Shih-Miao Chin

Global Optimization of Emergency Evacuation Assignments

Conventional emergency evacuation plans often assign evacuees to fixed routes or destinations based mainly on geographic proximity. Such approaches can be inefficient if the roads are congested, blocked, or otherwise dangerous because of the emergency. By not constraining evacuees to prespecified destinations, a one-destination evacuation approach provides flexibility in the optimization process. We present a framework for the simultaneous optimization of evacuation-traffic distribution and assignment. Based on the one-destination evacuation concept, we can obtain the optimal destination and route assignment by solving a one-destination traffic-assignment problem on a modified network representation. In a county-wide, large-scale evacuation case study, the one-destination model yields substantial improvement over the conventional approach, with the overall evacuation time reduced by more than 60 percent. More importantly, emergency planners can easily implement this framework by instructing evacuees to go to destinations that the one-destination optimization process selects.

Proposed Framework for Simultaneous Optimization of Evacuation Traffic Destination and Route Assignment

In the conventional evacuation planning process, evacuees are assigned to fixed destinations mainly on the basis of geographical proximity. However, the use of such prespecified destinations (an origin-destination table) almost always results in less-than-optimal evacuation efficiency because of uncertain road conditions, including traffic congestion, road blockage, and other hazards associated with the emergency. By relaxing the constraint of assigning evacuees to prespecified destinations, a one-destination evacuation (ODE) concept has the potential to improve evacuation efficiency greatly. To this end, a framework for the simultaneous optimization of evacuation traffic distribution and assignment is proposed. The ODE concept can be used to obtain an optimal destination and route assignment by solving a one-destination (1D) traffic assignment problem on a modified network representation. When tested for a countywide special event-based evacuation case study, the proposed 1D model presents substantial im...

Estimating the Impact of Pickup- and Delivery-Related Illegal Parking Activities on Traffic

Illegal parking of delivery trucks used for pickup and delivery (PUD) reduces traffic capacity and causes delays. A geographically based combinatorial model was developed to estimate the extent of capacity losses and subsequent delays. The model uses a geographically based inference engine to extract data from several large-scale databases and process the data. These data are presented and compared with data from other temporary loss-of-capacity events. Because only weekday and daytime activities were studied, the resulting estimate of the national PUD effect is somewhat conservative.

Short-Term Freeway Speed Profiling Based on Longitudinal Spatiotemporal Dynamics

Short-term traffic forecasting accuracy is related closely to the use of neighboring traffic information. Multivariate forecasting methods are becoming more popular because of their ability to capture both temporal and spatial evolvement in traffic. However, little attention has been given to quantify the effect of upstream and downstream traffic information, and the vast majority of published studies assume that the spatiotemporal relationship is specified in advance. Thus, the selection of surrounding traffic information as input parameters is somewhat arbitrary. To address that issue, this study investigated spatiotemporal relationships of speed series from consecutive segments under different traffic conditions by using the link speeds for nine segments extending over 12 mi on I-24 in Nashville, Tennessee. A prewhitened cross-correlation technique was proposed first to clarify the cross correlations between two speed series. The prewhitened cross-correlation function was performed on speed series for consecutive freeway segments for periods including the morning peak, midday off-peak, and evening peak. The analysis results showed that the correlations for consecutive segments were highly related to traffic conditions and that the effect of downstream traffic increased with the severity of congestion. Influences of upstream and downstream locations on current traffic were also found to be not symmetric in regard to the current site. The algorithm on properly choosing neighboring traffic information was proposed, and the lagged regression model with correctly identified input parameters (segments) outperformed others.

