Citation

Islam M, Rahman M, Chowdhury M, Comert G, Sood ED, Apon A. IEEE Trans. Vehicular Tech. 2020; 69(9): 9402-9416.

Copyright

(Copyright © 2020, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TVT.2020.2982189

PMID

unavailable

Abstract

Vehicle-to-pedestrian (V2P) communication can significantly improve pedestrian safety in a connected vehicle environment. However, pedestrian safety is hindered as pedestrians often do not carry hand-held devices that provide low latency wireless communication (e.g., dedicated short-range communication (DSRC)-enabled device or emerging 5G-enabled cell phone) to communicate with nearby connected vehicles. The contribution of this paper lies in developing a vision-based approach to generate personal safety messages (PSMs) in real-time utilizing video streams from roadside traffic cameras, following the standard of the Society of Automotive Engineers (SAE) (SAE J2945) that can be used by connected vehicle pedestrian safety applications. Our analysis reveals that the vision-based approach can estimate pedestrians' location and speed more accurately than existing DSRC-enabled pedestrian hand-held devices. A system-level validation was performed by developing a connected vehicle related pedestrian safety application, "pedestrian in signalized crosswalk warning (PSCW)," that uses the generated PSMs from our vision-based approach. The results from the calculated average time-to-collision (TTC) value demonstrate the efficacy of our method in generating real-time collision warnings to avoid possible vehicle-pedestrian collisions. Our analysis also shows that the vision-based pedestrian safety warning system satisfies the latency requirement for the PSCW safety application in a connected vehicle environment.

Language: en

Keywords

computer vision; connected vehicle; Connected vehicles; Dedicated short range communication; deep learning; low latency wireless communication; pedestrian in signalized crosswalk warning; pedestrian location; pedestrian safety; pedestrian speed; pedestrians; personal safety messages; PSCW safety application; PSMs; real-time collision warnings; Real-time systems; road safety; road traffic; road vehicles; roadside traffic cameras; SAE J2945; Safety; Sensors; Society of Automotive Engineers; system-level validation; Time division multiplexing; time-to-collision; traffic engineering computing; vehicle-pedestrian collisions; vehicle-to-pedestrian communication; video signal processing; video streaming; video streams; vision-based pedestrian safety warning system; vision-based personal safety messages generation; vulnerable road user; Wireless fidelity