Modelling Individual Preferences to Study and Predict Effects of Traffic Policies

Nguyen, Johannes; Powers, Simon; Urquhart, Neil; Farrenkopf, Thomas; Guckert, Michael

Abstract

Traffic can be viewed as a complex adaptive system in which systemic patterns arise as emergent phenomena. Global behaviour is a result of behavioural patterns of a large set of individual travellers. However, available traffic simulation models lack of concepts to comprehensibly capture preferences and personal objectives as determining factors of individual decisions.
This limits predictive power of such simulation models when used to estimate the consequences of new traffic policies. Effects on individuals must not be ignored as these are the basic cause of how the system changes under interventions. In this paper, we present a simulation framework in which the self-interested individual and its decision-making is placed at the center of attention. We use semantic reasoning techniques to model individual decision-making on the basis of personal preferences that determine traffic relevant behaviour. As this initially makes the simulations more complex and opaque the simulation framework also comprises tools to inspect rule evaluation providing a necessary element of explainability. As proof of concept we discuss an example scenario and demonstrate how this type of modelling could help in evaluating the effects of new traffic policies on individual as well as global system behaviour.

Citation

Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021, October). Modelling Individual Preferences to Study and Predict Effects of Traffic Policies. Presented at PAAMS: International Conference on Practical Applications of Agents and Multi-Agent Systems, Salamanca, Spain

• Presentation Conference Type: Conference Paper (published)
• Conference Name: PAAMS: International Conference on Practical Applications of Agents and Multi-Agent Systems
• Start Date: Oct 6, 2021
• End Date: Oct 8, 2021
• Acceptance Date: Jun 21, 2021
• Online Publication Date: Sep 25, 2021
• Publication Date: 2021
• Deposit Date: Jul 15, 2021
• Publicly Available Date: Sep 26, 2022
• Publisher: Springer
• Pages: 163-175
• Series Title: Lecture Notes in Computer Science
• Series Number: 12946
• Series ISSN: 0302-9743
• Book Title: Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection 19th International Conference, PAAMS 2021, Salamanca, Spain, October 6–8, 2021, Proceedings
• ISBN: 978-3-030-85738-7
• DOI: https://doi.org/10.1007/978-3-030-85739-4_14
• Keywords: Traffic Simulation, Agent Modelling, Policy Assessment
• Public URL: http://researchrepository.napier.ac.uk/Output/2786923