{"id":1770,"date":"2024-07-29T08:47:40","date_gmt":"2024-07-29T07:47:40","guid":{"rendered":"https:\/\/babel.isa.uma.es\/kipr\/?p=1770"},"modified":"2024-07-29T08:47:40","modified_gmt":"2024-07-29T07:47:40","slug":"rl-to-learn-the-coordination-of-different-goals-in-autonomous-driving","status":"publish","type":"post","link":"https:\/\/babel.isa.uma.es\/kipr\/?p=1770","title":{"rendered":"RL to learn the coordination of different goals in autonomous driving"},"content":{"rendered":"

J. Liu, J. Yin, Z. Jiang, Q. Liang and H. Li, Attention-Based Distributional Reinforcement Learning for Safe and Efficient Autonomous Driving,<\/strong> IEEE Robotics and Automation Letters, vol. 9, no. 9, pp. 7477-7484, Sept. 2024 DOI: 10.1109\/LRA.2024.3427551<\/a>.<\/h4>\n

Autonomous driving vehicles play a critical role in intelligent transportation systems and have garnered considerable attention. Currently, the popular approach in autonomous driving systems is to design separate optimal objectives for each independent module. Therefore, a major concern arises from the fact that these diverse optimal objectives may have an impact on the final driving policy. However, reinforcement learning provides a promising solution to tackle the challenge through joint training and its exploration ability. This letter aims to develop a safe and efficient reinforcement learning approach with advanced features for autonomous navigation in urban traffic scenarios. Firstly, we develop a novel distributional reinforcement learning method that integrates an implicit distribution model into an actor-critic framework. Subsequently, we introduce a spatial attention module to capture interaction features between the ego vehicle and other traffic vehicles, and design a temporal attention module to extract the long-term sequential feature. Finally, we utilize bird’s-eye-view as a context-aware representation of traffic scenarios, fused by the above spatio-temporal features. To validate our approach, we conduct experiments on the NoCrash and CoRL benchmarks, especially on our closed-loop openDD scenarios. The experimental results demonstrate the impressive performance of our approach in terms of convergence and stability compared to the baselines.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"

J. Liu, J. Yin, Z. Jiang, Q. Liang and H. Li, Attention-Based Distributional Reinforcement Learning for Safe and Efficient Autonomous …<\/span> Read More →<\/span><\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14],"tags":[248,150],"class_list":["post-1770","post","type-post","status-publish","format-standard","hentry","category-applications-of-reinforcement-learning-to-robots","tag-autonomous-vehicles","tag-behaviour-based-architectures"],"_links":{"self":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1770"}],"collection":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1770"}],"version-history":[{"count":1,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1770\/revisions"}],"predecessor-version":[{"id":1771,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1770\/revisions\/1771"}],"wp:attachment":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1770"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1770"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1770"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}