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This paper presents a heuristic contraflow-based reconfiguration evacuation algorithm, which is named Capacity-Constrained Contraflow Adaption (CC-Adap). First, it effectively calculates optimal candidate routes for evacuation. Second, an evaluation method is proposed for estimating these candidate routes. Third, CC-Adap utilizes a contraflow-based method to reconfigure the evacuation routes to improve capacity constraints. Fourth, traffic conditions are updated in real time. Fifth, CC-Adap reuses historical evacuation routes to reduce the computational cost and accelerate the evacuation process. Experimental results show that CC-Adap generates high-performing evacuation strategies and can be used to tackle large-scale evacuation planning.

In recent years, both natural and man-made disasters have posed serious threats to humans, such as Hurricane Andrew [

A well-known routing algorithm, namely, Capacity-Constrained Route Planner (CCRP) [

In this paper, we propose a Capacity-Constrained Contraflow Adaption (CC-Adap) algorithm for effective evacuation. CC-Adap consists of five steps. First, we utilize an evacuation algorithm to generate optimal candidate routes for evacuees, which finds the routes with maximal flow rate among all the available routes from source vertices to sink vertices. Second, we propose an evaluation method for heuristically evaluating the candidate routes’ capabilities based on the traffic conditions and determining the appropriate routes for evacuation. Then, we implement a contraflow-based method for optimizing the routes’ performances and reducing traffic congestion. Next, traffic conditions are updated in real time to make the route planning more practical. Finally, CC-Adap reuses the historical evacuation routes before calculating the available routes at each new time step. Experimental results indicate that CC-Adap boosts performance in evacuation route planning.

The remainder of this paper is organized as follows: Section

To the best of our knowledge, the existing methods can be divided into descriptive and prescriptive approaches [

The aim of descriptive methods is to simulate traffic evacuation situations as vividly as possible. Many traffic evacuation simulation tools have been proven to be capable of solving complex traffic evacuation problems, including MITSIMLab [

Prescriptive methods typically provide suggested schedules for evacuation planners, aiming at reducing traffic congestion and minimizing total evacuation time. Zeng and Wang made a small modification to CCRP to improve the performance, which gives priority to longer evacuation routes for evacuating evacuees [

Previous works [

Above-mentioned contraflow-based methods are selected to generate contraflow strategy that can tackle capacity constraints effectively [

So, this paper presents a prescriptive algorithm to generate appropriate contraflow strategy and optimal evacuation plan. For the first difficulty, the presented algorithm utilizes Greedy method and iterative optimization technique to select the to-be-reversed edges on the evacuation routes. For the second difficulty, the ideal direction of these to-be-reversed edges is determined by the traffic flow on the evacuation routes.

Various methods, such as simulation [

Suppose we are given a multisource and multisink transportation network

Each vertex

Each edge

There are different traffic elements in transportation network including buildings, crossroads, playgrounds, shelters, and parks. Buildings, crossroads, and playgrounds are the most common traffic elements in transportation network. Figure

Illustration of the vertices and edges.

Source vertex

Transition vertex

Sink vertex

The objective of transportation evacuation is to find an optimal plan with minimum evacuation time. The objective function is defined in

Formula (

In a large transportation network, long distance traffic jams usually cover the roads when emergencies occur. Contraflow-based methods are considered effective techniques for remedying traffic congestion [

Figure

An evacuation scenario and two contraflow-based evacuation plans.

Original network

Evacuation planning 1

Evacuation planning 2

This paper proposes the CC-Adap algorithm, which heuristically evaluates the evacuation routes, and integrates it with a contraflow-based method for distributing the evacuation routes with the least traffic congestion and maximal flow rate to evacuees. In addition, CC-Adap reuses historical evacuation routes to reduce computational costs and accelerate the evacuation process. Algorithm

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For a given network

CC-Adap utilizes the evacuation route generation method in the Max-Flow Rate Priority (MFRP) algorithm [

The main strategy of the MFRP algorithm [

The use of low-quality routes might aggravate traffic congestion and increase the total evacuation time. CC-Adap introduces a parameter

where

The

Greedy method can be used in evacuation route planning [

Figure

Example of the proposed contraflow-based method.

Original network

Select evacuation route

Contraflow result

After evacuees are transferred from source vertex to sink vertex, the available residual capacities of transition vertices and edges along route

Based on (

When there is no available evacuation route at the current time step, CC-Adap proceeds to the next time step (

The

In each iteration, the generated route

There are many evacuation algorithms that can provide evacuation route planning, such as the classical CCRP algorithm [

In this paper, we use the following notations to describe evacuation situations:

The purpose of this section is to evaluate the feasibility of using CC-Adap in evacuation planning. CC-Adap is compared with CCRP and MFRP to determine whether CC-Adap can be used for evacuation planning and to optimize evacuation plans by applying a contraflow-based method.

In this section, two experiments are carried out. Each experiment has five test groups and the number of vertices, edges, source, and sink vertices is fixed. We vary the number of evacuees from 20000 to 100000. Figures

Evacuation quality in a small transportation network.

Evacuation quality in a large transportation network.

The purpose of this section is to evaluate the scalability of CC-Adap to complex evacuation situations and CC-Adap is compared with CCRP, MFRP, and Greedy algorithms.

Evacuation quality with respect to the number of edges.

Evacuation quality with respect to the number of evacuees.

Evacuation quality with respect to the number of source and sink vertices.

Evacuation quality of large-scale transportation network evacuation.

There are many dynamic factors that are critical to the transportation network, such as number of evacuees and affected areas, which makes evacuation management a daunting task. These dynamic factors can be evaluated systematically by building appropriate evacuation models [

This paper presents a heuristic contraflow reconfiguration evacuation algorithm, which is called Capacity-Constrained Contraflow Adaption algorithm. CC-Adap can heuristically evaluate evacuation routes to assign high-quality routes to evacuees. Moreover, the proposed contraflow-based method is applied to reconfigure evacuation routes to reduce traffic congestion and improve evacuation performance. Meanwhile, CC-Adap reuses historical evacuation routes to reduce computational costs and accelerate the evacuation process. Experimental results have shown that the CC-Adap algorithm can optimize evacuation route planning in terms of evacuation time and run time.

However, more research is required for CC-Adap. First, a more effective evacuation route generation method should be constructed. Second, the evaluation method should be improved to evaluate the evacuation routes more effectively.

The data used to support the findings of this study are available from the first author.

The authors declare that they have no conflicts of interest.

This work is supported by the National Key Research and Development Program of China (no. 2016YFB0502600) and the National Natural Science Foundation of China (no. 41701594).