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Open AccessJournal ArticleDOI

Modeling Lane-Changing Behavior in a Connected Environment: A Game Theory Approach

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TLDR
A lane-changing model based on a game-theoretical approach that endogenously accounts for the flow of information in a connected vehicular environment is presented and provides a greater level of realism than a basic gap-acceptance model.
Abstract
Vehicle-to-Vehicle communications provide the opportunity to create an internet of cars through the recent advances in communication technologies, processing power, and sensing technologies. A connected vehicle receives real-time information from surrounding vehicles; such information can improve drivers’ awareness about their surrounding traffic condition and lead to safer and more efficient driving maneuvers. Lane-changing behavior,as one of the most challenging driving maneuvers to understand and to predict, and a major source of congestion and collisions, can benefit from this additional information.This paper presents a lane-changing model based on a game-theoretical approach that endogenously accounts for the flow of information in a connected vehicular environment.A calibration approach based on the method of simulated moments is presented and a simplified version of the proposed framework is calibrated against Next Generation Simulation (NGSIM) data. The prediction capability of the simplified model is validated. It is concluded the presented framework is capable of predicting lane-changing behavior with limitations that still need to be addressed. Finally, a simulation framework based on the fictitious play is proposed. The simulation results revealed that the presented lane-changing model provides a greater level of realism than a basic gap-acceptance model.

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Citations
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Journal ArticleDOI

Ramp metering control under stochastic capacity in a connected environment: A dynamic bargaining game theory approach

TL;DR: The outcomes indicate that the proposed cooperative model with stochastic capacity considerations outperforms the deterministic capacity-based models in regard to effectiveness and equity properties, however, the centralized approach performs slightly better in respect to system-wide efficiency.

Optimizing Traffic Flow Efficiency by Controlling Lane Changes: Collective, Group and User Optima

TL;DR: The proposed genetic algorithm can be further extended to a more effective in-car advice system, which can improve traffic efficiency through communication with partly automated vehicles.
Proceedings ArticleDOI

Data-driven situation awareness algorithm for vehicle lane change

TL;DR: Experimental results show that the proposed Data-Driven Situation Awareness algorithm obtains better filtering and projection accuracy in comparison with the Kalman filter without clustering.
Proceedings ArticleDOI

A Game Theoretic Model for Aggregate Bypassing Behavior of Vehicles at Traffic Diverges

TL;DR: This work presents a macroscopic model for predicting the number of vehicles that bypass at a traffic diverge, taking into account the selfishness of vehicles in selecting their lanes, and proves that the equilibrium is unique under mild assumptions.
Posted Content

A Game Theoretic Macroscopic Model of Bypassing at Traffic Diverges with Applications to Mixed Autonomy Networks

TL;DR: A macroscopic model for predicting the number of vehicles that bypass at a traffic diverge is presented and it is demonstrated how the model can be utilized in scenarios where a central authority can dictate the lane choice and trajectory of certain vehicles so as to increase the overall vehicle mobility at a Traffic diverge.
References
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Journal ArticleDOI

Congested traffic states in empirical observations and microscopic simulations

TL;DR: It is shown that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way, and a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.
Journal ArticleDOI

Games with Incomplete Information Played by Bayesian Players, I-III

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