DEVELOPMENT OF A MIXED-FLOW OPTIMIZATION SYSTEM FOR EMERGENCY EVACUATION IN URBAN NETWORKS

In most metropolitan areas, an emergency evacuation may demand a potentially large number of evacuees to use transit systems or to walk over some distance to access their passenger cars. In the process of approaching designated pick-up points for evacuation, the massive number of pedestrians often incurs tremendous burden to vehicles in the roadway network. Hence, one critical issue in a multi-modal evacuation planning is the effective coordination of the vehicle and pedestrian flows by considering their complex interactions. The purpose of this research is to develop an integrated system that is capable of generating the optimal evacuation plan and reflecting the real-world network traffic conditions caused by the conflicts of these two types of flows. The first part of this research is an integer programming model designed to optimize the control plans for massive mixed pedestrian-vehicle flows within the evacuation zone. The proposed model, integrating the pedestrian and vehicle networks, can effectively account for their potential conflicts during the evacuation. The model can generate the optimal routing strategies to guide evacuees moving toward either their pick-up locations or parking areas and can also produce a responsive plan to accommodate the massive pedestrian movements. The second part of this research is a mixed-flow simulation tool that can capture the conflicts between pedestrians, between vehicles, and between pedestrians and vehicles in an evacuation network. The core logic of this simulation model is the Mixed-Cellular Automata (MCA) concept, which, with some embedded components, offers a realistic mechanism to reflect the competing and conflicting interactions between vehicle and pedestrian flows. This study is expected to yield the following contributions * Design of an effective framework for planning a multi-modal evacuation within metropolitan areas; * Development of an integrated mixed-flow optimization model that can overcome various modeling and computing difficulties in capturing the mixed-flow dynamics in urban network evacuation; * Construction and calibration of a new mixed-flow simulation model, based on the Cellular Automaton concept, to reflect various conflicting patterns between vehicle and pedestrian flows in an evacuation network

Improving Network Reliability: Analysis, Methodology, and Algorithms

The reliability of networking and communication systems is vital for the nation's economy and security. Optical and cellular networks have become a critical infrastructure and are indispensable in emergency situations. This dissertation outlines methods for analyzing such infrastructures in the presence of catastrophic failures, such as a hurricane, as well as accidental failures of one or more components. Additionally, it presents a method for protecting against the loss of a single link in a multicast network along with a technique that enables wireless clients to efficiently recover lost data sent by their source through collaborative information exchange. Analysis of a network's reliability during a natural disaster can be assessed by simulating the conditions in which it is expected to perform. This dissertation conducts the analysis of a cellular infrastructure in the aftermath of a hurricane through Monte-Carlo sampling and presents alternative topologies which reduce resulting loss of calls. While previous research on restoration mechanisms for large-scale networks has mostly focused on handling the failures of single network elements, this dissertation examines the sampling methods used for simulating multiple failures. We present a quick method of nding a lower bound on a network's data loss through enumeration of possible cuts as well as an efficient method of nding a tighter lower bound through genetic algorithms leveraging the niching technique. Mitigation of data losses in a multicast network can be achieved by adding redundancy and employing advanced coding techniques. By using Maximum Rank Distance (MRD) codes at the source, a provider can create a parity packet which is e ectively linearly independent from the source packets such that all packets may be transmitted through the network using the network coding technique. This allows all sinks to recover all of the original data even with the failure of an edge within the network. Furthermore, this dissertation presents a method that allows a group of wireless clients to cooperatively recover from erasures (e.g., due to failures) by using the index coding techniques

BUILDING PRELIMINARY GUIDELINE FOR EARTHQUAKE EVACUATION

Disaster frequency appears to be increasing. The impact of those disasters has increased substantially in terms of mortality and economic losses. Evacuation, as an inevitable part of disaster management systems, plays a critical role in disaster mitigation. The efficiency of all-hazard disaster evacuation could be increased by making appropriate decisions on policies and practices for planning, preparedness and response, and taking certain traffic operations, management and control. Common principles for large disaster evacuation have been established, mostly based on the experience of hurricane events. However, earthquakes have a series of special characteristics, which are different from other disasters, such as being hard to predict and leading to a great deal of secondary disasters. The 1994 Northridge earthquake in California and the 2008 Wenchuan earthquake in China are chosen as examples to track and compare disaster response, including evacuation effectiveness. A primary guideline for earthquake evacuation plan is developed in this study

Analytical model for staging emergency evacuations

Disaster response in areas of high population density is centered on the efficient evacuation of people and possibly goods. Developing evacuation plans suitable for different levels of urgency based on the intensity of threat is a challenging task. In case of densely populated cities (e.g., New York, Los Angeles), the level of threat is enhanced by the congestion of their transportation systems, and the decision to evacuate a region simultaneously or by dividing it into multiple stages (or zones) affects the required evacuation time and associated delays. The evolution of the traffic conditions on the evacuation route can vary significantly based on the type of evacuation strategy employed (i.e., simultaneous or staged). In this dissertation, mathematical models are developed for estimating evacuation time and delay. Evacuation time is the time for evacuating all vehicles from a designated region, while delay includes queuing and moving delays incurred by evacuees. The base model handles a uniform demand distribution over the evacuation route and deterministic evacuees\u27 behavior. The relationship between delay and evacuation time is investigated, and the impact of a staged versus a simultaneous evacuation is analyzed. A numerical method is adopted to determine the optimal number of staging zones. A sensitivity analysis is conducted of parameters (e.g., demand density, access flow rate, and evacuation route length) affecting evacuation time and delay. To account for the heterogeneous demand distribution over the evacuation region and evacuees\u27 behavioral responses to an evacuation order (e.g., fast, medium, and slow), a more realistic model is developed by enhancing the base model. Based on a numerical searching process, the enhanced model determines the optimal time windows and lengths of individual staged zones dependent on the demand distribution, behavioral response, and evolution of traffic conditions on the evacuation route. The applicability of the model is demonstrated with a numerical example. Results indicate that evacuation time and delay can be significantly reduced if a staged evacuation can be appropriately implemented. Finally, the impact of compliance is investigated. Compliance is defined as the conformity of a staged zone to its demand loading pattern. It is found that the level of compliance and deviation from scheduled access time influence the effectiveness of staging. Further, a method to revise the optimal staging scheme to accommodate the noncompliant demand is illustrated. The models developed in this research can serve as useful tools to provide suitable guidelines for emergency management authorities in making critical decisions during the evacuation process