Evacuation planning in the Auckland Volcanic Field, New Zealand: a spatio-temporal approach for emergency management and transportation network decisions

Auckland is the largest city in New Zealand (pop. 1.5 million) and is situated atop an active monogenetic volcanic field. When volcanic activity next occurs, the most effective means of protecting the people who reside and work in the region will be to evacuate the danger zone prior to the eruption. This study investigates the evacuation demand throughout the Auckland Volcanic Field and the capacity of the transportation network to fulfil such a demand. Diurnal movements of the population are assessed and, due to the seemingly random pattern of eruptions in the past, a non-specific approach is adopted to determine spatial vulnerabilities at a micro-scale (neighbourhoods). We achieve this through the calculation of population-, household- and car-to-exit capacity ratios. Following an analysis of transportation hub functionality and the susceptibility of motorway bridges to a new eruption, modelling using dynamic route and traffic assignment was undertaken to determine various evacuation attributes at a macro-scale and forecast total network clearance times. Evacuation demand was found to be highly correlated to diurnal population movements and neighbourhood boundary types, a trend that was also evident in the evacuation capacity ratio results. Elevated population to evacuation capacity ratios occur during the day in and around the central city, and at night in many of the outlying suburbs. Low-mobility populations generally have better than average access to public transportation. Macro-scale vulnerability was far more contingent upon the destination of evacuees, with favourable results for evacuation within the region as opposed to outside the region. Clearance times for intra-regional evacuation ranged from one to nine hours, whereas those for inter-regional evacuation were found to be so high, that the results were unrealistic. Therefore, we conclude that, from a mobility standpoint, there is considerable merit to intra-regional evacuation

Operational Impact of Shadow Evacuation on Regional Road Networks During Short-Notice Emergency Evacuations

As part of evacuation planning, development of effective tactical and operational strategies are essential to safely and efficiently mobilize the public away from the threat. Evacuations are classified by the time between notification and the anticipated arrival of the threat which can be categorized as short, or no-notice emergencies. Emergencies involve the computation of the time required to evacuate the area of risk, which is the time to clear a radius of up to about 10-miles around the nuclear power plant, known as the emergency planning zone (EPZ). These evacuation time estimates (ETE) also account for the evacuation of the public outside the defined area of risk. Typically, this area extends five miles outside the EPZ boundary and it is commonly referred to as the shadow evacuation region. Although shadow evacuation could create significant traffic congestion that affects the EPZ clearance process, there is limited research quantifying this effect. The objective of this research was to study the impacts of shadow evacuation to the overall EPZ clearance process. To accomplish this, the research used microscopic traffic simulation to assess the effect of different shadow participation rates for three hypothetical nuclear power plants with distinct population sizes surrounding the plant (small, medium, and large) and roadway characteristics. The guidance in NUREG/CR-7002 for ETE studies recommends a 20 percent participation rate that was based on previous studies, research related to ETE demographics, public response, and other contributing factors. However, the 20 percent recommendation may be conservative. The results suggested that small population sites are not impacted significantly by varying the shadow participation rates. However, medium and large population sites showed a noticeable effect, particularly in those corridors with less capacity. If the shadow evacuation participation rate is increased to 40 percent, the ETE to evacuate 90 percent of the population is increased by up to 10 percent in medium-sized areas, and up to 19 percent in large areas. Under the same conditions, the ETE to evacuate 100 percent of the population increases by less than 5 percent for medium-sized areas and less than 3 percent for large areas

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

Absence of freight transportation plans in state and county emergency operations plans

