2019/02/09 by Yang Liu, Liu, Yang, Samitha Samaranayake +1 · 1 citation
Engineering · Social Sciences · #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Smart Parking Systems Research #Systems and Control (eess.SY) #Transportation Planning and Optimization #Transportation and Mobility Innovations #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1902.03374
openalex publication_date 2019/02/09 · openalex created_date 2019/08/22 · openalex updated_date 2026/07/28
We present a probabilistic proactive rebalancing method and speed-up techniques for improving the performance of a state-of-the-art real-time high-capacity fleet management framework [1]. We improve on both computational efficiency and system performance. The speed-up techniques include search-space pruning and I/O cost reduction for parallelization, reducing the computation time by up to 97.67%, in experiments on taxi trips in New York City. The proactive rebalancing routes idle vehicles to future demands based on probabilistic estimates from historical demand, increasing the service rate by 4.8% on average, and decreasing the waiting time and total delay by 5.0% and 10.7% on average, respectively.