Abstract
En-route planning is a dynamic planning process to find the optimal route (e.g., shortest route) while driving. The goal of this paper is to mimic a realistic drivers' en-route planning behavior under the situations with incomplete information about road conditions using the Extended Belief-Desire-Intention (E-BDI) framework. The proposed E-BDI based en-route planning is able to find a new route to the destination based on the predicted road conditions inferred by drivers' own psychological reasoning. A main challenge of such a detailed E-BDI model is a high computational demand needed to execute a large scale road network, which is typical in a big city. To mitigate such a high computational demand, a hierarchical route planning approach is also proposed in this work. The proposed approach has been implemented in Java-based E-BDI modules and DynusT® traffic simulation software, where a real traffic data of Phoenix, Arizona is used. To validate the proposed hierarchical approach, the performance of the en-route planning modules under the different aggregation levels is compared in terms of their computational efficiency and modeling accuracy. The validation results reveal that the proposed en-route planning approach efficiently generates a realistic route plan with individual driver's prediction of the road conditions.
| Original language | English (US) |
|---|---|
| Title of host publication | IIE Annual Conference and Expo 2014 |
| Publisher | Institute of Industrial Engineers |
| Pages | 547-556 |
| Number of pages | 10 |
| ISBN (Print) | 9780983762430 |
| State | Published - 2014 |
| Event | IIE Annual Conference and Expo 2014 - Montreal, Canada Duration: May 31 2014 → Jun 3 2014 |
Other
| Other | IIE Annual Conference and Expo 2014 |
|---|---|
| Country | Canada |
| City | Montreal |
| Period | 5/31/14 → 6/3/14 |
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Keywords
- Agent-based simulation
- Belief-desire-intention
- En-route planning
- Hierarchical route planning
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Control and Systems Engineering
Cite this
Hierarchical en-route planning under the extended belief-desire-intention (E-BDI) framework. / Kim, Sojung; Son, Young-Jun; Tian, Ye; Chiu, Yi-Chang; David Yang, C. Y.
IIE Annual Conference and Expo 2014. Institute of Industrial Engineers, 2014. p. 547-556.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Hierarchical en-route planning under the extended belief-desire-intention (E-BDI) framework
AU - Kim, Sojung
AU - Son, Young-Jun
AU - Tian, Ye
AU - Chiu, Yi-Chang
AU - David Yang, C. Y.
PY - 2014
Y1 - 2014
N2 - En-route planning is a dynamic planning process to find the optimal route (e.g., shortest route) while driving. The goal of this paper is to mimic a realistic drivers' en-route planning behavior under the situations with incomplete information about road conditions using the Extended Belief-Desire-Intention (E-BDI) framework. The proposed E-BDI based en-route planning is able to find a new route to the destination based on the predicted road conditions inferred by drivers' own psychological reasoning. A main challenge of such a detailed E-BDI model is a high computational demand needed to execute a large scale road network, which is typical in a big city. To mitigate such a high computational demand, a hierarchical route planning approach is also proposed in this work. The proposed approach has been implemented in Java-based E-BDI modules and DynusT® traffic simulation software, where a real traffic data of Phoenix, Arizona is used. To validate the proposed hierarchical approach, the performance of the en-route planning modules under the different aggregation levels is compared in terms of their computational efficiency and modeling accuracy. The validation results reveal that the proposed en-route planning approach efficiently generates a realistic route plan with individual driver's prediction of the road conditions.
AB - En-route planning is a dynamic planning process to find the optimal route (e.g., shortest route) while driving. The goal of this paper is to mimic a realistic drivers' en-route planning behavior under the situations with incomplete information about road conditions using the Extended Belief-Desire-Intention (E-BDI) framework. The proposed E-BDI based en-route planning is able to find a new route to the destination based on the predicted road conditions inferred by drivers' own psychological reasoning. A main challenge of such a detailed E-BDI model is a high computational demand needed to execute a large scale road network, which is typical in a big city. To mitigate such a high computational demand, a hierarchical route planning approach is also proposed in this work. The proposed approach has been implemented in Java-based E-BDI modules and DynusT® traffic simulation software, where a real traffic data of Phoenix, Arizona is used. To validate the proposed hierarchical approach, the performance of the en-route planning modules under the different aggregation levels is compared in terms of their computational efficiency and modeling accuracy. The validation results reveal that the proposed en-route planning approach efficiently generates a realistic route plan with individual driver's prediction of the road conditions.
KW - Agent-based simulation
KW - Belief-desire-intention
KW - En-route planning
KW - Hierarchical route planning
UR - http://www.scopus.com/inward/record.url?scp=84910100305&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84910100305&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84910100305
SN - 9780983762430
SP - 547
EP - 556
BT - IIE Annual Conference and Expo 2014
PB - Institute of Industrial Engineers
ER -