A rapid development of Connected Vehicle (CV) technology has been observed around the globe in the past decade. The problems that the conventional traffic management systems bear are believed to be able to be solved by introducing the technology. This CV technology puts diagnostic sensors onto vehicles/infrastructures and cause the data collected to be transmitted wirelessly between vehicles and nearby infrastructures. It would no longer rely on conventional data collection equipment, like loop detector or video detections, and it collects much more information than the conventional ways. Measurements that are previously unknown are available, which include, but are not be limited to, vehicle speeds, positions, arrival rates, rates of acceleration and deceleration, queue lengths, and stopped time. With this extra information, many applications are made possible. However, on the other hand, the accuracy and the stability of sensors cause challenges for the development of CV application, for instance, accuracy of GPS, communication delay, and LIDAR accuracy. These factors require special design embedded in those CV applications to accommodate the limitation of sensors. This special issue aims to serve as a major platform to facilitate the discussion and exchange of research ideas and technology development, encourage multidimension knowledge sharing, and enhance research activities in investigating sensors in Connected Vehicle technology.

This special issue solicits novel contributions on all aspects of theoretical and applied studies in sensors in Connected Vehicle technology. This special issue is open to the entire international research community.

Potential topics include but are not limited to the following:

• Vehicle platooning (truck or passenger vehicles) Cooperative Adaptive Cruise Control (CACC) considering sensors’ limitation
• Intelligent and adaptive signal control in urban networks using various CV sensors’ data
• Automated guided vehicles considering sensors’ limitation
• Big-data-enabled urban traffic system operation and optimization
• Mobile devices in smart transportation systems
• Intelligent monitoring of transportation systems
• Data collection, filtering, and distribution of traffic information
• Energy efficient operation and optimization using CV information