Paper Info
Title
Freeway Travel-Time Estimation Based on Temporal–Spatial Queueing Model
Abstract
Travel time serves as a fundamental measurement for transportation systems and becomes increasingly important to both drivers and traffic operators. Existing speed interpolation algorithms use the average speed time series collected from upstream and downstream detectors to estimate the travel time of a road link. Such approaches often result in inaccurate estimations or even systematic bias, particularly when the real travel times quickly vary. To get rid of this problem, Coifman proposed a creative interpolation algorithm based on kinetic-wave models. This algorithm reconstructs vehicle trajectories according to the velocities and the headways of vehicles. However, it sometimes gives significant biased estimation, particularly when jams emerge from somewhere between the upstream and downstream detectors. To make an amendment, we design a new algorithm based on the temporal–spatial queueing model to describe the fast travel-time variations using only the speed and headway time series that is measured at upstream and downstream detectors. Numerical studies show that this new interpolation algorithm could better utilize the dynamic traffic flow information that is embedded in the speed/headway time series in some special cases.
Year
DOI
Venue
2013
10.1109/TITS.2013.2256132
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
VEHICLE TRAJECTORIES,SIGNAL PRIORITY,LOOP DETECTORS,PREDICTION,SYSTEMS
Journal
14
Issue
ISSN
Citations 
3
1524-9050
6
PageRank 
References 
Authors
0.50
8
4
Name
Order
Citations
PageRank
Li Li1581109.68
Chen X211414.01
Li Zhiheng37713.27
Zhang Lei4131.86