Modeling human driving behavior

The goal of this thesis paper is to explore models that can predict and anticipate driver behaviors on the road and give probabilities on future actions of neighboring vehicles, while being lightweight enough to be formally verifiable. This thesis starts with looking into related work and doing a short literature review on previous work on driver models. We then talk about the available datasets used to perform such work, different models used (from classic regressions to neural networks) and finally present my approach and my results.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Koutentakis, Dimitrios.

Advisor dc:contributor.advisor

• Daniel Jackson.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

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

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/129895

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/129895