{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/110608"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/110608","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Continuous integration and testing for autonomous racing in simulation","abstract":"Self-driving autonomous vehicles (AVs) have recently gained in popularity as a research topic. The safety of AVs is exceptionally important as failure in the design of an AV could lead to catastrophic consequences. AV systems are highly heterogeneous with many different and complex components, so it is difficult to perform end-to-end testing. One solution to this dilemma is to evaluate AVs using simulated racing competition. In this thesis, we present a simulated autonomous racing competition, Generalized RAcing Intelligence Competition (GRAIC). To compete in GRAIC, participants need to submit their controller files which are deployed on a racing ego-vehicle on different race tracks. To evaluate the submitted controller, we also developed a testing pipeline, Autonomous System Operations (AsOps). AsOps is an automated, scalable, and fair testing pipeline developed using software engineering techniques such as continuous integration, containerization, and serverless computing. In order to evaluate the submitted controller in non-trivial circumstances, we populate the race tracks with scenarios, which are pre-defined traffic situations commonly seen in the real road. We present a dynamic scenario testing strategy that generates new scenarios based on the results of the ego-vehicle passing through previous scenarios.","abstract_html":"Self-driving autonomous vehicles (AVs) have recently gained in popularity as a research topic. The safety of AVs is exceptionally important as failure in the design of an AV could lead to catastrophic consequences. AV systems are highly heterogeneous with many different and complex components, so it is difficult to perform end-to-end testing. One solution to this dilemma is to evaluate AVs using simulated racing competition. In this thesis, we present a simulated autonomous racing competition, Generalized RAcing Intelligence Competition (GRAIC). To compete in GRAIC, participants need to submit their controller files which are deployed on a racing ego-vehicle on different race tracks. To evaluate the submitted controller, we also developed a testing pipeline, Autonomous System Operations (AsOps). AsOps is an automated, scalable, and fair testing pipeline developed using software engineering techniques such as continuous integration, containerization, and serverless computing. In order to evaluate the submitted controller in non-trivial circumstances, we populate the race tracks with scenarios, which are pre-defined traffic situations commonly seen in the real road. We present a dynamic scenario testing strategy that generates new scenarios based on the results of the ego-vehicle passing through previous scenarios.","abstract_has_math":false,"creators":["Jiang, Minghao"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Mitra, Sayan"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09-17T01:13:35Z","date_published":"2021-09-17T01:13:35Z","updated_at":"2026-07-22T22:24:52Z","subjects":["Self-driving autonomous vehicle","continuous integration and testing","simulated autonomous racing competition"],"languages":["en"],"rights":["Copyright 2021 Minghao Jiang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/110608","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mitra, Sayan"]},{"key":"dc:creator","label":"Author","values":["Jiang, Minghao"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-09-17T01:13:35Z","2021-04-30","2021-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Self-driving autonomous vehicle","continuous integration and testing","simulated autonomous racing competition"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Minghao Jiang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/110608"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Self-driving autonomous vehicles (AVs) have recently gained in popularity as a research topic. The safety of AVs is exceptionally important as failure in the design of an AV could lead to catastrophic consequences. AV systems are highly heterogeneous with many different and complex components, so it is difficult to perform end-to-end testing. One solution to this dilemma is to evaluate AVs using simulated racing competition. In this thesis, we present a simulated autonomous racing competition, Generalized RAcing Intelligence Competition (GRAIC). To compete in GRAIC, participants need to submit their controller files which are deployed on a racing ego-vehicle on different race tracks. To evaluate the submitted controller, we also developed a testing pipeline, Autonomous System Operations (AsOps). AsOps is an automated, scalable, and fair testing pipeline developed using software engineering techniques such as continuous integration, containerization, and serverless computing. In order to evaluate the submitted controller in non-trivial circumstances, we populate the race tracks with scenarios, which are pre-defined traffic situations commonly seen in the real road. We present a dynamic scenario testing strategy that generates new scenarios based on the results of the ego-vehicle passing through previous scenarios.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo terms","The student, Minghao Jiang, accepted the attached license on 2021-04-30 at 12:41.","The student, Minghao Jiang, submitted this Thesis for approval on 2021-04-30 at 14:08.","This Thesis was approved for publication on 2021-04-30 at 14:26.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16627 on 2021-09-16 at 16:49:49","Made available in DSpace on 2021-09-17T01:13:35Z (GMT). No. of bitstreams: 2 JIANG-THESIS-2021.pdf: 7492479 bytes, checksum: 46cd5bc9d71bf346a70497a30ae86542 (MD5) LICENSE.txt: 4210 bytes, checksum: 9bd61422be8a9aea4a72b51df9e606ce (MD5) Previous issue date: 2021-04-30"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Continuous integration and testing for autonomous racing in simulation"]}]}],"canonical_facts":{"dc:contributor":["Mitra, Sayan"],"dc:creator":["Jiang, Minghao"],"dc:date":["2021-09-17T01:13:35Z","2021-04-30","2021-05"],"dc:description":["Self-driving autonomous vehicles (AVs) have recently gained in popularity as a research topic. The safety of AVs is exceptionally important as failure in the design of an AV could lead to catastrophic consequences. AV systems are highly heterogeneous with many different and complex components, so it is difficult to perform end-to-end testing. One solution to this dilemma is to evaluate AVs using simulated racing competition. In this thesis, we present a simulated autonomous racing competition, Generalized RAcing Intelligence Competition (GRAIC). To compete in GRAIC, participants need to submit their controller files which are deployed on a racing ego-vehicle on different race tracks. To evaluate the submitted controller, we also developed a testing pipeline, Autonomous System Operations (AsOps). AsOps is an automated, scalable, and fair testing pipeline developed using software engineering techniques such as continuous integration, containerization, and serverless computing. In order to evaluate the submitted controller in non-trivial circumstances, we populate the race tracks with scenarios, which are pre-defined traffic situations commonly seen in the real road. We present a dynamic scenario testing strategy that generates new scenarios based on the results of the ego-vehicle passing through previous scenarios.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo terms","The student, Minghao Jiang, accepted the attached license on 2021-04-30 at 12:41.","The student, Minghao Jiang, submitted this Thesis for approval on 2021-04-30 at 14:08.","This Thesis was approved for publication on 2021-04-30 at 14:26.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16627 on 2021-09-16 at 16:49:49","Made available in DSpace on 2021-09-17T01:13:35Z (GMT). No. of bitstreams: 2 JIANG-THESIS-2021.pdf: 7492479 bytes, checksum: 46cd5bc9d71bf346a70497a30ae86542 (MD5) LICENSE.txt: 4210 bytes, checksum: 9bd61422be8a9aea4a72b51df9e606ce (MD5) Previous issue date: 2021-04-30"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/110608"],"dc:language":["en"],"dc:rights":["Copyright 2021 Minghao Jiang"],"dc:subject":["Self-driving autonomous vehicle","continuous integration and testing","simulated autonomous racing competition"],"dc:title":["Continuous integration and testing for autonomous racing in simulation"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:52Z"}