CN111739303A - Evaluation method and device of intelligent high-speed rain and fog driving safety guidance system - Google Patents
Evaluation method and device of intelligent high-speed rain and fog driving safety guidance system Download PDFInfo
- Publication number
- CN111739303A CN111739303A CN202010834571.0A CN202010834571A CN111739303A CN 111739303 A CN111739303 A CN 111739303A CN 202010834571 A CN202010834571 A CN 202010834571A CN 111739303 A CN111739303 A CN 111739303A
- Authority
- CN
- China
- Prior art keywords
- rain
- effect
- evaluation
- driving safety
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- Atmospheric Sciences (AREA)
- Traffic Control Systems (AREA)
Abstract
The embodiment of the application provides an evaluation method and a device for an intelligent high-speed rain and fog driving safety guidance system, wherein the method comprises the following steps: determining a plurality of working modes; respectively collecting evaluation data sets related to vehicle running characteristics in each working mode of the plurality of working modes, wherein the data of the evaluation data sets comprise vehicle data or flow data, and the vehicle data comprise: speed data and headway data; and evaluating the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability. The embodiment of the application provides an effect evaluation method for a rain and fog driving safety guidance system of an expressway from the perspective of traffic flow theory and traffic engineering, and the evaluation method can evaluate the performance of the rain and fog system from the perspective of setting the rain and fog driving safety guidance system, namely adjusting the whole traffic flow.
Description
Technical Field
The application relates to the field of evaluation methods, in particular to an evaluation method and device of an intelligent high-speed rain and fog driving safety induction system.
Background
In recent years, in order to improve the operation management level of highways in low-visibility severe weather such as rain and fog, increase the road driving safety and comfort under adverse conditions and reduce the accident occurrence probability, a rain and fog driving safety induction system serving as one of intelligent high-speed core systems is installed on multiple highways such as beijing, Sichuan, Jiangxi, Anhui and the like in China, and multiple management and control strategies including road linear strengthening, trail tracking and rear-end collision prevention warning and the like are formed by combining multiple colors and flicker frequencies of roadside multifunctional fog lamps. The whole traffic flow can be stably operated under the low visibility.
The rain and fog driving safety inducing system realizes that highway management under low-visibility severe weather such as rain and fog is from passive prompt to active prevention and control, so that the highway rain and fog driving safety inducing system is researched and developed by multiple companies, has similar main functions, and forms a new industry and a new state of traffic safety.
The inventor of the application finds that for the new industry, the existing product detection means mostly depend on software and hardware functional performance, and a corresponding evaluation method for the fundamental purpose of installing a rain and fog driving safety guidance system (namely, adjusting the whole traffic flow so as to reduce the accident rate) is still blank. The inventor of the embodiment of the application thinks that in order to scientifically and reasonably evaluate the regulation effect and the effect of the rain and fog driving safety induction system on the whole traffic flow of the highway and provide a new basis for product comparison and selection for the new traffic safety industry, an effect evaluation method aiming at the intelligent high-speed rain and fog driving safety induction system is needed to be provided from the perspective of traffic flow theory and traffic engineering, and a comprehensive evaluation standard of the intelligent high-speed rain and fog driving safety induction system is established.
Disclosure of Invention
The evaluation method and the device provided by the embodiment of the application aim at setting the intelligent high-speed rain and fog driving safety guidance system, and a complete set of effect evaluation method is provided from the perspective of traffic flow theory and traffic engineering, so that the evaluation on the rain and fog driving safety guidance system is more reasonable and accurate.
In a first aspect, some embodiments of the present application provide an effect evaluation method of an intelligent high-speed rain and fog driving safety guidance system, where the effect evaluation method includes: determining a plurality of working modes; respectively collecting evaluation data sets related to vehicle running characteristics in each working mode of the plurality of working modes, wherein the evaluation data sets comprise: vehicle data or flow data, the vehicle data comprising: speed data and headway data; and evaluating the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability.
