Genetically generated bionic driver models for autonomous road vehicles

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/304399
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2021-80 Shishir Gurushanthappa & Olle Lindgren.pdfMaster Thesis1.96 MBAdobe PDFView/Open
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dc.contributor.authorGurushanthappa, Shishir-
dc.contributor.authorLindgren, Olle-
dc.contributor.departmentChalmers tekniska högskola / Institutionen för mekanik och maritima vetenskapersv
dc.date.accessioned2021-12-10T12:28:29Z-
dc.date.available2021-12-10T12:28:29Z-
dc.date.issued2021sv
dc.date.submitted2020-
dc.identifier.urihttps://hdl.handle.net/20.500.12380/304399-
dc.description.abstractFor autonomous road vehicles, control is often divided into longitudinal and lateral control. This thesis focuses on lateral control driver models derived from a cognitive perspective. A genetic algorithm is used to generate driver models expressed in a domain-specific language. The project focuses on isolating perceptual cues. The objective function for the genetic algorithm is computed as the difference between the estimated steering angles and the observed steering angles in the vehicle. The recordings were captured from a Volvo XC90 driving a single scenario with an S-shaped test track at different speeds, and with different drivers. The resulting driver models are within 1-2 degrees of the recorded steering angles, and more significantly, the DSL sentences are very similar regardless of driver or speed, and stable between different runs. The project’s results show that the implementation of the genetically generated driver models is possible for lateral control. This genetic algorithm serves as a platform for the future inclusion of external factors affecting the dynamics of the vehicle. The identified model and parameters can be tested for representing a real-world driving case. Keywords:sv
dc.language.isoengsv
dc.relation.ispartofseries2021:80sv
dc.setspec.uppsokTechnology-
dc.subjectautonomous drivingsv
dc.subjectdomain-specific languagesv
dc.subjectgenetic programmingsv
dc.subjectgenetic algorithmsv
dc.subjectdriver modelssv
dc.subjectstochastic optimizationsv
dc.subjectautonomous road vehiclessv
dc.titleGenetically generated bionic driver models for autonomous road vehiclessv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH-
dc.contributor.examinerBenderius, Ola-
dc.contributor.supervisorBenderius, Ola-
dc.identifier.coursecodeMMSX30sv
Collection:Examensarbeten för masterexamen // Master Theses



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