Modeling driving decisions with latent plans

Driving is a complex task that includes a series of interdependent decisions. In many situations, these decisions are based on a specific plan. The plan is however unobserved or latent and only the manifestations of the plan through actions are observed. Examples include selection of a target lane before execution of the lane change, choice of a merging tactic before execution of the merge. Change in circumstances (e.g. reaction of the neighboring drivers, delay in execution) can lead to updates to the initially chosen plan. These latent plans are ignored in the state-of-the-art driving behavior models. Use of these myopic models in the traffic simulators often lead to unrealistic traffic flow characteristics and incorrect representation of congestion. A modeling methodology has been formulated to address the effects of unobserved plans in the decisions of the drivers and hence overcome the deficiency of the existing driving behavior models and simulation tools. The actions of the driver are conditional on the current plan. The current plan can depend on previous plans and be influenced by anticipated future conditions. A Hidden Markov Model is used to address the effect of previous plans in the choice of the current plan and to capture the state-dependence among decisions. Effects of anticipated future circumstances in the current plan are captured through predicted conditions based on current information. The heterogeneity in decision making and planning capabilities of drivers are explicitly addressed. The methodology has been applied in developing driving behavior models for four traffic scenarios: freeway lane changing, freeway merging, urban intersection lane choice and urban arterial lane changing. In all applications, the models are estimated with disaggregate trajectory data using the maximum likelihood technique.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Choudhury, Charisma Farheen, 1978-

Advisor dc:contributor.advisor

• Moshe E. Ben-Akiva.

• 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/1721.1/42220

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/42220