Browsing by Author "Kaur, Mavjot"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Leading Pedestrian Intervals at Intersections in Proximity to Schools: An Evaluation of Safety and Effectiveness
    (University of Waterloo, 2024-08-21) Kaur, Mavjot
    Pedestrians encounter substantial risks on roadways, particularly at signalized intersections where their exposure to traffic is unavoidable. A predominant cause of pedestrian crashes at these intersections is drivers' failure to yield while making turning maneuvers. One effective countermeasure proposed to mitigate this issue is Leading Pedestrian Interval (LPI), which provides pedestrians with a walk signal during the 'all red' phase, preceding the green signal for parallel vehicular traffic. This timing allows pedestrians to establish themselves in the crosswalk, thereby enhancing their visibility to drivers. Despite extensive research demonstrating the effectiveness of LPIs, there is a lack of research regarding their safety effect when implemented at signalized intersections near schools and the factors influencing their effectiveness. Many existing guidelines and safety programs recommend LPI implementation near schools as part of comprehensive pedestrian safety strategies, highlighting the need to evaluate these proposed guidelines. The main goal of this research is to assess the effectiveness of implementing LPIs at signalized intersections near schools. Additionally, the study aims to analyze in detail the factors that influence pedestrian crash risk in this context. The case study was conducted using ten-year crash data from thirty-three signalized intersections in the Region of Waterloo. An Empirical Bayesian (EB) before and-after analysis was utilized to evaluate the impact of LPIs on pedestrian safety. Comprehensive data collection efforts were made to gather the necessary information for developing the Safety Performance Function (SPF) model. The collected data comprised detailed records of traffic volumes, pedestrian counts, roadway and intersection characteristics, and historical crash data. In this study, two SPF models were selected using different traffic exposure variables. One model used Estimated Daily Traffic (EDT), while the other employed surrogate exposure measure - the number of legs with commercial entries/exits or residential driveways within 50 meters of the intersection (NCE). Several key factors were identified that increase pedestrian crash risks at intersections, including residential and commercial areas, the presence of commercial entries/exits or residential driveways, longer crosswalks, non-conventional crosswalk markings, and higher pedestrian and vehicular volumes. In contrast, certain factors were found to decrease pedestrian crashes at intersections, such as the presence of slip lanes and missing sidewalks. The effectiveness of LPIs was evaluated using Crash Modification Factors (CMFs). The results suggest a 26.8% reduction in pedestrian–vehicle crashes at treated intersections. The effectiveness of iv LPIs is significantly improved under certain conditions. LPIs are more effective at intersections with high pedestrian and vehicle volumes and those with complete pedestrian infrastructure, such as all sidewalks and non-conventional crosswalk markings. Conversely, LPIs are less effective at intersections with slip lanes. Calibrating the model significantly enhanced estimate accuracy and further reduced the CMF to 0.65, underscoring the importance of proper calibration to accurately measure the true impact of pedestrian safety measures.