Simulation-driven Based Utility Evaluation and Recommendation of Expressway Proactive Speed Limit

doi:10.16182/j.issn1004731x.joss.22-FZ0903

Abstract

Abstract:

Outside the specific punishment area, the traditional roadside passive speed limit mode lacks traffic management, and thus which indirectly leads to the inconsistency or even sudden change of vehicle behaviors in time and space, thereby affects the traffic efficiency and safety. Focusing on the proactive speed limit mode at vehicle side, a utility evaluation and recommendation method is proposed, which carries out the multi-scenario traffic simulation for varied proactive and passive speed limit considering road line types, traffic flow and vehicle type proportion. From the two perspectives of safety and efficiency, the utility evaluation indicators and weights are extracted through surrogate safety assessment model and traffic flow operation status, and the integrated learning method is used in further prediction and analysis. The results show that the proactive speed limiting mode can improve the safety and adjusting efficiency. In proactive speed limit, the prediction stability and accuracy of GBDT (gradient boosting decision tree) regression model are higher (R²=0.984).

Key words: proactive speed limit, passive speed limit, traffic simulation, expressway, evaluation indicator, ensemble learning

CLC Number:

TP391.9

Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang. Simulation-driven Based Utility Evaluation and Recommendation of Expressway Proactive Speed Limit[J]. Journal of System Simulation, 2022, 34(12): 2522-2534.

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线形	小汽车限速	货车限速
直道	100~120	80~100
弯道	90~110	70~90
坡道	90~110	70~90
匝道主路	95~115	75~95

方法	安全评价指标							效率评价指标
方法	TTC	PET	maxS	DeltaS	DR	mTTC	mPET	空间平均车速	路段交通密度	路段饱和度
熵权法	0.400	0.296	0.173	0.031	0.030	0.025	0.046	0.928	0.026	0.046
灰色关联度	0.143	0.142	0.142	0.145	0.141	0.143	0.143	0.337	0.337	0.326
主成分分析	0.216	0.214	0.203	0.143	0.078	0.036	0.111	0.393	0.326	0.281
综合权重	0.254	0.209	0.161	0.110	0.088	0.080	0.100	0.541	0.239	0.220

模型	MSE	RMSE	MAE	MAPE	R²
线性回归	0.012	0.111	0.079	26.067	0.707
ADABOOST	0.002	0.047	0.031	7.338	0.946
GBDT	0.001	0.026	0.018	4.241	0.984
CATBOOST	0.001	0.028	0.018	4.383	0.981

道路类型	可选速度区间/(km/h)	预测最高得分	推荐限速值/(km/h)
道路类型	可选速度区间/(km/h)	预测最高得分	小型车辆	大型车辆
直道	100~125	0.988	123	103
弯道	90~110	0.891	93	73
坡道	90~110	0.949	97	77
匝道主路	95~115	0.876	102	82

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