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Travel time statistical modeling with the Halphen distribution family
- Source :
- Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017, 〈10.1080/15472450.2017.1326115〉, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017, ⟨10.1080/15472450.2017.1326115⟩
- Publication Year :
- 2017
- Publisher :
- HAL CCSD, 2017.
-
Abstract
- International audience; This paper introduces the Halphen distribution family for modeling travel time distributions and their reliability on single road links. This probability family originally used in hydrology has a set of relevant characteristics. It is composed of three probability distribution functions for which the mathematical properties are described here. The paper uses a graphical representation, the δ-Moment Ratio Diagram (δ-MRD). This tool allows characterizing travel time reliability as well as selecting best distribution candidates within the fitting processes, by considering empirical data sets. A systematic methodology is developed to take advantage of both aspects. From maximum log-likelihood estimation it is shown that Halphen distributions are amongst the best state-of-the-art solutions for the travel time modeling purpose. This global framework is validated using two empirical data sets: an urban data set gathered in Portland, Oregon (USA) and a periurban data set from Lyon (France). The model calibration is eased through the use of the δ-MRD; this property opens new research directions about the mapping between traffic states and statistical modeling. It comes out from all these considerations that the Halphen family is suitable to describe accurately the travel time dynamics on single links. Therefore it could be part of a decision support system for practitioners interested in travel time variability.
- Subjects :
- Computer science
Diagram (category theory)
Aerospace Engineering
010501 environmental sciences
computer.software_genre
01 natural sciences
Set (abstract data type)
[INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY]
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
0502 economics and business
Econometrics
[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]
Representation (mathematics)
Reliability (statistics)
0105 earth and related environmental sciences
050210 logistics & transportation
[STAT.AP]Statistics [stat]/Applications [stat.AP]
Mathematical model
Applied Mathematics
05 social sciences
[ STAT.AP ] Statistics [stat]/Applications [stat.AP]
Statistical model
Computer Science Applications
Data set
[ INFO.INFO-CY ] Computer Science [cs]/Computers and Society [cs.CY]
Control and Systems Engineering
Automotive Engineering
Probability distribution
Data mining
computer
Software
Information Systems
Subjects
Details
- Language :
- French
- ISSN :
- 15472450 and 15472442
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017, 〈10.1080/15472450.2017.1326115〉, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017, ⟨10.1080/15472450.2017.1326115⟩
- Accession number :
- edsair.doi.dedup.....59fb376099e4288e15f6023b2276db12