{"id":160255,"date":"2010-10-26T00:00:00","date_gmt":"2010-10-26T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/drive-smartly-as-a-taxi-driver\/"},"modified":"2018-10-16T20:13:56","modified_gmt":"2018-10-17T03:13:56","slug":"drive-smartly-as-a-taxi-driver","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/drive-smartly-as-a-taxi-driver\/","title":{"rendered":"Drive smartly as a taxi driver"},"content":{"rendered":"<div class=\"asset-content\">\n<p>GPS-equipped taxis are mobile sensors probing the traffic flow on road surfaces, and taxi drivers are experienced drivers who can usually find out the fastest path to a destination based on their knowledge. In this demo, we provide a user with the practically fastest path to a destination at a given departure time in terms of taxi drivers\u2019 intelligence mined from historical GPS trajectories of taxis. We build our system, called T-Drive, by using a real trajectory dataset generated by over 33,000 taxis in a period of 3 months, and conduct both synthetic experiments and in-the-field evaluations. As a result, our method outperforms the real-time-traffic-based (RT) and the speed-constraint-based (SC) approaches in both efficiency and effectiveness.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>GPS-equipped taxis are mobile sensors probing the traffic flow on road surfaces, and taxi drivers are experienced drivers who can usually find out the fastest path to a destination based on their knowledge. In this demo, we provide a user with the practically fastest path to a destination at a given departure time in terms [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-160255","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"UIC 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