In the past five years, Hoogendoorn’s research has involved i) theory, modelling, and simulation of multi-class traffic and transportation networks; ii) development of methods for integrated control of these networks (regional network management, crowd management); iii) impact of uncertainty of travel behaviour and network operations; iv) impact of ICT (information, driver support, etc.) on network flow operations, and v) fundamentals of traffic network dynamics. In all these topics, his work has focussed on both recurrent for recurrent and non-recurrent (emergency) situations.
He has focussed on innovative approaches to collect detailed, microscopic traffic data and the use of these data to underpin the models and theories that he has developed (VIDI grant). Microscopic traffic data are collected from an airborne platform using advanced video techniques, resulting in a new generic theory of driving behaviour, with as key elements driver adaptation, inter-driver heterogeneity, and multi-vehicle anticipation, as well as new insights into the key differences in driving behaviour in case of normal and non-recurrent conditions; additional evidence of which was found by studying twenty instrumented vehicles used to investigate driving behaviour and long-term changes therein due to advanced driver support systems. Research on such driver support system was also performed in the ROTAS project (NWO/Connekt), in which an overtaking assistant was developed and tested in the driving simulator. This work is currently furthered in projects involving cooperative vehicles on behalf of respectively Toyota and Shell. Based on years of work on (multi-class) traffic flow theory, Hoogendoorn and his co-workers developed and implemented control algorithms and paradigms for active network traffic management. On behalf of the Dutch road authority, he is currently developing and implementing the control algorithms for the Field Operational Test Integrated Network Management Amsterdam (PPA).
Hoogendoorn has initiated and supervised pedestrian research at TU Delft. He developed the NOMAD pedestrian simulation model based on state-of-the-art walking experiments. Recent work involves using UAV’s to monitor crowd dynamics, as well as advanced data collection in large railway stations using Bluetooth and special cameras on behalf of NS Port. He has furthermore been involved in the design assessment of the future Al Mataf mosque in Mekkah.
Research on travel behaviour in uncertain situations and the impact of traffic information thereon has led to the development of the Travel Simulator Laboratory. Furthermore, Hoogendoorn’s group has been working on methods to characterise and model, and control uncertainty in traffic operations and travel behaviour for both urban and freeway networks.
Hoogendoorn has initiated, performed and supervised research on evacuation modelling for buildings and for regional networks. He acquired a VICI grant, focussing on transport and optimal traffic management in case of exceptional events. In the scope of this project, he has been supervising the development of a new multi-user virtual traffic and travel behaviour laboratory based on 3D internet technology to study the emergent behaviour of evacuees, which was successfully tested during the 2012 TRB annual meeting in Washington DC.
At the age of 36, Hoogendoorn was appointed the prestigious TU Delft Antonie van Leeuwenhoek professorship in 2006. Under his supervision, 18 PhD students have by now graduated successfully.