Cooperative Method of Traffic Signal Optimization and Speed Control of Connected Vehicles at Isolated Intersections

Xu, Biao; Ban, Xuegang; Bian, Yougang; Li, Wan; Wang, Jianqiang; Li, Keqiang

doi:10.1109/tits.2018.2849029

Cited by 194 publications

(80 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…e data analysis results in Table 1 further indicate that the correlation between the jerk e ect and driving behavior increases by 50.6% on average compared to that of an RV since V2V communication technology provides instant information regarding the interactions between vehicles [33,36,37]. is nding may improve the stability of connected tra c ow.…”

Section: Data Mining Analysismentioning

confidence: 96%

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Hui

Liu

et al. 2020

Journal of Advanced Transportation

View full text Add to dashboard Cite

The existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the change in the traffic jerk effect between inactive and active vehicle-to-vehicle (V2V) communications based on field experimental data. Data mining results show that the correlation between the jerk effect and the driving behavior increases by 50.6% on average when V2V messages are received. In light of the data analysis results, a new car-following model is proposed to explore the jerk effect in a connected environment. The model parameters are calibrated, and the results show that the standard deviation between the new model simulation data and the observed data decreases by 38.2% compared to that of the full velocity difference (FVD) model. Linear and nonlinear analyses of the calibrated model are then carried out to evaluate the connected traffic flow stability. Finally, the theoretical analysis is verified by simulation experiments. Both the theoretical and simulation results show that the headway amplitude and velocity fluctuations are reduced when considering the jerk effect in a connected environment, and the traffic flow stability is improved.

show abstract

Section: Data Mining Analysismentioning

confidence: 96%

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Hui

Liu

et al. 2020

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…Xu et al [12] proposed a cooperative method of traffic signal control and vehicle speed optimization for connected automated vehicles, which optimizes the traffic signal timing and vehicles' speed at the same time. In the optimization of the traffic signal timing, they calculated the optimal traffic signal timing and vehicles' travel time to minimize the total trip time of all vehicles.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

Han¹,

Lee

Park

et al. 2019

Journal of Advanced Transportation

View full text Add to dashboard Cite

This study aims to develop an optimal signal control algorithm for signalized intersections using individual vehicle’s trajectory data under the vehicle-to-infrastructure (V2I) communication environment. The optimal signal control algorithm developed in this study consists of three modules, namely, a phase group length computation module, a split distribution module, and a phase sequence assignment module. A set of analyses using a microscopic simulation model, VISSIM, was conducted for evaluating the effectiveness of the V2I-based optimal signal control algorithm proposed in this study. The analysis results show that the performance of the V2I-based optimal signal control algorithm is superior to the actuated as well as the fixed signal control methods in an isolated intersection and a 2X3 signalized intersection network. In addition, this study investigated the minimum market penetration rate of V2I equipped vehicles for which the V2I-based optimal signal control algorithm is applicable.

show abstract

“…A method to process C2I communication data for tailback length approximation in urban networks was provided, and the tailback length could be used as a criterion to be optimized within signal control methods and used to provide an individual driver with optimal speed to pass the signalized intersection without stopping [56]. A cooperative method of traffic signal control and vehicle speed optimization for connected automated vehicles was proposed, and simulation showed a significant improvement of transportation efficiency and fuel economy [57]. Meanwhile, given the assumption of advanced communication technology between approaching vehicles and signal controller, a signal control algorithm was developed which allows for vehicle paths and signal control to be jointly optimized [58].…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Left-Turn Signal Control Method for Improving Intersection Capacity in a Connected Vehicle Environment

et al. 2019

View full text Add to dashboard Cite

Setting up an exclusive left-turn lane and corresponding signal phase for intersection traffic safety and efficiency will decrease the capacity of the intersection when there are less or no left-turn movements. This is especially true during rush hours because of the ineffective use of left-turn lane space and signal phase duration. With the advantages of vehicle-to-infrastructure (V2I) communication, a novel intersection signal control model is proposed which sets up variable lane direction arrow marking and turns the left-turn lane into a controllable shared lane for left-turn and through movements. The new intersection signal control model and its control strategy are presented and simulated using field data. After comparison with two other intersection control models and control strategies, the new model is validated to improve the intersection capacity in rush hours. Besides, variable lane lines and the corresponding control method are designed and combined with the left-turn waiting area to overcome the shortcomings of the proposed intersection signal control model and control strategy.

show abstract

Cooperative Method of Traffic Signal Optimization and Speed Control of Connected Vehicles at Isolated Intersections

Cited by 194 publications

References 29 publications

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

A Novel Left-Turn Signal Control Method for Improving Intersection Capacity in a Connected Vehicle Environment

Contact Info

Product

Resources

About