Spatiotemporal Aggregation Strategies with Discount as an Incentive for Demand Responsive Transit

Demand responsive transit (DRT) service is reemerging as a flexible and sharable strategy to mitigate the ever-growing car ownership and environmental pollution. Nevertheless, encouraging passengers to accept spatiotemporal aggregation remains an often-overlooked but critical problem. In this paper, two strategies for aggregating passenger demand are proposed to improve the performance of the DRT system. The discount incentive mechanism is to induce passengers toward long-term use. A solution approach based on variable neighborhood descent is developed to accelerate the computational performance and enhance the solution quality. In addition, a Beijing case study offers support for the impact of spatiotemporal aggregation strategies on DRT system. The results reveal that two strategies drastically improve the profit while reducing the average fare. Therefore, spatiotemporal aggregation strategies with a discount as an incentive facilitate constructing a flexible DRT service.