2013 Session: 772

• Empirical Evacuation Response Curve During Hurricane Irene in Cape May County, New Jersey
  Abstract: Understanding evacuation response behavior is critical for public officials in deciding when to issue emergency evacuation orders during an impending hurricane. Such behavior is typically measured by an evacuation response curve that represents the proportion of total evacuation demand over time during evacuation. This study analyzes evacuation behavior and constructs the evacuation response curve based on traffic data collected during Hurricane Irene (2011) in Cape May County, New Jersey. The evacuation response curve follows a general S-shape with sharp upward changes in slope following the issuance of mandatory evacuation notices. The sharp upward changes in slope represent quick response behavior, which may be in part caused by an easily mobilized tourist population, lack of hurricane evacuation experience, and/or the nature of the location, which in this case is a rural area with limited evacuation routes. Moreover, the widely used S-curves with different mathematical functions and state-of-art behavior models are calibrated and compared with empirical data. The results show that the calibrated S-curves with Logit and Rayleigh functions fit better with empirical data. The evacuation behavior analysis and calibrated evacuation response models based on this recent Hurricane evacuation event may benefit evacuation planning in similar areas. In addition, traffic data used in this study may also be valuable for the comparative analysis of traffic patterns between the evacuation periods and regular weekdays/weekends.
  Authors: Li, Jian; Ozbay, Kaan; Bartin, Bekir; Iyer, Shrisan; Carnegie, Jon
  Authors: Li, Jian; Ozbay, Kaan; Bartin, Bekir; Iyer, Shrisan; Carnegie, Jon
  Year: 2013
  Document Type: Paper
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-0285
• Sensitivity of Evacuation Performance Estimates to Evacuee Route Choice Behavior
  Abstract: The objective of this paper is to illustrate the sensitivity of evacuation travel time estimates with respect to the assumptions made regarding evacuee route choice behavior. The user equilibrium (UE) assignment procedure in which evacuees are assumed to choose the shortest (or fastest) path from their origins to destinations is considered as the base case. Very few studies have documented the actual route choice behavior of evacuees during a hurricane. These studies were used to develop realistic route choice behavior assumptions - the different types of route choices and proportion of evacuees for those types. The impact of route choice behavior on evacuation performance, especially travel times, was then explored using a large-scale regional simulation model of the Hampton Roads region in Virginia. The model was developed in an earlier study using real-world network data and actual evacuee behavioral data. The analysis indicated that using UE to generate average travel time estimates for evacuation planning significantly underestimates the actual travel times realized during an evacuation. The extent of underestimation of evacuation travel times depends on the total evacuation demand (a function of storm intensity), and the percent of evacuees willing to use en-route information to seek alternate routes when facing congestion. For the three en-route percentages reported in the literature i.e., 30%, 50%, and 70%, the UE travel times were 48%, 37%, and 29% lower than actual travel times realized in a category 1; 99%, 78%, and 63% lower in a category 2; and 88%, 72%, and 52% lower in a category 3 evacuation.
  Authors: Fang, Lei; Edara, Praveen
  Authors: Fang, Lei; Edara, Praveen
  Year: 2013
  Document Type: Paper
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-2227
• Modeling of Bus Transit Driver Availability for Effective Emergency Evacuation in Disaster Relief
  Abstract: Evacuation population without access to personal automobiles are expected to utilize transit, especially buses, to reach safer regions. For a transit agency, operation problems to be considered include establishing bus launch areas, positioning the minimum number of required buses and, coordination of transit operators, especially addressing the question of whether the number of drivers will be sufficient to cover the number of vehicles (i.e. buses) planned to be used during the evacuation. It is also highly probable that during an emergency, absenteeism rates for the bus drivers might increase. In this study, we develop two stochastic models to determine extra driver needs during an emergency evacuation operation and to provide optimal solutions using well-established concepts in mathematical programming. Firstly we reviewed the existing literature needed to develop an effective methodology for the development of optimal extraboard management strategies and found that although several recent reports clearly mention the problem of not having sufficient number of bus drivers during emergency evacuation operations (5, 7) there is no analytical study that incorporates the optimal extraboard size problem into emergency evacuation operations. Secondly, two mathematical models are presented in this report. The aim of the developed models are to fill the gap in the literature for determining optimal extraboard size for transit operations during an emergency evacuations. The models are designed to capture different characteristics of decision-makers regarding their risk-taking behavior. Lastly, these models are tested using hypothetical examples based on real-world data extracted from New Jersey. Results show that both models give reasonable extraboard size estimates and under different conditions the models are responsive to the changes in cost and quality of service preferences. The results are encouraging in terms of the models’ usefulness for real-world applications.
  Authors: Morgul, Ender Faruk; Cavus, Ozlem; Ozbay, Kaan; Iyigun, Cem
  Authors: Morgul, Ender Faruk; Cavus, Ozlem; Ozbay, Kaan; Iyigun, Cem
  Year: 2013
  Document Type: Paper
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-4602
• Predictive Qualities of Evacuation Time-Dependent Sequential Logit Demand Model
  Abstract: The results of a study that examined the predictive accuracy of time-dependent sequential logit evacuation demand model is presented in this paper. Predictive accuracy of a time-dependent sequential logit demand model calibrated on Hurricane Gustav’s data was tested on stated choice data collected on nine hypothetical storms. The stated choice data was collected using a novel methodology and a mail-out mail-back self-administered survey from 300 households in New Orleans region. The percentage root mean square error of prediction ranged from 10.39 to 26.74 for all the storms. The results of the empirical analysis suggest that a disaggregate evacuation demand model can be used to predict future evacuation behavior with reasonable levels of accuracy. The results will prove useful for researchers working in evacuation demand modeling and evacuation simulation.
  Authors: Gudishala, Ravindra; Wilmot, Chester G.
  Authors: Gudishala, Ravindra; Wilmot, Chester G.
  Year: 2013
  Document Type: Paper
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-4552
• Empirical Evacuation Response Curve During Hurricane Irene in Cape May County, New Jersey
  Authors: Li, Jian
  Authors: Li, Jian
  Year: 2013
  Document Type: Presentation
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-0285
• Sensitivity of Evacuation Performance Estimates to Evacuee Route Choice Behavior
  Authors: Edara, Praveen
  Authors: Edara, Praveen
  Year: 2013
  Document Type: Presentation
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-2227
• Modeling of Bus Transit Driver Availability for Effective Emergency Evacuation in Disaster Relief
  Authors: Morgul, Ender Faruk
  Authors: Morgul, Ender Faruk
  Year: 2013
  Document Type: Presentation
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-4602
• Predictive Qualities of Evacuation Time-Dependent Sequential Logit Demand Model
  Authors: Gudishala, Ravindra
  Authors: Gudishala, Ravindra
  Year: 2013
  Document Type: Presentation
  Subject: Operations and Traffic Management; Safety and Human Factors; Security and Emergencies
  Session: 772
  Paper Number: 13-4552