Paper Info
Title
ROThAr: Real-Time On-Line Traffic Assignment with Load Estimation
Abstract
More and more drivers use on-board units to help them navigate in the increasing urbanised environment they live and work in. These system (e.g., routing applications on smart phones) are now very often on-line, and use information from the traffic situation (e.g., accidents, congestion) to get the best route. We can now envisage a world where all trips are assigned and updated by such an on-line system, making the best routing decisions based on traffic conditions. The problem is that current systems consider only 'local' elements (e.g., driver preference and current traffic condition) and do not make routing decisions from a global perspective. This can lead to a lot of similar routing assignments that could lead to further traffic congestion. The objective of the next generation on-line navigation systems is then to come up with a 'smart', real-time route assignment, which balances the load between the different road segments and offers the best quality to the drivers. However, every routing decision made has an impact on the traffic conditions (one more vehicle on the road segments selected) and computing the load induced by the trips is a computationally heavy problem. This paper addresses this question of real-time on-line traffic assignment, and shows that under certain conditions it is possible to have (i) an accurate estimation of the load and travel time on every road segment and (ii) an optimised traffic assignment that adapts to divergence and evolutions (e.g., accidents) of the system.
Year
DOI
Venue
2013
10.1109/DS-RT.2013.17
DS-RT
Keywords
Field
DocType
similar routing assignment,traffic situation,current traffic condition,load estimation,real-time on-line traffic assignment,routing decision,traffic congestion,optimised traffic assignment,traffic condition,road segment,best routing decision
Traffic optimization,Traffic flow,Static routing,Computer science,Policy-based routing,Floating car data,Computer network,Vehicle Information and Communication System,Traffic congestion reconstruction with Kerner's three-phase theory,Traffic engineering
Conference
ISSN
Citations 
PageRank 
1550-6525
2
0.44
References 
Authors
2
3
Name
Order
Citations
PageRank
Takfarinas Saber1254.90
Anthony Ventresque210817.08
John Murphy359752.43