Interactive route choice and prescriptive information on degradable network. (December 2022)

• Record Type: Journal Article
• Authors: Li, Manman; Lu, Jian; Sun, Jiahui
• Is Part Of: Simulation. Volume 98:Number 12(2022)
• Page Start: 1179
• Page End: 1191
• Publication Date: 2022-12
• Subjects: Day-to-day traffic assignment model -- system evolution -- prescriptive information -- degradable network -- cumulative prospect theory; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/00375497221105527
• Languages: English
• ISSNs: 0037-5497

Abstract

This study models and analyzes the dynamic interaction between route choice and prescriptive information on a degradable network. The predictively prescriptive information is first explicitly modeled based on travelers' behavior and historical data. Its accuracy is then dynamically measured to adjust the information compliance rate based on travelers' expectations and experiences. Finally, a logit function is adopted to describe travelers' route choice. Based on the proposed model, the dynamic interaction between route choice and prescriptive information on a degradable network is investigated by theoretical analyses and numerical experiments, which provides insights for the design and operation of advanced traveler information systems and traffic management.