CN115512549A - Traffic information dynamic updating system and method for intelligent automobile - Google Patents
Traffic information dynamic updating system and method for intelligent automobile Download PDFInfo
- Publication number
- CN115512549A CN115512549A CN202211473591.5A CN202211473591A CN115512549A CN 115512549 A CN115512549 A CN 115512549A CN 202211473591 A CN202211473591 A CN 202211473591A CN 115512549 A CN115512549 A CN 115512549A
- Authority
- CN
- China
- Prior art keywords
- time
- road section
- passing
- predicted
- target road
- 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
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000004458 analytical method Methods 0.000 claims abstract description 34
- 238000012545 processing Methods 0.000 claims abstract description 25
- 230000008569 process Effects 0.000 claims abstract description 10
- 230000008859 change Effects 0.000 abstract description 2
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000001149 cognitive effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
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
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
-
- 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
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096827—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed onboard
Abstract
The invention relates to a traffic information dynamic updating system for an intelligent automobile, which comprises: the real-time acquisition component is arranged in the intelligent automobile and used for acquiring the rest road sections of the current driving route in real time in the driving process of the intelligent automobile; the intelligent analysis component is used for executing a prediction analysis action of the passing time length dynamically updated at the reference time aiming at each residual road section of the current driving route; and the duration processing component is used for accumulating the predicted passing durations corresponding to the road sections respectively so as to obtain the reference passing duration of the current driving route. The invention also relates to a traffic information dynamic updating method for the intelligent automobile. According to the method and the device, each road section formed by the driving route can be acquired in real time in the process that the driver drives the intelligent automobile, and the reliability of the predicted passing time length corresponding to each road section is guaranteed by adopting a mode of dynamic change of the reference data, so that key information is provided for selection of the driving strategy of the driver.
Description
Technical Field
The invention relates to the field of intelligent automobile traffic assistance, in particular to a system and a method for dynamically updating traffic information of an intelligent automobile.
Background
The intelligent automobile is a humanized new generation automobile, has a multifunctional integrated comprehensive system, intensively applies the technologies of computer, modern sensing, information fusion, communication, artificial intelligence, automatic control and the like, and is a typical high and new technology comprehensive body. Except for a visual display of automobiles such as a central touch screen and an instrument panel, other applications of most of existing intelligent automobiles can check automobile data, and therefore users are well helped to efficiently acquire real-time data of the automobiles.
In the intelligent automobile driving, due to the fact that cognitive resources are limited, a large amount of information is flooded to burden of a driver. The instrument panel of the vehicle is changed from a simple vehicle driving information display to a complex environment system for bearing vehicle information and interacting the vehicle with other information. The driver needs to acquire the road condition and vehicle condition information related to driving in such a complex information system and also needs to switch among the state information in time, so that the convenience and the high efficiency of visualization are realized. Thus, a number of degrees of application of visual association are common in smart cars.
Even so, the applications commonly used in smart cars are still mainly related to the estimation of the time-consuming duration of the remaining driving routes, so that the driving route selection and the driving strategy selection of the driver can be provided with key data, and the related technical solutions of the time-consuming duration estimation have long been related to, for example:
the patent publication No. CN114396961A provides a method, a device, equipment and a product for assisting navigation of a vehicle, and relates to the technical field of car networking and intelligent cabins, in particular to the technical field of automatic parking, navigation assistance and intelligent identification. The specific implementation scheme is as follows: detecting whether a navigation planning route of a vehicle passes through a target area or not, wherein a preset distance exists between the target area and the current position of the vehicle; if the navigation planning route is detected to be routed to the target area, acquiring relevant recommendation information of the target area, and outputting prompt information corresponding to the target area, wherein the prompt information comprises at least one of the following information: the residual driving distance and the residual driving duration of the vehicle running to the target area, and the related recommendation information; and responding to a navigation switching instruction, switching the navigation planning route into a target navigation route going to the target area, and driving to the target area according to the target navigation route.
