A Car-Following Model Considering Preceding Vehicle’s Lane-Changing Process

Car following and lane changing are two common driving behaviors in the traffic flow. Preceding vehicle's lane changing is affected by the surroundings and will have a greater influence on the followers' driving decision. The existing car-following theory does not fully take it into consideration that the followers' driving behavior may change during a lane-changing process. In order to reflect the driving decision in a complex traffic flow more precisely, the influence on the following vehicle during the preceding vehicle's lane-changing process is studied. First, the different types of stimulus during the preceding vehicle's lane-merging (LM) process and the space gain effect produced by the preceding vehicle's lane-passing (LP) behavior are analyzed. Then, the LM-FVDM and LP-FVDM are proposed based on the classical car-following model-FVD model. Finally, the linear stability theory, numerical simulation, and NGSIM data sets are used to analyze and validate the performance of the LM-FVDM and LP-FVDM. The numerical simulation results show that the model can reasonably reflect the driving decision of the following vehicle in various scenarios, and verification based on NGSIM shows that the $R$ -squared of vehicles' speed and distance is significantly better than the FVD model, which can more effectively reflect the speed adjustment process of the following vehicle during the preceding vehicle's lane-changing process in the real traffic flow.