Transport engineering has become an increasingly important discipline in the engineering domain. Traffic flow theory is the foundation of most transport engineering studies. Moreover, the analysis of traffic flow is also the core of transport system analysis. The traditional traffic flow data used in modeling and validating traffic flow models are mainly loop detector data (fixed locations) and floating vehicle data (fixed vehicles), which are at relatively low resolution.

With the new advances of traffic data collection, Bluetooth data, social media data, smartphone data, global positioning system (GPS) data, machine vision data, vehicle to vehicle/infrastructure communication, and other sensor-based data, collecting high-resolution vehicle trajectories on a large scale becomes realistic, which provides an unprecedented opportunity for researchers to scrutinize vehicle movements, pinpoint locations of conflicts and disturbances, and fully describe tempo-spatial evolution of traffic flow dynamics and measure its impact on road safety. In this regard, it is with a high need to explore the role that new advances in data collection and analytics can play in improving the performance of traffic flow models and traffic operations. With increasing high-resolution traffic and transport data, traffic flow models, and transport system analysis can be revolutionized and informed.

The aim of this Special Issue is to collate original research articles and review articles discussing the recent progress and advances in this area of research, with an attempt to benefit research communities and practitioners. This Special Issue also solicits novel contributions on all aspects of theoretical and/or applied research in data-informed traffic flow modeling and traffic operations.

Potential topics include but are not limited to the following:

• Application of big data for traffic flow model development
• Applications of big data for improving transport system operations
• Adopting advanced data analytics for traffic flow development
• Adopting advanced data analytics for improving traffic operations
• Multiple-type data analytics and bottleneck treatment
• Multiple-type data analytics and freeway operations
• Application of sensor data to smooth traffic flow dynamics
• Applications of vehicle to vehicle/infrastructure data
• Multiple-type data analytics and transit system operations
• Data-informed transport network modelling