Routing Hazardous Materials around the District of Columbia Area

The recent hazardous material (hazmat) shipment ban in Washington, D.C., has led to debates, legal challenges, and considerations by other major cities to pursue similar actions. This article presents a methodology for evaluating hazmat shipment routing options on railroad networks under situations such as the shipment ban. A case study involving three alternatives is presented. Population and other vulnerable people within a 0.8 km (or 0.5 mile) radius buffer zone along the rail line are used to evaluate the potential risk associated with ultra-hazardous material (i.e., explosives, flammable gasses, poisonous gasses, and poisonous materials) shipments. Based on this study, it is concluded that moderate increases in ton-km, and subsequently time in transit, will be a result from the rerouting. On the other hand, the overall population at risk will see a reduction. The population-at-risk burden, however, is simply shifted from one location to other locations. This article also identifies areas for potential follow-up efforts.

Geospatial Products and Techniques at the Center for Transportation Analysis

ABSTRACT This paper highlights geospatial science-related innovations and developments conducted by the Center for Transportation Analysis (CTA) at the Oak Ridge National Laboratory. CTA researchers have been developing integrated inter-modal transportation solutions through innovative and cost-effective research and development for many years. Specifically, this paper profiles CTA-developed Geographic Information System (GIS) products that are publicly available. Examples of these GIS-related products include: the CTA Transportation Networks; GeoFreight system; and the Web-based Multi-Modal Routing Analysis System. In addition, an application on assessment of railroad hazmat routing alternatives is also discussed.

A Kriging based spatiotemporal approach for traffic volume data imputation

Along with the rapid development of Intelligent Transportation Systems, traffic data collection technologies have progressed fast. The emergence of innovative data collection technologies such as remote traffic microwave sensor, Bluetooth sensor, GPS-based floating car method, and automated license plate recognition, has significantly increased the variety and volume of traffic data. Despite the development of these technologies, the missing data issue is still a problem that poses great challenge for data based applications such as traffic forecasting, real-time incident detection, dynamic route guidance, and massive evacuation optimization. A thorough literature review suggests most current imputation models either focus on the temporal nature of the traffic data and fail to consider the spatial information of neighboring locations or assume the data follow a certain distribution. These two issues reduce the imputation accuracy and limit the use of the corresponding imputation methods respectively. As a result, this paper presents a Kriging based data imputation approach that is able to fully utilize the spatiotemporal correlation in the traffic data and that does not assume the data follow any distribution. A set of scenarios with different missing rates are used to evaluate the performance of the proposed method. The performance of the proposed method was compared with that of two other widely used methods, historical average and K-nearest neighborhood. Comparison results indicate that the proposed method has the highest imputation accuracy and is more flexible compared to other methods.

Shared Freight Transportation and Energy Commodities Phase One: Coal, Crude Petroleum, & Natural Gas Flows

The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of nationwide freight movements among states and major metropolitan areas for all modes of transportation. It provides a national picture of current freight flows to, from, and within the United States, assigns selected flows to the transportation network, and projects freight flow patterns into the future. The latest release of FAF is known as FAF4 with a base year of 2012. The FAF4 origin-destination-commodity-mode (ODCM) matrix is provided at national, state, major metropolitan areas, and major gateways with significant freight activities (e.g., El Paso, Texas). The U.S. Department of Energy (DOE) is interested in using FAF4 database for its strategic planning and policy analysis, particularly in association with the transportation of energy commodities. However, the geographic specification that DOE requires is a county-level ODCM matrix. Unfortunately, the geographic regions in the FAF4 database were not available at the DOE desired detail. Due to this limitation, DOE tasked Oak Ridge National Laboratory (ORNL) to assist in generating estimates of county-level flows for selected energy commodities by mode of transportation.

RTMAS: an expert system for real time monitoring and analysis of traffic during evacuations

An imminent hurricane, a problem with a nuclear reactor, the escape of a dangerous gas, a large chemical spill, or even a serious threat from a foreign country are all examples of some very recent reasons for large urban populations to leave their homes until the threat to their lives and property has passed. Whether largely spontaneous, or carefully orchestrated by local authorities, such evacuations may take place over many hours or even days. To date, there has been no significant monitoring of large scale evacuations, since they occur as either rapidly developing localized threats, such as hurricanes, or for more protracted threat build-ups.