![\"tdrive_tdrive-t-drive-small\"](\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2010\/09\/tdrive_tdrive-t-drive-small-257x300.jpg\")
A\u00a0prototype has been built based on a\u00a0real-world trajectory dataset generated by 30,000 taxis in Beijing in\u00a0a period of 3 monthes.<\/p>\nThe service is available (within Microsoft corpnet), which\u00a0provides\u00a0a user\u00a0with the practically fastest path with less online computation and according to your departure time.<\/p>\n<\/div>\n
Three Challenges in T-Drive:<\/p>\n
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- Intelligence Modeling<\/li>\n
- Data sparseness<\/li>\n
- Low-sampling-rate of the trajectories<\/li>\n<\/ul>\n\t\n\t\t\t\t\t\n\t\t\t\t
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First, taxi drivers are experienced drivers who can usually find out the fastest path to send passengers to a destination based on their knowledge. Second, the GPS-equipped taxis are mobile sensors probing the traffic flows on road surfaces. So, the taxi trajectories contain the information of both human knowledge of experienced drivers and traffic patterns.<\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t
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\n\t\t\t\n\t\t\t\t<\/p>\nRefer to our T-Drive publication<\/a> on ACM SIGSPATIAL GIS 2010, which won the best paper runner up award and was featured on the homepage\u00a0MIT Technology review.<\/p>\n
1. landmark graph building<\/p>\n
2. Travel time estimation<\/p>\n
3. two-stage routing.<\/p>\n
![\"\"](\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/tdrive-methodology.jpg\")
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\n\t\t\t\n\t\t\t\t<\/p>\nWe evaluate the system with extensive experiments and in-the-field evaluations. The results show that our method signi cantly outperforms both the speed-constraint-based and the real-time-traffic-based method in the aspects of e ectiveness and efficiency. Given over 5 taxis in a region of 1km2, more than 60% of our routes are faster than that of the speed-constraint-based approach, and 50% of these routes are at least 20% faster than the latter. On average, our method can save about 16% of time for a trip, i.e., 5 minutes per 30-minutes driving.<\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t
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- “A driving route made just for you (opens in new tab)<\/span><\/a>“, MIT Technology Review, 2011.8.30. (Another Chinese version (opens in new tab)<\/span><\/a>).<\/li>\n
- Adding cabbie know-how to online maps (opens in new tab)<\/span><\/a>, Technology Review, news featured on the first page, 2010.11.6<\/li>\n
- Follow that cab! Racing Google Maps on city streets (opens in new tab)<\/span><\/a>, NewScientist, 2010.11.5<\/li>\n
- Microsoft aims to improve maps with GPS data from 33,000 Beijing cab drivers (opens in new tab)<\/span><\/a>, engadget, 2010.11.9<\/li>\n
- Cabbies help Microsoft Improve Online Mapping (opens in new tab)<\/span><\/a>, Wired, November 10, 2010.<\/li>\n<\/ul>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t
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- International Patent. MS 328341.01, MS1-4911US, “Route Computation Based on Route-Oriented Vehicle Trajectories”, 12\/28\/2009<\/li>\n
- US Patent. MS328342.01, MS1-4909US, “Map-Matching for Low-Sampling-Rate GPS Trajectories”, 12\/30\/2009<\/li>\n<\/ul>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t<\/div>\n\t\n","protected":false},"excerpt":{"rendered":"
T-drive is a smart driving direction services based on GPS trajectories of a large number of taxis. It helps user find out the practically fastest path to a destination at a given departure time. A\u00a0prototype has been built based on a\u00a0real-world trajectory dataset generated by 30,000 taxis in Beijing in\u00a0a period of 3 monthes. The […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556,13555],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-170558","msr-project","type-msr-project","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-search-information-retrieval","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2010-09-16","related-publications":[159101,160121,160255,161297,161298,161563,161600,161664,161748,162522,163177],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[],"msr_research_lab":[199560],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170558","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":3,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170558\/revisions"}],"predecessor-version":[{"id":391646,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170558\/revisions\/391646"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=170558"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=170558"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=170558"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=170558"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=170558"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
- Adding cabbie know-how to online maps (opens in new tab)<\/span><\/a>, Technology Review, news featured on the first page, 2010.11.6<\/li>\n
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