Traffic Evacuation Research Articles

Modeling Traffic Disruptions during Mass Evacuation

Abstract This study develops a traffic evacuation microsimulation model that accounts for disruptions during evacuation. The proposed model considers vehicle collision related disruptions endogenous to the traffic simulation model. A rich collision data set ‘Nova Scotia Collision Record Database’ is utilized for the study. A Bayes theory approach is adopted to determine the most likely collision hotspots, which are coded within a dynamic traffic microsimulation model using a collision generation module. In total, six hotspots are identified that hinder evacuation traffic flows within an evacuation area. The results reveal that collisions significantly impact evacuation. For instance, collision-related disruption increases complete evacuation time by almost 50% compared to evacuation scenario without disruptions. Downtown street may anticipate a long queue of 1km just within the 3rd hour of evacuation. The simulation results will help emergency professionals to understand the network vulnerability to incidents and develop contingency plans to deal with uncertainties of evacuation.

Tsunami-induced traffic evacuation strategy optimization

An optimal traffic evacuation strategy is of practical importance to minimize potential devastating damages caused by tsunamis. In this study, we developed a tsunami-induced, network-wide traffic evacuation optimization strategy. A hierarchical evacuation structure is established to guide vehicle routing decisions. At the first stage of evacuation, the optimization objective is to minimize the maximum evacuation time for all the individual evacuees from affected areas to temporary shelter zones to satisfy their primary safety needs within the shortest time periods. At the second stage of evacuation, the optimization objective aims to minimize the total evacuation time of all the evacuees from temporary shelter zones to safe zones. The lexicographic minimax optimization and Tabu search techniques are adopted to obtain a unique solution. Numerical examples are conducted to demonstrate the effectiveness of the developed model based on a real transportation network in Honolulu, Hawaii. The proposed evacuation strategy contributes to the state of the art by innovatively balancing the evacuation safety priority and the evacuation efficiency in the hierarchical evacuation structure. The research findings are helpful for decision makers to develop optimal tsunami-induced, network-wide traffic evacuation strategies.

Mapping knowledge structure and research trends of emergency evacuation studies

To understand the current development and status of research on emergency evacuation, the published literature in the Web of Science core database from 2008 to 2018 were taken as the research objects, and the knowledge structure and research trends in the field of emergency evacuation were visualized and analyzed by using the scientific mapping knowledge domain. It is found that research on emergency evacuations throughout the world has a basic theoretical framework, but the various research branches have not yet formed a perfect knowledge network. The results show that China's publishing volume ranks first among countries/regions, and Tsinghua University has the largest number of publications among related institutions; traffic evacuation modeling, group behavior and crowd evacuation are the main knowledge groups for emergency evacuation research; the research fields mainly include disaster emergency management, personnel evacuation simulation and emergency traffic evacuation; and the research topic of emergency evacuation mainly evolves into three core paths, namely, “disaster - management - preparation - response – information”, “evacuation - behavior - model - cellular automaton - time – design” and “evacuation - behavior - simulation - social force model - exit choice”. Crowd evacuation and exit choice have become the frontiers of current emergency evacuation research.

浅谈某核电一期（AP1000）汽机房建筑设计

A nuclear power project phase I (AP1000) has many “world No.1”. It is so many “first”, put forward unprecedented challenges to the design of the turbine building. This paper introduces the composition of each part of the turbine building, and analyses the problems of the turbine building, such as traffic evacuation, fire prevention, waterproof, lighting, ventilation, corrosion prevention. The characteristics of turbine building design are further discussed. The energy saving of turbine building and the design method and process of the building facade are also analyzed. The completion and production of the Nuclear Power Project Phase I have accumulated valuable experience and provided reference for subsequent projects.

