Adaptive routing behavior with real time information under multiple travel objectives

Real time information about traffic conditions is becoming widely available through various media, and the focus on Advanced Traveler Information Systems (ATIS) is gaining importance rapidly. In such conditions, travelers have better knowledge about the system and adapt as the system evolves dynamically during their travel. Drivers may change routes along their travel in order to optimize their own objective of travel, which can be characterized by disutility functions. The focus of this research is to study the behavior of travelers with multiple trip objectives, when provided with real time information. A web based experiment is carried out to simulate a traffic network with information provision and different travel objectives. The decision strategies of participants are analyzed and compared to the optimal policy, along with few other possible decision rules and a general model is calibrated to describe the travelers' decision strategy. This research is a step towards calibrating equilibrium models for adaptive behavior with multiple user classes.

Name thesis:degree_name

Master of Science in Engineering

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Civil Engineering

Grantor

The University of Texas at Austin

Year dc:date.issued

2013

Author dc:creator

• Venkatraman, Ravi

Advisor dc:contributor.advisor

• Boyles, Stephen David, 1982-

• Adaptive routing
• Real time information
• Online shortest paths
• Routing games
• Driving behavior

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/2152/22293

OAI identifier oai:identifier

oai:repositories.lib.utexas.edu:2152/22293