一种基于偏移量的车辆碰撞检测与避碰系统
A Novel Collision Detection and Avoidance system for Midvehicle using Offset-based Curvilinear Motion
摘要：
在密集的交通和高速的道路条件下，由于前车和后车驾驶员的注意力分散，是导致车中碰撞的主要原因。鉴于这种情况下，碰撞检测和碰撞避免算法被称为中间车辆碰撞检测和避免系统（MCDAS），提出了避免在主机车辆两端可能发生的碰撞。具体地，基于恒定速度（CV）模型的方法解决了两种场景，第一种场景包括两个子场景，即，a）在没有前端车辆的情况下加速主车辆的后端碰撞避免机制和b）基于前部和主车辆偏移（位置）的弯道运动，而另一种场景处理平行停车问题。宿主车辆基于偏移的曲线运动在避免来自前端车辆的威胁中起着至关重要的作用。主车辆在考虑可能的CV的情况下实现左侧和右侧的期望曲线策略，以避免两端碰撞。在该方法中，路径约束适用于具有所需方向的两个场景。MCDAS覆盖车辆运动学的Monte Carlo分析表明，急性歧视与一致的性能验证的碰撞模拟与实时数据。
英文摘要：
Major cause of midvehicle collision is due to the distraction of drivers in both the Front and rear-end vehicle witnessed in dense traffic and high speed road conditions. In view of this scenario, a crash detection and collision avoidance algorithm coined as Midvehicle Collision Detection and Avoidance System (MCDAS) is proposed to evade the possible crash at both ends of the host vehicle. The method based upon Constant Velocity (CV) model specifically, addresses two scenarios, the first scenario encompasses two sub-scenario namely, a) A rear-end collision avoidance mechanism that accelerates the host vehicle under no front-end vehicle condition and b) Curvilinear motion based on front and host vehicle offset (position), whilst, the other scenario deals with parallel parking issues. The offset based curvilinear motion of the host vehicle plays a vital role in threat avoidance from the front-end vehicle. A desired curvilinear strategy on left and right sides is achieved by the host vehicle with concern of possible CV to avoid both end collisions. In this methodology, path constraint is applicable for both scenarios with required direction. Monte Carlo analysis of MCDAS covering vehicle kinematics demonstrated acute discrimination with consistent performance for the collision validated on simulated with real-time data.
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。
