An Automatic Conflict Detection Framework for Urban Intersections Based on an Improved Time Difference to Collision Indicator

Urban road intersections are one of the key components of road networks. Due to complex and diverse traffic conditions, traffic conflicts occur frequently. Accurate traffic conflict detection allows improvement of the traffic conditions and decreases the probability of traffic accidents. Many time-based conflict indicators have been widely studied, but the sizes of the vehicles are ignored. This is a very important factor for conflict detection at urban intersections. Therefore, in this paper we propose a novel time difference conflict indicator by incorporating vehicle sizes instead of viewing vehicles as particles. Specially, we designed an automatic conflict recognition framework between vehicles at the urban intersections. The vehicle sizes are automatically extracted with the sparse recurrent convolutional neural network, and the vehicle trajectories are obtained with a fast-tracking algorithm based on the intersection-to-union ratio. Given tracking vehicles, we improved the time difference to the conflict metric by incorporating vehicle size information. We have conducted extensive experiments and demonstrated that the proposed framework can effectively recognize vehicle conflict accurately.

Signal Control Method for through and Left-Turn Shared Lane by Setting Left-Turn Waiting Area at Signalized Intersections

This paper proposes a signal control method for the through and left-turn shared lanes at signalized intersections to solve traffic conflicts between left-turn vehicles and opposing through vehicles by setting left-turn waiting area (LWA). Delays and stops are weighted to form an integrated performance index (PI) in a vehicle-to-infrastructure cooperation system. The PI models pertaining to all vehicles are established based on the LWA intersection. In addition, an optimized method of signal timing parameters is constructed by minimizing the average PI. VISSIM simulation shows that the average PI decreases by 6.51% compared with the original layout and signal timing plan of the intersection, since the increased delay of the side-road left-turn vehicles is insufficient to offset the reduced delay of the side-road through vehicles after the improvement. The sensitivity analysis shows that the greater the traffic volume of the phase including the through and left-turn shared lanes, the higher the operation efficiency of the LWA intersection compared with the typical permitted phase intersection. When the left-turn vehicles of the shared lanes in each cycle are less than the stop spaces, the LWA intersection can effectively reduce the average PI of the shared lanes. Furthermore, the more the stop spaces in the LWA, the lower the average PI in the same traffic conditions.

Ride in Peace: How Cycling Infrastructure Types Affect Traffic Conflict Occurrence in Montréal, Canada

Urban cycling is increasingly common in many North American cities and has the potential to address key challenges of urban mobility, congestion, air pollution and health. However, lack of safety is often cited by potential bike users as the most important deterrent to cycling. This study aimed to evaluate the effect of cycling facility type on traffic conflict likelihood. Four participants recorded a total of 87 h (1199 km) of video, which was reviewed by trained observers to identify and characterize traffic conflicts, yielding 465 conflicts with vehicles and 209 conflicts with pedestrians. Bootstrapped generalized additive logit regressions (GAM) were built to predict traffic conflict likelihood. Results show that while cycling on an off-street bike path effectively reduces the likelihood of conflict with a vehicle, it increases the probability of conflict with a pedestrian. Bike lanes were associated with an increase in the likelihood of a conflict with a vehicle. Decision makers should favor physically segregated and clearly marked cyclist-only facilities to ensure safe and efficient conditions for commuter cyclists.

Safety Evaluation of Turbo-Roundabouts with and without Internal Traffic Separations Considering Autonomous Vehicles Operation

The paper presents a microsimulation approach for assessing the safety performance of turbo-roundabouts where Cooperative Autonomous Vehicles “CAVs” have been introduced into the traffic mix alongside conventional vehicles “CVs”. Based on the analysis of vehicle trajectories from VISSIM and subsequent analysis of traffic conflicts through the Surrogate Safety Assessment Model (SSAM), the research aims to evaluate the safety benefits of turbo-roundabouts where the lanes are physically separated by raised curbs, compared to roundabouts without such curbs. The paper will then describe the methodological path followed to build VISSIM models of turbo-roundabouts with and without raised curbs in order to calibrate the simulation models and estimate the potential conflicts when a higher percentage of CAVs are introduced into the traffic mix. A criterion has been also proposed for setting properly the principal SSAM filters. The results confirmed both higher safety levels for turbo-roundabouts equipped with raised lane dividers compared to turbo-roundabout solutions without curbs, and better safety conditions under the traffic mix of CVs and CAVs. Therefore, it follows that, in absence of crash data including CAVs, the surrogate measures of safety are the only approach in which the safety performance of any roundabout or road entity can be evaluated.

Are Older Drivers Safe on Interchanges? Analyzing Driving Errors Causing Crashes

Older drivers are prone to driving errors that can lead to crashes. The risk of older drivers making errors increases in locations with complex roadway features and higher traffic conflicts. Interchanges are freeway locations with more driving challenges than other basic segments. Because of the growing population of older drivers, it is vital to understand driving errors that can lead to crashes on interchanges. This knowledge can assist in developing countermeasures that will ensure safety for all road users when navigating through interchanges. The goal of this study was to determine driver, environmental, roadway, and traffic characteristics that influence older drivers’ errors resulting in crashes along interchanges. The analysis was based on three years (2016–2018) of crash data from Florida. A two-step approach involving a latent class clustering analysis and the penalized logistic regression was used to investigate factors that influence driving errors made by older drivers on interchanges. This approach accounted for heterogeneity that exists in the crash data and enhanced the identification of contributing factors. The results revealed patterns that are not obvious without a two-step approach, including variables that were not significant in all crashes, but were significant in specific clusters. These factors included driver gender and interchange type. Results also showed that all other factors, including distracted driving, lighting condition, area type, speed limit, time of day, and horizontal alignment, were significant in all crashes and few specific clusters.

Comprehensive Operation Risk Assessment of a Highway Maintenance Area Based on Reliability

To study the influence of various working conditions on traffic safety in the maintenance area of a mountain expressway, 675 groups of PTV VISSIM traffic simulation experiments were designed with various traffic organization modes, traffic volumes, traffic compositions, activity area lengths, and speed limit values. The results show that the activity area length of a closed lane, a compressed lane, and a borrowed opposite lane had no marked influence on the traffic conflicts. There was a significant positive correlation between the proportion of trucks and the number of traffic conflicts, and the number of traffic conflicts increased significantly with an increase in traffic volume. In the closed lane and borrowed opposite lane scenarios, the increase in traffic conflicts was more obvious with the increase in traffic volume. There were obvious differences in the number of traffic conflicts under different forms of traffic organization. The number of conflicts in the compressed lane scenario was the lowest, and in the borrowed opposite lane scenario the number of conflicts was the highest. There was a significant correlation between a decrease in the speed limit and an increase in the number of traffic conflicts. Finally, with traffic volume, truck proportion, and speed limit values as independent variables and reliability as a dependent variable, linear regression equations of reliability were established for three traffic organization scenarios: closed lane, borrowed opposite lane, and compressed lane.