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Highway Networks Dynamic Route Guidance Decision Model And Algorithm Design In Disastrous Conditions

Posted on:2011-05-30Degree:MasterType:Thesis
Country:ChinaCandidate:X HanFull Text:PDF
GTID:2132360305460473Subject:Traffic safety engineering
Abstract/Summary:PDF Full Text Request
In recent years, Chinese highway transport developed rapidly with the rapid development of society and economy. Especially in highway construction, Chinese highway networks have been basically formed through the construction of recent decades. However, the harmony between the rapid growth of highway mileage and relatively low levels of highway is poor. This clash has also brought traffic jam, traffic safety, environmental pollution and other social issues. Especially in the disastrous conditions, based on Route Guidance System traffic volume are distributed reasonably to reduce secondary accident, guide traffic effectively and evacuate traffic in the scene of the accident. By Route Guidance System traffic jam can be reduced, and travel time and costs can be reduced also. Therefore, in the disastrous conditions researching Route Guidance must makes sense at all.This paper research Determined Route Guidance System and route guidance decision problem in the disastrous conditions. Based on the summary and analysis, Dynamic Route Guidance System in the disastrous conditions is structured. Structure Dynamic route guidance decision model, by minimum time resistance function, expense cost function, traffic jam cost function and highway property cost function. Through Comparative analysis of the existing algorithms Arithmetic, ant colony algorithm is chosen. To applying to disastrous conditions, this article used modified ant colony algorithm to solve that model. Finally, using real data, these come from highway network from Jinan to Tyan. Based on examples, provide reference for route guidance System. At the same time achieve highway efficiency and passenger satisfaction.
Keywords/Search Tags:Disastrous Conditions, Determined Route Guidance Decision Model, Modified Ant Colony Algorithm
PDF Full Text Request
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