Publication: Updating of travel behavior model parameters and estimation of vehicle trip chain based on plate scanning
3
0
Issued Date
2014
Resource Type
File Type
application/pdf
ISSN
15472450
Other identifier(s)
2-s2.0-84904217363
Rights Holder(s)
Scopus
Bibliographic Citation
Journal of Intelligent Transportation Systems: Technology, Planning, and Operations. Vol 18, No.4 (2014), p.393-409
Suggested Citation
Siripirote T., Sumalee A., Watling D.P., Shao H. Updating of travel behavior model parameters and estimation of vehicle trip chain based on plate scanning. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations. Vol 18, No.4 (2014), p.393-409. doi:10.1080/15472450.2013.806761 Retrieved from: https://hdl.handle.net/20.500.14740/6345
Author(s)
Abstract
This article proposes a maximum-likelihood method to update travel behavior model parameters and estimate vehicle trip chain based on plate scanning. The information from plate scanning consists of the vehicle passing time and sequence of scanned vehicles along a series of plate scanning locations (sensor locations installed on road network). The article adopts the hierarchical travel behavior decision model, in which the upper tier is an activity pattern generation model, and the lower tier is a destination and route choice model. The activity pattern is an individual profile of daily performed activities. To obtain reliable estimation results, the sensor location schemes for predicting trip chaining are proposed. The maximum-likelihood estimation problem based on plate scanning is formulated to update model parameters. This problem is solved by the expectation-maximization (EM) algorithm. The model and algorithm are then tested with simulated plate scanning data in a modified Sioux Falls network. The results illustrate the efficiency of the model and its potential for an application to large and complex network cases. © Taylor and Francis Group, LLC.
Subject(s)
Chains
Complex networks
Location
Maximum likelihood
Maximum likelihood estimation
Maximum principle
Scanning
Transportation
Vehicles
EM algorithms
Estimation of vehicles
Estimation results
Expectation-maximization algorithms
Maximum likelihood methods
Model and algorithms
Travel behavior modeling
Trip chaining
Parameter estimation
Complex networks
Location
Maximum likelihood
Maximum likelihood estimation
Maximum principle
Scanning
Transportation
Vehicles
EM algorithms
Estimation of vehicles
Estimation results
Expectation-maximization algorithms
Maximum likelihood methods
Model and algorithms
Travel behavior modeling
Trip chaining
Parameter estimation