The embodiment of the application provides an effect evaluation method for a rain and fog driving safety guidance system of an expressway from the perspective of traffic flow theory and traffic engineering, and the evaluation method can evaluate the performance of the rain and fog system from the perspective of setting the rain and fog driving safety guidance system, namely adjusting the whole traffic flow.
In some embodiments, the plurality of operating modes includes: a normal environment mode, a special weather environment mode and a control mode adopting the rain and fog driving safety guidance system.
Some embodiments of this application are through the definition contain the installation rain fog driving safety induction system and do not contain a plurality of operating modes that this system's multiple condition corresponds, come the analysis to the regulation effect to speed after installing rain fog driving safety induction system, have promoted the accuracy to the evaluation result of rain fog driving safety induction system.
In some embodiments, the acquiring evaluation data sets related to the driving characteristics of the vehicle in each of the plurality of operation modes comprises: selecting a plurality of discontinuous sections from a road section provided with the rain and fog traffic safety guidance system; acquiring the speed of a first vehicle passing through each section of the plurality of sections of the first lane in each working mode of the plurality of working modes; and under each working mode, acquiring a headway time distance between the first vehicle and a preceding vehicle when the first vehicle passes through each section of the plurality of sections of the first lane, wherein the headway time distance is used for representing a time interval between two adjacent vehicles which at least comprise the first vehicle and pass through the same section.
Some embodiments of the application provide one kind and gather the data on a plurality of sections and estimate the performance of rain and fog driving safety induction system, have further promoted the accuracy of aassessment.
In some embodiments, the effect evaluation method further comprises: and determining to terminate the data acquisition process of each working mode in the plurality of working modes according to the set acquisition duration.
Some embodiments of this application still terminate the data acquisition process through setting for data acquisition time, avoid the wasting of resources that the unlimited collection of data acquisition process caused can promote data acquisition's time fairness between a plurality of data indexes simultaneously, promote the uniformity to the index of rain and fog driving safety induction system performance aassessment.
In some embodiments, before the evaluating the operation effect of the driving safety inducing system according to the evaluation data set, the effect evaluation method further includes: determining the average speed and the standard deviation of the speed of each section in the plurality of sections according to the acquired speed; the evaluation of the operation effect of the rain and fog driving safety guidance system according to the evaluation data set comprises the following steps: and comparing the average speed, the speed standard deviation and the headway time distance in each working mode of the plurality of working modes to determine the running effect.
Some embodiments of the application estimate the performance of the rain and fog driving safety guidance system through the average speed and the standard deviation of the speed of the section, and improve the safety and efficiency of performance estimation.
In some embodiments, before the evaluating the operation effect of the driving safety inducing system according to the evaluation data set, the effect evaluation method further includes: determining the traffic volume passing through every hour according to the acquired traffic data; the evaluating the operation effect of the rain and fog driving safety inducing system according to the evaluation data comprises the following steps: and comparing the hourly traffic volume in each working mode of the plurality of working modes to determine the operation effect.
Some embodiments of the application also evaluate the performance of the rain and fog driving safety guidance system through the traffic flow, and the evaluation method and the data acquisition process are related, simple and easy to implement.
In some embodiments, the evaluating the operation effect of the driving safety inducing system according to the evaluation data includes: and comparing and analyzing the index change trend in each working mode of the plurality of working modes, wherein the index comprises: obtaining the average speed, the standard deviation of the speed and the headway of each section in the plurality of sections through the evaluation data set; and determining the significant change characteristics of the index caused by the adoption of the rain and fog driving safety inducing system, wherein the plurality of sections are discontinuous sections selected from a road section provided with the rain and fog driving safety inducing system.
Some embodiments of the application also evaluate the performance of the rain and fog driving safety guidance system by analyzing the change trend and the significance change, and improve the visualization and rationalization of the evaluation result.
In a second aspect, an embodiment of the present application provides an effect evaluation device of an intelligent high-speed rain and fog driving safety guidance system, the device includes: an operating mode determination module configured to determine a plurality of operating modes; a data collection module configured to collect evaluation data sets related to vehicle driving characteristics in each of the plurality of operation modes, respectively, wherein the evaluation data sets include: speed data and headway; and the effect evaluation module is configured to evaluate the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability.