Natural disasters have the ability to disrupt structured systems in the United States, such as transportation systems and freight routes. When a natural disaster occurs, freight is forced to reroute around the effected areas. Rerouting slows recovery efforts, as well as normal transportation of goods within the United States. Therefore, natural disasters, with respect to freight routes, have widespread impacts and the possibility for acute hardship in disaster-prone areas. This thesis examines how comprehensive state and local level emergency operations plans are with respect to freight transportation rerouting following a natural disaster. Coastal cities can modify freight routes and this rerouting might affect recovery efforts and the normal flow of freight. First, seven coastal cities emergency operations plans are examined for specific elements of freight transportation planning. From there, the project determined how complete local level emergency operations plans are in terms of freight transportation and the framework needed for a freight transportation plan. The result of this research was policy recommendations to improve the resiliency of freight transportation networks surrounding coastal cities and incorporate freight transportation planning into emergency operations. The resiliency of freight routes following natural disasters is important because there can be widespread effects on the delivery of goods to the U.S. as well as recovery supplies to the effected area. If freight routes could be modeled to efficiently deliver rescue supplies and goods, while also minimizing the environmental effects, the benefits of uninterrupted service to the transportation system and society could possibly be substantial. The transportation system cannot encounter difficulties whenever a natural or manmade disaster occurs; therefore the United States needs to be better equipped to counteract interruptions in freight routes

Maryland State Highway Administration Climate Change Adaptation Plan with Detailed Vulnerability Assessment

This report presents the results of a Climate Resilience Pilot Project conducted by the Maryland State Highway Administration (SHA) and sponsored in part by the Federal Highway Administration (FHWA). The primary objectives of the Pilot Study are to assess the vulnerability of SHA\u2019s transportation assets (roads and bridges) to climate variables or stressors, to develop engineering approaches to address current and future climate induced risks and to make recommendations for policy or process changes to improve the resiliency of Maryland\u2019s highway system. This Pilot Study serves as a model from which SHA will be able to establish the framework and process for asset vulnerability assessment, prioritization, and adaptation in response to climate change. Another objective of the Pilot Study is interagency knowledge transfer and mutual capacity building. As such, the Pilot Study will share information on methods used and lessons learned with other state Departments of Transportations and government agencies for the purpose of expanding the transportation sector\u2019s ability to respond to ongoing climate change impacts across jurisdictions. A framework was developed for the vulnerability assessment. Asset and climate information was compiled from a variety of reputable sources. Predictive models were developed using recent Light Detection and Ranging (LiDAR) information from the State of Maryland and Hazus modeling. Three primary assets were evaluated: bridges (including small structures), roadways, and small culverts/drainage conveyances. Each of the climate variables were reviewed and evaluated for their potential impacts on Maryland\u2019s transportation assets and it was determined that sea level change, storm surge from extreme weather events, and increased intensity in precipitation would have the greatest impact on the transportation assets under study

Evaluating Travelers Experience with Highway Advisory Radio (HAR) And Citizens Band Radio Advisory System (CBRAS) On Florida\u27s Turnpike Enterprise Toll Roadways And Florida Interstate Highways

