NDLI: A hybrid modeling approach for parking and traffic prediction in urban simulations

Content Provider	Springer Nature Link
Author	Beheshti, Rahmatollah Sukthankar, Gita
Copyright Year	2014
Abstract	Urban simulations are an important tool for analyzing many policy questions relating to the usage of public space, roads, and communal transportation; they can be used to predict the long-term impact of new construction projects, traffic restrictions, and zoning laws. However, it is unwise to rely upon predictions from a single model since each technique possesses different strengths and weaknesses and can be highly sensitive to the choice of parameters and initial conditions. In this article, we describe a hybrid approach for combining agent-based and stochastic simulations (Markov chain Monte Carlo, MCMC) to improve the accuracy and reduce the variance of long-term predictions. In our proposed approach, the agent-based model is used to bootstrap the proposal distribution for the MCMC estimator. To demonstrate the applicability of our modeling technique, this article presents a case study describing the usage of our hybrid simulation method for forecasting transportation patterns and parking lot utilization on a large university campus. A comparison of our simulation results against an independently collected dataset reveals that our hybrid approach accurately predicts parking lot usage and performs significantly better than other comparable modeling techniques. Developing novel architectures for combining the predictions of agent-based models can produce insights that are different than simply selecting the best model.
Starting Page	333
Ending Page	344
Page Count	12
File Format	PDF
ISSN	09515666
Journal	AI & SOCIETY
Volume Number	30
Issue Number	3
e-ISSN	14355655
Language	English
Publisher	Springer London
Publisher Date	2014-02-14
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Agent-based modeling Markov chain Monte Carlo (MCMC) Transportation simulation Urban modeling Artificial Intelligence (incl. Robotics) Computer Science Engineering Economics, Organization, Logistics, Marketing Control, Robotics, Mechatronics Performing Arts Methodology of the Social Sciences
Content Type	Text
Resource Type	Article
Subject	Philosophy Artificial Intelligence Human-Computer Interaction

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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