Research On The Vulnerability Of Urban Road Traffic Network Considering Multi-point Concurrent Accidents

There is no doubt that the urban road traffic network as an important carrier of urban traffic activities has an important impact on the daily travel of urban residents,the normal play of urban functions and the emergency evacuation of emergency events.However,with the development of the economy and the increase of social activities,the scale of the urban road traffic network is expanding and it is more susceptible to various types of accidents,such as natural disasters,traffic accidents,terrorist attacks and road failures.As a result,the vulnerability of urban road traffic network has gradually become obvious.Since the happening of accident not only causes the traffic congestion to affect the traffic trip,it may also lead to the failure of the road that will cause the passenger queue to overflow and the traffic flow will be redistributed.At the same time,it may cause domino effect due to the traffic overload on adjacent sections,which will lead to a large area of traffic congestion,and even cause the paralysis of traffic network.As a result,it is of great practical significance to study the vulnerability of urban road traffic network and put forward the control strategy.The method of deleting nodes or edges is generally used to simulate random damage and vandalism in the existing research.But the method is to destroy one by one in chronological order,which has a big difference from the traffic accident in reality.In fact,the probability value of a traffic accident is related to the traffic flow condition,and the traffic accident has the feature of multi-point concurrent.In addition,the road traffic network has self-repairing ability,and the failure part will gradually recover due to its own repairing mechanism.Under the premise of accident multi-point concurrency and road network self-repair ability,this paper comprehensively considers the relationship between road traffic flow and capacity,and the influence of random factors that give certain probability to the accident of each road in the network,and selects network efficiency and network overall efficiency as measure indicator to analyze the vulnerability of road traffic and the vulnerability of road traffic network with self-repair ability under the traffic accident concurrency environment,and to propose the vulnerability control strategy for urban road traffic network.In view of the impact of accident multi-point concurrency and road self-repair ability on road network vulnerability,this paper mainly draws the following conclusions:(1)Compared with single-point accident,multi-point concurrent accidents is more destructive,which has greater impact on urban road traffic network and makes the network fall into paralysis faster.Therefore,when controlling the vulnerability of road network,we should focus on avoiding the situations of multi-point concurrent accidents.An important method is to investigate hidden dangers of road network throughout the city and focus on maintaining accident-prone sections.(2)Compared with the traffic off-peak period,the urban road traffic network is more vulnerable in the peak period,which is more likely to cause cascading failures.It shows that traffic flow is the key factor affecting the vulnerability of the road network.So the traffic flow of congested sections should be dredged in time during the peak period.Therefore,more maintenance costs of the road network need to be invested in the peak period.(3)The self-repair ability of the road has an important impact on the vulnerability of road network.The stronger the road repair ability is,the lower the vulnerability of road network will be.But the marginal utility of the repair ability decreases gradually.It shows that the control of road network vulnerability can start with repairing the failed road section,but at the same time,the cost of repairing the failed road section should be balanced with the vulnerability of road network that can be reduced by repairing the failed road section.