S63-S1 Public transportation and big data: data processing and valuation
Tracks
Special Session
| Thursday, August 29, 2019 |
| 4:30 PM - 6:00 PM |
| MILC_Room 310 |
Details
Convenor(s): Patrick Bonnel, Oscar Egu, Catherine Morency, Martin Trépanier / Chair: Patrick Bonnel
Speaker
Ms Manlika Sukitpaneenit
Ph.D. Student
Imperial College London
High spatial resolution traffic flow and emissions based on taxi GPS data in Bangkok, Thailand
Author(s) - Presenters are indicated with (p)
Manlika Sukitpaneenit (p), Marc E. J. Stettler
Discussant for this paper
Oscar Egu
Abstract
A high spatial resolution traffic flow is an important input variable for vehicle emissions estimates and health impact assessments. Due to the limited number of fixed detectors on roads, it is a challenging task to estimate the traffic flow on the entire the road network. In this study, we demonstrate a methodology for predicting traffic flow using the GPS data from public taxis (probe vehicles). The fundamental diagram, which describes the relationship between traffic flow, speed, and density, is applied in order to estimate the flow. Uncertainty in the estimated traffic flow is also quantified and propagated to uncertainties in vehicle emissions estimates. The methodology is applied to a case study in Bangkok Metropolitan Region, Thailand using data from approximately 3,000 taxis, to estimate the average vehicle speed on each road segment. A validation of the traffic flow estimates is performed for each road categories.
Mr Oscar Egu
Ph.D. Student
LAET-ENTPE, University of Lyon
Comparing origin-destination matrices derived from smart card data with a large scale OD survey. A case study in Lyon.
Author(s) - Presenters are indicated with (p)
Oscar Egu (p)
Discussant for this paper
Manlika Sukitpaneenit
Abstract
see extended abstract
