Enhanced stability of car-following model upon incorporation of short-term driving memory

• Published in: Communications in nonlinear science & numerical simulation Vol. 47; pp. 139 - 150
• Main Authors: Liu, Da-Wei, Shi, Zhong-Ke, Ai, Wen-Huan
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.06.2017; Elsevier Science Ltd
• Subjects: Anticipation behavior; Automobiles; Behavior; Car following; Car-following model; Computer simulation; Critical point; Driving; Driving memory; Memory; Numerical analysis; Stability; Traffic flow; Traffic models; Driving memory; Anticipation behavior; Traffic flow; Car-following model
• ISSN: 1007-5704; 1878-7274
• DOI: 10.1016/j.cnsns.2016.11.007

• A new car-following model considering short-term driving memory was proposed.• Short-term driving memory was introduced to modify the driver's anticipation behavior.• Linear stability analysis and nonlinear analysis are conducted.• The memory period for the best driving characteristics was obtained.• Vehicle's motion during the starting and braking process were investigated. Based on the full velocity difference model, a new car-following model is developed to investigate the effect of short-term driving memory on traffic flow in this paper. Short-term driving memory is introduced as the influence factor of driver's anticipation behavior. The stability condition of the newly developed model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Via numerical method, evolution of a small perturbation is investigated firstly. The results show that the improvement of this new car-following model over the previous ones lies in the fact that the new model can improve the traffic stability. Starting and breaking processes of vehicles in the signalizedintersection are also investigated. The numerical simulations illustrate that the new model can successfully describe the driver's anticipation behavior, and that the efficiency and safety of the vehicles passing through the signalized intersection are improved by considering short-term driving memory.