Incident-Related Travel Time Estimation Using a Cellular Automata Model

The purpose of this study was to estimate the drivers' travel time with the occurrence of an incident on freeway. Three approaches, which were shock wave analysis, queuing theory and cellular automata models, were initially considered, however, the first two macroscopic models were indicated to underestimate travel time by previous literature. A microscopic simulation model based on cellular automata was developed to attain the goal. The model incorporated driving behaviors on the freeway with the presence of on-ramps, off-ramps, shoulder lanes, bottlenecks and incidents. The study area was a 16 mile eastbound section of I-66 between US-29 and I-495 in northern Virginia. The data for this study included loop detector data and incident data for the road segment for the year 2007. Flow and speed data from the detectors were used for calibration using quantitative and qualitative techniques. The cellular automata model properly reproduced the traffic flow under normal conditions and incidents. The travel time information was easily obtained from the model. The system is promising for travel time estimation in near real time.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Civil Engineering

Department dc:contributor.department

Civil Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2009

Author dc:creator

• Wang, Zhuojin

Chair dc:contributor.committeechair

• Murray-Tuite, Pamela Marie

Committee members dc:contributor.committeemember

• Lu, Chang-Tien
• Abbas, Montasir M.

• travel time
• Cellular Automata
• incident

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-06182009-154412

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/33644