{"id":170558,"date":"2010-09-16T23:38:30","date_gmt":"2010-09-16T23:38:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/t-drive-driving-directions-based-on-taxi-traces\/"},"modified":"2017-06-19T13:28:23","modified_gmt":"2017-06-19T20:28:23","slug":"t-drive-driving-directions-based-on-taxi-traces","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/t-drive-driving-directions-based-on-taxi-traces\/","title":{"rendered":"T-Drive: Driving Directions based on Taxi Traces"},"content":{"rendered":"<p class=\"asset-content\">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.<\/p>\n<p class=\"asset-content\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-216190 alignright\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2010\/09\/tdrive_tdrive-t-drive-small-257x300.jpg\" alt=\"tdrive_tdrive-t-drive-small\" width=\"257\" height=\"300\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2010\/09\/tdrive_tdrive-t-drive-small-257x300.jpg 257w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2010\/09\/tdrive_tdrive-t-drive-small.jpg 500w\" sizes=\"(max-width: 257px) 100vw, 257px\" \/>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>\n<div id=\"en-usprojectstdrivedefault\" class=\"page-content\">\n<p>The 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<p>Three Challenges in T-Drive:<\/p>\n<ul>\n<li>Intelligence Modeling<\/li>\n<li>Data sparseness<\/li>\n<li>Low-sampling-rate of the trajectories<\/li>\n<\/ul>\n\t\t\t<div class=\"moray-accordion\" data-show=\"false\">\n\t\t\t\t\t\t\t<div class=\"clearfix\">\n\t\t\t\t\t<div\n\t\t\t\t\t\tclass=\"btn-group align-items-center mb-g float-sm-right\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\tdata-mount=\"collapse-controls\"\n\t\t\t\t\t\tdata-bi-aN=\"accordion-collapse-controls\"\n\t\t\t\t\t\tdata-target=\"#accordion-1\">\n\t\t\t\t\t\t<button class=\"btn btn-link m-0\" aria-disabled=\"false\" aria-pressed=\"false\" data-action=\"expand\" type=\"button\" data-bi-cN=\"Expand all\">Expand all<\/button>\n\t\t\t\t\t\t<span aria-hidden=\"true\"> | <\/span>\n\t\t\t\t\t\t<button class=\"btn btn-link m-0\" aria-disabled=\"false\" aria-pressed=\"false\" data-action=\"collapse\" type=\"button\" data-bi-cN=\"Collapse all\">Collapse all<\/button>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<ul class=\"accordion\" id=\"accordion-1\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li class=\"m-0\">\n\t\t\t<h4 class=\"accordion-header\">\n\t\t\t\t<button\n\t\t\t\t\tclass=\"btn btn-collapse m-0\"\n\t\t\t\t\ttype=\"button\"\n\t\t\t\t\tdata-mount=\"collapse\"\n\t\t\t\t\tdata-target=\"#collapse-2\"\n\t\t\t\t\taria-expanded=\"false\"\n\t\t\t\t\taria-controls=\"collapse-2\">\n\t\tMotivation\t\t\t\t<\/button>\n\t\t\t<\/h4>\n\t\t\t<div class=\"collapse\" id=\"collapse-2\">\n\t\t\t\t<div class=\"accordion-body\">\n\t\t\t\t\t\t\t\t\t\t<p>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\t<\/div>\n\t\t\t<\/div>\n\t\t<\/li>\n\t\t\t\t\t\t<li class=\"m-0\">\n\t\t\t<h4 class=\"accordion-header\">\n\t\t\t\t<button\n\t\t\t\t\tclass=\"btn btn-collapse m-0\"\n\t\t\t\t\ttype=\"button\"\n\t\t\t\t\tdata-mount=\"collapse\"\n\t\t\t\t\tdata-target=\"#collapse-3\"\n\t\t\t\t\taria-expanded=\"false\"\n\t\t\t\t\taria-controls=\"collapse-3\">\n\t\tMethodology\t\t\t\t<\/button>\n\t\t\t<\/h4>\n\t\t\t<div class=\"collapse\" id=\"collapse-3\">\n\t\t\t\t<div class=\"accordion-body\">\n\t\t\t\t\t\t\t\t\t\t<\/p>\n<p>Refer to our <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/t-drive-driving-directions-based-on-taxi-trajectories\/\">T-Drive publication<span class=\"sr-only\"> (opens in new tab)<\/span><\/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<p>1. landmark graph building<\/p>\n<p>2. Travel time estimation<\/p>\n<p>3. two-stage routing.