Patent publication No. CN112298184A provides a driving switching method, apparatus, device and storage medium based on artificial intelligence; the method and the device can determine the current driving mode of the vehicle and the current driving state of the vehicle in the current driving mode; acquiring historical driving time data of a vehicle; performing data analysis on the historical driving time data to obtain driving time distribution characteristics of the vehicle in each driving mode and predicted driving time of the vehicle in the current driving state; establishing a driving time distribution relation of the vehicle between driving modes based on the driving time distribution characteristics; generating a driving mode switching condition of the vehicle in the current driving mode based on the driving time distribution relation and the predicted driving time; and when the current driving time of the vehicle in the current driving mode is detected to meet the driving mode switching condition, switching the current driving mode of the vehicle to the target driving mode. The scheme can improve the switching efficiency of the driving modes of the vehicle.
Patent publication No. CN112146670A discloses a method, system, computer device and storage medium for planning a driving path, the method comprising: the method comprises the steps of searching for alternative parking places according to a destination, planning alternative driving paths according to the alternative parking places, obtaining total time required by a user to reach the destination from the current position through each alternative parking place according to each alternative parking place and the corresponding alternative driving path, determining a target parking place according to the priority of the total time required by the user to reach the destination from each alternative parking place through each alternative parking place, and planning a target driving path through the target parking place.
However, how to achieve the precision of the lean and refined data is one of the targets urgently pursued by each technical scheme, because of the diversity and variability of traffic data, the high-precision estimation which consumes a long time has a bottleneck.
Disclosure of Invention
In order to solve the technical problems in the related field, the invention provides a system and a method for dynamically updating traffic information of a smart car, which can acquire all road sections formed by a driving route in real time in the process of driving the smart car by a driver, predict the passing time of the current road section based on the multiple historical passing time of the current time section and the same vehicle type in the same time section, acquire the time section in which the second road section falls based on the passing time of the current time section, continuously predict the predicted passing time of the passing second road section based on the time section in which the second road section falls, and recur sequentially.
According to an aspect of the present invention, there is provided a traffic information dynamic update system for an intelligent automobile, the system including:
the real-time acquisition component is arranged in the intelligent automobile and used for acquiring the rest road sections of the current driving route in real time in the driving process of the intelligent automobile;
the intelligent analysis component is arranged near the real-time acquisition component, is connected with the real-time acquisition component, and is used for executing the following predicted analysis actions of the passing time length for each residual road section of the current driving route: taking the remaining first road section of the current driving route as a target road section, taking the current time as the target road section to acquire reference time required by corresponding predicted passing time, predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time corresponding to the target road section when the automobile with the same type as the intelligent automobile passes through the target road section in a time interval falling in the reference time for the last time, taking the predicted time obtained after the current time extends the predicted passing time as the next road section of the target road section to acquire the reference time required by the corresponding predicted passing time, so as to execute acquisition of the predicted passing time of the next road section of the target road section, and successively iterating in the above way to acquire each predicted passing time corresponding to each remaining road section of the current driving route;
the duration processing component is connected with the intelligent analysis component and used for receiving each predicted passing duration corresponding to each remaining road section of the current driving route, accumulating the predicted passing durations to obtain the duration consumed by the intelligent automobile for completing each remaining road section of the current driving route and outputting the duration as the reference passing duration of the current driving route;
the real-time acquisition component, the intelligent analysis component and the duration processing component are used for re-executing the acquisition and output of the reference passing duration of the current driving route at regular time intervals;
the step of predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time lengths corresponding to the fact that the vehicles of the same type as the intelligent automobile pass through the target road section for multiple times recently in the time interval falling to the reference time comprises the following steps: and taking the arithmetic mean of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section.
