A Framework for Developing and Integrating Effective Routing Strategies Within the Emergency Management Decision-Support System, Research Report 11-12

This report describes the modeling, calibration, and validation of a VISSIM traffic-flow simulation of the San José, California, downtown network and examines various evacuation scenarios and first-responder routings to assess strategies that would be effective in the event of a no-notice disaster. The modeled network required a large amount of data on network geometry, signal timings, signal coordination schemes, and turning-movement volumes. Turning-movement counts at intersections were used to validate the network with the empirical formula-based measure known as the GEH statistic. Once the base network was tested and validated, various scenarios were modeled to estimate evacuation and emergency vehicle arrival times. Based on these scenarios, a variety of emergency plans for San José’s downtown traffic circulation were tested and validated. The model could be used to evaluate scenarios in other communities by entering their community-specific data

An Online Decision-Theoretic Pipeline for Responder Dispatch

The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies fail to capture the dynamically changing environments under which critical emergency response occurs, and therefore, fail to be implemented in practice. Any holistic approach towards creating a pipeline for effective emergency response must also look at other challenges that it subsumes - predicting when and where incidents happen and understanding the changing environmental dynamics. We describe a system that collectively deals with all these problems in an online manner, meaning that the models get updated with streaming data sources. We highlight why such an approach is crucial to the effectiveness of emergency response, and present an algorithmic framework that can compute promising actions for a given decision-theoretic model for responder dispatch. We argue that carefully crafted heuristic measures can balance the trade-off between computational time and the quality of solutions achieved and highlight why such an approach is more scalable and tractable than traditional approaches. We also present an online mechanism for incident prediction, as well as an approach based on recurrent neural networks for learning and predicting environmental features that affect responder dispatch. We compare our methodology with prior state-of-the-art and existing dispatch strategies in the field, which show that our approach results in a reduction in response time with a drastic reduction in computational time.Comment: Appeared in ICCPS 201

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Seeing the invisible: from imagined to virtual urban landscapes

Urban ecosystems consist of infrastructure features working together to provide services for inhabitants. Infrastructure functions akin to an ecosystem, having dynamic relationships and interdependencies. However, with age, urban infrastructure can deteriorate and stop functioning. Additional pressures on infrastructure include urbanizing populations and a changing climate that exposes vulnerabilities. To manage the urban infrastructure ecosystem in a modernizing world, urban planners need to integrate a coordinated management plan for these co-located and dependent infrastructure features. To implement such a management practice, an improved method for communicating how these infrastructure features interact is needed. This study aims to define urban infrastructure as a system, identify the systematic barriers preventing implementation of a more coordinated management model, and develop a virtual reality tool to provide visualization of the spatial system dynamics of urban infrastructure. Data was collected from a stakeholder workshop that highlighted a lack of appreciation for the system dynamics of urban infrastructure. An urban ecology VR model was created to highlight the interconnectedness of infrastructure features. VR proved to be useful for communicating spatial information to urban stakeholders about the complexities of infrastructure ecology and the interactions between infrastructure features.https://doi.org/10.1016/j.cities.2019.102559Published versio

Texas Transportation Researcher

Quarterly publication of the Texas A&M Transportation Institute discussing their research as well as professional and service activities. It includes articles about research and innovations in various areas related to transportation in Texas

The Camp Nou Stadium as a testbed for city physiology: a modular framework for urban digital twins

In this paper, the Camp Nou stadium is used as a testbed for City Physiology, a theoretical framework for urban digital twins. With this case study, the modularity and adaptability of the framework, originally intended for city-scale simulations, are tested on a large facility venue. As a proof of concept, several statistical techniques and an agent-based simulation platform are coupled to simulate a crowd in the stadium, and a process of four steps is followed to build the case study. Both the conceptual (interdomain) and technical (domain specific) layers of the digital twin are defined and connected in a nonlinear process so that they represent the complexity of the object to be simulated. &e result obtained is a strategy to build a digital twin from the domain point of view, paving the way for more complex, more ambitious simulatorsThis project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the IoTwins Project (Grant agreement no. 857191). I. Meta was partially funded by the Agencia Estatal de Investigación-Ministerio de Ciencia Innovación (AEI MICINN) and the European Social Fund (ESF) under the FPI program (scholarship no. PRE2019-090239).Peer ReviewedPostprint (published version