In some embodiments, the apparatus further comprises: and the index calculation module is configured to determine the average speed and the standard deviation of the speed of each section in a plurality of sections according to the speed acquired by the data acquisition module, wherein the plurality of sections are discontinuous sections selected from a road section provided with the rain and fog driving safety induction system.
In a third aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, can implement the method of the first aspect.
In a fourth aspect, an embodiment of the present application provides an information processing apparatus, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the method according to the first aspect.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flowchart of an effect evaluation method for an intelligent high-speed rain and fog driving safety guidance system according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another exemplary method for evaluating an effect of the intelligent high-speed rain and fog driving safety guidance system according to the embodiment of the present application;
fig. 3 is a block diagram of an effect evaluation device for an intelligent high-speed rain and fog driving safety guidance system according to an embodiment of the present disclosure;
fig. 4 is a block diagram of an information processing apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
An object of some embodiments of the present application is to provide an effect evaluation method for an intelligent high-speed rain and fog driving safety guidance system. On the basis of fully understanding the rain and fog system principle, typical scenes (namely a plurality of working modes) of system work are defined, evaluation data acquisition based on vehicle running characteristics (namely vehicle speed, headway or flow data) is carried out, indexes such as speed, speed standard deviation and headway are selected, and effect evaluation is carried out on the highway rain and fog driving safety inducing system.
Referring to fig. 1, fig. 1 is a method for evaluating an effect of an intelligent high-speed driving safety guidance system according to some embodiments of the present application, the method including: s110, determining a plurality of working modes; s120, respectively collecting evaluation data sets related to vehicle running characteristics in each working mode of the plurality of working modes, wherein the evaluation data sets comprise: vehicle data or flow data, the vehicle data comprising: speed data and headway; and S130, evaluating the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability. For example, the plurality of operating modes include: a normal environment mode, a special weather environment mode and a control mode adopting the rain and fog driving safety guidance system. Some embodiments of this application are through the definition contain the installation rain fog driving safety induction system and do not contain a plurality of operating modes that this system's multiple condition corresponds, come the analysis installation to the regulation effect of flow and speed behind the rain fog driving safety induction system, have promoted the accuracy to the evaluation result of rain fog driving safety induction system.
In some embodiments, S120 comprises: selecting a plurality of discontinuous sections from a road section provided with the rain and fog traffic safety guidance system; acquiring the speed of a first vehicle passing through each section of the plurality of sections of the first lane in each working mode of the plurality of working modes; and acquiring a headway distance between the first vehicle and a front vehicle when the first vehicle passes through each section of the plurality of sections of the first lane in each of the plurality of working modes, wherein the headway distance is used for representing a time interval of two adjacent vehicles passing through the same section, and the two adjacent vehicles at least comprise the first vehicle. Some embodiments of the application provide one kind and gather the data on a plurality of sections and estimate the performance of rain and fog driving safety induction system, have further promoted the accuracy of aassessment. To terminate the data collection process immediately, in some embodiments, the method further comprises: and determining to terminate the data acquisition process of each working mode in the plurality of working modes according to the set acquisition duration.
It should be noted that, in some embodiments of the present application, the requirement for selecting the "non-continuous" section may include (i) number requirement: 3-5; distance requirement: the interval is not more than 200 m; position requirement: the initial point and the end point of the rain and fog driving safety guidance system are respectively required to be provided with a data acquisition section, and the rest sections are arranged in the middle section of the system at equal intervals. The first vehicle of some embodiments of the present application generally refers to any vehicle passing through the first lane, and similarly, the first lane generally refers to any lane on the road section to be analyzed. It can be understood that the data acquisition process according to some embodiments of the present application can obtain the speed of each vehicle passing through all the sections (i.e., the set discontinuous sections) on each lane, and can obtain the headway between any two vehicles passing through each lane. For example, the headway between any two vehicles can be determined by the time difference of the same profile using the same location (e.g., bumper) of the two vehicles.
