Abstract
Traffic speed is one of the basic variables that indicates the level of service of a road entity. It plays an essential role in transportation planning and management. This study attempts to establish a prediction model for speed distribution, in terms of average travel speed and standard deviation, using probe vehicle data in Hong Kong. Taking advantage of detailed traffic flow data obtained from the annual traffic census, a comprehensive traffic information database can be established using the geographical information system technique. The effects of traffic flow, road geometry, and weather conditions on speed distribution are determined using the Markov-chain Monte Carlo (MCMC) simulation approach full Bayesian method.
Original language | English |
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Pages (from-to) | 1188-1195 |
Number of pages | 8 |
Journal | Journal of Transportation Engineering |
Volume | 138 |
Issue number | 10 |
DOIs | |
Publication status | Published - 1 Oct 2012 |
Externally published | Yes |
Keywords
- Bayesian analysis
- Geometry
- Global positioning system
- Monte carlo method
- Traffic speed
- Weather conditions
ASJC Scopus subject areas
- Civil and Structural Engineering
- Transportation