Formal Modeling Method for Prediction of Safe Vehicle Following Mode

The traditional modeling methods of vehicle following are unable to traverse each possible control input and the uncertain motion states, which means that these methods are insufficient to ensure the integrity and reliability of prediction of the safe following behavior of surrounding vehicles in theory. Therefore, a formal modeling method based on reachability analysis and the representation of reachable sets is proposed to predict the safety vehicle following mode here. In this paper, the stochastic reachable set with ergodicity property is applied to characterize the uncertain prediction for the behavior of surrounding vehicle. Based on the discretization of the state and control input space of vehicle, the stochastic reachable sets of vehicles are abstracted to Markov chains that are used to express the random change of system states further. The accurate prediction probability of state change of vehicle can be achieved. In addition, a security incidence matrix of states and control inputs between correlated vehicles in following mode is structured offline. The offline simulations are helpful to improve the efficiency of online computing. The incidence matrix reflecting the correlation of vehicles approximately is applied to describe the rule of control input selection of surrounding vehicle under the safety following mode. Finally, the possible safe following behaviors of surrounding vehicle can be estimated and analyzed online by synthesizing the current states information of related vehicles, Markov chains and incidence matrix. The results of numerical verification show that the proposed modeling method formulates the whole set of safe following behaviors and process completely, and improves the accuracy of prediction significantly. Besides, the results also reveal that the method is effective to model, analysis and verify the security of following control strategy. Copyright © 2021 Acta Automatica Sinica. All rights reserved.