The goal of this thesis is to evaluate travelers\u27 experience with Highway Advisory Radio (HAR) and Citizens\u27 Band Radio Advisory System (CBRAS) technologies on both Florida Interstate Highway system (FIH) and the Florida Turnpike Enterprise (FTE) toll roads. To achieve this goal, two different survey tools were used. The first tool is a random digit dialing phone survey known as CATI (Computer-Assisted Telephone Interviewing). The second tool is a field survey that intercepts travelers at the Florida Turnpike Enterprise (FTE) service plazas and the Florida Interstate Highway (FIH) rest areas. HAR and CBRAS are traditional components of the Advanced Traveler Information Systems (ATIS). This thesis pays special attention to the effectiveness of HAR and CBRAS in improving travelers\u27 experience. Feedback to analyze these two technologies was collected via a telephonic survey and a field survey. Two different field surveys (one for HAR and one for CBRAS) were designed and implemented to obtain feedback on these technologies. The field survey for CBRAS is unique and has never been done before for this purpose. A sample size of 1000 HAR surveys was collected through the CATI phone survey. Field surveys were collected at five locations across the state, including central, southeast, and southwest regions of Florida. The HAR field survey sample size was 1610 and the CBRAS field survey sample size was 613. All field surveys were conducted by UCF students at each of the five locations, over a 13-week data collection period. The HAR messages were designed to alert drivers of any adverse roadway traffic or weather conditions. The CBRAS is limited to truck drivers with the closed system radio pre-installed in their vehicles. However, truck drivers were also asked some questions on HAR if they do not use CBRAS. Basic statistical analysis was used to determine a number of performance indicators which include system\u27s use and awareness, usability of provided information, route diversion, and travelers\u27 demographics. In addition, the two HAR phone and field samples were combined together and examined using a decision tree model. Target questions were selected from the survey to build the tree network. The tree model aimed at identifying trends between categorical differences of travelers with respect to specific questions. Understanding travelers\u27 satisfaction with HAR is critical to knowing its benefits. The ending results indicated that both basic statistical analysis and the decision tree model are in agreement. A comparison between HAR phone and field surveys indicates the following. Travelers interviewed for the HAR field survey were more aware of the HAR than travelers surveyed by phone. A small portion of the surveyed samples used HAR (22% and this was consistent between the phone and the field surveys). Also, 80% or more were satisfied with HAR for both phone and field samples and the majority (85% or more) supported its continuation as an indication of willingness to use it in the future, especially in emergency conditions. In terms of the types of messages they want to hear from HAR, traffic congestion was the most common. Dynamic Message Signs (DMS) were the most preferred source of travel information and were the alternative for HAR, if HAR gets terminated. This was followed by smartphone applications which received twice as much support from field surveyed travelers (28%) when compared to phone surveyed travelers (15%). The CATI Phone Survey was biased towards elderly people (60% of the sample) and mainly females (58%) that use the FTE roadway system. Users satisfied with the system are those who only use these roadways once per week or less. The survey ultimately shows that travelers rely on modern modes of obtaining traffic information than traditional ones, such as HAR. DMS, and smart phone applications are leading communication tools among all type of travelers. The HAR field survey was less biased with respect to age and gender distribution (56% were under 50 and 62% were males). Both surveys indicate that the sample is well educated (about 60% have an associate degree or higher). CBRAS serves a small segment of commercial truck drivers (only 12% out of 613 used CBRAS). However, this small segment used it heavily (84% used it sometimes, often, or always). And 92% of CBRAS users were satisfied or strongly satisfied with it. CBRAS was used mostly for route divergence, with 72% of the drivers relying on it for this purpose. Truck drivers who never used CBRAS (88% of the sample) were asked questions about HAR. Only 27% of them used HAR and 57% of these used it sometimes, often, or always with 72% of the truck users being satisfied with HAR compared to the 92% satisfied with CBRAS. The most common complaint about HAR by truck drivers was that it is not easy to access or understand. Based on responses of truck drivers for both HAR and CBRAS field surveys above, it seems that GPS navigation was the most preferred source of travel information (28%). In addition to the basic statistics, a decision tree model, using SAS Enterprise Miner was performed. The statistical analysis results indicated satisfaction of travelers. The decision tree model was used to predict and profile responses to all answered questions that each survey shared. Training data was included in the model and the model was able to leverage the questions. Results of the decision tree model predicted high user satisfaction rates. Analyses of the three implemented surveys show that HAR and CBRAS technologies are not used by a large proportion of travelers, but their users are typically satisfied with these technologies. A small portion of the surveyed sample of truck drivers uses CBRAS but they use it heavily and were very satisfied with it. The travelers\u27 satisfaction level with HAR was high. The HAR and CBRAS systems are in the middle of a heated competition lead by digital communication, it may be a sign of the time to create HAR/CBRAS smart phone applications for the longevity of these traditional technologies

