Impact of road environment on drivers' behaviors in dilemma zone: Application of agent-based simulation.

At a signalized intersection, there exists an area where drivers become indecisive as to either stop their car or proceed through when the traffic signal turns yellow. This point, called a dilemma zone, has remained a safety concern for drivers due to the great possibility of a rear-end or right-angle crash occurring. In order to reduce the risk of car crashes at the dilemma zone, Institute of Transportation Engineers (ITE) recommended a dilemma zone model. The model, however, fails to provide precise calculations on the decision of drivers because it disregards the supplemental roadway information, such as whether a red light camera is present. Hence, the goal of this study was to incorporate such roadway environmental factors into a more realistic driver decision-making model for the dilemma zone. A driving simulator was used to determine the influence of roadway conditions on decision-making of real drivers. Following data collection, each driver's decision outcomes were implemented in an Agent-Based Simulation (ABS) so as to analyze behaviors under realistic road environments. The experimental results revealed that the proposed dilemma zone model was able to accurately predict the decisions of drivers. Specifically, the model confirmed the findings from the driving simulator study that the changes in the roadway environment reduced the number of red light violations at an intersection.

Examining driver behavior using data gathered from red light photo enforcement cameras.

INTRODUCTION: To develop an effective driver assistance system that can prevent red light violations, it is important to have a thorough understanding of contributing factors and circumstances surrounding such violations. METHODS: Red light violation behavior was examined using about 47,000 violation records that were captured by photo enforcement cameras from 11 signalized intersections in the city of Sacramento, California, over a four-year period. This examination identified factors with strong correlation to red light running behavior. RESULTS: Key findings based on Sacramento's red light violation records include: (a) younger drivers showed a higher tendency of running the red light and were more likely to commit such a violation at speeds above the posted speed limit; (b) off-peak time period between 8 p.m. to 5 a.m. had lower violation counts, but red light violators in this time frame had a higher propensity of racing through intersections at high speeds; (c) also during the time period between 8 p.m. to 5 a.m., violators showed a higher probability of entering intersections two or more seconds after the onset of red light; and (d) violators were less likely to cross high traffic-volume intersections with speeds greater than the posted speed limit. DISCUSSION: Sacramento's data suggest that some red light violators might have committed such an offense unintentionally. The top three violation speeds were all below 20 mph and more than 94% of red light runners crossed intersections within 2 seconds after the onset of the red light. IMPACT ON INDUSTRY: In the next several years, studies will be executed to assess whether a red light violation warning system can reduce "unintentional red light running" such as drivers who made incorrect judgment regarding the adequate time to clear the intersection and inattentive motorists who fail to observe the presence and status of the red light.