The ThirdWorkshop on Data-driven Intelligent Transportation

被引:0
|
作者
Wei, Hua [1 ]
Sheron, Guni [2 ]
Wu, Cathy [3 ]
Chawla, Sanjay [4 ]
Li, Zhenhui [5 ]
机构
[1] New Jersey Inst Technol, Newark, NJ 07102 USA
[2] Texas A&M Univ, College Stn, TX USA
[3] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[4] Qatar Comp Res Inst, Doha, Qatar
[5] Yunqi Acad Engn, Hangzhou, Peoples R China
关键词
Transportation; spatio-temporal data mining; urban computing;
D O I
10.1145/3511808.3557496
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traffic is the pulse of the city. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Intelligent transportation enables the city to function in a more efficient and effective way. A wide range of city data become increasingly available, such as taxi trips, surveillance camera data, human mobility data from mobile phones or location-based services, events from social media, car accident reports, bike-sharing information, Points-Of-Interest, traffic sensors, public transportation data, and many more. This abundance of data poses a grand challenge to the CIKM research community: How to utilize such data toward city intelligence, across various transportation tasks? The 3rd workshop of "Data-driven Intelligent Transportation" welcomes articles and presentations in the areas of transportation systems, data mining, and artificial intelligence, conveying new advances and developments in theory, modeling, simulation, testing, case studies, as well as large-scale deployment.
引用
收藏
页码:5177 / 5178
页数:2
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