Do high visibility crosswalks improve pedestrian safety? A correlated grouped random parameters approach using naturalistic driving study data. (June 2021)

• Record Type: Journal Article
• Authors: Pantangi, Sarvani Sonduru; Ahmed, Sheikh Shahriar; Fountas, Grigorios; Majka, Kevin; Anastasopoulos, Panagiotis Ch.
• Is Part Of: Analytic methods in accident research. Volume 30(2021)
• Publication Date: 2021-06
• Subjects: Pedestrian crosswalks -- Driving behavior -- Pedestrian safety -- Correlated grouped random parameters -- Naturalistic driving study; Accidents -- Research -- Methodology -- Periodicals; Accidents -- Prevention -- Periodicals; 363.100721
• DOI: 10.1016/j.amar.2020.100155
• Languages: English
• ISSNs: 2213-6657

Abstract

Highlights: Effectiveness of various High Visibility Crosswalk (HVC) types was evaluated. Naturalistic Driving Study data were used to identify driving behavioral change. Various safety surrogate measures were statistically modeled. Correlated grouped random parameters models with panel effects were estimated. The HVC presence was found to modify driving behavior and improve pedestrian safety. Abstract: In this study, the effectiveness of High-Visibility Crosswalks (HVCs) in improving pedestrian safety at urban settings is assessed using SHRP2 (Second Strategic Highway Research Program) Naturalistic Driving Study (NDS) data. Various HVCs located at different positions on the roadway segment (mid-block vs end-of-block) and featuring different HVC marking designs (continental, bar-pair, and ladder) were selected for the assessment. As no pedestrian-vehicle crashes or conflicts were identified from the forward-facing videos and time series information of the SHRP2 Naturalistic Driving Study data, crash surrogate measures (i.e., speed; acceleration; throttle pedal actuation; and brake application) were employed to identify and analyze modifications in driving behavior at or near the HVCs. The surrogate measures were statistically modeled using a correlated grouped random parameters estimation framework. This can account for panel effects arising from multiple traversals undertaken by each participant, for the effect of unobserved characteristics, as well as for their unobserved correlations, which constitute possible misspecification issues of statistical modeling. The results of the analysis showed that the presence of HVC modifies driving behavior, thus reducing the risk of motor vehicle – pedestrian conflicts. Apart from the presence of HVC, the HVC type (ladder, continental or bar-pair), the HVC location (mid-block or end-of-block) and various driver, roadway and trip characteristics were found to affect the vehicle speed, acceleration, throttle pedal actuation, and brake application.