Collaborative Exploratory Research: The Anticipatory Route Guidance Problem

Kachani, Soulaymane; Perakis, Georgia; University Transportation Research Center; New York (State). Dept. of Transportation

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Collaborative Exploratory Research: The Anticipatory Route Guidance Problem

2006-07-01
By Kachani, Soulaymane ; Perakis, Georgia

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English

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Creators:

Kachani, Soulaymane ; Perakis, Georgia

Kachani, Soulaymane ; Perakis, Georgia Less -
Corporate Creators:

University Transportation Research Center ; New York (State). Dept. of Transportation

University Transportation Research Center ; New York (State). Dept. of Transportation Less -
Corporate Contributors:

United States. Department of Transportation
Subject/TRT Terms:

[+]

Advanced Driver Information Systems Cooperation Fixed Routes Highways I73: Traffic Control Operations And Traffic Management Route Guidance
Publication/ Report Number:

SPR ID# C-05-04 ; 49777-1805

SPR ID# C-05-04 ; 49777-1805 Less -
Resource Type:

Research Paper
Geographical Coverage:

New York (New York) ; United States

New York (New York) ; United States Less -
TRIS Online Accession Number:

01079113
Edition:

Final Report
Corporate Publisher:

New York (State). Dept. of Transportation
Abstract:

Finding solutions to fixed point problems can help government and industry leaders to plan for real world success. One concrete example of problem solving which may be amenable to fixed point solution is the anticipatory route guidance problem (ARG). An exercise in dynamic traffic userequilibrium, this problem envisions a communications system which transmits dynamic, shortest path traffic data to drivers. But anything that influences the path-choice decisions of drivers will, in itself, affect traffic conditions on the ground. The challenge is clear: develop a model in which shortest-path forecasting does not become a selfdefeating prophecy. This research develops and evaluates a software system which explores the ARG problem from a fixed point perspective. A significant part of our research consists in identifying the best algorithms for step size computation. Methods evaluated include: MSA (Method of successive averaging), Polyak iterate averaging method, and a variety of potential optimization line search methods.
Format:

PDF
Collection(s):

US Transportation Collection
Main Document Checksum:

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urn:sha256:7563280d2b05c3fe99fa0910ff0ad3819088955013343592d6ed5911442c80f5
Download URL:

https://rosap.ntl.bts.gov/view/dot/40181/dot_40181_DS1.pdf
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Collaborative Exploratory Research: The Anticipatory Route Guidance Problem

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