Evacuation Plans and Simulations for Crowd Egress – A Review

Due to growing population density and increasing complexity and congestion of human habitat evacuation planning is essential to avoid major loss of life during a natural or un-natural disaster. The paper provides a review of existing evacuation systems and strategies and also points out the possible research directions. Intelligent Evacuation Management System coupled with evolutionary and machine learning techniques such as PSO,ACO , k-mean clustering is a promising solution to ensure safe and jostle free egress of people.

Mobility as a Resource (MaaR) for resilient human-centric automation: a vision paper

With technological advances, mobility has been moving from a product (i.e., traditional modes and vehicles), to a service (i.e., Mobility as a Service, MaaS). However, as observed in other fields (e.g. cloud computing resource management) we argue that mobility will evolve from a service to a resource (i.e., Mobility as a Resource, MaaR). Further, due to increasing scarcity of shared mobility spaces across traditional and emerging modes, the transition must be viewed within the critical need for ethical and equitable solutions for the traveling public (i.e., research is needed to avoid hyper-market driven outcomes for society). The evolution of mobility into a resource requires novel conceptual frameworks, technologies, processes and perspectives of analysis. A key component of the future MaaR system is the technological capacity to observe, allocate and manage (in real-time) the smallest envisionable units of mobility (i.e., atomic units of mobility capacity) while providing prioritized attention to human movement and ethical metrics related to access, consumption and impact. To facilitate research into the envisioned future system, this paper proposes initial frameworks which synthesize and advance methodologies relating to highly dynamic capacity reservation systems. Future research requires synthesis across transport network management, demand behavior, mixed-mode usage, and equitable mobility

Minimal Evacuation Times and Stability

We consider a system where packets (jobs) arrive for processing using one of the policies in a given class. We study the connection between the minimal evacuation time and the stability region of the system and show that evacuation time optimal policies can be used for stabilizing the system (and for characterizing its stability region) under broad assumptions. Conversely, we show that while a stabilizing policy can be suboptimal in terms of evacuation time, one can always design a randomized version of any stabilizing policy that achieves an optimal evacuation time in the asymptotic regime when the number of evacuated packets scales to infinity