Modeling drivers' acceleration and lane changing behavior

This thesis contributes to the development cf microscopic traffic performance models which includes the acceleration and lane changing models. It enhances the existing models and develops new ones. Another major contribution of this thesis is the empirical work, i.e., estimating the models using statistically rigorous methods and microscopic data collected from real traffic. The acceleration model defines two regimes of traffic flow: the car-following regime and the free-flow regime. In the car-following regime, a driver is assumed to follow his/her leader, while in the free-flow regime, a driver is assumed to try to attain his/her desired speed. A probabilistic model, that is based on a time headway threshold, is used to determine the regime the driver belongs to. Heterogeneity across drivers is captured through the headway threshold and reaction time distributions. The parameters of the car-following and free-flow acceleration models along with the headway threshold and reaction time distributions are jointly estimated using the maximum likelihood estimation method. The lane changing decision progress is modeled as a sequence of three steps: decision to consider a lane change, choice of a target lane, and gap acceptance. Since acceptable gaps are hard to find in a heavily congested traffic, a forced merging model that captures forced lane changing behavior and courtesy yielding is developed. A discrete choice model framework is used to model the impact of the surrounding traffic environment and lane configuration on drivers' lane changing decision process. The models are estimated using actual traffic data collected from Interstate 93 at the Central Artery, located in downtown Boston, MA, USA. In addition to assessing the model parameters from statistical and behavioral standpoints, the models are validated using a microscopic traffic simulator. Overall, the empirical results are encouraging, and demonstrate the effectiveness of the modeling framework.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

1999

Author dc:creator

• Ahmed, Kazi Iftekhar

Advisor dc:contributor.advisor

• Moshe E. Ben-Akiva and Haris N. Koutsopoulos.

• Civil and Environmental Engineering

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/9662

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/9662