Recent data have shown that pedestrian fatalities have increased by 44% from 2010 to 2019. In 2019, 6,590 pedestrians died of traffic crashes, and 20% occurred at intersections, the highest in 30 years. These saddening facts, unfortunately, suggest that walking or biking is even less safe today although driving is safer thanks to numerous efforts in vehicular technologies. Smart transportation is successful only if it provides equitable safety for all road users. Flash yellow arrow (FYA) is a left-turn strategy at signalized intersections in North America. It allows left-turn vehicles to cross when the gaps of opposing through-traffic are perceived as safe. But it cannot separate concurrent crossing pedestrians and left-turn vehicles. To address this issue, a novel dynamic flash yellow arrow (D-FYA) solution is developed using the light detection and ranging (LiDAR)-based tracking technique. It can address the safety concerns in the FYA while recovering the permissive left-turn capacity after the concurrent pedestrians are cleared. Depending on the pedestrian volumes, the corresponding FYA with each cycle will either start as scheduled, be postponed, or be canceled within each cycle. The proposed D-FYA was deployed at an intersection next to the campus of the University of Texas at Arlington, and its real-time D-FYA decisions in the field were verified over 100 traffic signal cycles through simultaneous observation in the field. The proposed D-FYA solution was further evaluated within a traffic signal simulation platform to compare its mobility performance with another two permissive left-turn strategies: (1) protected + permissive left turn (PPLT), and (2) PPLT with minus-pedestrian phase. The experiment results revealed the D-FYA is accurate and adaptive compared with the other two permissive left-turn strategies.


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    Title :

    Developing a Tracking-Based Dynamic Flash Yellow Arrow Strategy for Permissive Left-Turn Vehicles to Improve Pedestrian Safety at Intersections


    Additional title:

    J. Transp. Eng., Part A: Systems




    Publication date :

    2023-04-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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