TY - JOUR
T1 - A rule-based mode choice model - INSIM expert system
AU - Memon, Abdul Ahad
AU - Meng, Meng
AU - Wong, Yiik Diew
AU - Lam, Soi-Hoi
PY - 2015/4/30
Y1 - 2015/4/30
N2 - 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.
AB - 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.
U2 - 10.1061/(ASCE)TE.1943-5436.0000753
DO - 10.1061/(ASCE)TE.1943-5436.0000753
M3 - Article
SN - 2690-4098
VL - 141
JO - Transportation Engineering Journal of ASCE
JF - Transportation Engineering Journal of ASCE
IS - 4
M1 - 04014088
ER -