models created by the authors that yielded values of both the rear-end and lane-change crash risks using real-time loop detector data. Route diversion was applied at different network loading levels to determine the effects of diverting vehicles at different levels of congestion. The study shows that route diversion is an effective crash prevention strategy when the freeway is operating in uncongested conditions. In this situation, the crash risk decreases between the locations where vehicles are diverted from and where the diverted vehicles re-enter the freeway. In general, diverting more vehicles and diverting vehicles further downstream serves to improve the overall safety benefits experienced. The only downside to diverting more vehicles or diverting them further downstream is the increased overall travel time; however, the travel time increase encountered in this study was within acceptable limits of about 5% during the uncongested conditions.

Analysis of the cars lane changes accidents

Experimental cars crashes test are valuable tools for improve overall automotive safety. Lane change crashes (or more properly, the lane change family of crashes) are defined in this paper, in according with generally accepted sense when a car collides with a vehicle running on a neighboring band when the first leaves its lane. Such collision results from various vehicle maneuvers including typical lane change or others. For present paper, the main aim is to quantify the post lane changes collisions parameters for endorsed influences over possible more dangerous traffic accidents occurring. Other goal of the paper was the study of speeds differences over changes in cars initials trajectories.

Safety Analysis of Horizontal Curves Using Real Traffic Data

Researchers are still seeking a better understanding of the parameters that affect safety in horizontal curves. Curves are one of the most critical sections of the road network contributing to a high percentage of serious runoff accidents and lane-changing crashes. Moreover, driving in curves requires combined control of both steering and speed, taking into account the dynamic response and limits of the car. The objectives of this study were to evaluate the safety performance of horizontal curves by analyzing vehicle dynamic signals, such as lateral acceleration and speed, as well as quantitative analysis of lane-changing maneuvers. The study uses real traffic environments where driver behavior and vehicle response data were recorded and stored during regular operations without subjecting the driver to any experimental controls. A total of 96 curves, equally distributed for left and right turn directions, have been collected and grouped according to their radii. The analysis identified frequent overtaking and lane-change maneuvers on the curves, of which 20% more lane changes occurred on right curves than on left curves. Lane-change maneuvers also increased significantly with increasing curve radius. The curve entrance was found to be the most dangerous segment of a curve. Current design practice assumes the safety risk is constant when driving along horizontal curves. The results also showed that drivers consider curve radius in choosing their driving speed rather than the posted speed limit of the curves. The study showed how road design influences the driver's strategy by establishing links between curve features, vehicle dynamic responses, and the driver's behavior. Analyzing road characteristics gave insight into how road geometry affects the vehicle dynamics relevant to safety and driving strategy through curves. The findings are useful inputs for reviewing curve design, selecting appropriate countermeasures, and improving active safety devices.

Dynamic Variable Speed Limit Strategies for Real-Time Crash Risk Reduction on Freeways

Recent research at the University of Central Florida involving crashes on I-4 in Orlando, Florida, has led to the creation of new statistical models capable of determining the crash risk on the freeway in real time. The potential benefits of variable speed limit (VSL) implementation for reducing the crash risk along the freeway at different loading scenarios was studied. VSL strategies were used in a networkwide attempt to reduce rear-end and lane-change crash risks where speed differences between upstream and downstream vehicles were high. The idea of homogeneous speed zones also was introduced in this study to determine the distance over which variable speed limits should be implemented from a station of interest. This idea is unique because it is the first time a dynamic distance has been considered for VSL implementation. This study shows that VSL is an effective crash prevention strategy when the freeway is operating in uncongested conditions. Specifically, in free-flow conditions and conditions approaching congestion, VSL can be used to reduce crash risk and prevent crash occurrence. It was also confirmed that the effects of crash migration increase as the level of congestion increases, and specific implementation techniques were found to better resist those effects. VSL was not found to effectively reduce crash risk in congested situations. This finding is sustained with logic and is supported by previous research.

Lane change behavior with a side blind zone alert system

This in-traffic study explored the effect of a side blind zone alert (SBZA) system on driver lane change behavior. Such a system may help drivers avoid lane change crashes by warning them with a side mirror display when a vehicle is detected in their blind zone. Participants drove with and without the SBZA system enabled, and were instructed to evaluate vehicle ride characteristics and only given an “incidental” system explanation. Overall, drivers failed to execute “over the shoulder” (blind zone) glances for 68 and 85% of the left and right lane changes, respectively. This suggests that the SBZA display provides information to the driver that often fails to be obtained via over the shoulder glances. In addition, when the SBZA system was enabled there was a 31% reduction in left lane changes attempted without the driver checking the left mirror, and a 23% reduction in right lane changes attempted without the driver checking the inside mirror. These results, coupled with the assumption that “did not see other vehicle” is a principal causal factor in many lane change crashes, suggests that the SBZA system may assist drivers in avoiding lane change crashes.

