行人环境下电动滑板车的主动避撞系统
Active Collision Avoidance System for E-Scooters in Pedestrian Environment
AI总结：
针对城市行人密集区域电动滑板车的碰撞安全隐患，本研究提出融合带状态精炼模块的LSTM行人轨迹预测与滑板车运动规划的新型eCAS避撞系统，经ETH、UCY数据集验证可提升密集区域通行适应性，为城市交通参与者安全提供保障。
摘要：
在城市区域的密集环境中，电动滑板车已迅速成为一种备受青睐的交通方式。在满足现代出行需求的同时，它们也带来了显著的安全挑战，尤其是在与行人交互时。通常而言，电动滑板车被建议在自行车道/人行道上骑行，或与汽车共享道路，最高时速约为15-20英里，其灵活性远高于行人和骑行者，速度也快得多。准确预测行人运动，再辅以滑板车的运动控制，对于最大限度降低碰撞风险、让滑板车无缝融入行人密集区域至关重要。针对这些安全问题，本研究提出了一种新型电动滑板车避撞系统（eCAS），该系统配备行人轨迹预测方法，采用集成了状态精炼模块的先进LSTM网络。这种前瞻性模型旨在确保滑板车在行人流量大的区域能够畅通无阻地行驶，不会发生碰撞。研究结果在两个公开数据集ETH和UCY上得到验证，取得了令人鼓舞的成果。我们的模型展现出了出色的行人路径预测能力，还优化了滑板车的路径规划，使其在人口密集区域具备更强的适应性。本研究证明了将行人轨迹预测与滑板车运动规划相结合的潜力。随着电动滑板车在城市环境中日益普及，这类技术进步对于保障城市交通所有参与者的安全已变得至关重要。
英文摘要：
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 LSTM network integrated with a state refinement module. This proactive model is designed to ensure unobstructed movement in areas with substantial pedestrian traffic without collisions. Results are validated on two public datasets, ETH and UCY, providing encouraging outcomes. Our model demonstrated proficiency in anticipating pedestrian paths and augmented scooter path planning, allowing for heightened adaptability in densely populated locales. This study shows the potential of melding pedestrian trajectory prediction with scooter motion planning. With the ubiquity of electric scooters in urban environments, such advancements have become crucial to safeguard all participants in urban transit.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
