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Title:Continuous integration and testing for autonomous racing in simulation
Author(s):Jiang, Minghao
Advisor(s):Mitra, Sayan
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Self-driving autonomous vehicle
continuous integration and testing
simulated autonomous racing competition
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.
Issue Date:2021-04-30
Type:Thesis
URI:http://hdl.handle.net/2142/110608
Rights Information:Copyright 2021 Minghao Jiang
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05


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