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首页> 外文会议>18th world congress on intelligent transport systems, 2011 ITS America's annual meeting and exposition. >DESIGN OF ADAPTIVE LONGITUDINAL CONTROL FOR COGNITIVE CONNECTED VEHICLE
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DESIGN OF ADAPTIVE LONGITUDINAL CONTROL FOR COGNITIVE CONNECTED VEHICLE

机译：认知互联车辆的自适应纵向控制设计。

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摘要

Cognitive connected vehicles, when not under human control, will require essential features ofrnadaptive longitudinal control, including the essential collision avoidance capability. The controlrnsystem design integrates intelligent technology and abstracted human factors. This paper presentsrna model for aiding the design of an adaptive longitudinal control system that meets these criteria.rnThe cognitive vehicle is expected to have the capability of information on location and distancernbetween vehicles obtained on-line. In off-line research, simulation techniques can be used forrnthis purpose. This information is combined with Monte Carlo simulation and Bayesian statisticalrnmodel for the identification of condition and the optimal course of active safety action thatrnrequire deceleration for avoiding rear collision or acceleration for attaining the target distancernfrom the leading vehicle. This model has the capability of smooth operation in longitudinalrncontrol in order to avoid abrupt speed changes in vehicle-following operating mode. The modelrnstructure and algorithm are presented and an illustrative example is provided. The longitudinalrncontrol system is mainly intended for on-line use in actual driving conditions. Also, it can bernused in off-line safety and traffic flow studies in association with microsimulators of traffic.
机译：认知连接的车辆在不受人为控制时，将需要自适应纵向控制的基本功能，包括基本的避免碰撞能力。控制系统设计融合了智能技术和抽象的人为因素。本文提出了一种模型来帮助设计满足这些标准的自适应纵向控制系统。认知车辆有望具有在线获取的车辆之间位置和距离信息的能力。在离线研究中，模拟技术可用于此目的。该信息与蒙特卡洛模拟和贝叶斯统计模型相结合，用于识别状况和主动安全行动的最佳过程，从而需要减速来避免向后碰撞或加速，以达到与领先车辆的目标距离。该模型具有在纵向控制中平稳运行的能力，以避免在车辆跟随的运行模式中突然的速度变化。给出了模型的结构和算法，并提供了一个示例。纵向控制系统主要用于实际驾驶条件下的在线使用。而且，它可以与离线交通仿真器一起用于离线安全和交通流量研究中。

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