{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/saferoute-learning-to-navigate-streets-safely","title":"SafeRoute: Learning to Navigate Streets Safely in an Urban Environment","arxiv_id":"1811.01147","date":"2018-11-03","proceeding":null,"authors":["Sharon Levy","Wenhan Xiong","Elizabeth Belding","William Yang Wang"],"abstract":"Recent studies show that 85% of women have changed their traveled route to\navoid harassment and assault. Despite this, current mapping tools do not\nempower users with information to take charge of their personal safety. We\npropose SafeRoute, a novel solution to the problem of navigating cities and\navoiding street harassment and crime. Unlike other street navigation\napplications, SafeRoute introduces a new type of path generation via deep\nreinforcement learning. This enables us to successfully optimize for\nmulti-criteria path-finding and incorporate representation learning within our\nframework. Our agent learns to pick favorable streets to create a safe and\nshort path with a reward function that incorporates safety and efficiency.\nGiven access to recent crime reports in many urban cities, we train our model\nfor experiments in Boston, New York, and San Francisco. We test our model on\nareas of these cities, specifically the populated downtown regions where\ntourists and those unfamiliar with the streets walk. We evaluate SafeRoute and\nsuccessfully improve over state-of-the-art methods by up to 17% in local\naverage distance from crimes while decreasing path length by up to 7%.","url_abs":"http://arxiv.org/abs/1811.01147v1","url_pdf":"http://arxiv.org/pdf/1811.01147v1.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":"saferoute-learning-to-navigate-streets-safely","repo_url":"https://github.com/sharonlevy/SafeRoute","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"task_slug":"navigate","task_name":"Navigate"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}