CN-122024508-A - Method for determining traffic information quantity cooperative threshold of vehicle-mounted and road scene

CN122024508ACN 122024508 ACN122024508 ACN 122024508ACN-122024508-A

Abstract

The invention discloses a method for determining traffic information quantity synergy threshold values of a vehicle-mounted and road scene, which comprises the steps of dividing traffic information sources of the road scene and display elements of a vehicle-mounted interaction interface into a plurality of categories, calculating information quantity of each category based on an information entropy model, determining weights of each category, respectively obtaining total information quantity of the road scene and total information quantity of the vehicle-mounted interaction interface, constructing a function of the traffic information quantity and gaze entropy based on Wundt curves, obtaining eye movement gaze data of a driver under driving scenes with different combinations of the total information quantity of the road scene and the total information quantity of the vehicle-mounted interaction interface, calculating gaze entropy values, taking the traffic information quantity as input and the gaze entropy values as output, and performing parameter fitting on the function to obtain a minimum threshold value and a maximum threshold value of the traffic information quantity. According to the invention, the gazing probability distribution difference corresponding to different traffic information amounts is reflected by gazing entropy values, so that the information amount change can be realized by quantization indexes, and the influence of the information complexity on the driving behavior is truly reflected.

Inventors

LI JINGYU
QIAN DEMENG
ZHANG WEIHUA
FENG ZHONGXIANG

Assignees

安徽理工大学

Dates

Publication Date: 20260512
Application Date: 20260130

Claims (8)

1. A method for determining traffic information amount cooperative threshold of vehicle-mounted and road scene, comprising the steps of: Dividing traffic information sources of road scenes and display elements of vehicle-mounted interaction interfaces into a plurality of categories, calculating information quantity of each category based on an information entropy model, determining weights of each category, and obtaining total information quantity of the road scenes respectively And total information quantity of vehicle-mounted interaction interface ; Construction of function of traffic information quantity and gaze entropy based on Wundt curve The traffic information amount is the total information amount of the road scene Total information quantity of vehicle-mounted interaction interface And (3) summing; obtaining the total information quantity of the driver in the road scene Total information volume of vehicle-mounted interactive interface Eye movement fixation data under different combined driving scenes, and calculating a fixation entropy value based on the eye movement fixation data; taking the traffic information amount as input and the gaze entropy value as output, and applying the function to the traffic information amount Performing parameter fitting to obtain the minimum threshold value of the traffic information quantity And a maximum threshold value 。
2. The method for determining traffic information volume cooperative threshold for vehicle-mounted and road scene as recited in claim 1, wherein the function constructed based on Wundt curve The method comprises the following steps: Wherein, the Is a bonus function of the information and, Is a penalty function for the information; is a constant, indicating the maximum prize value, Is a constant, indicating a maximum penalty value; Representing a minimum information amount threshold value, Representing a maximum information amount threshold; , Is the slope.
3. The method for determining the traffic information amount synergy threshold of the vehicle-mounted and road scene according to claim 1, wherein the calculation step of the gaze entropy value comprises dividing the gaze point of the driver into a plurality of interest areas, and calculating gaze entropy information contained in each interest area respectively, wherein the calculation formula of the total gaze entropy value is as follows: Wherein, the Representing the number of the regions of interest; , Representative of the first Gaze entropy information contained in the individual regions of interest, For the driver's point of gaze to fall at Probability of individual regions of interest; , Expressed as the maximum gaze entropy value; To the driver at the first Average gaze duration of individual regions of interest.
4. The method for determining traffic information amount cooperative threshold for vehicle-mounted and road scene according to claim 3, wherein the method for dividing the gaze point into regions of interest comprises a mechanical division method, a one-by-one statistical method, a dynamic clustering method, And (5) clustering.
5. The method for determining the traffic information quantity cooperative threshold value of the vehicle-mounted and road scene according to claim 1, wherein the optimization algorithm adopted by the parameter fitting is a gradient descent method or an Adam optimizer.
6. The method for determining traffic information amount cooperative threshold according to claim 1, wherein the method for determining weights of respective categories includes a hierarchical analysis method, an entropy weight method, a best-worst method, or a Delphi expert domestic discipline.
7. The method for determining the traffic information quantity cooperative threshold value of the vehicle-mounted and road scene according to claim 1, wherein the traffic information source of the road scene comprises a meaning class, a motion class, a physical class and an environment class, and the display element of the vehicle-mounted interaction interface comprises Chinese characters, english letters, arabic numerals, characters, colors and icons.
8. The method for determining traffic information amount cooperative threshold for vehicle-mounted and road scene according to claim 1, wherein the information entropy model comprises Shannon entropy model, renyi entropy model or tsalis entropy model.

