Intelligent Transportation Systems (ITS) have achieved an immense positive impact on transportation in modern cities. These systems can be designed to, for example, increase safety, improve traffic management operations, reduce shipping costs, enhance information services, and protect infrastructure. They process huge amounts of data that are collected by a versatile set of sensors, extracting a lot of different traffic-related information.
One way to collect traffic data is by using smartphones. Smartphones offer many options for collecting, saving, and processing data with a user-friendly interface. In particular, many established methods within data mining, artificial intelligence (AI), and the Internet of Things (IoT) have been proposed to solve sensing, networking, and signal processing problems that show up in transportation applications. Additionally, one may make use of knowledge from disciplines such as civil engineering, electrical engineering, communication, computer science, statistics, and psychology. The purpose of this special issue is to provide a link between academia and industry by focusing on modern AI algorithms applied to data collected from smartphone-embedded sensors to show how smartphones can improve safety and mobility in transportation. Papers that present reviews or experiment results on smartphone data by different AI technologies, or theoretical topics related to improving transportation issues, are welcome.

Aims and Scope:

1. Smartphone Applications in Transportation
2. Intelligent Transportation Systems based on Smartphones
3. Smartphone Data Mining
4. Smartphone Sensors Fusion
5. Traffic monitoring by smartphones
6. Incident detection by smartphones
7. Road Quality Assessment
8. Maneuvers Recognition
9. Driving Style Evaluation
10. Driving Score Prediction