Skip navigation

Rule-based mode choice model: INSIM expert system

Rule-based mode choice model: INSIM expert system

Memon, A. A., Meng, M. ORCID: 0000-0001-7240-6454, Wong, Y. D. and Lam, S. H. (2014) Rule-based mode choice model: INSIM expert system. Journal of Transportation Engineering, 141 (4):04014088. ISSN 2473-2907 (Print), 2473-2893 (Online) (doi:https://doi.org/10.1061/(ASCE)TE.1943-5436.0000753)

[img] PDF (Author Accepted Manuscript)
22696 MENG_Rule-Based_Mode_Choice_Model_2014.pdf - Accepted Version
Restricted to Registered users only

Download (671kB) | Request a copy

Abstract

This paper presents an innovative rule-based intelligent network simulation model (INSIM) expert system (IES) which simulates real-time mode choice decision-making process of commuters in the presence of multimodal traveler information. The IES captures interactions among available modes and decides on the commuter’s mode based on a commuter’s socioeconomic traits and prevailing travel condition. The commuter’s mode choice behavior is modeled and represented by cognitive rules in the rule-base of the IES. Two important characteristics of the IES, the reliability and the adaptive learning, are highlighted. Three different models, i.e., (1) pure rule-based model (PRB), (2) discrete choice model (DCM), and (3) probabilistic model (COM) are introduced to formulate the mode choice decisions. Simulation results show that the highest level of accuracy can be achieved by applying the PRB model to generate mode choice decisions.

Item Type: Article
Uncontrolled Keywords: Integrated traveler information; Traffic simulation; Rule-based; Mode choice
Subjects: H Social Sciences > HE Transportation and Communications
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Connected Cities Research Group
Faculty of Business > Department of Systems Management & Strategy
Last Modified: 11 Feb 2019 16:02
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/22696

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics