基于多智能体的车路协同环境下单车道微观交通流模型

Single Lane Microscopic Traffic Flow Model Based on Multi-Agent in CVIS Circumstance

摘要:

车路协同环境(Cooperative Vehicles Infrastructure System, CVIS) 不同于传统的交通环境，以往的交通流模型建立在传统交通环境下，无法描述CVIS环境下的交通流微观特性。本文首先提出车辆多智能体(Vehicle Multi-Agent, VMA)的概念及其属性列表。其次，提出在传统环境下和CVIS环境下的车辆决策机制，分析两者在交叉口及路段上对于交通状态判断与决策的差异。在此基础上，提出在车路协同环境下的单车道微观交通流模型，给出车辆的微观动力学模型，包括加速模型和减速模型，同时考虑交叉口的信号灯对于车辆行为的影响。最后，数据实验将分析车辆在两种不同环境中的时空轨迹图以及宏观的交通参数，如整体行程时间，平均行程时间以及平均延误等。结果表明，CVIS环境下的车辆比传统环境下的车辆总行驶时间、平均行程时间以及平均延误均有极大降低，提高了通行的效率，车队速度方差减小，提高了车队行驶的稳定性。

Abstract:

CVIS (Cooperative Vehicles Infrastructure System) is different from traditional traffic circumstance and traditional traffic flow models which are based on traditional traffic circumstance are not adept to describe the traffic flow characteristics in CVIS circumstance. Concepts and attributes list of VMA (Vehicle Multi Agent) are presented at first. Then, decision strategies in both traditional circumstance and CVIS circumstance are compared to analysis differences in traffic status judgment and decision at intersection and link between two circumstances. Based on those, single lane traffic flow models in CVIS circumstance are presented in this paper. Microscopic traffic flow models such as acceleration and deceleration are given in this paper. Furthermore, the intersection impacts are also considered in this paper to analyze signal influence. The numeral experiments analyze the trajectories and macroscopic parameters, such as total travel time, average travel time and average delay, in both circumstances. The results show that VMAs in CVIS circumstance have great decline in total travel time, average travel time and average delay time which indicate that vehicles in CVIS are more stable and successive than those in traditional circumstance. Beside, velocity variances in CVIS are lower than those in traditional circumstance which increases the fleet stable.