According to another aspect of the present invention, there is also provided a method for dynamically updating traffic information of a smart car, the method including:
the real-time acquisition component is arranged in the intelligent automobile and used for acquiring the remaining road sections of the current driving route in real time in the driving process of the intelligent automobile;
the intelligent analysis component is arranged near the real-time acquisition component and connected with the real-time acquisition component, and is used for executing the following predictive analysis actions of the passing time length for each residual road section of the current driving route: taking the remaining first road section of the current driving route as a target road section, taking the current time as the target road section to obtain reference time required by corresponding predicted passing time, predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time of the automobile with the same type as the intelligent automobile passing through the target road section respectively corresponding to the reference time within a time interval falling on the reference time, taking the prediction time obtained after the current time extends the predicted passing time as the next road section of the target road section to obtain the reference time required by the corresponding predicted passing time, so as to execute the acquisition of the predicted passing time of the next road section of the target road section, and successively iterating in the above way to obtain each predicted passing time corresponding to each remaining road section of the current driving route;
the use duration processing component is connected with the intelligent analysis component and is used for receiving each predicted passing duration corresponding to each remaining road section of the current driving route, accumulating the predicted passing durations to obtain the duration consumed by the intelligent automobile for driving all the remaining road sections of the current driving route and outputting the duration as the reference passing duration of the current driving route;
the real-time acquisition component, the intelligent analysis component and the duration processing component perform acquisition and output of the reference passing duration of the current driving route again at regular time intervals;
the step of predicting the predicted passing time length of the intelligent automobile passing through the target road section according to the multiple-pass time lengths respectively corresponding to the fact that the vehicles of the same type as the intelligent automobile pass through the target road section in the time interval of the reference time falling for the latest multiple times comprises the following steps: and taking the arithmetic mean of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section.
The invention is more advanced than the prior art in that: the reference time, namely the starting time, of each remaining road section of the current driving route of the intelligent automobile is obtained in a dynamic iteration mode, so that the accuracy of predicting the time consumption of the current driving route of the intelligent automobile is improved, and the technical problem that the time consumption of the remaining driving route of the current driving route is difficult to predict with high accuracy in the prior art is solved.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 1 is a block diagram illustrating a traffic information dynamic update system for a smart car according to a first embodiment of the present invention.
Fig. 2 is a flowchart illustrating steps of a traffic information dynamic updating method for an intelligent vehicle according to a second embodiment of the present invention.
Detailed Description
An embodiment of a traffic information dynamic update method for an intelligent vehicle according to the present invention will be described in detail with reference to the accompanying drawings.
First embodiment
Fig. 1 is a block diagram illustrating a traffic information dynamic update system for a smart car according to a first embodiment of the present invention, the system including:
the real-time acquisition component is arranged in the smart car and used for acquiring the rest road sections of the current driving route in real time in the driving process of the smart car;
the intelligent analysis component is arranged near the real-time acquisition component, is connected with the real-time acquisition component, and is used for executing the following predicted analysis actions of the passing time length for each residual road section of the current driving route: taking the remaining first road section of the current driving route as a target road section, taking the current time as the target road section to acquire reference time required by corresponding predicted passing time, predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time corresponding to the target road section when the automobile with the same type as the intelligent automobile passes through the target road section in a time interval falling in the reference time for the last time, taking the predicted time obtained after the current time extends the predicted passing time as the next road section of the target road section to acquire the reference time required by the corresponding predicted passing time, so as to execute acquisition of the predicted passing time of the next road section of the target road section, and successively iterating in the above way to acquire each predicted passing time corresponding to each remaining road section of the current driving route;
the duration processing component is connected with the intelligent analysis component and used for receiving each predicted passing duration corresponding to each of the rest road sections of the current driving route, accumulating the predicted passing durations to obtain the duration consumed by the intelligent automobile for driving the rest road sections of the current driving route and outputting the duration as the reference passing duration of the current driving route;
the real-time acquisition component, the intelligent analysis component and the duration processing component are used for re-executing the acquisition and output of the reference passing duration of the current driving route at regular time intervals;
the step of predicting the predicted passing time length of the intelligent automobile passing through the target road section according to the multiple-pass time lengths respectively corresponding to the fact that the vehicles of the same type as the intelligent automobile pass through the target road section in the time interval of the reference time falling for the latest multiple times comprises the following steps: taking the arithmetic mean of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time lengths as the predicted passing time lengths of the intelligent automobile passing through the target road section;
for example, the predicted passing time length of the smart car passing through the target road section, which is obtained by taking an arithmetic average of the remaining passing time lengths obtained by removing a maximum value of a preset ratio from the multiple passing time lengths, as a prediction, includes: when the arithmetic mean value of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-passing time lengths is 2 minutes, the predicted passing time length of the intelligent automobile passing through the target road section is 2 minutes;
for another example, the predicted passing time length of the smart car passing through the target road section, which is obtained by taking an arithmetic average of the remaining passing time lengths obtained by removing the maximum value of the preset ratio from the multiple-pass time length, as the prediction, includes: when the arithmetic mean value of the remaining passing time obtained after the maximum value of the preset proportion is removed from the multi-time passing time is 500 milliseconds, the predicted passing time of the intelligent automobile passing through the target road section is 500 milliseconds.
