Combining New Data Gathering Technology and City Analytics to Investigate Pedestrian Movements
Henri Palm, DAT.Mobility, Luc Wismans, University of Twente, Eric De Kievit, City of Amsterdam
The city of Amsterdam has to deal with urban density, crowding and security problems. A case study named “the Red Carpet” was conducted, in which various pedestrian sensing technologies were tested simultaneously.
Little is known about pedestrian movements, densities and presence in city centers, although this knowledge could improve city planning, design of infrastructure and management of traffic flows. New data sources available due to fast developments in information and communication technology offer new possibilities for monitoring. Knowledge on pedestrian movements in city centers is essential for adequate city planning, road design, traffic management and security. As the city of Amsterdam has to deal with urban density, crowding and security problems, a case study named “the Red Carpet” was conducted, in which various pedestrian sensing technologies were tested simultaneously. The study area “Red Carpet” lies within the city center of Amsterdam.
The “Red Carpet” study focused on the movement of pedestrians between the Central Station and the Reguliersbreestraat vice versa. The municipality of Amsterdam formulated specific research questions regarding the movement of pedestrians between certain locations within the study area, which formed the basis for the installation of sensing technology in the area. The duration of the pilot was nearly 3 months at the end of 2014.
Questions regarding the movement of pedestrians in the city center (i.e. their numbers and routes) and additional characteristics like origin, number of foreigners, frequency of visits, activities and trip duration were addressed. Four sensing technologies were deployed: (1) WiFi, (2) a dedicated mobility app using GPS, (3) GSM (mobile phone data) and (4) a smart camera. This paper presents and discusses the results and possibilities of the various sensing technologies.
The results show the potential of getting insights in pedestrian movements and that the sources can provide complementary information. However, although the device generated data can provide distributions of pedestrian movement. Possible biases in representation and expansion are important aspects when these data sources are used especially regarding unique visitors. The GPS data was analyzed but turned out not to be representative. The results which were representative show that Saturday is the busiest day in pedestrian movements in the City and that these are mainly foreign visitors.
The results of the pilot will be used for developing a policy framework on pedestrians and crowd management.
Association for European Transport