<\/p>\n<p><span id=\"de2c9628-5f71-4002-a4bf-5c366fbe315d\" class=\"ImageBlock fn\"><img decoding=\"async\" id=\"Imagede2c9628-5f71-4002-a4bf-5c366fbe315d\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/tdrive-methodology.jpg\" alt=\"\" \/><span id=\"ImageCaptionde2c9628-5f71-4002-a4bf-5c366fbe315d\" class=\"ImageCaptionCoreCss ImageCaption\"><\/span><\/span><\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/li>\n\t\t\t\t\t\t<li class=\"m-0\">\n\t\t\t<h4 class=\"accordion-header\">\n\t\t\t\t<button\n\t\t\t\t\tclass=\"btn btn-collapse m-0\"\n\t\t\t\t\ttype=\"button\"\n\t\t\t\t\tdata-mount=\"collapse\"\n\t\t\t\t\tdata-target=\"#collapse-4\"\n\t\t\t\t\taria-expanded=\"false\"\n\t\t\t\t\taria-controls=\"collapse-4\">\n\t\tResults\t\t\t\t<\/button>\n\t\t\t<\/h4>\n\t\t\t<div class=\"collapse\" id=\"collapse-4\">\n\t\t\t\t<div class=\"accordion-body\">\n\t\t\t\t\t\t\t\t\t\t<\/p>\n<p>We 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\t<\/div>\n\t\t\t<\/div>\n\t\t<\/li>\n\t\t\t\t\t\t<li class=\"m-0\">\n\t\t\t<h4 class=\"accordion-header\">\n\t\t\t\t<button\n\t\t\t\t\tclass=\"btn btn-collapse m-0\"\n\t\t\t\t\ttype=\"button\"\n\t\t\t\t\tdata-mount=\"collapse\"\n\t\t\t\t\tdata-target=\"#collapse-5\"\n\t\t\t\t\taria-expanded=\"false\"\n\t\t\t\t\taria-controls=\"collapse-5\">\n\t\tNews\t\t\t\t<\/button>\n\t\t\t<\/h4>\n\t\t\t<div class=\"collapse\" id=\"collapse-5\">\n\t\t\t\t<div class=\"accordion-body\">\n\t\t\t\t\t\t\t\t\t\t<ul>\n<li>&#8220;<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.technologyreview.com\/communications\/38454\/?a=f\">A driving route made just for you<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>&#8220;, MIT Technology Review, 2011.8.30. (Another <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.mittrchinese.com\/\/single.php?p=137609\">Chinese version<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>).<\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.technologyreview.com\/computing\/26686\/?p1=A2\">Adding cabbie know-how to online maps<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Technology Review, news featured on the first page, 2010.11.6<\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.newscientist.com\/article\/dn19703-follow-that-cab-racing-google-maps-on-city-streets.html\">Follow that cab! Racing Google Maps on city streets<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, NewScientist, 2010.11.5<\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.engadget.com\/2010\/11\/09\/microsoft-aims-to-improve-maps-with-gps-data-from-33-000-beijing\/\">Microsoft aims to improve maps with GPS data from 33,000 Beijing cab drivers<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, engadget, 2010.11.9<\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.wired.com\/autopia\/2010\/11\/cabbies-help-microsoft-improve-online-mapping\/\">Cabbies help Microsoft Improve Online Mapping<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Wired, November 10, 2010.<\/li>\n<\/ul>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/li>\n\t\t\t\t\t\t<li class=\"m-0\">\n\t\t\t<h4 class=\"accordion-header\">\n\t\t\t\t<button\n\t\t\t\t\tclass=\"btn btn-collapse m-0\"\n\t\t\t\t\ttype=\"button\"\n\t\t\t\t\tdata-mount=\"collapse\"\n\t\t\t\t\tdata-target=\"#collapse-6\"\n\t\t\t\t\taria-expanded=\"false\"\n\t\t\t\t\taria-controls=\"collapse-6\">\n\t\tPatents\t\t\t\t<\/button>\n\t\t\t<\/h4>\n\t\t\t<div class=\"collapse\" id=\"collapse-6\">\n\t\t\t\t<div class=\"accordion-body\">\n\t\t\t\t\t\t\t\t\t\t<ul>\n<li>International Patent. MS 328341.01, MS1-4911US, &#8220;Route Computation Based on Route-Oriented Vehicle Trajectories&#8221;, 12\/28\/2009<\/li>\n<li>US Patent. MS328342.01, MS1-4909US, &#8220;Map-Matching for Low-Sampling-Rate GPS Trajectories&#8221;, 12\/30\/2009<\/li>\n<\/ul>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t<\/div>\n\t\t\n","protected":false},"excerpt":{"rendered":"<p>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 [&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":""},"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":[161664,161748,162522,163177,159101,160121,160255,161297,161298,161563,161600],"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"}],"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}]}}