Urban road traffic accident emergency rescue path planning method

Abstract

The invention discloses an urban road traffic accident emergency rescue path planning method which comprises the following steps: 1) generating an urban road network topological structure chart, and obtaining traffic flow data and rescue starting and ending point information; 2) analyzing urban road traffic accident emergency rescue characteristics, and selecting a proper rescue path planning method evaluation index; 3) constructing a basic framework of the timing coevolution path planning, and explaining an optimization principle of the timing coevolution path planning systematacially; 4) designing a suitable solving algorithm based on the operational characteristics of urban road vehicles; 5) defining a calculation method of uncertainty factors in the actual traffic environment of the urban road network; 6) outputting the rescue route planning result through computer programming. The invention can solve the problem of urban road emergency rescue path planning.

Description

technical field [0001] The invention relates to the technical field of optimality and stability of emergency rescue path planning for urban road traffic accidents, in particular to a planning method for emergency rescue paths for urban road traffic accidents. Background technique [0002] Emergency rescue is a key means to prevent the further deterioration of the impact of urban road traffic accidents and ensure the safety of the injured. According to the World Health Organization, the number of people injured in road traffic accidents is 30 million to 50 million every year, of which about 1.2 million are injured and die, that is, an average of 3,300 people die every day, and the number of casualties will increase by about 65% in the next 20 years. The frequent occurrence of traffic accidents and the sharp increase in the number of injured people force the emergency response efficiency to be further improved in order to control the injuries of the injured, restrain the secon...

AI Technical Summary

Problems solved by technology

In real-world applications, the path planning process of the online optimization method has significant time lag, and cannot bypass the upcoming congestion area in advance, which increases the rescue travel time

On the other hand, since the online optimization method cannot predict the dissipation trend of the congested area, it is easy to take a detour decision with a longer travel time, which further increases the rescue travel time

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