In some embodiments, the method for evaluating an effect before S130 further comprises: and determining the average speed and the standard deviation of the speed of each section in the plurality of sections according to the acquired speed. S130 may include: and comparing the average speed, the speed standard deviation and the headway time distance in each working mode under the plurality of working modes to determine the running effect. Some embodiments of the application estimate the performance of the rain and fog driving safety guidance system through the average speed and the standard deviation of the speed of the section, and improve the safety and efficiency of performance estimation.
In some embodiments, before S130 is performed, the effect evaluation method further includes: determining the traffic volume passing through every hour according to the acquired traffic data; s130 includes: and comparing the hourly traffic volume in each working mode under the plurality of working modes to determine the operation effect. Some embodiments of the application also evaluate the performance of the rain and fog driving safety guidance system through the traffic flow, and the evaluation method and the data acquisition process are related, simple and easy to implement.
In some embodiments, S130 comprises: and comparing and analyzing the index change trend in each working mode of the plurality of working modes, wherein the index comprises: obtaining the average speed, the standard deviation of the speed and the headway of each section in the plurality of sections through the evaluation data set; and determining the significant change characteristics of the index caused by the adoption of the rain and fog driving safety induction system. Some embodiments of the application also evaluate the performance of the rain and fog driving safety guidance system by analyzing the change trend and the significance change, and improve the visualization and rationalization of the evaluation result.
The following describes an effect evaluation method for the intelligent high-speed rain and fog driving safety guidance system according to the embodiment of the present application with reference to fig. 2.
As shown in fig. 2, the effect evaluation method includes:
and S110, determining an effect evaluation working mode set (namely determining a plurality of working modes of the S110).
First, the definition of the operation mode is exemplified
The effect evaluation of the rain and fog driving safety guidance system on the expressway is carried out according to the system working mode setting and modes, so that the effect of the system in each working mode is obtained. Therefore, the embodiment of the application needs to determine the system effect evaluation working mode. According to the application environment and the management and control strategy of the conventional rain and fog driving safety guidance system, the modes can be divided into the following categories:
(1) in the first mode: normal environment (denoted by letter N, where N is a natural number greater than 1)
And defining the specific subclass Nx of the class according to an application normal environment preset by the rain and fog driving safety guidance system. For example, Nx values may include N1 and N2, where N1: daytime normal environment. The daytime normal condition refers to a condition of good visibility, no rainfall, snowfall or fog, good illumination, and normal temperature and humidity during the daytime. N2: and (5) normal environment at night. The night normal condition refers to the condition that the day is completely black, no rainfall, snowfall or fog exists, the illumination is good, and the temperature and the humidity are normal.
(2) In the second mode: special weather environments (denoted by letter W), and subcategories by Wy, for example, Wy values may include W1, W2, and W3, where W1: a rainfall environment. W2: and 4, snowing environment. W3: fog, haze and other low visibility environments.
(3) In the third mode: the administration mode (denoted by the letter C).
Subcategories are denoted by Cz. Only the control modes of four common rain and fog driving safety guidance systems are listed below, and the control modes can be redefined according to the actual control modes of the systems in application. For example, Cz values can include C1, C2, C3, and C4.
C1 indicates the rain-fog traffic safety guidance system is off.
C2 shows that the yellow light of the rain and fog traffic safety guidance system is always on.
C3 shows the flashing of yellow lights of the rain and fog traffic safety guidance system.
C4 represents trail tracking for the rain-fog traffic safety guidance system.
It should be noted that the specific meanings of the above control modes C1, C2, C3 and C4 can be redefined according to the actual control modes of different driving safety inducing systems. For example, if a driving safety guidance system in a rainy fog day has two control modes, namely a red light flashing function and a trail tracking function, C2 may represent the red light flashing control mode, and C3 may represent the trail tracking control mode.
The three categories of modes are combined with each other to form a system effect evaluation operation mode set M (i.e. determining S110 a plurality of operation modes), wherein: m = { M1, M2, M3, … …, Mi, … …, Mn }, n = x × y × z, Mi = { Nx, Wy, Cz }.
At S120, effect evaluation data of each mode based on the vehicle running characteristic is collected (corresponding to S120).
