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This paper proposes a hybrid target selection model combining a lightweight long short-term memory (LSTM) based deep learning classifier and rule-based methods. Key input features are identified and processed to enhance training. The LSTM model is validated for accuracy and efficiency against bidirectional LSTM (Bi-LSTM) variations. Compared to the single approach, the hybrid model integrates the LSTM classifier and rule-based methods with a synthesizer, demonstrating improved accuracy, better interpretability, and a potentially higher functional safety level. Integrated into TDA4VM, the hybrid model shows timely and complementary target selection performance in actual urban and highway tests with low computation costs, proving its theoretical value and engineering prospects.<\/jats:p>","DOI":"10.1145\/3716631","type":"journal-article","created":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T09:09:50Z","timestamp":1739005790000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["A Hybrid Target Selection Model of Functional Safety Compliance for Autonomous Driving System"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7185-4607","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"first","affiliation":[{"name":"School of Vehicle and Mobility, Tsinghua University, Beijing, China and Automotive Autonomous Driving Techniques, UISEE (Shanghai) Automotive Technologies LTD., Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8619-0234","authenticated-orcid":false,"given":"Zihan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China and Automotive Autonomous Driving Techniques, UISEE (Shanghai) Automotive Technologies LTD., Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8681-7067","authenticated-orcid":false,"given":"Mengchi","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Vehicle and Mobility, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8516-1185","authenticated-orcid":false,"given":"Qing","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Vehicle and Mobility, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9333-7416","authenticated-orcid":false,"given":"Keqiang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Vehicle and Mobility, Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,2,21]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"NTSB. 2018. 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