Impact of earthquake-induced bridge damage and time evolving traffic demand on the road network resilience

Kilanitis, Ioannis; Sextos, Anastasios

doi:10.1016/j.jtte.2018.07.002

Cited by 33 publications

(13 citation statements)

References 20 publications

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“…However, in most cases, road network data is not readily available. Therefore, ITS developers will have insufficient road information and insufficient POI information [33].…”

Section: Application Of Intelligent Road Network Trafficmentioning

confidence: 99%

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

et al. 2024

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With the rapid increase in the number of private cars and buses in the country, the living standard has gradually improved, and vehicles as a means of transportation commonly used by people have caused more traffic accidents. The present study mainly discusses the theoretical models and methods of VR technology and road network traffic status information accident prediction perception on the Internet of Vehicles (IoV) environment. Use of VR technology to simulate the experimental environment. The main techniques of VR real-time rendering are the visualization and roaming of large-area spatial data and the simulation of things that currently exist in computer vision simulation methods. Use VR technology to simulate ordinary highways, and use VR technology to simulate six sets of virtual cars. Use the real-time positioning function and data transmission function of the IoV technology to systematically collect driving data in the VR environment and advance collisions in advance to perceive and control the speed of the cars. Experimental data shows that when the time level is 2, the brake response sensitivity in the data is 88.9%, and the brake sensitivity value is relatively high. When the distance level is 1, the car safety factor value is 97.5%, and the data value is the highest. The research results show that when the time level is 2, the brake sensitivity value is relatively high, indicating that the VR technology and the traffic network information environment accident prediction effect on the Internet of Vehicles environment are better. When the distance level is 1, the performance of road network traffic status information accident perception based on VR technology and IoV environment is the best. Through the real-time sharing of the image recognition performance of VR technology and the geographic location of the Internet of Vehicles technology, the real-time prediction and perception of road network traffic status information accidents can minimize the chances of accidents.

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“…However, in most cases, road network data is not readily available. Therefore, ITS developers will have insufficient road information and insufficient POI information [33].…”

Section: Application Of Intelligent Road Network Trafficmentioning

confidence: 99%

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

et al. 2024

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“…While structural damages from earthquakes have been investigated in various capacities, there has been a limited examination of the impact on traffic networks and the resilience of bridges after earthquakes [14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Additionally, most impact analyses of traffic networks have been based on the simplified application of traffic capacity.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Cho

Lee

et al. 2021

Applied Sciences

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Highway systems play a key role in providing mobility to society, especially during emergency situations, including earthquakes. Bridges in highway systems are susceptible to damage from earthquakes, causing traffic capacity loss leading to a serious impact on surrounding areas. To better prepare for such scenarios, it is important to estimate capacity loss and traffic disruptions from earthquakes. For this purpose, a traffic-capacity-analysisbased methodology was developed to model the performance of a transportation network immediately following an earthquake using a macroscopic multi-level urban traffic planning simulation model EMME4. This method employs the second order linear approximation (SOLA) traffic assignment and calculates total system travel time for various capacity loss scenarios due to bridge damage from earthquakes. It has been applied to Pohang City in Korea to evaluate the performance of traffic networks in various situations. The results indicate a significant increase in travel time and a decrease in travel speed as the intensity of an earthquake increases. However, the impact on traffic volume varies depending on the bridges. It is assumed that the location of the bridges and traffic routing patterns might be the main reason. The results are expected to help estimate the impact on transportation networks when earthquakes cause traffic capacity loss on bridges.

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“…After the creation of the network geometry in SUMO and the determination of the segments that can be affected by roadblocks, the network can be modified to take into account these new conditions, generating disrupted versions of the network. In previous studies, for example, network disruptions have been modeled by closing the traffic in the affected segments 9,23 or by modifying the traffic capacity and/or speed as a function of the initial characteristics and extent of the damage. 8,37…”

Section: Network Disruptions In a Sumo Networkmentioning

confidence: 99%

“…Numerous studies consider fixed demand models, whereby traffic demands are the same before and after the event (e.g., Shiraki et al and Jayaram & Baker 17,22 ). Nevertheless, the network traffic after a seismic event can be significantly changed, not only due to changes in the network capacity during the recovery process 23 but also due to modifications of the post-earthquake traveling needs of the population. Different models have been developed to overcome this issue, in particular by modifying the origin destination (OD) matrix 24 or by applying a variable demand model.…”

Section: Introductionmentioning

confidence: 99%

Application of open tools and datasets to probabilistic modeling of road traffic disruptions due to earthquake damage

Costa

Figueiredo

Silva

et al. 2020

Earthq Engng Struct Dyn

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Summary The disruption of a transportation network can have a high social and economic impact on the welfare of a society, as it can significantly affect the daily routines of a community. Although many studies have focused on the estimation of physical risk in the components that compose these networks, only a limited number have analyzed their interconnections and impact in the traffic flow. The present study analyzes how earthquake damage can disrupt the road network in an urban environment, and how this will influence the ability of the population to travel. Traffic due to daily commutes is modeled for different layouts of the network, corresponding to possible disruptions caused by earthquake damage. The duration and length of each trip were calculated both for the undamaged network conditions and for the disrupted network. The increase in the median duration and length of each trip allows estimating the economic loss for each event due to drivers' delay. By combining the probability of a specific road being blocked with its number of users, the average number of affected vehicles was estimated, and the most critical segments identified. The methodology was applied to a case study concerning the road network of the area around the Italian city of Messina in Sicily. The results were calculated for both a repetition of the well‐known historical event of 1908 and a set of simulated earthquakes consistent with the national probabilistic seismic hazard model of Italy.

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Impact of earthquake-induced bridge damage and time evolving traffic demand on the road network resilience

Cited by 33 publications

References 20 publications

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Application of open tools and datasets to probabilistic modeling of road traffic disruptions due to earthquake damage

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