2024/01/09 by Yuanjie Tu, Tu, Yuanjie, Moein Khaloei +5
Engineering · Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Transportation Planning and Optimization #Transportation and Mobility Innovations #Urban and Freight Transport Logistics
paper · pdf · doi:10.48550/arxiv.2402.01650
openalex publication_date 2024/01/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
A generalized additive mixed model was estimated to investigate the factors that impact ridehailing driver trip request acceptance choices, relying on 200 responses from a stated preference survey in Seattle, US. Several policy recommendations were proposed to promote trip request acceptance based on ridehailing drivers willingness to accept compensation for undesired trip features. The findings could be useful for transportation agencies to improve ridehailing service efficiency, better fulfill urban mobility needs, and reduce environmental burden.