江浩斌　胡子牛　刘擎超　秦洪懋　孟天闯

摘   要：提出了一种面向智能网联汽车的中心式匝道合流协同控制方法. 首先建立了中心式匝道合流协同控制模型，然后通过离散化将其转化为非线性最优化问题，并采用NOMAD算法求解. 进行了100组仿真实验，通过随机设置不同的初始化条件对所提方法的有效性以及车辆油耗影响因素进行了研究，并与其他文献的方法进行对比. 研究结果表明，本文所提方法对不同的初始合流场景有较好的控制效果，与对比文献中的方法相比，可使车辆平均油耗降低42.38%，显著提高了匝道合流过程中车辆的燃油经济性.

关键词：智能网联汽车;匝道合流;协同控制;中心式方法;燃油经济性

中图分类号：U461.8                     文献标志码：A

Centralized Coordinated Ramp Merging Control

for Intelligent and Connected Vehicles

JIANG Haobin1，HU Ziniu1，LIU Qingchao1，QIN Hongmao2，MENG Tianchuang3

（1. School of Automotive and Traffic Engineering，Jiangsu University，Zhenjiang 212000，China;

2. College of Mechanical and Vehicle Engineering，Hunan University，Changsha 410082，China;

3. School of Vehicle and Mobility，Tsinghua University，Beijing 100084，China）

Abstract：This paper proposes a centralized coordinated ramp merging control method for intelligent connected vehicles. First，a model of centralized coordinated ramp merging control is established. Then， the model is converted to a non-linear optimization problem through discretization，which can be solved by the NOMAD algorithm. Simulations with different randomly initialized merging conditions are performed to verify the effectiveness of the proposed method and to discuss the impact on fuel consumption. Besides，the proposed method is compared with the methods in existing literature，and the results show that the proposed method is effective under different initial merging conditions. Compared with the benchmark method，the proposed method reduces the average fuel consumption by 42.38%.

Key words：intelligent and connected vehicles;ramp merging;coordinated control;centralized approach;fuel economy

交通擁堵已成为城市发展的痛点问题，匝道合流是造成城市高架道路和高速公路交通拥堵的主要原因之一[1]. 2014年，美国城市地区交通拥堵的总成本估计为1 600亿美元，额外消耗31亿加仑燃料[2].交通拥堵降低了交通效率，增加了碰撞风险[3]，增加了出行时间[4]，给乘客带来不适，导致油耗和排放过多[5-6].实际上，匝道合流操作对于驾驶员来说，必须综合考虑周围环境的各类因素. 通常，试图合流的车辆可能会在入口匝道上先减速，等待合适的合流机会，同时根据对安全间距和主流车辆速度的判断，以确定加速的程度和时间.即使驾驶员最终顺利完成合流，实际的合流过程也不一定是全局最优的，安全性、经济性和……