Modeling Lane-based Traffic Flow In Emergency Situations In The Presence Of Multiple Heterogeneous Flows

In recent years, natural, man-made and technological disasters have been increasing in magnitude and frequency of occurrence. Terrorist attacks have increased after the September 11, 2001. Some authorities suggest that global warming is partly the blame for the increase in frequency of natural disasters, such as the series of hurricanes in the early-2000\u27s. Furthermore, there has been noticeable growth in population within many metropolitan areas not only in the US but also worldwide. These and other facts motivate the need for better emergency evacuation route planning (EERP) approaches in order to minimize the loss of human lives and property. This research considers aspects of evacuation routing never before considered in research and, more importantly, in practice. Previous EERP models only either consider unidirectional evacuee flow from the source of a hazard to destinations of safety or unidirectional emergency first responder flow to the hazard source. However, in real-life emergency situations, these heterogeneous, incompatible flows occur simultaneously over a bi-directional capacitated lane-based travel network, especially in unanticipated emergencies. By incompatible, it is meant that the two different flows cannot occupy a given lane and merge or crossing point in the travel network at the same time. In addition, in large-scale evacuations, travel lane normal flow directions can be reversed dynamically to their contraflow directions depending upon the degree of the emergency. These characteristics provide the basis for this investigation. This research considers the multiple flow EERP problem where the network travel lanes can be reconfigured using contraflow lane reversals. The first flow is vehicular flow of evacuees from the source of a hazard to destinations of safety, and the second flow is the emergency first responders to the hazard source. After presenting a review of the work related to the multiple flow EERP problem, mathematical formulations are proposed for three variations of the EERP problem where the objective for each problem is to identify an evacuation plan (i.e., a flow schedule and network contraflow lane configuration) that minimizes network clearance time. Before the proposed formulations, the evacuation problem that considers only the flow of evacuees out of the network, which is viewed as a maximum flow problem, is formulated as an integer linear program. Then, the first proposed model formulation, which addresses the problem that considers the flow of evacuees under contraflow conditions, is presented. Next, the proposed formulation is expanded to consider the flow of evacuees and responders through the network but under normal flow conditions. Lastly, the two-flow problem of evacuees and responders under contraflow conditions is formulated. Using real-world population and travel network data, the EERP problems are each solved to optimality; however, the time required to solve the problems increases exponentially as the problem grows in size and complexity. Due to the intractable nature of the problems as the size of the network increases, a genetic-based heuristic solution procedure that generates evacuation network configurations of reasonable quality is proposed. The proposed heuristic solution approach generates evacuation plans in the order of minutes, which is desirable in emergency situations and needed to allow for immediate evacuation routing plan dissemination and implementation in the targeted areas

The MATSim Network Flow Model for Traffic Simulation Adapted to Large-Scale Emergency Egress and an Application to the Evacuation of the Indonesian City of Padang in Case of a Tsunami Warning

The evacuation of whole cities or even regions is an important problem, as demonstrated by recent events such as evacuation of Houston in the case of Hurricane Rita or the evacuation of coastal cities in the case of Tsunamis. This paper describes a complex evacuation simulation framework for the city of Pandang, with approximately 1,000,000 inhabitants. Padang faces a high risk of being inundated by a tsunami wave. The evacuation simulation is based on the MATSim framework for large-scale transport simulations. Different optimization parameters like evacuation distance, evacuation time, or the variation of the advance warning time are investigated. The results are given as overall evacuation times, evacuation curves, an detailed GIS analysis of the evacuation directions. All these results are discussed with regard to their usability for evacuation recommendations.BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIENBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacitie

A Generalized Minimum Cost Flow Model for Multiple Emergency Flow Routing

During real-life disasters, that is, earthquakes, floods, terrorist attacks, and other unexpected events, emergency evacuation and rescue are two primary operations that can save the lives and property of the affected population. It is unavoidable that evacuation flow and rescue flow will conflict with each other on the same spatial road network and within the same time window. Therefore, we propose a novel generalized minimum cost flow model to optimize the distribution pattern of these two types of flow on the same network by introducing the conflict cost. The travel time on each link is assumed to be subject to a bureau of public road (BPR) function rather than a fixed cost. Additionally, we integrate contraflow operations into this model to redesign the network shared by those two types of flow. A nonconvex mixed-integer nonlinear programming model with bilinear, fractional, and power components is constructed, and GAMS/BARON is used to solve this programming model. A case study is conducted in the downtown area of Harbin city in China to verify the efficiency of proposed model, and several helpful findings and managerial insights are also presented

Large-scale Zone-based Evacuation Planning: Generating Convergent and Non-Preemptive Evacuation Plans via Column Generation

In zone-based evacuations, the evacuated region is divided into zones, and vehicles follow the single evacuation path assigned to their corresponding zone. Ideally, these evacuation paths converge at intersections to reduce driver hesitation; and non-preemptive schedules ensure that the evacuation of a zone proceeds without interruptions once it starts. We present a column-generation algorithm that produces convergent and non-preemptive evacuation plans in real large-scale evacuation scenarios. Furthermore, we compare our algorithm against existing models that produce convergent paths or non-preemptive schedules separately. Finally, we use a traffic simulator to evaluate the quality of the generated plans

Evacuation Planning Based on the Contraflow Technique With Consideration of Evacuation Priorities and Traffic Setup Time

Evacuation planning with the contraflow technique is a complex planning problem. The problem is further complicated when more realistic situations such as evacuation priorities and the setup time for the contraflow operation are considered. Such a complex problem has yet to be discussed in the present literature. In this paper, we present a multipleobjective optimization model for this problem and a two-layer algorithm to solve this model. Experiments on three transportation networks with different network scales are presented to show the excellent performance of the proposed model and algorithm.published_or_final_versio

Using Contraflow on a Road Segment to Improve Emergency Response Vehicle Speed in a Connected Vehicle Environment

Emergency response vehicles (ERVs) need to reach their destinations as fast as possible. Road congestion and unpredictable movement of non-emergency vehicles (non-ERVs) makes it challenging for the ERV to move quickly. By using the autonomous/connected vehicle environment, instructions can be disseminated to the non-ERVs in the vicinity of the ERV to facilitate its passage within a link. In this thesis, an extension to a previously developed mathematical program is proposed to enable the ERV to use a contraflow lane when considerable speed gains can be potentially achieved. An experimental analysis is conducted to evaluate the sensitivity of the model’s output to traffic congestion, downstream non-ERV positions, ERV starting position, road composition, road segment length, and the length of the feasible stopping range for every non-ERV. Results showed that usage of contraflow was provided the least travel times for the ERV when it started in the left-most lane of the normal direction. Also, when the normal direction of the road was heavily congested as compared to the contraflow segment, the usage of contraflow by the ERV provided it the least travel times. In addition, a comparative study is performed to compare the proposed formulation with previously developed non-contraflow strategies as well as the currently adopted strategy requiring vehicles to move to the nearest edge. Results showed that the use of contraflow by the ERV provides improved travel times and average ERV speeds in many situations when the contraflow segment volume was sparse whereas the normal direction was congested. However, the computation times for the newly developed contraflow strategy were greater than the previously developed non-contraflow strategies. So, a heuristic was developed to reduce computational effort by cutting off the solver at a specified point, which was decided by how far the current feasible solution found was from the possible optimal solution (optimality gap). This heuristic not only provided improved computation times, but also results which did not statistically differ from the optimal results. The paths provided by the heuristic were also similar with the only difference being the points at which the lane changes happened. Hence, the utilization of this approach can potentially save lives due to reduced emergency response times