有轨电车交叉口速度自动引导方法及仿真评价

doi:10.16182/j.issn1004731x.joss.25-0358

系统仿真学报 ›› 2026, Vol. 38 ›› Issue (5): 1426-1439.doi: 10.16182/j.issn1004731x.joss.25-0358

• • 上一篇

有轨电车交叉口速度自动引导方法及仿真评价

滕靖¹^,², 童文聪¹^,³, 张中杰⁴, 姚幸⁴, 李君羡¹

^1.同济大学交通学院，上海 201804
^2.上海市多网多模式轨道交通协同创新中心，上海 201804
^3.上海市轨道交通结构耐久与系统安全重点实验室，上海 201804
^4.上海市城市建设设计研究总院，上海 200125

收稿日期:2025-04-28 修回日期:2025-06-22 出版日期:2026-05-21 发布日期:2026-05-29
通讯作者: 童文聪
第一作者简介:滕靖(1977-)，男，教授，博士，研究方向为轨道交通运输组织、多模式公共交通系统服务协同优化。
基金资助:
国家重点研发计划基金(2021YFB1600100)

Automatic Speed Guidance Method and Simulation Evaluation for Trams at Intersections

Teng Jing¹^,², Tong Wencong¹^,³, Zhang Zhongjie⁴, Yao Xing⁴, Li Junxian¹

^1.College of Transportation, Tongji University, Shanghai 201804, China
^2.Shanghai Collaborative Innovation Research Center for Multi-network & Multi-modal Rail Transit, Shanghai 201804, China
^3.Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety, Shanghai 201804, China
^4.Shanghai Urban Construction Design & Research Institute, Shanghai 200125, China

Received:2025-04-28 Revised:2025-06-22 Online:2026-05-21 Published:2026-05-29
Contact: Tong Wencong

摘要/Abstract

摘要：

针对当前人工驾驶模式缺乏速度调控机制及运行时间高离散性问题，提出了有轨电车交叉口速度自动引导方法。考虑交叉口潜在交通冲突造成的速度干扰，通过设定交叉口安全通过速度初始决策点，将运行曲线划分为确定段和干扰段。以松江有轨电车1号线为例，通过驾驶模拟实验获取人工驾驶运行轨迹，构建包含人工驾驶及交叉口速度自动引导的动态轨迹推演仿真模型，并基于自由驾驶和随机信号方案两个场景进行评价。实验结果表明：该方法有利于发挥车辆速度性能、吸收运行延误并减少交叉口停车次数，在线路行驶速度、运行时间可靠性和能耗等指标上显著优于人工驾驶，并在设置信号绿波线路上能产生更佳运行效益。

关键词: 有轨电车, 车速引导, 仿真评价, 驾驶模拟, 交叉口随机干扰, 速度曲线

Abstract:

To address the lack of speed regulation mechanism and the high dispersion of operational time in the current manual driving mode, this paper proposes an automatic speed guidance method for trams at intersections. Considering the speed disturbances caused by potential traffic conflicts at intersections, an initial decision point for safe passage speed at an intersection is established, dividing the operational curve into deterministic segments and disturbance-response segments. To verify the effectiveness of the method, a case study of Songjiang Tram Line 1 is conducted. Driving simulation experiments are performed to obtain manual driving trajectories, and a dynamic trajectory simulation model incorporating both manual driving and automatic speed guidance at intersections is developed.Evaluation is carried out under the two scenarios of free driving and stochastic signals. The experimental results show that the method enhances vehicle speed performance, absorbs operational delays, and reduces intersection stops. It significantly outperforms manual driving in terms of travel speed, time reliability, and energy efficiency. It achieves greater operational benefits on green wave-coordinated routes.

Key words: tram, speed guidance, simulation evaluation, driving simulation, intersection stochastic disturbances, speed profile

中图分类号:

TP391.9

滕靖,童文聪,张中杰等 . 有轨电车交叉口速度自动引导方法及仿真评价[J]. 系统仿真学报, 2026, 38(5): 1426-1439.

Teng Jing,Tong Wencong,Zhang Zhongjie,et al . Automatic Speed Guidance Method and Simulation Evaluation for Trams at Intersections[J]. Journal of System Simulation, 2026, 38(5): 1426-1439.

