Recent years have seen increasing deployment of radar-based technologies for vehicle detection at signalized intersections in the United States, mainly because they are nonintrusive, accurate, and robust to varying lighting, weather, and environmental conditions. In this paper, a radar-based detection technology is evaluated in the context of various weather and environmental conditions. High-resolution (100-ms sampling interval) data were collected in the field from two representative test sites. The detection errors were correlated with varying weather and environmental conditions using data-mining techniques, such as conditional inference trees and regression models. It shown that false and stuck-on call errors tend to increase under more-adverse weather conditions (e.g., rain and thunderstorms). Visibility, glare, and uneven shadows appear to be irrelevant. The near-side mounting location is associated with reduced missed-call, false-call, and dropped-call errors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Performance of Smart Sensor Detectors for Stop-Bar Detection at Signalized Intersections


    Contributors:


    Publication date :

    2017-02-24




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Performance of Wireless Magnetometers for Stop Bar Detection at Signalized Intersections

    Yang, Jidong J. / Zuo, Bashan | Transportation Research Record | 2018


    Estimating Pedestrian Volumes for Signalized and Stop-Controlled Intersections

    Le, Minh / Geedipally, Srinivas R. / Fitzpatrick, Kay et al. | Transportation Research Record | 2020


    Influence Area at Signalized and Stop-Control Intersections: Operational Analysis

    Raza, Sajid / Al-Kaisy, Ahmed / Washburn, Scott et al. | Transportation Research Record | 2023