Route Choice-Based Socio-Technical Macroscopic Traffic Model

Tanushree Roy, Satadru Dey

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Human route choice is undeniably one of the key contributing factors towards traffic dynamics. However, most existing macroscopic traffic models are typically concerned with driving behavior and do not incorporate human route choice behavior models in their formulation. In this paper, we propose a socio-technical macroscopic traffic model that characterizes the traffic states using human route choice attributes. Essentially, such model provides a framework for capturing the Cyber-Physical-Social coupling in smart transportation systems. To derive this model, we first use Cumulative Prospect Theory (CPT) to model the human passengers' route choice under bounded rationality. These choices are assumed to be influenced by traffic alerts and other incomplete traffic information. Next, we assume that the vehicles are operating under a non-cooperative cruise control scenario. Accordingly, human route choice segregates the traffic into multiple classes where each class corresponds to a specific route between an origin-destination pair. Thereafter, we derive a Mean Field Game (MFG) limit of this non-cooperative game to obtain a macroscopic model which embeds the human route choice attribute. Finally, we analyze the mathematical characteristics of the proposed model, present simulation studies to illustrate the model behavior and show comparison with existing traffic model.

Original languageEnglish (US)
Pages (from-to)5781-5791
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number6
StatePublished - Jun 1 2023

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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