Work

More Than Following: Introducing Reversing Behavior for Irregular‐Aware Traffic Simulation by Interactive Editing

Year: 2025

Type: article

Abstract: ABSTRACT Though current traffic simulation methods can produce impressive results, reversing behavior is always ignored, potentially reducing the diversity and plausibility of simulation data. Furthermore, while common traffic behaviors like following‐the‐leader and lane changing can be easily simulated, efficiently generating irregular cases in a human‐in‐the‐loop manner with specific motions based on user desires is less discussed. To address the gap, we present a novel interactive traffic editing and simulation framework that enables users to regulate vehicles via simple inputs to introduce reversing and generate desired trajectory data with both car‐following and irregular driving behaviors. With key states specified, lane‐level navigation, including forward/backward directions, is planned through heuristic search. The customized navigation brings the vehicles' new trajectories with both car‐following and reversing, and their surrounding neighbors are also adjusted accordingly. To provide smooth and plausible motions after editing, vehicles are updated via the optimization‐based simulation method, which takes vehicle kinematics, self‐motivation, path keeping, collision avoidance, and special interaction rules into account. We demonstrate that our framework can generate uncommon traffic cases and validate it through extensive experiments.

Source: Computer Animation and Virtual Worlds

DOI: 10.1002/cav.70071

Authors: Yi Han, He Wang, Xiaogang Jin

Institutions: State Key Laboratory of Computer Aided Design and Graphics, Zhejiang University, University College London

Language: English

Topic: Simulation and Modeling Applications

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: green

Funder: National Natural Science Foundation of China