Taxonomy of Shared Autonomous Vehicle Fleet Management Problems to Inform Future Transportation Mobility. Issue 1 (2017)

• Record Type: Journal Article
• Authors: Hyland, Michael F.; Mahmassani, Hani S.
• Is Part Of: Transportation research record. Volume 2653:Issue 1(2017)
• Page Start: 26
• Page End: 34
• Publication Date: 2017
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2653-04
• Languages: English
• ISSNs: 0361-1981

Abstract

This paper presents a taxonomy for classifying vehicle fleet management problems, across several dimensions, to inform future research on autonomous vehicle (AV) fleets. Modeling the AV fleet management problem will bring about new classes of vehicle routing, scheduling, and fleet management problems; nevertheless, the existing literature related to vehicle routing, scheduling, and fleet management is a valuable foundation for future research on the AV fleet management problem. This paper classifies the broadly defined AV fleet management problem by using existing taxonomic categories in the literature; adds additional, or more nuanced, dimensions to existing taxonomic categories; and presents new taxonomic categories to classify specific AV fleet management problems. The broadly defined AV fleet management problem can be classified as a dynamic multivehicle pickup and delivery problem with explicit or implicit time window constraints. Existing studies that fit into this class of fleet management problems are reviewed. New taxonomy categories presented in this paper include fleet size elasticity, reservation structure, accept–reject decision maker, reservation time frame, ridesharing, vehicle repositioning, underlying network structure, and network congestion. Two goals of the taxonomy presented in this study are to provide researchers with a valuable reference as they begin to model AV fleet management problems and to present novel AV fleet management problems to spur interest from researchers.