Archives and Documentation Center
Digital Archives

Risk assessment of autonomous vehicle using Markov decision process

Show simple item record

dc.contributor Graduate Program in Industrial Engineering.
dc.contributor.advisor Güllü, Refik.
dc.contributor.author Derecik, Burak.
dc.date.accessioned 2023-03-16T10:30:01Z
dc.date.available 2023-03-16T10:30:01Z
dc.date.issued 2020.
dc.identifier.other IE 2020 D47
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/13438
dc.description.abstract Autonomous decision making of intelligent vehicle is one of the most critical and challenging module due to the fact that traffic of real world is uncertain, complex, continuous and vehicles interact with each other. In this thesis, a decision making based on reinforcement learning algorithms is proposed to represent ego vehicle behaviors interacting with the stochastic behaviors of the environmental vehicles in highway traffic. The presented solver algorithms are formulated as Markov Decision Process (MDP) for autonomous vehicle problems. Proposed algorithms are implemented in a simulation environment so that they are tested and analyzed with different scenarios. Then, efficiency of different imple mented algorithms are compared based on specified criteria. The simulation results of tested scenarios show that ego car is capable of lane change and accelerate or deceler ate in order to perform safe driving without any collision with other cars which have uncertain behavior in highway
dc.format.extent 30 cm.
dc.publisher Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020.
dc.subject.lcsh Automated vehicles.
dc.subject.lcsh Automobiles -- Automatic control.
dc.title Risk assessment of autonomous vehicle using Markov decision process
dc.format.pages xv, 73 leaves ;


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Digital Archive


Browse

My Account