Preemptive Spatiotemporal Trajectory Adjustment for Heterogeneous Vehicles in Highway Merging Zones

2025-09-30

AI Summary

To address driver perception latency and low spatiotemporal resource utilization in highway on-ramp merging zones, this paper proposes a heterogeneous vehicle cooperative control method based on preemptive trajectory adjustment. The approach innovatively integrates dual-positioning error with spatiotemporal trajectory tracking error to formulate a cooperative control strategy that accounts for vehicle-type characteristics, driver intent, and safety-preserving spatiotemporal separation. It further elucidates the dynamic merging mechanism under mixed-vehicle compositions. Through preemptive trajectory planning, coordinated spatiotemporal resource allocation, and high-fidelity multi-scenario simulation—validated via time-space-speed diagram analysis and closed-loop trajectory tracking control—the method significantly improves merging performance: average delays for mainline and ramp vehicles decrease by 90.24% and 74.24%, respectively, while simultaneously enhancing safety, longitudinal/lateral stability, and overall traffic throughput.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Multiagent Systems: Coordination and Collaboration

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Aiming at the problem of driver's perception lag and low utilization efficiency of space-time resources in expressway ramp confluence area, based on the preemptive spatiotemporal trajectory Adjustment system, from the perspective of coordinating spatiotemporal resources, the reasonable value of safe space-time distance in trajectory pre-preparation is quantitatively analyzed. The minimum safety gap required for ramp vehicles to merge into the mainline is analyzed by introducing double positioning error and spatiotemporal trajectory tracking error. A merging control strategy for autonomous driving heterogeneous vehicles is proposed, which integrates vehicle type, driving intention, and safety spatiotemporal distance. The specific confluence strategies of ramp target vehicles and mainline cooperative vehicles under different vehicle types are systematically expounded. A variety of traffic flow and speed scenarios are used for full combination simulation. By comparing the time-position-speed diagram, the vehicle operation characteristics and the dynamic difference of confluence are qualitatively analyzed, and the average speed and average delay are used as the evaluation indices to quantitatively evaluate the performance advantages of the preemptive cooperative confluence control strategy. The results show that the maximum average delay improvement rates of mainline and ramp vehicles are 90.24 % and 74.24 %, respectively. The proposed strategy can effectively avoid potential vehicle conflicts and emergency braking behaviors, improve driving safety in the confluence area, and show significant advantages in driving stability and overall traffic efficiency optimization.

Problem

• Addresses highway merging safety and efficiency for autonomous heterogeneous vehicles
• Quantifies safe spatiotemporal distance considering positioning and trajectory errors
• Proposes cooperative control strategy to reduce delays and prevent conflicts

Innovation

• Proposes preemptive spatiotemporal trajectory adjustment for autonomous vehicles
• Integrates vehicle type, driving intention, and safety distance
• Uses cooperative control strategy to improve merging efficiency