Active Collision Avoidance System for E-Scooters in Pedestrian Environment

作者：Xuke Yan, Dan Shen · 发表于：SAE International Journal of Advances and Current Practices in Mobility · 年份：2024 · DOI：10.4271/2024-01-2555 · 被引用次数：5 · 研究领域：Autonomous Vehicle Technology and Safety、Evacuation and Crowd Dynamics、Video Surveillance and Tracking Methods

<div class="section abstract"><div class="htmlview paragraph">In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module. This method predicts future trajectories by considering not just past pedestrian positions but also accounting for the behavior and locations of surrounding individuals, acknowledging the influence of human interactions. Leveraging the pedestrians’ estimated trajectories based on their historical behaviors, we have devised an e-scooter path planning system that relies on an interpolating curve planner, which can continuously analyze the driving scene, understand the behavior of other road u...