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A recently proposed third paradigm, direct perception, aims to\ncombine the advantages of both by using a neural network to learn appropriate\nlow-dimensional intermediate representations. However, existing direct\nperception approaches are restricted to simple highway situations, lacking the\nability to navigate intersections, stop at traffic lights or respect speed\nlimits. In this work, we propose a direct perception approach which maps video\ninput to intermediate representations suitable for autonomous navigation in\ncomplex urban environments given high-level directional inputs. Compared to\nstate-of-the-art reinforcement and conditional imitation learning approaches,\nwe achieve an improvement of up to 68 % in goal-directed navigation on the\nchallenging CARLA simulation benchmark. In addition, our approach is the first\nto handle traffic lights and speed signs by using image-level labels only, as\nwell as smooth car-following, resulting in a significant reduction of traffic\naccidents in simulation.","url_abs":"http://arxiv.org/abs/1806.06498v3","url_pdf":"http://arxiv.org/pdf/1806.06498v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"conditional-affordance-learning-for-driving","repo_url":"https://github.com/xl-sr/CAL","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"autonomous-navigation","task_name":"Autonomous Navigation"},{"task_slug":"imitation-learning","task_name":"Imitation Learning"},{"task_slug":"navigate","task_name":"Navigate"}],"methods":[{"method_slug":"carla","method_name":"CARLA"},{"method_slug":"entropy-regularization","method_name":"Entropy Regularization"},{"method_slug":"ppo","method_name":"PPO"},{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.06498","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1806.06498"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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