Spatio-temporal patterns of subjectively reported congestion in Tel Aviv metropolitan area [An article from: Journal of Transport Geography] Buy on Amazon

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Spatio-temporal patterns of subjectively reported congestion in Tel Aviv metropolitan area [An article from: Journal of Transport Geography]

AuthorE. Stern
PublisherElsevier
8.95 USD
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Book Details

Author(s)E. Stern
PublisherElsevier
ISBN / ASINB000RQZX0O
ISBN-13978B000RQZX02
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States  🇺🇸

Description

This digital document is a journal article from Journal of Transport Geography, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Traffic congestion is still one of the major problems of urban transportation. It is the aggregate outcome of individual, subjective, decisions in a changing traffic environment.The individual's decision making is affected, among other factors, by experience and direct information from the surrounding environment, or indirectly from the media. The subjective map created from this information provides the cognitive environment within which the driver makes decisions. This study examines the spatio-temporal changes in the subjective map of reported congestion as formed by radio broadcasts in the Tel Aviv metropolitan area. It aims to evaluate the spatio-temporal stability of the emerged congestion patterns as a basis for subjective decision making, and to explain its variability as a necessary base for any effort to relieve congestion. Results show that non-recurrent heavy congestion is likely to be unstable. The spatio-temporal fluctuations of congestion were found to associate with traffic volumes caused mainly by weekly-based commuters which include university students, soldiers, and government employees. Reported information was found suitable for longitudinal research, the only kind which enables a broad understanding of the spatio-temporal pattern and dynamics of traffic congestion.
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