Vehicle global path planning algorithm based on spatio-temporal characteristics of traffic

doi:10.3969/j.issn.1674-8484.2021.01.005

Abstract

Abstract:

A path planning algorithm based on spatiotemporal dynamic traffic information was proposed to reduce the travel time and energy consumption of hybrid electric vehicles (HEV). The factors that affect the vehicle travel time and the minimum energy consumption in the whole path were analyzed. The travel time and the path energy consumption are calculated based on the generalized regression network (GRNN) model. A vehicle path planning algorithm based on parallel A * algorithm was constructed to plan a shorter time-consuming or more energy-saving path for vehicles after determining the starting and ending positions. The virtual simulation test was implemented. The results show that the proposed algorithm can obtain a better travel path and reduce vehicle energy consumption by more than 11% or driving time by more than 13% compared with the calculation methods through average speed or power parameters. Therefore, the proposed algorithm can plan a better route for vehicles.

Key words: hybrid electric vehicle (HEV), urban traffic, path planning, space-time searching

CLC Number:

U469.7

DU Mao, YANG Lin, JIN Yue, TU Jiayu. Vehicle global path planning algorithm based on spatio-temporal characteristics of traffic[J]. Journal of Automotive Safety and Energy, 2021, 12(1): 52-61.

Figures/Tables 16

References 21

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平均车速		-0.42
车辆密度	ρ_i,t	0.64
道路长度	l_i	0.18
非绿灯的时长	r_i,t	0.08
路口长度	γ_i	0.11
通行功率	ē_i,t	-0.38
预估通行时长	τ_{i, t}	0.18
下一道路j的平均车速	v_j,t'	-0.29
下一道路j的车辆密度	ρ_j,t'	0.51
绿灯时长	j_i,t	-0.1

平均车速		-0.42
车辆密度	ρ_i,t	0.64
道路长度	l_i	0.18
非绿灯的时长	r_i,t	0.08
路口长度	γ_i	0.11
通行功率	ē_i,t	-0.38
预估通行时长	τ_{i, t}	0.18
下一道路j的平均车速	v_j,t'	-0.29
下一道路j的车辆密度	ρ_j,t'	0.51
绿灯时长	j_i,t	-0.1

ID		ρ_i,t	l_i	r_i,t	g_i,t	τ_{i, t}	ē_i,t		ρ_j,t'	γ_i	RE/%	MAE/s
1	√	√	√	√	√	√	√	√	√	√	10.39	2.95
2	√	√	√	√	√	√	√			√	8.66	2.59
3	√	√	√	√	√	√	√				8.60	2.51
4	√	√	√	√	√	√					8.97	2.65
5	√	√	√	√	√						8.97	2.66
6	√	√	√	√	√			√	√		9.68	2.78
7	√	√	√	√	√			√	√	√	10.01	2.87
8	√	√	√	√	√					√	8.71	2.64

ID		ρ_i,t	l_i	r_i,t	g_i,t	τ_{i, t}	ē_i,t		ρ_j,t'	γ_i	RE/%	MAE/s
1	√	√	√	√	√	√	√	√	√	√	10.39	2.95
2	√	√	√	√	√	√	√			√	8.66	2.59
3	√	√	√	√	√	√	√				8.60	2.51
4	√	√	√	√	√	√					8.97	2.65
5	√	√	√	√	√						8.97	2.66
6	√	√	√	√	√			√	√		9.68	2.78
7	√	√	√	√	√			√	√	√	10.01	2.87
8	√	√	√	√	√					√	8.71	2.64

	关联性
	DP油耗	参数1	参数2	参数3	参数4	参数5	参数6	参数7	参数8
DP油耗	1.00	0.90	0.63	0.44	0.66	-0.37	0.58	0.34	-0.46
参数1	0.90	1.00	0.92	0.30	0.83	-0.16	0.46	0.18	-0.25
参数2	0.63	0.92	1.00	0.61	0.62	-0.37	0.75	0.51	-0.49
参数3	0.44	0.30	0.61	1.00	-0.14	-0.57	0.80	0.86	-0.73
参数4	0.66	0.83	0.62	-0.14	1.00	0.35	0.06	-0.22	0.28
参数5	-0.37	-0.16	-0.37	-0.57	0.35	1.00	-0.64	-0.68	0.95
参数6	0.58	0.46	0.75	0.80	0.06	-0.64	1.00	0.92	-0.69
参数7	0.34	0.18	0.51	0.86	-0.22	-0.68	0.92	1.00	-0.73
参数8	-0.46	-0.25	-0.49	-0.73	0.28	0.95	-0.69	-0.73	1.00