图/表 24

图1

图2

图3

图4

图5

图6

图7

表1

实验车辆动力学参数

参数	值
车辆编组	5模块，2动1拖2悬浮
列车长度/m	32.6
空车质量/kg	41 693
最大运行速度/(km/h)	70
最大加速度/(m/s²)	1.3
最大减速度/(m/s²)	1.2
牵引反应延迟/ms	800
制动反应延迟/ms	400
基本阻力公式	$3.004 34 + 0.055 89 v + 0.000 37 v 2$

表1

图8

表2

实测站台停站时间统计

指标	$P 1$	$P 2$	$P 3$	$P 4$	$P 5$
平均值	18.0	19.6	19.9	18.4	19.4
标准差	3.6	3.7	5.1	3.4	3.6
中位数	17.5	19.1	18.5	17.9	19.1
极差	20.2	19.8	26.4	18.2	19.8

表2

图9

表3

图10

表4

人工驾驶区间运行时间统计

指标	$S 1$	$S 2$	$S 3$	$S 4$	$S 5$	$S 6$	$S 7$	全线路
平均值/s	30.59	35.88	54.15	33.65	50.76	31.85	43.2	369.12
标准差/s	1.94	3.99	4.03	2.43	4.21	2.03	3.86	16.83
最小值/s	27.6	26.4	48.7	28	41.4	28.2	37.8	331.5
中位数/s	30.2	35.25	53.45	33.1	50.05	31.6	42.3	367.35
最大值/s	41.2	50.6	76.1	42.2	62.9	39.4	54.9	427.5
离散系数/%	6.34	11.12	7.44	7.22	8.29	6.37	8.94	4.56

表4

图11

图12

图13

表5

自由驾驶场景下车辆到达交叉口时间统计

控制模式	指标	$I 2$	$I 3$	$I 4$	$I 5$	$I 6$	$I 7$	$I 8$
MD模式	均值/s	31.9	67.8	150.7	205.1	255.8	290.0	364.8
	极差/s	13.3	31.6	54.2	66.2	64.6	70.7	95
	标准差/s	2.0	5.1	8.0	9.9	12.0	12.9	16.8
	离散系数/%	6.39	7.46	5.30	4.84	4.71	4.45	4.60
ASG模式	均值/s	29.8	60.5	130.5	176.3	218.7	247.6	309.8
	极差/s	3.7	7.5	10.4	14.7	18.6	18.4	26.8
	标准差/s	0.8	1.7	2.3	3.3	4.2	4.3	5.4
	离散系数/%	2.74	2.88	1.77	1.89	1.93	1.74	1.76

表5

表6

现状交叉口信号控制方案 (s)

交叉口	$I 1$	$I 2$	$I 3$	$I 4$	$I 5$	$I 6$	$I 7$	$I 8$
绿灯时间	36	70	55	55	58	60	42	40
周期	140	140	140	140	140	140	140	140
相位差	61	75	71	40	40	73	63	0

表6

图14

表7

现状信号方案下线路关键运行指标对比

模式	$v l i n e$ /(km/h)	$E l i n e$ /(kW·h)	$S l i n e$	$σ l i n e$
变化量/%	21.8	7.4	-30.5	-52.1
MD	15.6	12.1	4.3	63.7
ASG	19.0	13.0	2.99	30.5

表7

图15

表8

现状信号方案下行驶速度提升情况统计 (%)

$v l i n e A S G$ / $v l i n e M D$	占方案比例
>105	66.75
>110	48.71
>120	15.26
>130	2.70
>140	0.32
>150	0.02

表8

表9

关键运行指标随车均交叉口停车次数变化分析

评价参数	MD模式下车均交叉口停车次数区间
评价参数	[0,1)	[1,2)	[2,3)	[3,4)	[4,5)	[5,6)	[6,7)	[7,8]	合计
$v l i n e M D$ /(km/h)	21.2	19.9	18.4	17.1	15.9	14.9	14	13.2	15.5
$v l i n e A S G$ /(km/h)	24.5	22.5	20.7	19	17.6	16.4	15.4	14.5	17.2
变化量/%	15.66	13.46	12.66	11.69	11.22	10.51	10.11	9.97	10.94
$E l i n e M D$ /( kW·h)	10.9	11.2	11.5	12.1	12.8	13.8	15	16.5	13.4
$E l i n e A S G$ /(kW·h)	12.5	12.4	12	11.4	10.7	9.8	9.1	8.3	10.3
变化量/%	14.33	10.94	4.26	-5.25	-16.22	-27.98	-39.22	-49.38	-21.70
$S l i n e M D$	0.87	1.75	2.64	3.58	4.54	5.51	6.49	7.47	4.99
$S l i n e A S G$	0.47	1.28	2.05	2.91	3.76	4.64	5.51	6.35	4.17
变化量/%	-46.48	-27.32	-22.34	-18.63	-17.12	-15.79	-15.11	-15.15	-16.82
$σ l i n e M D$	74.68	68.84	63.96	57.37	50.4	43.24	35.29	26.66	46.89
$σ l i n e A S G$	37.64	36.18	39.3	39.17	39.49	38.48	37.51	36.27	38.72
变化量/%	-49.59	-47.45	-38.56	-31.72	-21.65	-11.00	6.30	36.02	-17.43
方案数	7	331	3 686	15 788	31 314	30 950	15 054	2 870	100 000

表9

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描述	举例
累计运行时间/s	165.4
累计运行距离/m	1 633.1
瞬时速度/(km/h)	35.2
步长能耗/kJ	42.32

有轨电车交叉口速度自动引导方法及仿真评价

Automatic Speed Guidance Method and Simulation Evaluation for Trams at Intersections

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