Mathematical Modeling of Command-and-Control Strategies in Crowd Movement

Abstract

Mathematical models and solution frameworks are described for the assessment of command-and-control strategies in the centralized coordination of crowd movement. The effectiveness of several strategies–-from providing only information to reconfiguring the built environment through architectural design changes and forcing pedestrians to follow system-optimal evacuation routes–-is investigated and compared with the use of proposed mathematical formulations and computational solutions. These formulations and solutions are tested on an example network as an illustration. Differences in system performance under these strategies are assessed, and performance (as total travel time) is compared. Efficiency gains obtained with command-and-control strategies in crowd movement are investigated.

Pedestrian control measures for efficient emergency response management in mass gatherings

“…One of the interventions to reduce evacuation time is to provide the evacuees information about expected travel time on the links. Expected travel time ( tinash) is calculated using successive average with logit assignment (Feng et al , 2014) as explained in Section 2.1. Now, the utility uinash of link i is given by: …”

“…From these equilibrium flows, the expected travel time on links are calculated. The detailed procedure used to find the improved-spontaneous evacuation time is explained in Feng et al (2014). Then, the new utilities are calculated using equation (7).…”

“…As a result, in this article, utility is modeled as a function of travel distance and time. Further, the probability of choosing any route is estimated using s uccessive average with logit assignment (Feng et al , 2014).…”

“…As discussed above, apart from leadership and controlling the behavior of pedestrians, an alternative way to control the process of evacuation is adapting the physical infrastructure (redesign of network configuration) to human behavior. Changing the physical environment may change how individuals choose their evacuation path (Feng et al , 2014). These changes help in enhancing/limiting the use of certain routes, thus keeping a balance between the surge demand (due to evacuation) and available supply.…”

Using New Mode Choice Model Nesting Structures to Address Emerging Policy Questions: A Case Study of the Pittsburgh Central Business District

“…Gossling [7] and Feng [8] differentiate between such investments that entail a directive (also described as "command and control"; examples are law enforcement moving crowds after a sporting event or speed limits) and two other actions that do not require a centralized entity. These are: (1) investments that provide information only (e.g., changeable message signs indicating travel times on parallel routes thereby enabling travelers to reduce delay if they so choose); and (2) market-based approaches that are a combination of the former two categories (e.g., taxes on certain routes and subsidies for certain modes of travel).…”