Next, the detailed structure of the traffic information dynamic update system for an intelligent vehicle according to the present invention will be further described.
The system for dynamically updating the traffic information of the intelligent automobile can further comprise:
the reference clock equipment is respectively connected with the real-time acquisition component, the intelligent analysis component and the duration processing component;
and the reference clock equipment sends an operation triggering instruction to the real-time acquisition component, the intelligent analysis component and the duration processing component at regular time intervals.
The system for dynamically updating the traffic information of the intelligent automobile can further comprise:
and the central control display instrument is arranged at a central control console of the intelligent automobile, is connected with the duration processing part and is used for receiving and displaying the latest acquired reference passing duration of the current driving route.
In the traffic information dynamic updating system for smart cars:
taking the arithmetic mean of the remaining passing durations obtained after the maximum value of the preset proportion is removed from the multi-time passing durations as the predicted passing duration of the intelligent automobile passing through the target road section, wherein the predicted passing duration of the intelligent automobile passing through the target road section comprises the following steps: the ratio of the removed maximum values to the number of the multiple-time passing durations is half of the preset ratio;
the method comprises the following steps of taking the arithmetic mean of the remaining passing time lengths obtained by removing the maximum value of the preset proportion from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section, wherein the predicted passing time length of the intelligent automobile passing through the target road section comprises the following steps: the removed minimum values occupy half of the preset proportion of the number of the time duration of the multiple times.
In the traffic information dynamic updating system for smart cars:
taking the predicted time obtained after the current time extends the predicted passing time as the reference time required by acquiring the corresponding predicted passing time of the next road section of the target road section, so as to execute the acquisition of the predicted passing time of the next road section of the target road section, and thus, successively iterating to acquire each predicted passing time corresponding to each remaining road section of the current driving route respectively comprises the following steps: for the next road section of the target road section, predicting the predicted passing time of the intelligent automobile passing through the next road section according to the multiple-time passing time lengths which are respectively corresponding to the target road section when the automobile with the same type as the intelligent automobile passes through the next road section within the time interval of the reference time corresponding to the next road section for the last multiple times, and taking the predicted time obtained after the reference time corresponding to the next road section is extended to the predicted passing time length of the next road section as the reference time required by obtaining the corresponding predicted passing time length of the next road section so as to obtain the predicted passing time length of the next road section of the target road section;
the step of obtaining the predicted passing time corresponding to each of the remaining road sections of the current driving route by successive iteration by using the predicted time obtained after extending the predicted passing time at the current time as the reference time required for obtaining the corresponding predicted passing time of the next road section of the target road section to perform obtaining the predicted passing time of the next road section of the target road section includes: and for the next road section of the target road section, predicting the predicted passing time of the intelligent automobile passing through the next road section according to the multiple-time passing time length which corresponds to the fact that the automobile with the same type as the intelligent automobile passes through the next road section within the time interval which corresponds to the reference time of the next road section for multiple times recently, and taking the predicted time obtained after the reference time corresponding to the next road section is extended to the predicted passing time length of the next road section as the reference time required by acquiring the corresponding predicted passing time length of the third road section after the target road section so as to acquire the predicted passing time length of the third road section after the target road section.
