Co-Ride: Collaborative Preference-Based Taxi-Sharing and Taxi-Dispatch

Abstract

Taxi-sharing is an emergent transport mode, which has shown promising results economically, by splitting the travel cost between passengers and environmentally, by serving more people in each trip. Intelligent taxi-dispatch approaches can also manage demand by distributing taxis according to population density in a city. Current approaches to taxi-sharing recommend passengers share a taxi by matching their origin and destination, and taxi-dispatch approaches simply send more taxis to populated areas. However, each passenger may have multiple preferences (e.g., level of convenience, time, cost, and environmental factors), and require a mechanism that offers options considering these preferences. Similarly, taxi drivers may have multiple preferences (e.g., number of hours to work, minimum revenue per day) that need to be considered during a taxi-dispatch planning process. This paper presents a multi-agent collaborative passenger matching and taxi-dispatch model. Passengers and drivers are modeled as autonomous agents having multiple often-conflicting preferences. Passenger agents collaboratively take actions to form a group for a taxi-share, and taxi agents collaborate to achieve a dispatch plan.