Driver’s lane selection model based on multi-player dynamic game

Wang, Xiaoyuan; Liu, Yaqi; Wang, Fang; Liu, Zhiguo; Zhao, Hongjin; Xin, Junfeng

doi:10.1177/1687814018819903

Cited by 4 publications

(2 citation statements)

References 14 publications

(17 reference statements)

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“…Ali et al [22] proposed a mandatory lane-changing with incomplete information based on non-zerosum non-cooperative game applicable to traditional and connected environments. Wang et al [23] built a lane selection model based on multi-player dynamic game with complete information considering vehicle group situation. The drivers' payoffs were analyzed, and the Nash equilibrium solution was solved through backward induction.…”

Section: Introductionmentioning

confidence: 99%

Impact of Penetrations of Connected and Automated Vehicles on Lane Utilization Ratio

et al. 2022

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Lane Utilization Ratio (LUR), affected by lane selection behavior directly, represents the traffic distribution on different lanes of road section for a single direction. The research on LUR, especially under Penetration Conditions of Connected and Automated Vehicles (PCCAV), is not comprehensive enough. Considering the difficulty in the conduction of real vehicle experiment and data collection under PPCAV, the lane selection model based on phase-field coupling and set pair logic, which considers the full-information of lanes, was used to carry out microscopic traffic simulation. From the analysis of microsimulation results, the basic relationships between Penetration of Connected and Automated Vehicles (PCAV), traffic volume, and Lane-Changing Times, also that between PCAV, traffic volume, and LUR in the basic section of the urban expressway were studied. Moreover, the influence of driving propensity on the effect of PCAVs was also studied. The research results could enrich the traffic flow theory and provide the theoretical basis for traffic management and control.

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Section: Introductionmentioning

confidence: 99%

Impact of Penetrations of Connected and Automated Vehicles on Lane Utilization Ratio

et al. 2022

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“…Compared with another common driving behavior model (i.e. the lane-changing model [3] [4]), the car-following model describes the longitudinal behavior of vehicles in the current lane, which is very common in the restricted overtaking section (such as ramp) and the continuous-flow facilities (such as the highway).…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Car-Following Model Based on the Random Forest

Shi¹,

Wang²,

Zhong³

et al. 2021

WJET

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The car-following models are the research basis of traffic flow theory and microscopic traffic simulation. Among the previous work, the theory-driven models are dominant, while the data-driven ones are relatively rare. In recent years, the related technologies of Intelligent Transportation System (ITS) represented by the Vehicles to Everything (V2X) technology have been developing rapidly. Utilizing the related technologies of ITS, the large-scale vehicle microscopic trajectory data with high quality can be acquired, which provides the research foundation for modeling the car-following behavior based on the data-driven methods. According to this point, a data-driven car-following model based on the Random Forest (RF) method was constructed in this work, and the Next Generation Simulation (NGSIM) dataset was used to calibrate and train the constructed model. The Artificial Neural Network (ANN) model, GM model, and Full Velocity Difference (FVD) model are employed to comparatively verify the proposed model. The research results suggest that the model proposed in this work can accurately describe the carfollowing behavior with better performance under multiple performance indicators.

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