Second embodiment
Fig. 2 is a flowchart illustrating steps of a traffic information dynamic update method for a smart car according to a second embodiment of the present invention, the method including:
the real-time acquisition component is arranged in the intelligent automobile and used for acquiring the remaining road sections of the current driving route in real time in the driving process of the intelligent automobile;
the intelligent analysis component is arranged near the real-time acquisition component and connected with the real-time acquisition component, and is used for executing the following predictive analysis actions of the passing time length for each residual road section of the current driving route: taking the remaining first road section of the current driving route as a target road section, taking the current time as the target road section to obtain reference time required by corresponding predicted passing time, predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time of the automobile with the same type as the intelligent automobile passing through the target road section respectively corresponding to the reference time within a time interval falling on the reference time, taking the prediction time obtained after the current time extends the predicted passing time as the next road section of the target road section to obtain the reference time required by the corresponding predicted passing time, so as to execute the acquisition of the predicted passing time of the next road section of the target road section, and successively iterating in the above way to obtain each predicted passing time corresponding to each remaining road section of the current driving route;
the service duration processing component is connected with the intelligent analysis component and used for receiving each predicted passing duration corresponding to each remaining road section of the current driving route, accumulating the predicted passing durations to obtain the duration consumed by the intelligent automobile for completing each remaining road section of the current driving route and outputting the duration as the reference passing duration of the current driving route;
the real-time acquisition component, the intelligent analysis component and the duration processing component perform acquisition and output of the reference passing duration of the current driving route again at regular time intervals;
the step of predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time lengths corresponding to the fact that the vehicles of the same type as the intelligent automobile pass through the target road section for multiple times recently in the time interval falling to the reference time comprises the following steps: taking the arithmetic mean of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time lengths as the predicted passing time lengths of the intelligent automobile passing through the target road section;
for example, the predicted passing time length of the smart car passing through the target road section, which is obtained by taking an arithmetic average of the remaining passing time lengths obtained by removing the maximum value of the preset proportion from the multiple-pass time length, as the prediction, includes: when the arithmetic mean value of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multiple passing time lengths is 2 minutes, the predicted passing time length of the intelligent automobile passing through the target road section is 2 minutes;
for another example, the predicted passing time length of the smart car passing through the target road segment, which is obtained by dividing the multiple passing time length by the maximum value of the preset ratio, by the arithmetic mean of the remaining passing time lengths, as the prediction, includes: and when the arithmetic mean value of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time length is 500 milliseconds, the predicted passing time length of the intelligent automobile passing through the target road section is 500 milliseconds.
Next, the detailed steps of the traffic information dynamic update method for the intelligent vehicle according to the present invention will be further described.
The traffic information dynamic updating method for the intelligent automobile further comprises the following steps:
the reference clock equipment is respectively connected with the real-time acquisition component, the intelligent analysis component and the duration processing component;
and the reference clock equipment sends an operation triggering instruction to the real-time acquisition component, the intelligent analysis component and the duration processing component at regular time intervals respectively.
The dynamic traffic information updating method for the intelligent automobile further comprises the following steps:
and the central control display instrument is arranged at a central control console of the intelligent automobile, is connected with the duration processing part and is used for receiving and displaying the latest acquired reference passing duration of the current driving route.
In the traffic information dynamic updating method for the intelligent automobile:
the predicted passing time of the intelligent automobile passing through the target road section, which is obtained by taking the arithmetic mean of the remaining passing time obtained by removing the maximum value of the preset proportion from the multi-time passing time, as the prediction, comprises the following steps: the ratio of the removed maximum values to the number of the multiple-time passing durations is half of the preset ratio;
the method comprises the following steps of taking the arithmetic mean of the remaining passing time lengths obtained by removing the maximum value of the preset proportion from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section, wherein the predicted passing time length of the intelligent automobile passing through the target road section comprises the following steps: the removed minimum values occupy half of the preset proportion of the number of the time duration of the multiple times.
