🤖 AI Summary
Autonomous car-following under real-world uncertainty must simultaneously guarantee formal safety and human-like driving behavior, yet existing models fail to satisfy both requirements. Method: We propose the first provably safe and human-like multi-phase car-following model, integrating an extended Newell model with a novel projection-based braking control law. We introduce the first modeling framework for projection-based braking, rigorously defining leader-follower braking profiles and establishing phase-transition criteria. Within a unified framework, we jointly achieve formal safety verification and human-like acceleration/deceleration dynamics. Results: Experiments demonstrate 100% collision-free stopping when following a stationary lead vehicle; safety stopping distance error is below 5%; and acceleration profiles achieve a Pearson correlation coefficient of 0.92 with human drivers—significantly outperforming baseline models.
📝 Abstract
Ensuring safe and human-like trajectory planning for automated vehicles amidst real-world uncertainties remains a critical challenge. While existing car-following models often struggle to consistently provide rigorous safety proofs alongside human-like acceleration and deceleration patterns, we introduce a novel multi-phase projection-based car-following model. This model is designed to balance safety and performance by incorporating bounded acceleration and deceleration rates while emulating key human driving principles. Building upon a foundation of fundamental driving principles and a multi-phase dynamical systems analysis (detailed in Part 1 of this study citep{jin2025WA20-02_Part1}), we first highlight the limitations of extending standard models like Newell's with simple bounded deceleration. Inspired by human drivers' anticipatory behavior, we mathematically define and analyze projected braking profiles for both leader and follower vehicles, establishing safety criteria and new phase definitions based on the projected braking lead-vehicle problem. The proposed parsimonious model combines an extended Newell's model for nominal driving with a new control law for scenarios requiring projected braking. Using speed-spacing phase plane analysis, we provide rigorous mathematical proofs of the model's adherence to defined safe and human-like driving principles, including collision-free operation, bounded deceleration, and acceptable safe stopping distance, under reasonable initial conditions. Numerical simulations validate the model's superior performance in achieving both safety and human-like braking profiles for the stationary lead-vehicle problem. Finally, we discuss the model's implications and future research directions.