Impact of New Madrid Seismic Zone Earthquakes on the Central USA, Vol. 1 and 2

The information presented in this report has been developed to support the Catastrophic Earthquake Planning Scenario workshops held by the Federal Emergency Management Agency. Four FEMA Regions (Regions IV, V, VI and VII) were involved in the New Madrid Seismic Zone (NMSZ) scenario workshops. The four FEMA Regions include eight states, namely Illinois, Indiana, Kentucky, Tennessee, Alabama, Mississippi, Arkansas and Missouri. The earthquake impact assessment presented hereafter employs an analysis methodology comprising three major components: hazard, inventory and fragility (or vulnerability). The hazard characterizes not only the shaking of the ground but also the consequential transient and permanent deformation of the ground due to strong ground shaking as well as fire and flooding. The inventory comprises all assets in a specific region, including the built environment and population data. Fragility or vulnerability functions relate the severity of shaking to the likelihood of reaching or exceeding damage states (light, moderate, extensive and near-collapse, for example). Social impact models are also included and employ physical infrastructure damage results to estimate the effects on exposed communities. Whereas the modeling software packages used (HAZUS MR3; FEMA, 2008; and MAEviz, Mid-America Earthquake Center, 2008) provide default values for all of the above, most of these default values were replaced by components of traceable provenance and higher reliability than the default data, as described below. The hazard employed in this investigation includes ground shaking for a single scenario event representing the rupture of all three New Madrid fault segments. The NMSZ consists of three fault segments: the northeast segment, the reelfoot thrust or central segment, and the southwest segment. Each segment is assumed to generate a deterministic magnitude 7.7 (Mw7.7) earthquake caused by a rupture over the entire length of the segment. US Geological Survey (USGS) approved the employed magnitude and hazard approach. The combined rupture of all three segments simultaneously is designed to approximate the sequential rupture of all three segments over time. The magnitude of Mw7.7 is retained for the combined rupture. Full liquefaction susceptibility maps for the entire region have been developed and are used in this study. Inventory is enhanced through the use of the Homeland Security Infrastructure Program (HSIP) 2007 and 2008 Gold Datasets (NGA Office of America, 2007). These datasets contain various types of critical infrastructure that are key inventory components for earthquake impact assessment. Transportation and utility facility inventories are improved while regional natural gas and oil pipelines are added to the inventory, alongside high potential loss facility inventories. The National Bridge Inventory (NBI, 2008) and other state and independent data sources are utilized to improve the inventory. New fragility functions derived by the MAE Center are employed in this study for both buildings and bridges providing more regionally-applicable estimations of damage for these infrastructure components. Default fragility values are used to determine damage likelihoods for all other infrastructure components. The study reports new analysis using MAE Center-developed transportation network flow models that estimate changes in traffic flow and travel time due to earthquake damage. Utility network modeling was also undertaken to provide damage estimates for facilities and pipelines. An approximate flood risk model was assembled to identify areas that are likely to be flooded as a result of dam or levee failure. Social vulnerability identifies portions of the eight-state study region that are especially vulnerable due to various factors such as age, income, disability, and language proficiency. Social impact models include estimates of displaced and shelter-seeking populations as well as commodities and medical requirements. Lastly, search and rescue requirements quantify the number of teams and personnel required to clear debris and search for trapped victims. The results indicate that Tennessee, Arkansas, and Missouri are most severely impacted. Illinois and Kentucky are also impacted, though not as severely as the previous three states. Nearly 715,000 buildings are damaged in the eight-state study region. About 42,000 search and rescue personnel working in 1,500 teams are required to respond to the earthquakes. Damage to critical infrastructure (essential facilities, transportation and utility lifelines) is substantial in the 140 impacted counties near the rupture zone, including 3,500 damaged bridges and nearly 425,000 breaks and leaks to both local and interstate pipelines. Approximately 2.6 million households are without power after the earthquake. Nearly 86,000 injuries and fatalities result from damage to infrastructure. Nearly 130 hospitals are damaged and most are located in the impacted counties near the rupture zone. There is extensive damage and substantial travel delays in both Memphis, Tennessee, and St. Louis, Missouri, thus hampering search and rescue as well as evacuation. Moreover roughly 15 major bridges are unusable. Three days after the earthquake, 7.2 million people are still displaced and 2 million people seek temporary shelter. Direct economic losses for the eight states total nearly $300 billion, while indirect losses may be at least twice this amount. The contents of this report provide the various assumptions used to arrive at the impact estimates, detailed background on the above quantitative consequences, and a breakdown of the figures per sector at the FEMA region and state levels. The information is presented in a manner suitable for personnel and agencies responsible for establishing response plans based on likely impacts of plausible earthquakes in the central USA.Armu W0132T-06-02unpublishednot peer reviewe

Identifying and Evaluating the Impacts of the 2012 Olympics: London Borough of Hounslow

The purpose of this project was to assist the London Borough of Hounslow Contingency Planning Unit in identifying and evaluating the impacts of the 2012 Olympic Games. We gathered and derived data to present a quantitative representation of the borough with possible impacts. Analysis shows significant impacts, as Hounslow could see a 15% increase in population, a 37% increase in rail ridership, a 5% increase in emergency room visits, and an additional 2000 cars per day traveling through the borough