COMMUTING SERVICE PLATFORM: CONCEPT, METHOD, AND ANALYSIS

Abstract

Commuting congestion increases alongside the prosperity of urban cities. With the rapid development of ridesourcing services and the advances of connected and automated vehicles (CAV), researchers are seeking innovative approaches to alleviate commuting congestion. This research aims to build a commuting service platform (CSP) that alleviates congestion and increases mobility during peak hours. The pricing strategies and the route choices of the proposed CSP are studied. On the planning level, how CSP leverages emerging mobility services for commuting and connects directly commuters (employees) and their worksites (employers) is investigated. The planning level model shows how the price allocation, i.e., the prices charged to commuters and worksites, can impact the participation and profit of the CSPs, which is extended to consider locations of homes and worksites using a general modeling framework. On the operational level, a route choice model for an integrated, multimodal CAV ridesourcing and transit system is proposed. The route choice model captures the economic behaviors and interactions of the major players (i.e.. the ridesourcing company and customers) in the commuting scenario by optimizing the profit of the ridesourcing company and the utility of customers, as well as the optimal route choice to minimize congestion. The proposed CSP is prominent in building the next-generation travel demand management (TDM) strategies.