And carrying out data acquisition on the defined various modes Mi, and providing basic data for quantitative evaluation of system effects.
The collection method comprises the following steps:
(1) section selection
A plurality of (e.g., 3-5) sections are selected along the system-installation section according to the length of the system-installation section, each section being spaced apart by no more than a preset distance (e.g., 200 m). As an example, a data acquisition cross section is required to be arranged at each of an installation starting point and an installation ending point of the rain and fog traffic safety guidance system, and the rest cross sections can be arranged at the middle section of the system at equal intervals.
(2) Speed per vehicle for each lane
For the acquisition section Sj in the operating mode Mi, the speed of the vehicle a of the acquisition lane b passing through the acquisition section (for example, the speed may be expressed as VabMiSj in kilometer per hour).
(3) Time distance acquisition of each vehicle head of each lane
For the collection section Sj in the working mode Mi, the vehicle a of the collection lane b passes through the collection section and the headway of the front vehicle (for example, the headway can be expressed as habMiSj, unit: second).
(4) Minimum duration of data acquisition for each mode
The minimum time length of data acquisition of each mode can be set to be 15 minutes by comprehensively considering factors such as time required by switching of each mode of the system, inadmissible large span of total time length of data acquisition, response speed of total characteristics of traffic flow to the action of each mode and the like. It is understood that the set value of the minimum acquisition time period can be adjusted by those skilled in the art according to actual needs.
S125, calculating evaluation indexes based on the collected data
And carrying out index calculation on the acquired data such as speed, headway and the like. For example, the specific calculation method is as follows:
(1) speed of rotation
And selecting the average speed and the standard deviation of the speed as evaluation indexes. The speed and the average speed represent the speed of the vehicle motion, and are mainly used for analyzing whether the rain and fog driving safety guidance system can influence the running speed of the vehicle. The speed standard deviation is the average value of the distances of all the speed data from the average speed, the larger the speed standard deviation is, the larger the speed dispersion is, and the accident rate and the speed standard deviation are in positive correlation distribution, namely the accident rate is increased along with the increase of the speed standard deviation.
Average speed
And calculating the average speed of each acquisition section Sj of the lane b under the working mode Mi.
Standard deviation of velocity
And calculating the speed standard deviation of each acquisition section Sj for the lane b under the working mode Mi.
(2) Headway
The headway is the time interval between two adjacent vehicles passing through the same section. The larger the headway, the smaller the mutual influence between the vehicles, and the more favorable the driving.
The calculation process of the accumulated frequency of headway is explained below with an example.
For example, there are 100 headway data with a minimum of 1 second and a maximum of 10 seconds. Wherein:
if there are 7 samples in the range of 1-2 seconds, the frequency is 7/100=0.07, and the cumulative frequency value is 0.07
Secondly, if the headway value has 13 samples within the range of 2-3 seconds, the frequency is 13/100=0.13, and the cumulative frequency value is (r + ② =0.07+0.13= 0.20)
Thirdly, if the headway value has 20 samples within the range of 3-4 seconds, the frequency is 20/100=0.02, and the accumulated frequency value is (r + c) =0.07+0.13+0.02=0.40
And by analogy, the accumulated frequency value is 1 in the last interval.
And then drawing an accumulated frequency curve, wherein the abscissa is a locomotive headway interval, and the ordinate is an accumulated frequency value corresponding to each interval.
S130, analysis and evaluation method
According to the preset action of various management and control modes of the rain and fog driving safety guidance system, the following two items of analysis and evaluation are carried out: (1) and comparing the index change trends in all the modes, and analyzing the influence of system application in different modes on the traffic flow. For example: and comparing average speeds, standard deviation of speeds and headway in different modes. For example, the comparative analysis of headway may include: by accumulating the frequency curve, the catastrophe point of the variation of the headway can be found, the quantile of the headway can be found, and the upper limit value of the headway with the set percentage (namely twenty percent of the headway is determined to be less than 1 second) is further determined, so that the distribution rule and the characteristic value of the headway with or without the system are contrastively analyzed. (2) And (4) carrying out significance test, and analyzing whether the indexes are significantly changed due to system application. For example: and (3) carrying out independent sample test on the indexes under the condition of system existence or not, namely carrying out significance test on the difference of two groups of data, wherein a significance sig value (namely a statistical significance value), namely the probability in a test result reflects the possibility of occurrence of a certain event. Statistics the sig value obtained by the significance test method, for example, when the sig is less than 0.05, the statistical difference exists, which indicates that the rain and fog driving safety induction system has significant influence on the index.
