NDLI: State space reduction in modeling traffic network dynamics for dynamic routing under ITS

Content Provider	IEEE Xplore Digital Library
Author	Nejad, M.M. Mashayekhy, L. Taghavi, A. Chinnam, R.B.
Copyright Year	2011
Description	Author affiliation: Industrial and Systems Engineering Department, Wayne State University, Detroit, MI 48202 USA (Nejad, M.M.; Taghavi, A.; Chinnam, R.B.) \|\| Computer Science Department, Wayne State University, Detroit, MI 48202 USA (Mashayekhy, L.)
Abstract	Effective en route guidance for vehicles can play an important role in alleviating the negative impacts of evergrowing congestion. As network traffic conditions change due to recurrent and non-recurrent congestion, the optimal route can change, and updated directions should be given to the driver in real-time. However, the task of exploiting real-time traffic information for optimal routing is computationally challenging. On the other hand, simplistic schemes (e.g., assuming constant speeds for different network arcs across all hours of the day) lead only to poor travel time performance and driver dissatisfaction. Hence, there is need for compact yet effective representations of traffic network dynamics for supporting routing algorithms. In this paper, we propose two state space reduction approaches employing knowledge discovery and data mining (KDD) methods and mathematical programming (MP) to strike an effective balance between accuracy and state space reduction (i.e., compactness). In doing so, they exploit historical data from ITS systems. We demonstrate the performance of the proposed approaches using actual road network data from Southeast Michigan.
Starting Page	277
Ending Page	282
File Size	599840
Page Count	6
File Format	PDF
ISBN	9781457721984
ISSN	21530009
e-ISBN	9781457721977
DOI	10.1109/ITSC.2011.6082984
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicle dynamics Vehicles Heuristic algorithms Routing Real time systems Sensors Data mining
Content Type	Text
Resource Type	Article

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