Unlock instant, AI-driven research and patent intelligence for your innovation.

A Method for Quantifying Path Safety Level Based on Bayesian Joint Model

A joint model and path technology, which is applied in the traffic control system of road vehicles, traffic flow detection, special data processing applications, etc., can solve the problem of inaccurate road accident prediction and other problems

Active Publication Date: 2017-01-18
CENT SOUTH UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the technical problem of inaccurate road accident prediction at present, the present invention constructs a joint prediction model of intersection-road section-by-severity accident frequency according to the basic idea of ​​road traffic safety analysis, aiming at the accident data characteristics of each road entity in the travel road traffic network , and use this to calculate the quantitative index for evaluating the safety of travel routes

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Method for Quantifying Path Safety Level Based on Bayesian Joint Model
  • A Method for Quantifying Path Safety Level Based on Bayesian Joint Model
  • A Method for Quantifying Path Safety Level Based on Bayesian Joint Model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The accident prediction model designed by the present invention—the Bayesian joint prediction model of the intersection-road section severity accident frequency, combines the current most advanced method of intersection-road section accident joint prediction and accident frequency-severity joint prediction research, with road entities The accident frequency according to the severity is the prediction object, which is assumed to obey the Poisson distribution. In the connection function of Poisson distribution, the residual term representing the frequency correlation of each severe accident and the spatial correlation of adjacent entities is introduced respectively. Since road sections and intersections must have different safety factors, an indicator variable is used in the model to determine the road entity as road sections and intersections. The joint model is expressed as follows:

[0028] P ( Y ikt = ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The present invention discloses a method for quantifying path safety level based on a Bayes combined model. The method comprises the steps of utilizing a crossing-road section severity accident frequency Bayes combined forecasting model to estimate the severity accident rates of the road entities in a travel path, and weighting and summing the severity accident loss specific gravities to obtain a safety estimation index of a whole path. The method can be embedded in the systems conveniently, such as a path navigation system, a travel information service platform, etc., thereby providing the intelligent analysis means for the travel safety of the passengers.

Description

technical field [0001] The invention relates to a method for quantifying the safety level of a path, in particular to a method for quantifying the safety level of a path based on a Bayesian joint model. Background technique [0002] Path refers to the orderly arrangement of a series of connected intersections and road sections between any pair of OD points on the transportation network, from the point of origin to the point of attraction. In real life, when driving from one place to another, there are usually many different travel paths. When selecting a route, factors such as travel distance and travel time of the route are mainly considered. However, with the continuous improvement of urbanization and motorization in our country, the probability of accidents on the road is also increasing, and road traffic safety has become a very important social and economic issue. At the same time, in the process of traveling, people pay more and more attention to the safety level of ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G06F19/00
CPCG08G1/0104G16Z99/00
Inventor 黄合来曾强宋博许鹏鹏
Owner CENT SOUTH UNIV