The effect evaluation device of the embodiment of the present application is exemplarily described below with reference to fig. 3.
Referring to fig. 3, fig. 3 shows an effect evaluation device for an intelligent high-speed driving safety inducing system according to an embodiment of the present application, it should be understood that the device corresponds to the above-mentioned method embodiment of fig. 1 or fig. 2, and can perform various steps related to the above-mentioned method embodiment, and specific functions of the device can be referred to the above description, and detailed descriptions are appropriately omitted herein to avoid repetition. The device of fig. 3 includes at least one software function module which can be stored in a memory in the form of software or firmware or solidified in an operating system of the device, and the effect evaluation device for the highway driving safety system comprises: an operation mode determination module 101 configured to determine a plurality of operation modes; a data collection module 102 configured to collect evaluation data sets related to vehicle driving characteristics in each of the plurality of operation modes, respectively, wherein the evaluation data sets include: speed data and headway; and the effect evaluation module 103 is configured to evaluate the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability. In some embodiments, the apparatus further comprises: and the index calculation module is configured to determine the average speed and the standard deviation of the speed of each section in the plurality of sections according to the speed acquired by the data acquisition module.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the apparatus described above may refer to the corresponding process in the method of fig. 1 or fig. 2, and will not be described in detail herein.
Embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, may implement the method described in fig. 1 or fig. 2.
As shown in fig. 4, an information processing apparatus 400 according to an embodiment of the present application includes a memory 410, a processor 420, and a computer program stored in the memory 410 and executable on the processor 420, where the processor 420 can implement the methods shown in fig. 1 and fig. 2 when executing the programs (and read and execute the programs from the memory 410 via a bus 430), and can also be used to implement the methods described in the foregoing embodiments.
According to the control modes and the purposes of the highway rain and fog driving safety induction system under different environmental conditions, a whole set of quantitative evaluation method aiming at the effect of the system is provided based on traffic engineering, the comprehensive evaluation standard of the highway rain and fog driving safety induction system is perfected, and the standardization and the high efficiency of the highway rain and fog driving safety induction system are further promoted. At present, all evaluation methods for a rain and fog driving safety induction system are system function evaluation, but an evaluation method for traffic flow regulation and safety guarantee effects is not seen yet, so that the technical scheme of the embodiment of the application has no existing alternative scheme. That is, some embodiments of the present application data acquisition parameters: acquiring the speed and the headway of a single vehicle with a typical section, and evaluating the effect of each working mode of the rain and fog driving guidance system; data analysis of some embodiments of the present application evaluates content: and calculating the average speed, the standard deviation of the speed and the accumulated frequency of the headway of each section and each lane, analyzing the change trend of the indexes, and carrying out significance test.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (11)
1. The effect evaluation method of the intelligent high-speed rain and fog driving safety guidance system is characterized by comprising the following steps of:
determining a plurality of working modes;
respectively collecting evaluation data sets related to vehicle running characteristics in each working mode of the plurality of working modes, wherein the evaluation data sets comprise: vehicle data or flow data, the vehicle data comprising: speed data and headway data;
and evaluating the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability.
2. The effect evaluation method according to claim 1, wherein the plurality of operation modes include: a normal environment mode, a special weather environment mode and a control mode adopting the rain and fog driving safety guidance system.
3. The effect evaluation method according to claim 1, wherein the collecting evaluation data sets relating to the running characteristic of the vehicle in each of the plurality of operation modes, respectively, comprises:
selecting a plurality of discontinuous sections from a road section provided with the rain and fog traffic safety guidance system;
acquiring the speed of a first vehicle passing through each section of the plurality of sections of the first lane in each working mode of the plurality of working modes;
and under each working mode, acquiring a headway time distance between the first vehicle and a preceding vehicle when the first vehicle passes through each section of the plurality of sections of the first lane, wherein the headway time distance is used for representing a time interval between two adjacent vehicles which at least comprise the first vehicle and pass through the same section.
