R. Michael Robinson

Route Change Decision Making by Hurricane Evacuees Facing Congestion

Successful evacuations of metropolitan areas require overcoming unexpected congestion that reduces traffic flows. Congestion may result from accidents, incidents, or other events that reduce road capacity. Traffic professionals and emergency managers may promote deviations from planned routes to bypass an area of congestion and speed mass exit. However, some route changes may actually reduce traffic flow rates, and in these cases decision makers may want to discourage use of alternate routes. By using results of a behavioral survey of potential hurricane evacuees, this study identifies variables associated with the decision to alter routes and also identifies frequently used information sources. A dynamic traffic simulation with a decision-making model using this information is proposed as a means for evacuation decision makers to assess impacts of driver decisions. Results from more than 800 responses showed the potentially strong influence of effective advanced traveler information systems to support decisions made by hurricane evacuees on whether to use an alternate route when faced with congestion. Results of this study are a timely contribution to those seeking a better understanding of driver behavior during evacuations and improvement of emergency management efficiency and efficacy.

Evacuee Route Choice Decisions in a Dynamic Hurricane Evacuation Context

Very high traffic volumes may lead to extensive congestion during hurricane evacuations. Evacuation planners reduce this congestion by careful planning for multiple hurricane scenarios and assignment of evacuation routes and timing. This planning may be for naught if obstructions block key roadways. An advanced traveler information system (ATIS) may be used to guide evacuees to alternate routes, but how effective will that guidance be? Should the use of alternate routes be encouraged? How are drivers likely to respond to delays and information? Will information shorten or improve the reliability of travel times in emergency conditions? Integration of a dynamic evacuation simulation and a decision-making model (representative of the decisions made by potential hurricane evacuees when provided with information on downstream traffic congestion and alternate routes) can help emergency planners prepare for the unexpected. Advance modeling of likely accident locations and the severity can forecast the effects of alternate route use, help determine the best locations and timing of alternate route information, and support decision making. This study integrated an evacuee route choice decision model and a mesoscopic evacuation transportation simulation for southeastern Virginia. Study results show how the effects of ATIS can be tested in advance, thus allowing more comprehensive planning by emergency management and transportation professionals. Simulations of ATIS’ effectiveness in evacuation scenarios have been largely unexplored. Methods presented can be applied in a variety of evacuation scenarios and may be of particular value to emergency planners.

Simulation analysis for evacuation under congested traffic scenarios: a case study

In this paper a new simulation modeling approach to support evacuation traffic management is introduced and a case study is presented. Traditional traffic simulation models neglect some real-life factors that need to be considered in an evacuation, such as the effect of road information and active control measures to manage traffic flow while vehicles are competing to find the best or preferred route. A passive equilibrium-seeking modeling approach may not be suitable for evacuation trip analysis due to limited route capacity and likely severe congestion during an evacuation. This paper introduces a new updated cell transmission model using discrete-event simulation, which can review and analyze the preferred path of evacuation traffic from multiple starting locations (or originations) to multiple destinations. Using this approach, case studies are conducted based on the user equilibrium principle, since it represents a natural behavior in an evacuation process. This research also demonstrates that, with the help of the cell transmission simulation model, an active traffic control mechanism can be evaluated. This study found that active traffic control measures are capable of decreasing total travel time during an evacuation by thousands of vehicle hours. Incorporating behavior consideration into the evacuation planning can help form a more accurate and realistic analysis of an evacuation plan.

Cyber risk to transportation, industrial control systems, and traffic signal controllers

This paper is a result of a cyber risk assessment with a goal of increasing awareness to operators of infrastructure, managers, and political leadership. Senior executives and political leaders have a very limited understanding of industrial control systems (ICS) and of the crucial role ICS provide to public/private infrastructure, industry, and military systems. Therefore, to accomplish our purpose, we conducted a cyber-risk study focusing on a bridge tunnel ICS and a cyber event that tampered with traffic light operation—two scenarios of concern for senior leaders. In this paper, we present the analytic approach, discuss our model and simulation, and analyze the results using a notational data and generic system description. As a result of this study, we were able to discuss the importance of controls systems with senior leaders. We were able to demystify what we mean by “cyber”, showing that it is possible through simulation to inject the effects of cyber scenarios of concern into simulations to assess impact. Most importantly, during a system audit, ICS operators with decades of engineering experience began to realize that the ICS is vulnerable to willful intrusion.

Conceptualizing intragroup and intergroup dynamics within a controlled crowd evacuation

Social dynamics play a critical role in successful pedestrian evacuations. Crowd modeling research has made progress in capturing the way individual and group dynamics affect evacuations; however, few studies have simultaneously examined how individuals and groups interact with one another during egress. To address this gap, the researchers present a conceptual agent-based model (ABM) designed to study the ways in which autonomous, heterogeneous, decision-making individuals negotiate intragroup and intergroup behavior while exiting a large venue. A key feature of this proposed model is the examination of the dynamics among and between various groupings, where heterogeneity at the individual level dynamically affects group behavior and subsequently group/group interactions. ABM provides a means of representing the important social factors that affect decision making among diverse social groups. Expanding on the 2013 work of Vizzari et al., the researchers focus specifically on social factors and decision making at the individual/group and group/group levels to more realistically portray dynamic crowd systems during a pedestrian evacuation. By developing a model with individual, intragroup, and intergroup interactions, the ABM provides a more representative approximation of real-world crowd egress. The simulation will enable more informed planning by disaster managers, emergency planners, and other decision makers. This pedestrian behavioral concept is one piece of a larger simulation model. Future research will build toward an integrated model capturing decision-making interactions between pedestrians and vehicles that affect evacuation outcomes.

