Dynamic control strategies for managing pedestrian flows

Pedestrians, like drivers, generally dislike congestion. This is true for most pedestrian environments: trains stations, airports, or shopping malls. Furthermore, pedestrian congestion also influences the attractiveness of public transportation networks. Therefore, preventing, or at least limiting, congestion from occurring inside walkable environments is critical. Although the desire to reduce, or limit, congestion appears unquestioned, the solutions to achieve this are challenging and diverse. The range of possible measures goes from adequate design considerations during the construction phase to dynamically controlled devices for managing pedestrian flows. In this thesis we discuss, design, and evaluate several innovative dynamic control strategies dedicated to managing pedestrian flows.Installing hardware is not sufficient, thorough understanding of the dynamics taking place inside a given infrastructure is critical. Furthermore, a framework for ensuring communication between the measurement devices, control algorithm and hardware is needed. For road traffic, this framework is called Dynamic Traffic Management Systems (DTMS). The specification of the pedestrian counterpart is discussed in this thesis: Dynamic Pedestrian Management Systems (DPMS). We compare the specificities of DTMS to DPMS and emphasize the characteristics of pedestrian dynamics. Furthermore, we propose several control strategies dedicated to pedestrian flows and evaluate their effectiveness. The first is gating, inspired from traffic lights and ramp metering in road networks. The second is the usage of flow separators to prevent bidirectional pedestrian flow from occurring. The third and final strategy we propose exploits moving walkways, by controlling their speed and direction, to influence pedestrian flows.The different control strategies illustrate the utilisation of the DPMS by simulating different case studies. The first control strategy we propose, gating, provides only minor improvements to the pedestrian dynamics. This occurs since the strategy is not tailored to pedestrian flow characteristics. The second strategy successfully improves pedestrian travel times by dynamically allocating walking space to antagonistic flows. The third strategy, where one flavour of the control algorithm integrates short term predictions, is highly successful at reducing congestion and improving travel times. The utilisation of moving walkways by the predictive algorithm emphasizes the trade-off between decreasing travel time and reducing congestion. Nevertheless, the computational cost is high. Finally, for all control strategies and all algorithms, some users are penalized, while others benefit from the strategy. Thanks to the different control strategies proposed in this thesis, we emphasize the need for control strategies which address pedestrian specific situations. Three specificities are identified: user compliance, available choices, and the complexity of pedestrian motion. Addressing these aspects is critical to develop successful strategies. The strategies we discuss can be applied in any pedestrian context. Nevertheless, the potential of the strategies developed in this thesis are still underexplored. Significant improvements can be expected with further development and calibration of the control algorithms. Furthermore, practical applications could be implemented with limited cost since most of the components for using simple strategies already exist.