Adaptation and Congestion in a Multi-Agent System to Analyse Empirical Traffic Problems

Abstract

This study discusses adaptation effects and congestion in a multi-agent system (MAS) to analyse real transport and traffic problems. Both methodological discussion and an empirical case study are presented in this chapter. The main focus is on the comparison of an analysis of a MAS simulation analysis and an analysis that solely uses discrete choice modelling. This study explains and discusses some important concepts in design empirical MAS in traffic and transportation, including validation Minority Game and adaptation effects. This study develops an empirical MAS simulation model based on real stated-preference data to analyse the effect of a real road-user charge policy and a complimentary park and ride scheme at the Upper Derwent Valley in the Peak District National Park, England. The simulation model integrates a transport mode choice model, Markov queue model, and Minority Game to overcome the disadvantages of a conventional approach. The results of the simulation model show that the conventional analysis overestimates the effect of the transportation and environment policy due to the lack of adaptation affects of agents and congestion. The MAS comprehensively analysed the mode choices, congestion levels, and the user utility of visitors while including the adaptability of agents. The MAS also called as agent-based simulation successfully integrates models from different disciplinary backgrounds, and shows interesting effects of adaptation and congestion at the level of an individual agent.