电动汽车混入条件下多方式动态交通分配模型

doi:10.3969/j.issn.1674-8484.2021.04.013

摘要/Abstract

摘要：

为解析电动汽车混入条件下多方式路网交通状态的判别及动态演化过程,提出一种基于行为分析的多方式动态交通分配模型。基于离散选择理论,构建了不同人群出行选择行为模型;基于点排队模型,动态考虑路网容量、电池剩余电量和充电站服务水平等因素,提出了多方式动态交通分配模型及求解算法;并进行了算例验证。结果表明：电动汽车初始荷电状态（SOC）、充电服务费及充电桩数量等因素均对交通系统产生显著影响。本文提出的公共充电设施容量配置方案可降低用户成本3.61%,降低充电桩购置成本15.86%,减少交通系统CO₂排放0.76%,同时提高充电站运营收益14.66%,提高充电站服务水平77.09%。

关键词: 交通工程, 电动汽车, 动态交通分配, 变分不等式, 出行行为分析

Abstract:

This paper proposed a multi-modal dynamic traffic assignment model based on travel behavior analysis to distinguish the transportation network status and to analyze the dynamic evolutionary process with the addition of electric vehicles (EVs). Established several travel behavior models for different travel groups based on a discrete choice theory. Proposed a multi-modal dynamic traffic assignment model and a corresponding algorithm based on the point queuing model, considering some factors like the network capacity, the battery surplus, and the charging-station service-level dynamically with doing a numerical example for verification. The results show that the factors, which impact transportation system significantly, include the EV State of Charge (SOC), the charging service fee, and the EV charging-pile number. The proposed scheme for public charging- facility capacity-allocation reduces the users’ cost by 3.61%, reduces the EV charging pile acquisition cost by 15.86%, reduces the CO₂ emission from transportation-system by 0.76%, increases the EV charging station operation income by 14.66%, and increases the level of service by 77.09%.

Key words: traffic engineering, electric vehicles (EVs), dynamic traffic assignment, variational inequality, travel behavior analysis

中图分类号:

U491.13

张锐, 姚恩建, 张永生. 电动汽车混入条件下多方式动态交通分配模型[J]. 汽车安全与节能学报, 2021, 12(4): 540-550.

ZHANG Rui, YAO Enjian, ZHANG Yongsheng. Multi-modal dynamic traffic assignment model with the addition of electric vehicles[J]. Journal of Automotive Safety and Energy, 2021, 12(4): 540-550.

图/表 13

参考文献 20

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路段编号	自由流时间 / s	通行能力/ (辆·h^-1)
1	126	3 838
2	153	2 731
3	68	3 735
4	60	4 498
5	90	3 838
6	78	3 598
7	102	3 598
8	86	3 735
9	66	3 598
10	99	3 838
11	117	3 838
12	153	3 838
13	72	3 735
14	114	4 498
15	216	3 838
16	105	3 598
17	900	40
18	900	52
19	900	16
20	21 600	10

路段编号	自由流时间 / s	通行能力/ (辆·h^-1)
1	126	3 838
2	153	2 731
3	68	3 735
4	60	4 498
5	90	3 838
6	78	3 598
7	102	3 598
8	86	3 735
9	66	3 598
10	99	3 838
11	117	3 838
12	153	3 838
13	72	3 735
14	114	4 498
15	216	3 838
16	105	3 598
17	900	40
18	900	52
19	900	16
20	21 600	10

起终点	路段构成
(O1, D)	路径1：3-6-9-12-15 路径2：3-8-13-16 路径3：1-4-9-14
(O2, D)	路径4：4-9-12-15 路径5：4-9-14
(O3, D)	路径6：5-10-15

起终点	路段构成
(O1, D)	路径1：3-6-9-12-15 路径2：3-8-13-16 路径3：1-4-9-14
(O2, D)	路径4：4-9-12-15 路径5：4-9-14
(O3, D)	路径6：5-10-15

出行方式	变量	参数估计
出行方式	变量	人群1	人群2	人群3	人群4
地铁	出行时间 / min	-0.086^**	-0.149^**	-0.066^**	-0.085^**
地铁	票价 / 元	-0.456^**	-0.342^**	-0.443^**	-0.207^**
公交车	出行时间 / min	-0.086^**	-0.149^**	-0.066^**	-0.085^**
公交车	票价 / 元	-1.230^**	-0.451^**	-1.406^**	-0.927^**
燃油汽车	出行时间 / min		-0.149^**		-0.085^**
	费用 / 元		-0.165^**		-0.089^**
	常量				-0.506^**
电动汽车在途充电	出行时间 / min			-0.066^**	-0.085^**
	费用 / 元			-0.195^**	-0.329^**
	剩余电量 / %			1.360	1.490^**
	消耗电量 / %			-0.141^**	-0.070^**
电动汽车终点充电	出行时间 / min			-0.066^**	-0.085^**
	费用 / 元			-0.195^**	-0.329^**
	剩余电量 / %			3.860^**	4.540^**
	消耗电量 / %			-0.141^**	-0.070^**