Abstract:

To analyze the car- following and lane- changing behaviors in mixed traffic flow nearwork area, this paper develops an improved cellular automaton model to describe connected vehicles' real-time communication and smaller safe distance. The lane- changing intention of human- driven and connected vehicles in different areas are analyzed separately. Then the anticipated lane-changing in communication area and mandatory lane-changing in work area based on distance acquisition and gap sorting are modeled for connected vehicles. The traffic flow distribution and movement for mixed traffic are simulated with a combination of human-driven vehicles' model. A numerical example is presented with MATLAB simulation for repeated times to eliminate random influence. The results indicate that the connected vehicles are able to expand capacity, improve average speed and reduce travel time. The results of lane-changing spot analysis shows that with large proportion of connected vehicles, the points of anticipated lane changing are closer to mandatory zones but human-driven vehicle's lane-changing point sees marginal impacts from the mixed traffic in work area.

Key words: intelligent transportation, connected vehicles' lane- changing model, improved cellular automaton, mixed traffic flow, work area

摘要：

为研究施工区网联车与普通车混行状态下的车流跟驰及换道行为，分析网联车的区域内通讯及更小安全车距等特性，改进普通车元胞自动机模型的减速规则和随机慢化规则，构建网联车跟驰模型。建立普通车和网联车在施工区不同区段的换道意向规则，基于车距采集和空位排序算法建立网联车在通讯区域的预期换道和施工区域的强制换道模型，结合普通车换道模型模拟施工区混行车辆的换道规则及车流分布规律。采用算例验证模型，运用MATLAB仿真，多次实验消除随机因素影响，结果验证了网联车对扩大通行能力，提高平均车速及降低走行时间的有效性；不同比例下的换道点分布显示，网联车比例越高，预期换道区的换道点越靠近强制换道区，且强制换道点越靠前；而普通车换道点分布受混行车流比例的影响较小。

关键词: 智能交通, 网联车换道模型, 改进元胞自动机, 混行车流, 施工区