|418-Part I: Pedestrian Simulation Fundamentals- Key phenomena and models that capture these|
Dr. Yufei Yuan is a researcher at the department of transport and planning at the Faculty of Civil Engineering and Geosciences at Delft University of Technology, the Netherlands. His research interest lies with traffic flow theory and simulation, data processing and analysis, traffic state estimation and prediction, network traffic management and analysis under normal conditions and evacuations, intelligent transportation systems in general for both “fast” vehicular traffic and “slow/active” modes (pedestrians and cyclists).
During the past years, he has been involved in several contract research projects at both national and international levels, which inspired his publications in peer-reviewed scientific journals (19 publications including IEEE-TITS, TR-Part B, TR-Part C, J-ITS, TRR and IET-ITS) and prestigious conferences (more than 50 publications, 2 best paper awards, 1 most inspiring session).
He has been working as a lecturer for a number of postgraduate courses, and as a daily/main supervisor for BSc students, MSc students and PhD students. He has been serving as a reviewer (associate editor) for many international conferences (including TRB, IEEE-ITSC, IFAC, ICNSC, PED, etc.) and journals (including TR-B, TR-C, IEEE-TITS, J-ITS, TTRA etc.). He was a visiting scholar at University of Southampton in the UK (with the scientific grant from the “COST Action”) and at research laboratory LICIT/IFSTTAR in France.
Active modes can play a major role in making cities liveable, either as a main mode of transport or support to public transport in multi modal trips. Walking becomes more and more important in people's daily life. In addition, more and larger gatherings take place, in both organized and spontaneous manners. Increasing amount of pedestrians may lead to incidents, with sometimes even fatal outcomes. Tragedies, like the one in Saudi Arabia in 2015, the stampede in Shanghai in 2015 new year eve, create societal upset and show the need for improved management of large gatherings.
This lecture series aims to give insight into the fundamentals of pedestrian walking behavior (e.g. basic traffic flow theory), and the self-organization phenomenon (Part I). These insights are then used to develop microscopic and macroscopic crowd simulation models (Part I and Part III), and further to formulate guidelines for crowd management. Besides, real-time crowd monitoring has shown to be an effective way to promote efficient and safe crowd management (Part II). Finally, how walking would interact with other transport modes in mixed traffic environment is discussed, and a shared space context considering bicycle traffic flow is used as a showcase (Part IV).