Simulacija evakuacije iz Terazijskog tunela

Evacuation presents a very complex and difficult task that implies the safest, shortest and fastest convoying of people, animals and material resources from an endangered object or location to a secure location. Different objects, different locations and different scenarios demand different evacuation strategies. One of very specific objects for evacuation is a road traffic tunnel. Because of the presence of a number of vehicles and people within limited space, road traffic tunnel evacuation can be an extremely unpredictable and dangerous task, which has already been confirmed by many accidents. There are also other aggravating circumstances such as tunnel length, fast spreading of smoke (especially of CO2 - carbon dioxide and COcarbon monoxide) and fire in closed areas, limited options for approach to the accident place and many others, very often impossible to predict. One of very good, economical and safe ways for the prediction and analysis of evacuation situations and scenarios is the usage of simulation software. This paper has been written to show a simulation of evacuation from the road traffic tunnel at Terazije in Belgrade for different scenarios and for different speeds of participants

Efficient multi-vehicle navigation based on trajectory vector features considering non-uniform destination distribution for emergency evacuation

In recent years, large-scale events have been held frequently, and more and more people are participating in these activities. When encountering an emergency, it is necessary to quickly evacuate the participating people. A reasonable traffic evacuation plan is an important part of the efficient evacuation. However, the uneven geographical distribution of a large number of vehicles and participants poses a challenge for efficient evacuation planning. An efficient emergency evacuation plan needs to minimise evacuation time and traffic congestion. Reasonable route selection and traffic flow assessment are key to the evacuation plan. In this paper, we propose an efficient multi-vehicle navigation method based on trajectory vector features considering non-uniform destination distribution for emergency evacuation. First, we employ the CrossRank algorithm to extract the real-time state vector of roads and then navigate the vehicle based on these state vectors. In addition, spatial diversity theory is introduced into our model for the non-uniform distribution of multiple vehicle evacuation. We conduct a series of multi-vehicle navigation simulation experiment on a real taxi trajectory data set. The experimental results demonstrate that our approach is effective and efficient.

Efficient multi-vehicle navigation based on trajectory vector features considering non-uniform destination distribution for emergency evacuation

In recent years, large-scale events have been held frequently, and more and more people are participating in these activities. When encountering an emergency, it is necessary to quickly evacuate the participating people. A reasonable traffic evacuation plan is an important part of the efficient evacuation. However, the uneven geographical distribution of a large number of vehicles and participants poses a challenge for efficient evacuation planning. An efficient emergency evacuation plan needs to minimise evacuation time and traffic congestion. Reasonable route selection and traffic flow assessment are key to the evacuation plan. In this paper, we propose an efficient multi-vehicle navigation method based on trajectory vector features considering non-uniform destination distribution for emergency evacuation. First, we employ the CrossRank algorithm to extract the real-time state vector of roads and then navigate the vehicle based on these state vectors. In addition, spatial diversity theory is introduced into our model for the non-uniform distribution of multiple vehicle evacuation. We conduct a series of multi-vehicle navigation simulation experiment on a real taxi trajectory data set. The experimental results demonstrate that our approach is effective and efficient.

Big data oriented intelligent traffic evacuation path fuzzy control system

Big data oriented intelligent traffic evacuation path fuzzy control system

Emergency evacuation routing, at critical condition (earthquake), using Analytical Hierarchy Process Technique, and based on the actual weight of the sub-criteria related to the alternative

In recent years, research on emergency traffic evacuation has increased intensively. Detection of the optimal discharge route is one of the most important parts of crisis management due to the large number of effective measures. In this research, we have used the Analytical Hierarchy Process, taking into account three criteria, road capacity, population density, and structural parameters, and several sub-criteria, and taking into account the actual weight of the criteria for traffic emergency evacuation routing . The method presented in this research is not limited to these three criteria, and can be done with other criteria, based on the conditions of the case study area. The study area in this research is the region of Sabzemeydan, a region in Zanjan city (capital of Zanjan province, northwest of Iran), which has been studied based on the above criteria. The proposed route for emergency traffic evacuation in the studied area, using the proposed method in this research, has all the effective parameters in traffic evacuation, in times of crisis, and is the most optimal route for simultaneous examination based on their real impact.

