Mitigation strategy of cascading failures in urban traffic congestion based on complex networks

Abstract

Urban road traffic network is becoming increasingly complex. The increasing travel demand has exceeded facility supply of transportation system. Thus, a scientific way of transportation can solve the problem of traffic congestion. If some central intersections are congested, the road network could easily lose its travel efficiency and further lead to cascading failure. In this regard, from the viewpoint of complex networks, this paper provides a cascading failure mitigation strategy for the urban road traffic network. A load redistribution strategy is represented which can redistribute congestion load reasonably. Random and intentional failures are simulated with MATLAB on Barabási and Albert (BA) scale-free network. The indices related to complex network of different methods are compared on BA network and part of the real road network in Baoding City. The load redistribution strategy in this paper is implemented combined with user equilibrium assignment, then the travel time related to urban road network is compared with another method on the Sioux Falls network. The simulation results suggest that when the capacity parameter reaches the threshold, further increase has little effect on the mitigation time. Comparisons of other mitigation approaches verify the effectiveness of our approach in lessening cascading failure caused by traffic congestion. The increase in total network travel time and additional delay by reason of load redistribution is acceptable.

Grouting reinforcement strategy for tunnel sand layer based on BP neural network

“…; 𝐷 is the diameter of the grouted specimen, 𝐷 = 5𝑐𝑚; 𝑡 is the measurement time, 𝑡 = 7200𝑠; 𝑄 is the volume of water at the outflow end corresponding to the measurement time, 𝑐𝑚 3 .…”

“…The 21st century is the era of great development of tunnels and underground space for human beings [1]. In recent years, rapid economic development and population explosion have increased the demand for transportation and other infrastructure, and urban traffic congestion has become an increasingly prominent problem [2][3][4]. To alleviate urban traffic congestion, a number of solutions have been proposed [5][6].…”

Mode Choice Effect on the Number of En-route Travelers and Arrival Rates in an Urban Transport Network

“…The rapid expansion of urban areas has led to a significant rise in travel demand and private vehicle ownership [1]. However, the existing infrastructure has not been able to keep up with this growing demand [2], resulting in traffic congestion [3], increased emissions and air pollution [4], climate and environmental changes [5], and a higher rate of accidents [6]. As a consequence of traffic congestion, commuters have been experienced longer delays, increased travel time, and therefore the reliability of the road network has been decreased [7].…”

Analysis of Traffic Characteristics and Distance Optimization Design between Entrances and Exits of Urban Construction Projects and Adjacent Planar Intersections

“…The XGBoost, LSTM and GRU models developed by Mahmoud [9] measured values closer to real values in the field. Traffic light intersection data detection schemes using edge computing, or load redistribution strategies using rational allocation of congestion load, are more suitable for complex and variable intersections [10,11]. The queue length was analyzed to determine the optimal value of green time [12].…”