South Carolina statewide freight plan update 2022

This document contains a series of recommendations that will advance both national freight goals and SCDOT’s own transportation goals and assist in improving the efficient movement of freight on the National Highway Freight Network. As a planning and programming tool, this plan will be utilized as a guide in addressing statewide freight program investment priorities. As a dedicated document associated with the statewide multimodal planning process, the Statewide Freight Plan will improve the ability of the State to meet the national multimodal freight policy goals

Transportation asset management and climate change: an adaptive risk-oriented approach

Transportation Asset Management (TAM) systems are in use at many transportation agencies both in the United States and around the world. These asset management systems serve as strategic resource allocation frameworks and their degree of implementation and maturity varies. Climatic change, with its potentially adverse impacts on both the built and natural environments, has become of increasing concern around the globe. Given the uncertainties associated with changing climatic conditions, transportation agency stakeholders utilize risk-based decision-making approaches to identify climate change impacts that pose the greatest risk to transportation infrastructure assets. In conjunction with criticality assessments, emerging conceptual frameworks seek to identify higher-risk infrastructure assets, which are both critical to system operations and vulnerable to potential climate change impacts, through standalone study efforts. This research develops a risk-oriented decision-making framework to identify vulnerable, higher-risk transportation infrastructure assets within the context of existing transportation asset management systems. The framework assesses the relative maturity of an agency’s transportation asset management system and provides guidance as to how an agency’s existing tools and processes can be used to incorporate climate change considerations. This risk-based decision-making framework is applied to three case studies: one at the Metropolitan Atlanta Rapid Transit Authority, another at the Metropolitan Planning Commission in Savannah – Chatham County, and a statewide case study at the Georgia Department of Transportation. The results of this research demonstrate that readily-available climate projection data can be analyzed and displayed geospatially so that the potential impacts of climatic change on transportation infrastructure can be determined for specific geographic regions. In addition, existing roadway and bridge infrastructure datasets can also be displayed geospatially. The framework uses geospatially-referenced roadway and bridge asset data and multi-criteria decision analysis procedures to develop and visually display criticality scores. Overlaying climate projection data and criticality data helps identify higher-risk transportation infrastructure assets. This research demonstrates that climate change considerations can be effectively incorporated in existing decision-making processes at various levels of maturity of formal TAM systems, making this more broadly accessible to agencies and communities with potential climate hazards.Ph.D