A Survey on Traffic Evacuation Techniques in Internet of Things Network Environment

Objectives: System capacity has become a major concern while machine-to-machine (M2M) traffic evacuation has become a paramount interest due to the traffic congestion as well as overloading at the radio access and core network of the human-to-human (H2H) and machine-to-machine (M2M) communication framework of the 5G network. We therefore review the various solutions to the evacuation of M2M traffic with the aim of eliminating the said congestion. Methods/Statistical Analysis: We review various technologies including the low range radio technologies, and the long range wide area technologies available for internet of things (IoT) traffic otherwise called M2M traffic for decongesting the network and alleviating the M2M communication degradation effect on H2H communication. We also considered the application of massive MIMO in Heterogeneous networks for massive evacuation of the M2M traffic leading to greater separation of the H2H and M2M traffic and the eventual reduction of the network congestion. Findings: The application of massive MIMO for backhauling in macro cells for M2M traffic evacuation and which also provides 40 per cent capacity improvement via small cells placed indoor in a spatial densification heterogeneous network (HetNet) was considered as a good option for solving the above problems. Application/Improvement: A comprehensive survey on the use of the various techniques for traffic evacuation was not presented in the literature which we achieved in this paper.

An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

Traffic evacuation simulation based on multi-level driving decision model

Traffic evacuation is a critical task in disaster management. Planning its evacuation in advance requires taking many factors into consideration such as the destination shelter locations and numbers, the number of vehicles to clear, the traffic congestions as well as traffic road configurations. A traffic evacuation simulation tool can provide the emergency managers with the flexibility of exploring various scenarios for identifying more accurate model to plan their evacuation. This paper presents a traffic evacuation simulation system based on integrated multi-level driving-decision models which generate agents’ behavior in a unified framework. In this framework, each agent undergoes a Strategic, Cognitive, Tactical and Operational (SCTO) decision process, in order to make a driving decision. An agent’s actions are determined by a combination, on each process level, of various existing behavior models widely used in different driving simulation models. A wide spectrum of variability in each agent’s decision and driving behaviors, such as in pre-evacuation activities, in choice of route, and in the following or overtaking the car ahead, are represented in the SCTO decision process models to simulate various scenarios. We present the formal model for the agent and the multi-level decision models. A prototype simulation system that reflects the multi-level driving-decision process modeling is developed and implemented. Our SCTO framework is validated by comparing with MATSim tool, and the experimental results of evacuation simulation models are compared with the existing evacuation plan for densely populated Beijing, China in terms of various performance metrics. Our simulation system shows promising results to support emergency managers in designing and evaluating more realistic traffic evacuation plans with multi-level agent’s decision models that reflect different levels of individual variability of handling stress situations. The flexible combination of existing behavior and decision models can help generating the best evacuation plan to manage each crisis with unique characteristics, rather than resorting to a fixed evacuation plan.

Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities

This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper- and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization (PSO) method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.

A Multistage Multiobjective Model for Emergency Evacuation Considering ATIS

The impacts of advanced traveler information system’s (ATIS’s) penetration and compliance rates on network performances during hybrid traffic emergency evacuation are investigated in a degraded road network. Before traffic incident a Path-Size Logit (PSL) route choice model is integrated with constraints on the level of service (LOS) of traffic to formulate a bilevel programming model. It aims at minimizing traffic demand in road network which may locally deteriorate the LOS. The lower level is a PSL-stochastic user equilibrium model for multiple classes of users. During the ongoing incident, a multiobjective multiuser-class stochastic optimization model is established with the objectives of maximizing evacuation reliability and minimizing expected network travel time. Furthermore, computations and analyses are completed for five designated scenarios including a method proposed in previous literature. The results show that the evacuation reliability and different kinds of total expected travel time costs regularly increase with emergency traffic’s ATIS compliance rate and decrease with general traffic’s ATIS penetration rate. The research will help improve transport network performance when considering ATIS’s effect on hybrid traffic.

Traffic evacuation time under nonhomogeneous conditions

During many manmade and natural crises such as terrorist threats, floods, hazardous chemical and gas leaks, emergency personnel need to estimate the time in which people can evacuate from the affected urban area. Knowing an estimated evacuation time for a given crisis, emergency personnel can plan and prepare accordingly with the understanding that the actual evacuation time will take longer. Given the urban area to be evacuated, street widths exiting the area's perimeter, the area's population density, average vehicle occupancy, transport mode share and crawl speed, an estimation of traffic evacuation time can be derived. Peak-hour traffic data collected at three, midblock, Mumbai sites of varying geometric features and traffic composition were used in calibrating a model that estimates peak-hour traffic flow rates. Model validation revealed a correlation coefficient of +0.98 between observed and predicted peak-hour flow rates. A methodology is developed that estimates traffic evacuation time using the model.

