Social Transportation Systems

STS-TC Co-chairs and contacts (since 2014)


  • Zhiming Ding (, Beijing University of Technology, P.R.China.


  • Wei Chen, Zhejiang (, P.R.China.
  • Pu Wang, ( Central South University, P.R.China.

Short description of STS-TC

The ubiquity of mobile communication devices and the prosperity of location-based services are turning people and devices into ubiquitous social sensors for transportation. People experiencing traffic events can publish social media on transportation in real time, such as microblogs, images and videos. Various sensors equipped in mobile devices can uninterruptedly sense vast clues on urban dynamics. However, designing approaches and tools to leverage comprehensive social media and sensed data to enable intelligent transportations brings a unique set of research and engineering challenges. Social transportation (ST) is the study of how these changing research and engineering challenges lead to new explorations into intelligent transportation systems. Social transportation is the science and technology of data-driven, real-time, and situation-aware transportation foundation facilitated within a crowd sourcing context. Social transportation extends intelligent transportation to the cyber-physical-social system context and aims to empower traffic and transportation systems with insights and decisions derived from real-time social and physical data. Compared with traditional sensor-based transportation systems, social transportation emphasizes real-time computing and embedded applications in transportation systems with online and interactive big data at faster speed and lower cost.

The IEEE-ITSS committee on social transportation aims to address issues related to the representation, computing, communication, control, analysis and applications of social transportation in traffic and transportation systems. The technical topics include but not limited to:

Fundamental issues of social transportation theories and approaches, like crowd sensing, natural language processing, data mining, visualization, and web-based agent technology;

Real experiences with designing, building, deploying and evaluating social transportation systems, like location based services (LBS), decision-based services (DBS), and intelligence-based services (IBS);

Real-world applications describing cases of social transportation, and useful knowledge for solving traffic problems or improving the transportation performance.

Work Plan for 2017

Organize the workshop of social transportation in ITSC 2017.

A technical demonstration of traffic data collection and traffic sensing platform based on social media data in the city of Shenzhen.

A technical demonstration for driver source prediction platform for the city of Shenzhen.

Committee Members List

  • Dr. Long Chen,, Faculty of Science and Technology, University of Macau
  • Dr. Yisheng Lv,, Institute of Automation, Chinese Academy of Sciences
  • Dr. Hong Mo,, College of Electric and Information Engineering, Changsha University of Science and Technology
  • Dr. Lai Tu,, School of Electronics Information and Communications, Huazhong University of Science and Technology
  • Dr. Xiao Wang,, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
  • Dr. Fan Zhang,, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
  • Dr. Qingpeng Zhang,, Department of Systems Engineering and Engineering Management, City University of Hong Kong
  • Dr. Fenghua Zhu,, Institute of Automation, Chinese Academy of Sciences