EVALUATING URBAN DOWNTOWN ONE-WAY TO TWO-WAY STREET CONVERSION USING MICROSCOPIC TRAFFIC SIMULATION

Located in the heart of Silicon Valley, Downtown San Jose is attracting new residents, visitors, and businesses. Clearly, the mobility of these residents, visitors, and businesses cannot be accommodated by streets that focus on the single-occupancy automobile mode. To increase the potential for individuals to use non-single-occupancy modes of travel, the downtown area must have a cohesive plan to integrate multimodal use and public life. Complete streets are an integral component of the multi-modal transport system and more livable communities. Complete streets refer to roads designed to accommodate multiple modes, users, and activities including walking, cycling, transit, automobile, and nearby businesses and residents. A one-way to two-way street conversion is an example of a complete streets project. Similarly, tactical urbanism can provide cost-effective modifications (e.g., through temporary road closures for events like the farmers’ market) that enrich the public life in an urban environment. The ability to serve current and future transportation needs of residents, businesses and visitors through the creation of pleasant, efficient, and safe multimodal corridors is a guiding principle of a smart city. This research project addressed questions that guide the implementation of this overarching principle. These questions relate to travel patterns and potential network impacts of the conversion of the corridor(s) into complete streets. Towards that end, core network in downtown San Jose is simulated via a validated VISSIM model for 2015 traffic conditions (i.e., the base case or Scenario 0). Three scenarios are then modeled as variations to this model. The relevant model outputs from the base and scenario models provide easily digestible information the City can convey various impacts and trade-offs to partners and stakeholders prior to implementation of these plans. The scenarios modeled are based on stakeholder input. Microsimulation allows for detailed modeling and visualization of the transportation networks including movements of individual vehicles and pedestrians. The results based on 2040 traffic volumes provided by the city based on their long-range travel demand model clearly demonstrate that the existing network cannot support the projected level of travel demand. It indicates that the city needs an aggressive travel demand management program to curb the growth of automobile traffic. The output also includes 3-D animations of the traffic flow that can be used in public forums for community outreach. A discussion for such a campaign based on best practices around using these visualizations for public outreach is also provided. Located in the heart of Silicon Valley, Downtown San Jose is attracting new residents, visitors, and businesses. Clearly, the mobility of these residents, visitors, and businesses cannot be accommodated by streets that focus on the single-occupancy automobile mode. To increase the potential for individuals to use non-single-occupancy modes of travel, the downtown area must have a cohesive plan to integrate multimodal use and public life. Complete streets are an integral component of the multi-modal transport system and more livable communities. Complete streets refer to roads designed to accommodate multiple modes, users, and activities including walking, cycling, transit, automobile, and nearby businesses and residents. A one-way to two-way street conversion is an example of a complete streets project. Similarly, tactical urbanism can provide cost-effective modifications (e.g., through temporary road closures for events like the farmers’ market) that enrich the public life in an urban environment. The ability to serve current and future transportation needs of residents, businesses and visitors through the creation of pleasant, efficient, and safe multimodal corridors is a guiding principle of a smart city. This research project addressed questions that guide the implementation of this overarching principle. These questions relate to travel patterns and potential network impacts of the conversion of the corridor(s) into complete streets. Towards that end, core network in downtown San Jose is simulated via a validated VISSIM model for 2015 traffic conditions (i.e., the base case or Scenario 0). A number o Threef scenarios are then modeled as variations to this model. The relevant model outputs from the base and scenario models provide easily digestible information the City can convey various impacts and trade-offs to partners and stakeholders prior to implementation of these plans. The scenarios modeled are based on stakeholder input. Microsimulation allows for detailed modeling and visualization of the transportation networks including movements of individual vehicles and pedestrians. The results based on 2040 traffic volumes provided by the city based on their long-range travel demand model clearly demonstrate that the existing network cannot support the projected level of travel demand. It indicates that the city needs an aggressive travel demand management program to curb the growth of automobile traffic. The output also includes 3-D animations of the traffic flow that can be used in public forums for community outreach. A discussion for such a campaign based on best practices around using these visualizations for public outreach is also provided

Modeling influencing factors in a microscopic traffic simulator

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.Includes bibliographical references (p. 93-95).Microscopic traffic simulation is an important tool for traffic analysis and dynamic traffic management as it enables planners to evaluate traffic flow patterns, predict and evaluate the outcome of various response plans and assists in decision making. It is a vital tool for traffic management centers and can be helpful in developing contingency plans to enhance the safety and security of the transportation system. This thesis investigates the current state-of-the-practice in traffic microsimulation tools. A survey was developed and administered to developers. Results of the survey indicate critical gaps in including influencing external factors beyond the interaction of vehicles, such as incidents, work zones, or inclement weather, in traffic simulators. This thesis introduces a framework for incorporating such factors in existing models. The nature of the influencing factors limits disaggregate trajectory data collection generally needed to estimate driving behavior models. Therefore, an approach using aggregate calibration to refine and enhance existing driving behavior models is formulated. The aggregate calibration methodology is illustrated with a case study incorporating the effects of weather in driving behavior models using a freeway corridor in the Hampton Roads region of Virginia.(cont.) MITSIMLab, a microscopic traffic simulation laboratory that was developed for evaluating the impacts of alternative traffic management system designs at the operational level, is used for evaluation. The presence of precipitation was found to be significant in reducing speeds in the case study and was incorporated into the driving behavior models with aggregate calibration. This methodology was found to improve the simulation results, by reducing bias and variability. Assessment of the approach is discussed and recommendations for improvement and further study are offered.by Emily D. Sterzin.S.M