复杂交通流对混合交通的影响研究
Study on the Impact of Complex Traffic Flow on Mixed Traffic

随着AI (人工智能)的兴起，许多行业变得与人工智能息息相关，同时使得自动驾驶逐步变成现实。人工驾驶车辆跟自动驾驶车辆共存是实现完全自动驾驶的必经阶段。本文研究智能驾驶车辆的不同特征跟不同渗透率的实施，预计对城市道路交通流产生的影响。本文建立了使用描述智能驾驶车辆跟人工驾驶车辆的模型，运用自适应优先算法探究人机驾驶混合交通流不同的状态演变过程，为混合交通流的理论跟方法的研究奠定基础。研究发现：在不同天气条件下，随着自动驾驶车辆的渗透率分布不同，在一定程度上对混合交通流的交通和环境有着积极的影响，并且随着智能驾驶车辆渗透率提升到50%左右时，整体的运行时间优化了7.68%左右，在冰雪条件下，智能驾驶车辆渗透率在提升到30%时，运行时间的环比优化率达到了最高值为5.01%。这都表明随着智能驾驶车辆不断地增加有利于减轻交通拥堵。
With the rise of AI (Artificial Intelligence), many industries have become closely related to AI, while making autonomous driving a reality step by step. The coexistence of human-driven vehicles with autonomous vehicles is a necessary stage to achieve fully autonomous driving. In this paper, we study the expected impact on urban road traffic flow due to the implementation of different char-acteristics and penetration rates of smart driving vehicles. This paper establishes a model describing intelligent and human-driven vehicles and uses adaptive priority algorithms to investigate the different state evolution processes of human-machine driven hybrid traffic flows, laying the foundation for the study of the theory and methodology of hybrid traffic flows. The study found that under different weather conditions, with the different penetration rate distribution of autonomous vehicles, the traffic and environment of mixed traffic flow were positively affected to a certain extent, and the overall running time was optimized by 7.68% when the penetration rate of intelligent vehicles was increased to about 50%. Under the condition of snow and ice, when the penetration rate of intelligent driving vehicle increases to 30%, the optimization rate of running time reaches the highest value of 5.01%. This shows that the increasing number of smart driving vehicles will help reduce traffic congestion.