Information-based predictive congestion control for intelligent transportation management.

Author(s)
Bhattacharyya, A. Seetharam, A. & Naskar, M.K.
Year
Abstract

Third world cities are overpopulated and the number of vehicles plying on roads far exceeds the available traffic handling facilities resulting in frequent traffic congestions. Billions of dollars are being spent by the governments to construct over bridges for traffic management. This work proposes a unique solution scheme_in which current traffic information is gathered through inductive loop detectors, piezoelectric sensors and wireless sensor networks coupled with mobile telephony to predict traffic flow and control traffic dynamics. The device placements in turn are dependent on information concerning traffic history of the place. The scheme is modeled on the basis of load-based packet switching as in computer network theory and is cost-effective, business-oriented and hence sustainable and replicable. This work proves the effectiveness of the solution both mathematically and through simulated traffic dynamics for Jadavpur and Gariahat , two heavily_congested test cases in Calcutta, India. This is the first information-based decision making scheme which predicts the future for current congestion control using an integrated architecture of in-vogue techniques, sensor and cellular networks. (Author/publisher).

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Publication

Library number
I E145420 /70 /72 / ITRD E145420
Source

Advances in Transportation Studies. 2009. 19 (November) Pp5-16 (15 Refs.)

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.