Wu, Jayson (Dayong)Le, MinhUllman, JerryHuang, TianchenDarwesh, AmirSaripalli, Srikanth2024-02-262024-02-262023-09https://hdl.handle.net/10919/118142Roadway construction and maintenance have become increasingly common as the U.S. transportation system ages and the population and traffic volume increase. This places more and more work zone workers near high-speed vehicles and increases the probability of being struck by them. This project innovatively deployed 360-degree LiDAR sensors at the roadside and tested their potential to provide work zone safety in terms of detection accuracy, efficiency, and ease of use. Researchers developed a set of algorithms to collect and interpret real-time information for each approaching vehicle and worker (e.g., location, speed, and direction) in and outside work zones using roadside LiDAR. Ultimately, the outcome of this pilot study could lead to developing a full-scale warning system deployable in a real work zone environment. Such a system could detect and analyze live traffic and work zone activity, activate the appropriate warning scheme, and deliver information to roadway workers in work zones in a timely manner so they can take evasive actions instead of relying on traditional “passive” safety countermeasures. This kind of panoramic, trajectory-level data for work zone actors can be used to develop a next-generation work zone situational awareness system.application/pdfen-USCC0 1.0 UniversalLiDARSmart Work Zonesafetysituational awareness systemvehicle detection/trackingvulnerable road userReport