Application of Naturalistic Truck Driving Data to Analyze and Improve Car Following Models

This research effort aims to compare car-following models when the models are calibrated to individual drivers with the naturalistic data. The models used are the GHR, Gipps, Intelligent Driver, Velocity Difference, Wiedemann, and the Fritzsche model. This research effort also analyzes the Wiedemann car-following model using car-following periods that occur at different speeds. The Wiedemann car-following model uses thresholds to define the different regimes in car following. Some of these thresholds use a speed parameter, but others rely solely upon the difference in speed between the subject vehicle and the lead vehicle. This research effort also reconstructs the Wiedemann car-following model for truck driver behavior using the Naturalistic Truck Driving Study's (NTDS) conducted by Virginia Tech Transportation Institute. This Naturalistic data was collected by equipping 9 trucks with various sensors and a data acquisition system. This research effort also combines the Wiedemann car-following model with the GHR car-following model for trucks using The Naturalistic Truck Driving Study's (NTDS) data.

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

2011

Author dc:creator

• Higgs, Bryan James

Chair dc:contributor.committeechair

• Abbas, Montasir M.

Committee members dc:contributor.committeemember

• Medina, Alejandra
• Guo, Feng

• GHR Model
• Wiedemann Model
• Car Following
• Naturalistic Data

Statement dc:rights

• In Copyright

Licence dc:rights.uri

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

Dc Identifier Other

etd-12122011-152121

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/36089