01557882

Component

This paper explores a descriptive theory of multidimensional travel behavior, estimation of quantitative models, and demonstration in an agent-based microsimulation. A descriptive theory on multidimensional travel behavior is conceptualized. It theorizes multidimensional knowledge updating, search start/stopping criteria, and search/decision heuristics. These components are formulated or empirically modeled and integrated in a unified and coherent approach. The theory is supported by empirical observations and the derived quantitative models are tested by an agent-based simulation on a demonstration network. Based on artificially intelligent agents, learning and search theory, and bounded rationality, this paper makes an effort to build a sound theoretical foundation for the computational process approach and agent-based microsimulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modeled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioral dynamics.

This paper was sponsored by TRB committee ADB40 Transportation Demand Forecasting.

01550057

15-4480

English

20p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Decision making; Intelligent agents; Microsimulation; Travel behavior; Travel demand

Agent based models

Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2015 Paper #15-4480

TRIS, TRB, ATRI

Dec 30 2014 1:28PM