Body-pillar vision obstructions and lane-change crashes

Introduction This exploratory study investigated the relationship between vision obstructions from body pillars and lane-change crashes. Methods The vision obstructions were quantified by measuring, from the driver's perspective, the horizontal angular sizes and locations of the driver-side A-, B-, and C-pillars. The sample consisted of 21 vehicle models, including 13 passenger cars, 6 SUVs, 1 minivan, and 1 pickup truck. To control for driver differences, going-straight crashes were used for comparison, with the dependent variable being the ratio of lane-change crashes to going-straight crashes. The analysis used North Carolina crash data. Results The results of a multiple regression indicate that the relative frequency of lane-change crashes tended to increase with both wider A-pillars and with A-pillars located farther away from straight ahead. Impact on Industry The finding supports the hypothesis that visibility obstructions due to A-pillars have safety implications.

Influence of visibility out of the vehicle cabin on lane-change crashes

The influence of lateral visibility from the vehicle cabin on safety was evaluated by examining the differences in lane-change crashes of four-door and two-door body styles of the same vehicle models. These two vehicle styles were used because B-pillars (the pillars between the front and rear seats) on four-door models are farther forward, and thus nearer the fore-aft position of the driver. (Furthermore, the B-pillars on two-door models can be narrower, and some two-door models have no B-pillars at all.) To control for driver differences between these two body styles, going-straight-ahead crashes were used for comparison. The analysis used 2000–2003 North Carolina crash data, and considered the crash experience of four-door and two-door body styles for the same 10 vehicles for model years 1995 and newer. The main finding is that four-door body styles are more likely to be involved in lane-change crashes than are two-door body styles of the same vehicle models. This finding suggests that lateral visibility out of the vehicle cabin affects safety.

Lane Change Warning Design Guidelines

Five design guidelines were created to aid in the development of lane change crash avoidance systems (LCAS), using on-road data. In preparation for guideline development, field data were used to characterize a sample of lane changes and baseline (straight-ahead) driving events. Analysis of lane change frequency and duration, as well as turn signal use and eye glance movements revealed unique patterns among drivers and conditions. The “vehicle + signal” predictive logistic regression model is recommended, taking advantage of distance, time-to-collision (TTC), and turn signal data. Design guidelines as the basis for LCAS development were: 1) Warning levels should include presence detection and imminent warnings; 2) Display modality should be visual displays for presence detection and auditory/tactile displays for imminent warnings; 3) Display location (visual) should include forward and mirror locations; 4) Predictive warning algorithms should include TTC, distance, brake and turn signal use, eye behavior, lane position, side object information, and acceleration; 5) In terms of system integration, LCAS should be designed in the context of other in-vehicle systems to maximize effectiveness and safety. Prior to implementation, testing is strongly recommended regarding warning levels, display location, warning format, predictive algorithms, and alarm rates.

Effects of Nonplanar Driver-Side Mirrors on Lane-Change Crashes

In this quasi-experiment, we investigate the effects on lane-change crashes of nonplanar (spherical convex and multiradius) driver-side mirrors compared to planar mirrors. The analysis was based on 1,062 crashes reported from 1987 to 1998 to Finnish insurance companies for vehicles with passenger-side spherical convex mirrors and one of three types of driver-side mirror (planar, spherical convex, or multiradius). The results show that the mean effect of nonplanar mirrors compared to planar mirrors was a statistically significant decrease of 22.9% in lane-change crashes to the driver side. The effects of spherical convex and multiradius mirrors were not statistically different from each other. The nonplanar mirrors were beneficial especially for the high-risk driver groups, as well as for the lane-change situations and environmental conditions in which most lane-change crashes take place in the United States. These findings support the use of nonplanar driver-side mirrors. If drivers have problems with jud...

Operational and Behavioral issues in the Comprehensive Evaluation of Lane Change Crash Avoidance Systems

A variety of crash avoidance systems (CAS) technologies are currently under development or are already on the market. Evaluation of such technologies from a human factors standpoint is both urgent and complex. In this article I present a number of issues to which a comprehensive evaluation of CAS technologies should be addressed for lane change crash avoidance. These issues are posed in the form of a set of general questions within which methodological considerations are discussed and data needs are identified. Although the lane change crash problem is used as a focal point for discussion, the issues outlined in this article are considered fundamental to CAS evaluation in general.