Vehicle Dynamics Model for Estimating Typical Vehicle Accelerations

Abstract

Developing mathematical models for accurate estimation of the longitudinal acceleration behavior of drivers and vehicles is an important challenge in traffic engineering. The modeling of vehicle acceleration is complex because of its dependence on vehicle type and human driving behavior. Existing acceleration dynamics models have tied typical acceleration (the maximum acceleration that drivers would use in a free-flow condition) to maximum acceleration models that are descriptive of the maximum acceleration capability of the vehicle. Although this approach generally results in a better fitting of field data that are understandable and predictable, the proposed models do not take into account differing driving behaviors. The research presented in this paper develops a model that overcomes this limitation by explicitly incorporating driver behavior in the mathematical expression of a dynamics-based acceleration model. The proposed model has a flexible shape that allows it to incorporate driver variations. Furthermore, the model is demonstrated to be superior to similar models because it predicts more accurate acceleration levels in all domains.