4. The effect evaluation method according to claim 3, further comprising: and determining to terminate the data acquisition process of each working mode in the plurality of working modes according to the set acquisition duration.
5. The method of evaluating an effect according to claim 3,
before the evaluating the operation effect of the rain and fog driving safety inducing system according to the evaluation data set, the effect evaluating method further comprises the following steps:
determining the average speed and the standard deviation of the speed of each section in the plurality of sections according to the acquired speed;
the evaluation of the operation effect of the rain and fog driving safety guidance system according to the evaluation data set comprises the following steps: and comparing the average speed, the speed standard deviation and the headway time distance in each working mode of the plurality of working modes to determine the running effect.
6. The effect evaluation method according to claim 1, wherein before the evaluation of the operation effect of the rain driving safety guidance system based on the evaluation data set, the effect evaluation method further comprises: determining the traffic volume passing through every hour according to the acquired traffic data;
the evaluation of the operation effect of the rain and fog driving safety guidance system according to the evaluation data set comprises the following steps: and comparing the hourly traffic volume in each working mode of the plurality of working modes to determine the operation effect.
7. The effect evaluation method according to claim 1, wherein the evaluating the operation effect of the rain and fog driving safety guidance system according to the evaluation data comprises:
and comparing and analyzing the index change trend in each working mode of the plurality of working modes, wherein the index comprises: obtaining the average speed, the standard deviation of the speed and the headway of each section in a plurality of sections through the evaluation data set, wherein the sections are discontinuous sections selected from a road section provided with the rain and fog driving safety induction system;
and determining the significant change characteristics of the index caused by the adoption of the rain and fog driving safety induction system.
8. The utility model provides a high-speed rain and fog driving safety of wisdom inducible system's effect evaluation device which characterized in that, the device includes:
an operating mode determination module configured to determine a plurality of operating modes;
a data collection module configured to collect evaluation data sets related to vehicle driving characteristics in each of the plurality of operation modes, respectively, wherein the evaluation data sets include: vehicle data or flow data, the vehicle data comprising: speed data and headway data;
and the effect evaluation module is configured to evaluate the operation effect of the rain and fog driving safety guidance system according to the evaluation data set, wherein the effect comprises the regulation effect on the traffic flow and the effect of reducing the accident occurrence probability.
9. The effect evaluation apparatus according to claim 8, characterized in that the apparatus further comprises: and the index calculation module is configured to determine the average speed and the standard deviation of the speed of each section in a plurality of sections according to the speed acquired by the data acquisition module, wherein the plurality of sections are discontinuous sections selected from a road section provided with the rain and fog driving safety induction system.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, is adapted to carry out the method of any one of claims 1 to 7.
