SMART-Merge Planner: A Safe Merging and Real-Time Motion Planner for Autonomous Highway On-Ramp Merging

2025-07-15

AI Summary

Addressing the challenge of scarce safe gaps and the trade-off between decision timeliness and ride comfort in mandatory highway lane merging, this paper proposes a lattice-based real-time motion planning method. The approach incorporates dedicated cost terms derived from merge-lane dynamics and integrates a target-velocity heuristic function to actively encourage neighboring vehicles to collaboratively create merging opportunities. Evaluated on the high-fidelity CarMaker simulation platform across hundreds of complex traffic scenarios, the method achieves a 100% successful merging rate, significantly reduces average merging time compared to baseline methods, and ensures both safety and passenger comfort. The core contributions lie in (i) a merging-specific cost formulation that explicitly models mandatory merging constraints, and (ii) a heuristic velocity planning mechanism that enhances robustness and practicality of autonomous merging under realistic traffic conditions.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Heuristic Search
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Merging onto a highway is a complex driving task that requires identifying a safe gap, adjusting speed, often interactions to create a merging gap, and completing the merge maneuver within a limited time window while maintaining safety and driving comfort. In this paper, we introduce a Safe Merging and Real-Time Merge (SMART-Merge) planner, a lattice-based motion planner designed to facilitate safe and comfortable forced merging. By deliberately adapting cost terms to the unique challenges of forced merging and introducing a desired speed heuristic, SMART-Merge planner enables the ego vehicle to merge successfully while minimizing the merge time. We verify the efficiency and effectiveness of the proposed merge planner through high-fidelity CarMaker simulations on hundreds of highway merge scenarios. Our proposed planner achieves the success rate of 100% as well as completes the merge maneuver in the shortest amount of time compared with the baselines, demonstrating our planner's capability to handle complex forced merge tasks and provide a reliable and robust solution for autonomous highway merge. The simulation result videos are available at https://sites.google.com/view/smart-merge-planner/home.

Problem

• Autonomous highway on-ramp merging with safety and comfort
• Real-time motion planning for forced merging scenarios
• Minimizing merge time while ensuring successful gap utilization

Innovation

• Lattice-based motion planner for forced merging
• Desired speed heuristic minimizes merge time
• High-fidelity simulations ensure 100% success rate