Managing Emergency Traffic Evacuation With a Partially Random Destination Allocation Strategy: A Computational-Experiment-Based Optimization Approach

Natural or man-made disasters can cause huge losses of human life and property. One of the effective and widely used response and mitigation strategies for these disasters is traffic evacuation. Evacuation destination choice is critical in evacuation traffic planning and management. In this paper, we propose a partially random destination allocation strategy for evacuation management. We present a metamodel-based simulation optimization method to design the strategy. The proposed method uses a quadratic polynomial as a metamodel, within which a degree-free trust region algorithm is developed to solve the proposed model. The performance of the proposed method is evaluated based on a subnetwork of Beijing with two different traffic demands. Computational experiments demonstrate that the proposed method can yield a well-performed strategy, leading to reduced network clearance times.

Intersection Group Dynamic Subdivision and Coordination at Intraregional Boundaries in Sudden Disaster

This paper aims at the traffic flow agglomeration effect characteristics and rapid evacuation requirement in sudden disaster; operation time of intraregional boundaries traffic signal coordination was presented firstly. Then intraregional boundaries intersection group dynamic subdivision and consolidation method based on relative similarity degree and similarity coefficient of adjacent intersections was put forward. As to make the traffic control strategy adapt to traffic condition of different intraregional boundaries intersection groups, this paper proposes an intraregional boundaries traffic signal coordination and optimization technology based on organic computing theory. Finally, this paper uses Delphi 7.0, MapX, and Oracle developing a software package, combined with Paramics V6 Simulator to validate the methods of this paper. The result shows that it can obviously improve disaster affected regional traffic signal control efficiency which reduces average traffic delay by 30–35%, decreases vehicle queue by more than 20% and reduces evacuation time more than 13.06%.

Emergency Management and Planning Framework of Transportation Evacuation for Urban Flood Calamity

Flood is a common natural disaster and has happened frequently in decade years with a huge number of fatalities and property damages. These hazards typically necessitate the evacuation of local or regional populations to safe destinations or shelters and require a cooperation and interdependent relationship of several departments and organizations. This paper proposes that an urban evacuation management system framework for a deluge catastrophe can be modeled through the relationships between five components of interest: 1) evacuation road-network service capability; 2) human risk-attitude; 3) public or private decision; 4) weather and flood disaster monitoring; 5) inter-transit between city systems. We extract data from the strategies and propose a framework for residential evacuation management. This framework model is set up to help the local government quickly model the situation of the whole evacuation procedures and progresses to choose an optimum alternative from all the solutions and by identifying potential bottlenecks on traffic evacuation network and allocating resources reasonably to evacuate residents more safely and economically.

Modelling of lane-changing behaviour integrating with merging effect before a city road bottleneck

Merging behaviour is a compulsive action in a discretionary lane-changing traffic system, especially in a system with a bottleneck. This paper aims to investigate the generic lane-changing behaviour considering the merging effect before a city road bottleneck. Thus firstly the merging behaviour is distinguished from other generic lane-changing behaviour. Combining discretionary lane-changing and compulsive merging, we developed an integrative traffic model, in which a method to calculate the lane-changing probability and the merging probability was proposed. A simulation scenario derived from real life was conducted to validate the proposed programming algorithm. Finally, a discussion on the simulation findings shows that the merging influence can be expanded and the merging behaviour can increase the probability of local traffic jamming in its affected area of the adjacent lane. The distribution of the merging distance provides fundamental insights for actual traffic management. The result of the clearance time implies the position of the incident point has a significant effect on the clearing time and it is important to ensure the end (exit) of the road is unimpeded in traffic evacuation.

Urban Traffic Evacuation System for Comprehensive Railway Passenger Transport Hub and its Evacuation Efficiency Optimization Research

Comprehensive railway passenger transport hub (CRPTH) is important node in both railway passenger transport net and urban traffic net The efficiency of its passenger collecting and distributing impacts the level of service of both. In this paper, we proposed the concept of urban traffic evacuation system for CRPTH, clarified the quantitative indicators of its evacuation efficiency, and discussed the process of the system optimization.