Description

Method for determining traffic information quantity cooperative threshold of vehicle-mounted and road scene Technical Field The invention relates to the technical field of intelligent traffic, in particular to a method for determining traffic information quantity cooperative threshold values of vehicle-mounted and road scenes. Background In a driving task, a driver continuously acquires external information to reduce environmental uncertainty, so that a series of behaviors such as perception, decision making and operation are completed. With the development of the internet of vehicles technology, the vehicle-mounted interaction interface can provide rich information of people, vehicles, roads and environments. However, the information processing ability of the driver has a natural upper limit. When a road scene and a vehicle-mounted interface simultaneously present a large amount of information, information competition and resource occupation can be caused, and the problems of insufficient perception or distraction caused by information overload and the like occur. Currently, there are at least the following problems: 1. the road scene information and the vehicle-mounted interface information quantity respectively belong to two independent systems of road end-vehicle end, unified measurement standards are lacking, the existing research generally only independently determines an information quantity threshold value aiming at a certain side of a vehicle-mounted interactive interface or a road scene, and the road scene information and the vehicle-mounted interface information are not used as a combined information source in a driving task for unified evaluation. The single-side threshold method cannot reflect the synergistic effect between the road scene information quantity and the vehicle-mounted interface information quantity, is difficult to integrally describe the overall information load faced by a driver when executing a driving task, and has obvious limitations in the real driving environment. 2. The existing research has more attention to information overload and has insufficient attention to information. There is a lack of models capable of describing both "under-information" and "over-information" double-sided effects, and thus an optimal information volume interval cannot be determined. Disclosure of Invention In order to solve the technical problems in the background technology, the invention provides a vehicle-mounted and road scene traffic information volume cooperative threshold value determining method which can provide a proper information volume interval for a driver and is suitable for engineering design guidance. The invention provides a method for determining a traffic information quantity cooperative threshold value of a vehicle-mounted and road scene, which comprises the following steps: Dividing traffic information sources of road scenes and display elements of vehicle-mounted interaction interfaces into a plurality of categories respectively, calculating information quantity of each category based on an information entropy model, determining weight of each category, and obtaining total information quantity of the road scenes respectively through weighted summation And total information quantity of vehicle-mounted interaction interface; Construction of function of traffic information quantity and gaze entropy based on Wundt curveThe traffic information amount is the total information amount of the road sceneTotal information quantity of vehicle-mounted interaction interfaceAnd (3) summing; obtaining the total information quantity of the driver in the road scene Total information volume of vehicle-mounted interactive interfaceEye movement fixation data under different combined driving scenes, and calculating a fixation entropy value based on the eye movement fixation data; taking the traffic information amount as input and the gaze entropy value as output, and applying the function to the traffic information amount Performing parameter fitting to obtain the minimum threshold value of the traffic information quantityAnd a maximum threshold value。 Further, a function constructed based on Wundt curvesThe method comprises the following steps: Wherein, the Is a bonus function of the information and,Is a penalty function for the information; is a constant, indicating the maximum prize value, Is a constant, indicating a maximum penalty value; Representing a minimum information amount threshold value, Representing a maximum information amount threshold;, Is the slope. Further, the calculation step of the gaze entropy value comprises the steps of dividing the gaze point of a driver into a plurality of interest areas, and calculating gaze entropy information contained in each interest area respectively, wherein the calculation formula of the total gaze entropy value is as follows: Wherein, the Representing the number of the regions of interest;, Representative of the first Gaze entropy informat