Abstract

Trajectory planning is essential for ensuring safe driving in the face of uncertainties related to communication, sensing, and dynamic factors such as weather, road conditions, policies, and other road users. Existing car-following models often lack rigorous safety proofs and the ability to replicate human-like driving behaviors consistently. This article applies multi-phase dynamical systems analysis to well-known car-following models to highlight the characteristics and limitations of existing approaches. It begins by formulating fundamental principles for safe and human-like car-following behaviors, which include zeroth-order principles for comfort and minimum jam spacings, first-order principles for speeds and time gaps, and second-order principles for comfort acceleration/deceleration bounds as well as braking profiles. From a set of these zeroth- and first-order principles, it derives Newell’s simplified car-following model. Subsequently, the study analyzes phases within the speed-spacing plane for the stationary lead-vehicle problem in Newell’s model and its extensions, which incorporate both bounded acceleration and deceleration. It then analyzes the performance of the Intelligent Driver Model and the Gipps model. Through this analysis, the study highlights the limitations of these models with respect to some of the aforementioned principles. Numerical simulations and empirical observations validate the theoretical insights. Finally, it discuss future research directions to further integrate safety, human-like behaviors, and vehicular automation in car-following models, which are addressed in Part 2 of this study, where it develops a novel multi-phase projection-based car-following model that addresses the limitations identified there.