A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation

Yusuke Tanaka; Yuu Nakajima; Hiromitsu Hattori; Toru Ishida

doi:10.1007/978-3-642-01639-4_24

A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation

Yusuke Tanaka^*, Yuu Nakajima, Hiromitsu Hattori, Toru Ishida

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

We propose how to acquire driver's individual operation models using the three-dimensional driving simulator in order to implement distinct personalities on each agent. In this paper, operation models are defined as sets of prioritized operation rules, each of which consists of the world as observed by a driver and his/her next operation according to the observation. Each driver might have different set of rules and their priorities. We apply a method to acquire individual operation models using hypothetical reasoning. Because of the method, we are able to obtain operation models which can explain driver's operation during driving simulation. We show some operation models acquired from aged/young human drivers, and then clarify the proposed method can catch each driver's characteristics.

Original language	English
Title of host publication	Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers
Pages	278-287
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-01639-4_24
Publication status	Published - 2009
Externally published	Yes
Event	10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007 - Bangkok, Thailand Duration: 2007 Nov 21 → 2007 Nov 23

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5044 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007
Country/Territory	Thailand
City	Bangkok
Period	07/11/21 → 07/11/23

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-01639-4_24

Cite this

Tanaka, Y., Nakajima, Y., Hattori, H., & Ishida, T. (2009). A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation. In Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers (pp. 278-287). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5044 LNAI). https://doi.org/10.1007/978-3-642-01639-4_24

A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation. / Tanaka, Yusuke; Nakajima, Yuu; Hattori, Hiromitsu et al.
Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers. 2009. p. 278-287 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5044 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tanaka, Y, Nakajima, Y, Hattori, H & Ishida, T 2009, A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation. in Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5044 LNAI, pp. 278-287, 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Bangkok, Thailand, 07/11/21. https://doi.org/10.1007/978-3-642-01639-4_24

Tanaka Y, Nakajima Y, Hattori H, Ishida T. A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation. In Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers. 2009. p. 278-287. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-01639-4_24

Tanaka, Yusuke ; Nakajima, Yuu ; Hattori, Hiromitsu et al. / A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation. Agent Computing and Multi-Agent Systems - 10th Pacific Rim International Conference on Multi-Agents, PRIMA 2007, Revised Papers. 2009. pp. 278-287 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We propose how to acquire driver's individual operation models using the three-dimensional driving simulator in order to implement distinct personalities on each agent. In this paper, operation models are defined as sets of prioritized operation rules, each of which consists of the world as observed by a driver and his/her next operation according to the observation. Each driver might have different set of rules and their priorities. We apply a method to acquire individual operation models using hypothetical reasoning. Because of the method, we are able to obtain operation models which can explain driver's operation during driving simulation. We show some operation models acquired from aged/young human drivers, and then clarify the proposed method can catch each driver's characteristics.",

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AB - We propose how to acquire driver's individual operation models using the three-dimensional driving simulator in order to implement distinct personalities on each agent. In this paper, operation models are defined as sets of prioritized operation rules, each of which consists of the world as observed by a driver and his/her next operation according to the observation. Each driver might have different set of rules and their priorities. We apply a method to acquire individual operation models using hypothetical reasoning. Because of the method, we are able to obtain operation models which can explain driver's operation during driving simulation. We show some operation models acquired from aged/young human drivers, and then clarify the proposed method can catch each driver's characteristics.

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A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation

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