Multi-mode traffic cooperative evacuation method based on lane management

Abstract

The invention provides a multi-mode traffic cooperative evacuation method based on lane management, and the method comprises the steps: determining an evacuation demand according to the characteristics of a disaster, and discretizing an evacuation road network into a multi-layer multi-size cellular network according to the free flow speeds of different vehicles; based on the discretized multi-layer multi-size cellular network, taking the shortest emptying time of the whole system needing evacuation as an objective function, and taking a multi-mode fleet scale constraint, a multi-mode traffic network loading constraint, and a lane distribution and lane countercurrent constraint as constraint conditions, constructing a multi-mode traffic collaborative evacuation model; solving the multi-mode traffic collaborative evacuation model by adopting a tabu search algorithm; and carrying out multi-mode traffic cooperative evacuation organization according to a solving result. According to the method, the optimal coupling of the evacuation demand, the motorcade scale and the evacuation network capability is realized, the evacuation scheme generation efficiency is ensured, the traffic jam phenomenon in the evacuation process is avoided, and the secondary damage is reduced.

Description

technical field [0001] The invention relates to the field of traffic technology, in particular to a multi-mode traffic coordinated evacuation method based on lane management. Background technique [0002] Large-scale evacuation relying on the road network is an effective and extensive means to deal with various disaster events (such as hurricanes, floods, earthquakes, dangerous gas leaks, terrorist attacks, etc.), and scientific evacuation planning can minimize major casualties and property damage. In mass evacuations, the primary goal is to move disaster-affected residents to safe areas as quickly as possible while avoiding severe traffic congestion and secondary injuries. This requires managers to rationally configure fleets and allocate road resources according to evacuation needs, and at the same time consider the dynamics of evacuation traffic flow to formulate dynamic evacuation plans. [0003] In actual evacuation, there are often people with low mobility, such as t...

AI Technical Summary

Problems solved by technology

At present, there are few studies on organizing multi-modal traffic evacuation, mainly including: aiming at minimizing the evacuation time, balancing the traffic load in the entire road network through the multi-ant colony intelligent algorithm, but the evacuation traffic model of this method is static and cannot capture Traffic congestion during evacuation cannot provide a real-time evacuation schedule, and cannot provide a detailed lane management plan; considering the shortest total driving distance of all evacuated people as the objective function, establish a bus evacuation route planning based on the elimination of conflicts between reversible lanes and intersections model, and the genetic algorithm is selected to solve the model, and the optimal bus evacuation route planning scheme is obtained. However, this method ignores the impact of other vehicles on the bus by setting up dedicated lanes, and adopts a static evacuation traffic model, which cannot capture traffic congestion. Formulate a real-time evacuation schedule; establish a two-tier programming model that integrates mixed fleets and lane counterflow strategies, and use a two-tier algorithm consisting of a heuristic algorithm and a bus priority minimum cost flow algorithm to solve the problem. However, this method uses a static traffic model and cannot Capture traffic congestion and other phenomena in evacuation, and the efficiency of bi-level programming is low, so it is not suitable for real-time evacuation

[0004] The above methods mostly use static traffic models, without considering the dynamic evolution of various traffic flows in the network, and cannot capture traffic congestion

However, in large-scale evacuations, traffic jams are prone to occur, which may reduce evacuation efficiency and cause secondary damage

In addition, the above methods take the network clearing time as the objective function, but because the network clearing time is in a nonlinear and non-convex form, it cannot be directly optimized. Therefore, the model is mostly expressed as a two-level programming, and the model cannot be solved directly with the help of a commercial solver. large-scale application of the model

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