Generic Incident Model for Investigating Traffic Incident Impacts on Evacuation Times in Large-Scale Emergencies

Traffic incidents cause a ripple effect of reduced travel speeds, lane changes, and the pursuit of alternative routes that results in gridlock on the immediately affected and surrounding roadways. The disruptions caused by the secondary effects significantly degrade travel time reliability, which is of great concern to the emergency planners who manage evacuations. Outcomes forecast by a generic incident model embedded in a microscopic evacuation simulation, the Real-Time Evacuation Planning Model (RtePM), were examined to quantify the change in time required for an emergency evacuation that results from traffic incidents. The incident model considered vehicle miles traveled on each individual segment of the studied road network model. The two scenarios considered for this investigation were evacuations of (a) Washington, D.C., after a simulated terrorist attack and (b) Virginia Beach, Virginia, in response to a simulated hurricane. These results could help the emergency planning community understand and investigate the impact of traffic incidents during an evacuation.

Panic That Spreads Sociobehavioral Contagion in Pedestrian Evacuations

Crowds are a part of everyday public life, from stadiums and arenas to school hallways. Occasionally, pushing within the crowd spontaneously escalates to crushing behavior, resulting in injuries and even death. The rarity and unpredictability of these incidents provides few options to collect data for research on the prediction and prevention of hazardous emergent behaviors in crowds. This study takes a close look at the way states of agitation, such as panic, can spread through crowds. Group composition—mainly family groups composed of members with differing mobility levels—plays an important role in the spread of agitation through the crowd, ultimately affecting the exit density and evacuation clearance time of a simulated venue. This study used an agent-based model of pedestrian movement during the egress of a hypothetical room and adopted an emotional, cognitive, and social framework to explore the transference and dissipation of agitation through a crowd. The preliminary results reveal that average group size in a crowd is a primary contributor to the exit density and evacuation clearance time. The study provides the groundwork on which to build more elaborate models that incorporate sociobehavioral aspects to simulate human movement during panic situations and account for the potential for dangerous behavior to emerge in crowds.

Path Clearance for Emergency Vehicles Through the Use of Vehicle-to-Vehicle Communication

The study described in this paper evaluated and tested a new strategy to enable emergency response vehicles (EVs) to navigate through congestion at signalized intersections more efficiently. The proposed strategy involves the use of vehicle-to-vehicle communication to send messages to alert vehicles to the approach of the EV and to provide specific instructions on maneuvering to allow the EV to proceed through congested signalized intersections as quickly as possible. This movement is achieved by creation of a split in the vehicle queue in one lane at a critical location to allow the EV to proceed at its desired speed but minimize the disruption to the rest of the traffic. The proposed method uses kinematic wave theory (i.e., shock wave theory) to determine the critical point in the vehicle queue. The proposed method is simulated in a microscopic traffic simulator for evaluation. The results show that this strategy can significantly shorten the travel time for EVs through congested signalized intersections.

Integrating Truck Emissions Cost in Traffic Assignment

The adverse impacts of greenhouse gasses (GHG) and the imperative for reducing the existing rate of GHG production are well established. In the United States, the largest source of GHG emissions from human activities is from burning fossil fuels, primarily for the generation of electricity and transportation. The transportation sector accounts for 28% of all U.S. GHG production. Heavy-duty vehicles, such as large freight trucks, account for nearly one-fifth of the U.S. total, and this fraction is expected to grow rapidly. Consequently, many efforts are being used to reduce the total emissions of freight trucks. Most efforts emphasize one of four areas: engineering improvements to improve fuel economy or reduce emissions, shifts to other transport modes, improved logistics to reduce the movement of partially full or empty containers, and reduced travel costs for individual trucks. A few studies have assessed modifications to route choice considerations as a means of improving the fuel economy of individual vehicles and show potential gains. In this study, the potential gains of emissions-based route choice were assessed by integrating the U.S. Environmental Protection Agency motor vehicle emission simulator with a macroscopic regional traffic demand model. For this integration, route choices included a simplified emissions calculation within the repeated model iteration runs of an algorithm of the Frank–Wolfe type. The analyses suggested that reductions of freight truck emissions were possible and showed an example in which the total systems truck emissions were reduced by up to 0.61% (88.8 tons).

Exploring a Toll Auction Mechanism Enabled by Vehicle-to-Infrastructure Technology

High-occupancy toll (HOT) lanes—an increasingly popular solution for congested roadway networks—give drivers the option to access express lanes. The cost of entry often varies with demand, although no standard method of optimizing these price points exists. Using the principles of a Vickrey auction that incentivizes true-value bids, this paper proposes a tolling system that uses vehicle-to-infrastructure technology to optimize toll operator revenue with HOT lane usage. In the scenario, a roadway network consists of a HOT lane and a general-purpose lane, each with identical physical properties. Drivers can access the HOT lane at the start of the facility or at one interim point along the roadway. With the use of a triangular distribution to approximate the distribution of travelers’ value of time (VOT), the model explores the impact of varying the distributions mode on revenue earned by the toll operator. Results from the model indicate that when the toll operator maximizes the models revenue, the percentage of auction bids accepted for toll road access is robust to changes in the VOT distribution. This percentage equates to approximately 17% of vehicles accessing the facility. Given the difficulty in obtaining actual travelers’ distribution of VOT, this auction tolling mechanism implies that obtaining an exact VOT distribution may not be necessary for this type of tolling analysis.