HLSR: Hybrid Live Forecast Selective Dynamic Vehicle Rerouting

Forum topic · 小凯 · 2026-08-20

Summary

HLSR is a selective hybrid live-forecast vehicle rerouting framework for mitigating urban traffic congestion, proposed by Xiao Wang, Shun Ren Yang, and Hui Nien Hung (arXiv:2608.18056). While network-wide live travel-time shortest-path rerouting can be highly effective in simulation, it assumes essentially every on-road vehicle is replanned every decision period—an unrealistic requirement. HLSR instead fuses live edge speeds with short-horizon forecasts under a limited intervention scope. The framework builds on dual-threshold congestion detection, calibrated upstream selection, and driver-tailored travel-time prediction, and further introduces approaching-vehicle expansion, travel-time-weighted k-shortest-path generation, and a horizon-dependent hybrid live-forecast segment speed used in multi-cost route allocation. This selective approach reduces replanning overhead while targeting the vehicles and segments where rerouting yields the greatest benefit, addressing congestion-related productivity losses, travel costs, and emissions.

Paper Overview

Field: Machine Learning
Authors: Xiao Wang, Shun Ren Yang, Hui Nien Hung
Published: 2026-08-18
arXiv: 2608.18056

Abstract

Urban traffic congestion reduces productivity and increases travel cost and emissions. Network-wide live travel-time shortest-path rerouting can be highly effective in simulation, but assumes that essentially every on-road vehicle is replanned every decision period. We propose HLSR, a selective hybrid live-forecast vehicle rerouting framework that fuses live edge speeds with short-horizon forecasts under limited intervention scope. Building on dual-threshold congestion detection, calibrated upstream selection, and driver-tailored travel-time prediction, HLSR further introduces approaching-vehicle expansion, travel-time-weighted k-shortest-path generation, and a horizon-dependent hybrid live-forecast segment speed used in multi-cost route allocation.

Key Ideas

Selective rerouting: Instead of replanning every vehicle every decision period, HLSR targets a limited intervention scope.
Hybrid live-forecast fusion: Combines real-time edge speeds with short-horizon speed forecasts.
Core components:
Dual-threshold congestion detection
Calibrated upstream selection
Driver-tailored travel-time prediction
Approaching-vehicle expansion
Travel-time-weighted k-shortest-path generation
Horizon-dependent hybrid live-forecast segment speed for multi-cost route allocation

---

*Auto-collected on 2026-08-20.*