To facilitate the development of dynamic activity-based models for transport demand, the FEATHERS framework was developed. This framework suggests a four-stage development trajectory for a smooth transition from the four-step models toward static activity-based models in the short term and dynamic activity-based models in the long term. The development stages discussed in this paper range from an initial static activity-based model without traffic assignment to a dynamic activity-based model that incorporates rescheduling, learning effects, and traffic routing. To illustrate the FEATHERS framework, work that has been done on the development of static and dynamic activity-based models for Flanders (Belgium) and the Netherlands is discussed. First, the data collection is presented. Next, the four-stage activity-based model development trajectory is discussed in detail. The paper concludes with the presentation of the modular FEATHERS framework, which discusses the functionalities of the modules and how they accommodate the requirements imposed on the framework by each of the four stages.

Owing to their dynamic and multidisciplinary characteristics, Unmanned Aerial Vehicles (UAVs), or drones, have become increasingly popular. However, the civil applications of this technology, particularly for traffic data collection and analysis, still need to be thoroughly explored. For this purpose, the authors previously proposed a detailed methodological framework for the automated UAV video processing in order to extract multi-vehicle trajectories at a particular road segment. In this paper, however, the main emphasis is on the comprehensive analysis of vehicle trajectories extracted via a UAV-based video processing framework. An analytical methodology is presented for: (i) the automatic identification of flow states and shockwaves based on processed UAV trajectories, and (ii) the subsequent extraction of various traffic parameters and performance indicators in order to study flow conditions at a signalized intersection. The experimental data to analyze traffic flow conditions was obtained in the city of Sint-Truiden, Belgium. The generation of simplified trajectories, shockwaves, and fundamental diagrams help in analyzing the interrupted-flow conditions at a signalized four-legged intersection using UAV-acquired data. The analysis conducted on such data may serve as a benchmark for the actual traffic-specific applications of the UAV-acquired data. The results reflect the value of flexibility and bird-eye view provided by UAV videos; thereby depicting the overall applicability of the UAV-based traffic analysis system. The future research will mainly focus on further extensions of UAV-based traffic applications.