Transportation systems play a vital role in the development of countries. Advancements in ICT have provided novel opportunities in the transport sector for developing Intelligent Transportation Systems (ITS). An ITS includes all modes of telematics and provides integrated dynamically interacting multi-model communication systems between people (e.g., driver and user), vehicles (e.g., V2V), and infrastructure (e.g., V2I) to achieve enhanced safety and mobility while reducing the environmental impacts of transportation. The ITS focuses on four basic principles – sustainability, safety, integration, and responsiveness – to achieve prime objectives of ITS: access and mobility, environmental sustainability, and economic development.

Information is at the core of ITS, including static and real-time traffic data. The success of ITS depends on the collection, processing, integration, and supply of information. Researchers have presented several manifestations to extract and communicate information in ITS with sensor technology being used as main component. Governments, the automotive industry, and research community have developed propositions by fabricating sensors in-road and in-vehicle to ensure safety, comfort, and performance. A modern vehicle has several in-vehicle sensors (e.g., GPS, RADAR, microphone, video camera, ultrasonic, pressure, infrared, etc.) to provide information for applications including improving a vehicle’s performance and enhancing driving experience. The in-road sensors (e.g., traffic camera, Doppler radar, etc.) located on roadsides in transportation networks and smart cities provide information for novel services to drivers such as smart parking and reducing pricing according to congestion levels. However, theses propositions have disadvantages of high installation cost, traffic disruption during installation, maintenance, and repair, which can prevent the large-scale deployment of real-time traffic monitoring and control. Wireless sensor networks and IoT provide opportunities to connect in-vehicle and in-road sensors in a network and provide sensors to capture real-time traffic, road, and environmental data in multi-model vehicle-to-vehicle and vehicle-to-infrastructure paradigms. The enormous data generated by sensors needs processing, maintenance, and intelligent utilization. AI-based machine learning techniques can exploit sensors data science and analytics to provide autonomous transportation for benefits of green vehicles, decreasing vehicle accidents, effective traffic design and management, reducing pollution emission, and effective traffic analysis. Therefore, developments in both sensing material (i.e., precision, functionality, durability, and energy consumption) and data management (i.e., collecting, processing, sharing, and providing valuable information) in ITS are serious challenges and have been of great interest to researchers in recent years.

The purpose of this Special Issue is to serve as an outlet for disseminating in-vehicle, in-road, and IoT sensors design and sensors-based innovative solutions towards meeting the expectations of ITS. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Novel sensor-based ITS architectures with type, number, and positioning of sensors
• Low power/low-cost design for ITS sensors
• Sensor structure design using energy harvesting principles for power management in ITS
• Next-generation CMOS circuit design for ITS sensors
• Sensor design for low-power edge computing and IoT applications in ITS
• Smart sensors and wearable sensors design for ITS
• Sensor signal and data processing (validation, selection, and feature extraction) techniques and algorithms based on data driven, knowledge-based, or hybrid approach for real-time sensors data in ITS
• Sensor modeling and simulation for improved ITS
• Challenges and opportunities associated with sensors for accessible, sustainable, and economical ITS
• Sensor data fusion and distribution platforms for ITS
• The role and use of Internet-of-Things (IoT), expert systems, cloud computing, blockchain, and big data technologies in ITS
• Sensors and real-time sensing for AI-based autonomous vehicles and AI usage in ITS
• Emerging sensors-based automotive embedded systems technologies for ITS
• Sensors networks optimization and improving QoS for autonomous vehicle perception in ITS
• Surveys and original contributions about feasibility and applications of sensors and sensors data for supporting smart mobility solutions in ITS real applications