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A novel skateboarder-related near-crash identification method with roadside LiDAR data

机译:一种新的滑板相关的近碰撞识别方法,具有路边的LIDAR数据

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摘要

Skateboarding is being an emerging travel model, especially for young travelers. The conflict between skateboarders and the other road users has raised safety concerns for traffic engineers. Safety evaluation about skateboarder-related conflicts has not been well performed due to the low skateboarder-related crashes and the limited historical crash data. Near-crashes have been considered as surrogate data for skateboard-related safety evaluation. This paper developed a procedure to extract skateboarder-associated near-crashes automatically with the roadside Light Detection and Ranging (LiDAR). A new indicator: distance-deceleration-time profile (DDTP) which combined time, space, and deceleration information was introduced for skateboarder-pedestrian near-crash identification. The DDTP was developed for the roadside LiDAR data specially. The case studies showed that the proposed method can extract skateboarder-pedestrian safety-critical events with high accuracy. The proposed method can be also used for skateboarder-vehicle and skateboarder-bicycle near-crash identification.
机译:滑板是新兴旅行模式,特别是对于年轻的旅客来说。滑板和其他道路用户之间的冲突提高了交通工程师的安全问题。由于低滑板相关的崩溃和有限的历史崩溃数据,对滑板相关冲突的安全评估尚未充分利用。近崩溃已被视为用于滑板相关的安全评估的代理数据。本文制定了一种在路边光检测和测距(LIDAR)中自动提取滑板相关近碰撞的程序。一个新的指标:距离 - 减速时间曲线(DDTP),其中为Skateboarder-Seetrian近碰撞识别引入了综合时间,空间和减速信息。 DDTP是专门为Roadside Lidar数据开发的。案例研究表明,该方法可以高精度地提取滑板 - 行人安全关键事件。所提出的方法也可用于滑板 - 车辆和滑板 - 自行车近碰撞识别。

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