From Proximity to Priority: Optimizing Demand-Responsive Transit with Value of Waiting Time (VOWT)

Abstract: This research investigates the integration of the Value of Waiting Time (VOWT) into Demand-Responsive Transit (DRT) systems to enhance operational efficiency and improve customer satisfaction. Traditional DRT services dynamically adjust routes based on real-time demand but often neglect the varying sensitivities passengers have toward waiting times. We propose a VOWT-based framework that enables DRT operators to prioritize passengers based on their perceived waiting costs, allowing for a more equitable and responsive service. The novelty of this approach lies in the personalized route design, which incorporates travelers charateristics, such as age or special needs, and specific trip attributes, like higher VOWT for time-sensitive hospital trips. This ensures the system can adapt to individual passenger needs, providing a more customized and efficient transit experience. To solve the problem of minimizing the total weighted waiting time in pickup and dropoff problem, we utilize a multi-stage algorithm. The initial solution is constructed using the Parallel Cheapest Insertion Heuristic, which systematically assigns each pickup-dropoff pair to an available vehicle by minimizing insertion costs, derived from a travel time matrix. This stage ensures cost-effective and capacity-compliant route development. Following this, a Local Search Metaheuristic refines the solution by applying techniques, such as 2-opt and 3-opt, to iteratively reorder and swap routes, reducing the overall travel and waiting time. Experimental results, based on a simulated transportation network, demonstrate that incorporating VOWT significantly improves vehicle resource allocation and reduces waiting times, particularly benefiting vulnerable or high-priority passengers. The findings show the potential for VOWT to drive more personalized, equitable, and efficient transit services, with promising implications for real-world deployment.