面向智慧高速的合流区协作车辆冲突解脱协调方法

杨敏; 王立超; 张健; 冉斌; 吴静娴

doi:10.19818/j.cnki.1671-1637.2020.03.020

面向智慧高速的合流区协作车辆冲突解脱协调方法

doi: 10.19818/j.cnki.1671-1637.2020.03.020

杨敏^1,,
王立超¹,
张健^1, ,,
冉斌¹,
吴静娴²

1.
东南大学交通学院, 江苏南京 210096
2.
上海理工大学管理学院, 上海 200093

基金项目: 国家重点研发计划项目(2018YFB1600900);国家自然科学基金项目(51925801);中央高校基本科研业务费专项资金项目(2242019R40046)

详细信息

作者简介:
杨敏(1981-), 男, 安徽池州人, 东南大学教授, 工学博士, 从事智慧交通车路协同研究

通讯作者:
张健(1984-), 男, 安徽寿县人, 东南大学副教授, 工学博士

中图分类号: U491.255
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- 被引次数: 0
出版历程
- 收稿日期: 2019-12-04
- 刊出日期: 2020-06-25

Collaborative method of vehicle conflict resolution in merging area for intelligent expressway

1.
School of Transportation, Southeast University, Nanjing 210096, Jiangsu, China
2.
Business School, University of Shanghai for Science and Technology, Shanghai 200093, China

Funds: National Key Research and Development Project of China (2018YFB1600900, 2016YFB0100906); National Natural Science Foundation of China(51925801); Special Foundation for Basic Scientific Research of Central Colleges of China (2242019R40046)

More Information

Author Bio:
YANG Min(1981-), male, professor, PhD, yangmin@seu.edu.cn

Corresponding author: ZHANG Jian(1984-), male, associate professor, PhD, Jianzhang@seu.edu.cn

摘要

摘要: 根据网联自动驾驶车辆接近合流区的全过程特征, 设定智慧高速合流车辆行驶的协调控制流程; 针对高速公路合流区冲突风险问题, 考虑车辆时间需求强度、车辆类型和行驶意图等因素, 提出了基于合作博弈理论的高速公路合流区网联自动驾驶车辆冲突解脱协调方法; 利用MATLAB软件对不同条件下的车辆通过合流区进行了仿真验证。仿真结果表明: 智慧高速合流区车辆行驶协调规则能够实现网联自动驾驶车辆的通过请求协调, 在合作博弈作用下能够进一步实现冲突系统虚拟支付成本最低的车辆调整决策; 合流区车辆系统虚拟风险程度随着速度的降低而降低; 当严格执行协调决策时, 网联自动驾驶车辆在合流区通过过程中具有更高的稳定性; 当潜在冲突点长度在一定范围内, 两网联自动驾驶车辆行驶速度相同时的合作博弈效果优于车辆行驶速度不同时的合作博弈效果; 利用该协调方法将冲突解脱过程的虚拟支付成本降低了9%~14%, 大大提高了网联自动驾驶车辆合流区通过过程的安全性。
- 交通信息 /
- 智慧公路 /
- 车路协同 /
- 合作博弈 /
- 合流区 /
- 协调决策
Abstract: According to the characteristics of the entire process of connected autonomous vehicles approaching the merging area, the coordination control process of the vehicles driving in the intelligent expressway merging area was set. Aiming at solving the problem of conflict risk in expressway merging area, the factors such as vehicle time demand intensity, vehicle type, and driving intention were considered, and the conflict resolution coordination method of connected autonomous vehicles in expressway merging area was proposed based on cooperative game theory. The vehicle passing merging area under different conditions was simulated and verified by using MATLAB. Simulation result shows that coordination rules of the vehicles driving in the intelligent expressway merging area can realize the coordination of connected autonomous vehicles' passing request. Under the action of cooperative game, the vehicle adjustment decision with the lowest virtual payment cost in the conflict system can be further realized. The degree of vehicle system virtual risk in merging area decreases with the decrease of speed. When the coordination decision is strictly implemented, the connected autonomous vehicles have higher stability in the process of passing merging area. When the length of potential conflict point is within a certain range, the cooperative game effect of two connected autonomous vehicles with the same speed is better than the effect of vehicles with different speeds. The cooperative method reduces the virtual payment cost of the conflict resolution process by 9%-14%, and greatly improves the safety of the process of passing merging area of connected autonomous vehicles.
- traffic information /
- intelligent expressway /
- vehicle-road coordination /
- cooperative game /
- merging area /
- coordinated decision

HTML全文

图 1 智慧高速合流区组成

Figure 1. Composition of intelligent expressway merging area

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图 2 协调控制流程

Figure 2. Coordination control process

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图 3 车辆调整意图协调过程

Figure 3. Coordination process of vehicle adjustment intention

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图 4 场景1中不同b下c_j随k₁变化曲线

Figure 4. Change curves of c_j with k₁ under different b in scenario 1

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图 5 场景2中不同b下c_j随k₁变化曲线

Figure 5. Change curves of c_j with k₁ under different b in scenario 2

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图 6 场景3中不同b下c_j随k₁变化曲线

Figure 6. Change curves of c_j with k₁ under different b in scenario 3

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图 7 场景4中不同b下c_j随k₁变化曲线

Figure 7. Change curves of c_j with k₁ under different b in scenario 4

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图 8 各场景下c₁与c₁^*对比

Figure 8. Comparison between c₁ and c₁^* in each scenario

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图 9 各场景下c₂与c₂^*对比

Figure 9. Comparison between c₂ and c₂^* in each scenario

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图 10 各场景下c₃与c₃^*对比

Figure 10. Comparison between c₃ and c₃^* in each scenario

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表 1 决策联盟虚拟支付成本

Table 1. Virtual payment cost of decision alliances

决策联盟	车辆2调整	车辆2不调整
车辆1调整	(x₁, x₂)	(x₁, 0)
车辆1不调整	(0, x₂)	(∞, ∞)

下载: 导出CSV

表 2 四种场景下的参数

Table 2. Parameters of 4 scenarios

场景	主线车辆位置	S_i/m	v₁/(km·h^-1)	v₂/(km·h^-1)	l₁/m	l₂/m	a	b
1	内侧车道	100	60	60	15	15	1	2或3
2	内侧车道	100	60	40	15	15
3	外侧车道	100	60	60	15	20
4	外侧车道	100	60	40	15	20

下载: 导出CSV

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