Abstract
Crowd management measures have become more and more important not only to guarantee safety, but also to maintain good accessibility of public function, high throughput of pedestrian flows and high-quality public spaces, both during events and in daily operations. To support crowd management, information is necessary on the pedestrian traffic state for decision making on the operational level, and to support policy making regarding longer-term infrastructural changes. This paper introduces an innovative crowd monitoring system, which can be used in real-time, as well as for the analyses on historical data. The system consists of three components, namely data collection, traffic engineering functions and visualization. The core of the system consists of the traffic state estimation functions, using real-time data as input to calculate indicators, such as number of pedestrians present, speed, flow, travel time and route splits. The real-time data comes from counting systems, Wi-Fi sensors, and GPS trackers, but the system can easily be extended to include other types of sensors. Special attention has been paid to the visualization of the indicators, as it needs to be accurate, intuitive and flexible, to adjust to the user needs
Original language | English |
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Title of host publication | 97th Annual meeting of the Transportation Research board |
Publication status | Published - 2018 |
Event | TRB 2018: 97th Annual Meeting of the Transportation Research Board - Walter E. Washington Convention Center, Washington D.C., United States Duration: 7 Jan 2018 → 11 Jan 2018 Conference number: 97 |
Conference
Conference | TRB 2018: 97th Annual Meeting of the Transportation Research Board |
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Abbreviated title | TRB 2018 |
Country/Territory | United States |
City | Washington D.C. |
Period | 7/01/18 → 11/01/18 |
Keywords
- crowd monitoring
- pedestrian
- state estimation