11. An information processing apparatus comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program is operable to implement the method of any one of claims 1 to 7.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010834571.0A CN111739303A (en) | 2020-08-19 | 2020-08-19 | Evaluation method and device of intelligent high-speed rain and fog driving safety guidance system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010834571.0A CN111739303A (en) | 2020-08-19 | 2020-08-19 | Evaluation method and device of intelligent high-speed rain and fog driving safety guidance system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN111739303A true CN111739303A (en) | 2020-10-02 |
Family
ID=72658587
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010834571.0A Pending CN111739303A (en) | 2020-08-19 | 2020-08-19 | Evaluation method and device of intelligent high-speed rain and fog driving safety guidance system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111739303A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115116235A (en) * | 2022-05-20 | 2022-09-27 | 哈尔滨工业大学 | Active inducing method and device for highway flat curve section in foggy weather and low visibility |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101419749A (en) * | 2008-11-20 | 2009-04-29 | 陈伟 | Low-visibility road traffic guiding method |
CN103208194A (en) * | 2013-04-03 | 2013-07-17 | 昆明联诚科技有限公司 | Urban traffic signal cooperative control system |
CN108961790A (en) * | 2018-07-24 | 2018-12-07 | 河北德冠隆电子科技有限公司 | Bad weather pre-warning management system and method based on four-dimensional outdoor scene traffic simulation |
CN109523780A (en) * | 2018-07-19 | 2019-03-26 | 郭忠印 | A kind of mountainous area highway snowfall environment early warning system and method |
WO2020003697A1 (en) * | 2018-06-27 | 2020-01-02 | ソニー株式会社 | Evaluation device and evaluating method |
-
2020
- 2020-08-19 CN CN202010834571.0A patent/CN111739303A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101419749A (en) * | 2008-11-20 | 2009-04-29 | 陈伟 | Low-visibility road traffic guiding method |
CN103208194A (en) * | 2013-04-03 | 2013-07-17 | 昆明联诚科技有限公司 | Urban traffic signal cooperative control system |
WO2020003697A1 (en) * | 2018-06-27 | 2020-01-02 | ソニー株式会社 | Evaluation device and evaluating method |
CN109523780A (en) * | 2018-07-19 | 2019-03-26 | 郭忠印 | A kind of mountainous area highway snowfall environment early warning system and method |
CN108961790A (en) * | 2018-07-24 | 2018-12-07 | 河北德冠隆电子科技有限公司 | Bad weather pre-warning management system and method based on four-dimensional outdoor scene traffic simulation |
Non-Patent Citations (1)
Title |
---|
王敏: "高速公路常态性雾区行车智能诱导策略研究", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115116235A (en) * | 2022-05-20 | 2022-09-27 | 哈尔滨工业大学 | Active inducing method and device for highway flat curve section in foggy weather and low visibility |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Gårder | Pedestrian safety at traffic signals: a study carried out with the help of a traffic conflicts technique | |
CN104751642B (en) | A kind of advanced road real-time predictor method of traffic flow operation risk | |
CN111640295B (en) | Intersection accident black point distinguishing method based on potential conflict risk assessment | |
CN111951550B (en) | Traffic safety risk monitoring method and device, storage medium and computer equipment | |
CN101706996A (en) | Method for identifying traffic status of express way based on information fusion | |
US20220383738A1 (en) | Method for short-term traffic risk prediction of road sections using roadside observation data | |
KR102453688B1 (en) | System for assessmenting potential risk of traffic accident and method thereof | |
CN103971516B (en) | Traffic data preprocess method and road conditions detection method | |
CN103956052A (en) | Detecting method and system for road conditions | |
CN113936463A (en) | Tunnel traffic control method and system based on radar and video data fusion | |
CN111986480B (en) | Method, system and storage medium for evaluating influence of urban road traffic incident | |
CN111707476B (en) | Longitudinal driving capability detection method for automatic driving automobile | |
Aron et al. | Traffic indicators, accidents and rain: some relationships calibrated on a French urban motorway network | |
CN111739303A (en) | Evaluation method and device of intelligent high-speed rain and fog driving safety guidance system | |
CN111985749A (en) | Road risk assessment method and device | |
CN115273468B (en) | Traffic jam control strategy generation method and device | |
CN112927497B (en) | Floating car identification method, related method and device | |
CN117885745B (en) | Driving behavior monitoring system based on Internet of vehicles | |
Abhigna et al. | Effect of gap acceptance behavior of the right turning vehicles on the major road stream for uncontrolled three-legged intersections under mixed traffic conditions | |
CN112036709A (en) | Random forest based rainfall weather expressway secondary accident cause analysis method | |
CN118097973B (en) | Traffic peak-shifting risk management and control system for travel | |
CN114944083B (en) | Method for judging distance between running vehicle on expressway and front vehicle | |
CN117351726B (en) | Highway event early warning system and comprehensive perception method | |
Wang et al. | Empirical analysis of missing data issues for ATIS applications: Travel time prediction | |
Almutairi | Effect of traffic signal countdown timers and speed and red-light cameras on operation and safety |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201002 |
|
RJ01 | Rejection of invention patent application after publication |