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Urban Computing with Taxicabs Yu Zheng Microsoft Research Asia.

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Presentation on theme: "Urban Computing with Taxicabs Yu Zheng Microsoft Research Asia."— Presentation transcript:

1 Urban Computing with Taxicabs Yu Zheng Microsoft Research Asia

2 Motivation Urban computing for Urban planning Developing countries: Urbanization and city planning Developed countries: Urban reconstruction, city renewal, and sub- urbanization Questions What’s wrong with the city configurations? Does a carried out urban planning really works?

3 GPS-equipped taxis are mobile sensors

4 RankCitiesCountry/RegionTaxicabs 1The Mexico cityMexico103,000+ 2BangkokThailand80,000+ 3SeoulSouth Korea73,000+ 4BeijingChina67,000 5TokyoJapan60,000 6ShanghaiChina50,000+ 7New York CityUSA48,300 8buenos airesArgentina45,000 9MoscowRussia40,000 (1000,000) 10St.PaulBrazil37,000 11TianjinChina35,000 12TaipeiTaiwan31,000+ 13New Taipei CityTaiwan23,500 14Singapore 23,000 15OsakaJapan20,000 16Hong KongChina18,000+ 17WuhanChina18,000 18LondonEngland17,000 19HarbinChina17,000 20GuangzhouChina16,000+ 21ShenyangChina15,000+ 22ParisFrance15,000

5 What We Do Detect flawed urban planning using taxi trajectories Evaluate the carried out city configurations Reminder city planners with the unrecognized problems Challenges City-wide traffic modeling Embodying flaws and reveal their relationship

6 Methodology Partition a city into regions with major roads

7 Methodology Partition the trajectory dataset into some portions TimeWork dayRest day Slot 17:00am-10:30am9:00am-12:30pm Slot 210:30am-4:00pm12:30pm-7:30pm Slot 34:00pm-7:30pm7:30pm-9:00am Slot 47:30pm-7:00am WorkdayRest day

8 Methodology Project taxi trajectories onto these regions Building a region graph for each time slot

9 Methodology

10

11 Formulate skyline graphs Mining frequent patterns To avoid false alert Deep understanding

12 Evaluations Datasets2009. 3-52010.3-6 Number of taxis29,28630,121 Effective days89116 Number of points Total679M1,730M Per taxi/day306528 Distance (KM) Total310M600M Per taxi/day128171 Average sampling rate (s)10074 Ave. dist. between two points (m)457349

13 WorkdaysRest Days 2009 2010

14 Some flaws occurring in 2009 disappeared Example 1: Two roads launched in late 2009 Results

15 Some flaws occurring in 2009 still exist in 2010 Example 1: Subway line 14 and 15 Results

16 Conclusion Video

17 Thanks! Yu Zheng http://research.microsoft.com/en-us/people/yuzheng/ The Released Dataset: T-Drive taxi trajectories A demo in the demo session on Sept. 20.


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