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While model\u2010based planning has demonstrated reliability, it is beneficial to incorporate human demonstrations and align the results with human behaviors. This work aims at bridging the gap between model\u2010based planning and driver imitation by proposing a constraint imitative trajectory planning method (CITP). CITP integrates artificial potential field and dynamic movement primitives, which have achieved both the ability to imitate human demonstrations as well as ensure safety constraints. During the planning process, CITP first encodes human demonstrations, local driving target, and traffic obstacles as attractive or repulsive effects, and then the trajectory planning problem is solved through model predictive optimization. To address the dynamics of traffic scenarios, a hierarchical planning strategy is proposed based on the division of planning process. CITP is designed with five modules, including LSTM\u2010based target generation, encoding attractive and repulsive effects with target, demonstrations and obstacles, and trajectory planning with model predictive optimization. Data collection and experiments are carried out based on CARLA driving simulator, and the effectiveness in terms of both safety and consistency with human behavior are reported.<\/jats:p>","DOI":"10.1002\/aisy.202300269","type":"journal-article","created":{"date-parts":[[2023,8,20]],"date-time":"2023-08-20T17:10:04Z","timestamp":1692551404000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Safe and Human\u2010Like Trajectory Planning of Self\u2010Driving Cars: A Constraint Imitative Method"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1884-0641","authenticated-orcid":false,"given":"Mingyang","family":"Cui","sequence":"first","affiliation":[{"name":"School of Vehicle and Mobility Tsinghua University  Beijing 100084 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingbai","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Informatics Technical University of Munich  85748 Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaobing","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Vehicle and Mobility Tsinghua University  Beijing 100084 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4363-6108","authenticated-orcid":false,"given":"Jianqiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Vehicle and Mobility Tsinghua University  Beijing 100084 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenshan","family":"Bing","sequence":"additional","affiliation":[{"name":"Department of Informatics Technical University of Munich  85748 Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boqi","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering University of Michigan  Ann Arbor MI 48105 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alois","family":"Knoll","sequence":"additional","affiliation":[{"name":"Department of Informatics Technical University of Munich  85748 Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,8,16]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/aisy.202100211"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2913998"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3002505"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3144867"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3127219"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2477355"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3150748"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2021.3131141"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20255"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2021.3123341"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3008284"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2019.2898599"},{"key":"e_1_2_9_14_1","volume-title":"NVIDIA White Paper","author":"Nist\u00e9r D.","year":"2019"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12507"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3188662"},{"key":"e_1_2_9_17_1","doi-asserted-by":"crossref","unstructured":"M.Cui H.Wu X.Zhao Q.Xu J.Wang in2020 4th CAA Int. 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