2019 IEEE Symposium Series on Computational Intelligence

IEEE Symposium Series on Computational Intelligence

December 6-9, 2019 Xiamen, China


IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (IEEE CIVTS)

The research and development of intelligent vehicles and transportation systems are rapidly growing worldwide. Intelligent transportation systems are making transformative changes in all aspects of surface transportation based on vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) connectivity, and automated driving (AV). In addition with the decreasing sensor costs and computer chips, and increasing computing power and data storage capacity, it has become practical to build a host of intelligent devices in cars that can be used in airbag control, unwelcome intrusion detection, collision warning and avoidance, power management and navigation, driver alertness monitoring etc. Computational intelligence plays a vital role in building all types and levels of intelligence in vehicle and transportation systems.
The objective of this symposium is to provide a forum for researchers and practitioners to present advanced research in computational intelligence with a focus on innovative applications to intelligent vehicle and transportation systems. This symposium seeks contribution on the latest developments and emerging research in all aspects of intelligent vehicle and transportation systems.


Specific topics for the symposium include, but are not limited to:

  • Advanced transportation information, communication and management systems
  • Air, road, and rail traffic management
  • Automated driving and driverless car
  • Cloud computing and big data in transportation and vehicle systems
  • Collision detection and avoidance
  • Connected vehicles of the future
  • Driver assistance and automation systems
  • Driver state detection and monitoring
  • Learning and adaptive Control
  • Multimodal intelligent transport systems and services
  • Object recognitions such as pedestrian detection, traffic sign detection and recognition
  • Personalized driver and traveler support systems
  • Pervasive and ubiquitous computing in logistics
  • Route guidance systems
  • Simulation and forecasting models
  • Spatio-temporal traffic pattern recognition
  • Trip modeling and driver speed prediction
  • Vehicle communications and connectivity
  • Vehicle fault diagnostics and health monitoring
  • Vehicle energy management and optimization in hybrid vehicles

Symposium Chairs

Yi Lu Murphey

University of Michigan-Dearborn, Dearborn, MI 48128, USA.



Justin Dauwels

Nanyang Technological University, Singapore



Dev Kochhar

Ford Motor Company



Yuanxiang Li

Shanghai Jiao Tong University,



Program Committee

To be announced