研究人员提出HLSR框架，能智能重规划车辆路线，有效缓解城市交通拥堵，比传统方法更精准高效。
HLSR是一种新型交通拥堵避免框架，融合实时边缘速度与短期预测。该框架基于双阈值拥堵检测和校准上游选择，引入接近车辆扩展技术。系统采用行程时间加权k最短路径生成方法，适用于多成本路径分配场景。
HLSR: Hybrid Live Forecast Selective Dynamic Vehicle Rerouting for Real-Time Congestion Avoidance
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.