And in the traffic information dynamic updating method for the intelligent automobile:
taking the predicted time obtained after extending the predicted passing time at the current time as the reference time required by acquiring the corresponding predicted passing time for the next road section of the target road section, so as to execute the acquisition of the predicted passing time for the next road section of the target road section, and thus, successively iterating to acquire each predicted passing time corresponding to each remaining road section of the current driving route respectively comprises the following steps: for the next road section of the target road section, predicting the predicted passing time of the smart car passing through the next road section according to the multiple-time passing time lengths of the vehicles of the same type as the smart car passing through the target road section in the time interval of the multiple-time passing of the vehicles which pass through the target road section in the time interval of the reference time corresponding to the next road section, wherein the multiple-time passing time lengths are respectively corresponding to the multiple-time passing time lengths, the predicted time obtained after the reference time corresponding to the next road section is extended from the predicted passing time length of the next road section is used as the reference time required by the next road section of the next road section to obtain the corresponding predicted passing time length, and the obtaining of the predicted passing time length of the next road section of the target road section is executed;
the step of obtaining the predicted passing time corresponding to each of the remaining road segments of the current driving route through successive iteration by taking the predicted time obtained after extending the predicted passing time at the current time as the reference time required by obtaining the corresponding predicted passing time for the next road segment of the target road segment to obtain the predicted passing time of the next road segment of the target road segment includes: and for the next road section of the target road section, predicting the predicted passing time of the intelligent automobile passing through the next road section according to the multiple-time passing time length which corresponds to the fact that the automobile with the same type as the intelligent automobile passes through the next road section within the time interval which corresponds to the reference time of the next road section for multiple times recently, and taking the predicted time obtained after the reference time corresponding to the next road section is extended to the predicted passing time length of the next road section as the reference time required by acquiring the corresponding predicted passing time length of the third road section after the target road section so as to acquire the predicted passing time length of the third road section after the target road section.
In addition, in the system and the method for dynamically updating traffic information for a smart car, the obtaining of the predicted passing time of the next road segment of the target road segment by using the predicted time obtained after the current time extends the predicted passing time as the reference time required by obtaining the corresponding predicted passing time of the next road segment of the target road segment, so as to perform the obtaining of the predicted passing time of the next road segment of the target road segment, and thus the obtaining of each predicted passing time corresponding to each remaining road segment of the current driving route by successive iteration includes: and for a third road section behind the target road section, predicting the predicted passing time of the third road section after the intelligent automobile passes through the target road section according to the multiple passing time lengths respectively corresponding to the third road section after the intelligent automobile passes through the target road section in the time interval falling to the reference time corresponding to the third road section behind the target road section for the last multiple times, and taking the predicted time obtained after the reference time corresponding to the third road section behind the target road section is extended to the predicted passing time of the third road section behind the target road section as the reference time required by the fourth road section behind the target road section to obtain the corresponding predicted passing time so as to obtain the predicted passing time of the fourth road section behind the target road section.
The invention has the following three remarkable technical effects:
the method has the technical effects that a dynamic iteration mode is adopted to obtain the reference time, namely the starting time, of each residual road section of the current driving route of the intelligent automobile, so that the time consumption prediction precision of the current driving route of the intelligent automobile is improved;
the method has the advantages that the predicted passing time of the intelligent automobile passing through the road sections is predicted according to the multiple passing time corresponding to the time interval of the intelligent automobile passing through the road sections in the time interval falling on the reference moment in the last multiple times of vehicles of the same type as the intelligent automobile, so that the reliability of the predicted data of the passing time of each specific road section is guaranteed;
the method has the advantages that the passing time of the current driving route of the intelligent automobile is predicted once every fixed time, and therefore a data lag scene is avoided.
By adopting the system and the method for dynamically updating the traffic information of the intelligent automobile, disclosed by the invention, aiming at the technical problem that the residual consumed time of the current driving route is difficult to predict with high precision in the prior art, each road section formed by the driving route can be obtained in real time in the process that a driver drives the intelligent automobile, and the reliability of the predicted passing time corresponding to each road section is ensured by adopting a mode of dynamic change of reference data, so that key information is provided for the selection of the driving strategy of the driver.
The embodiments of the present invention are not limited to the above-described embodiments, and various modifications can be made without departing from the scope of the present invention.
Claims (10)
1. A system for dynamically updating traffic information for a smart car, the system comprising:
the real-time acquisition component is arranged in the smart car and used for acquiring the rest road sections of the current driving route in real time in the driving process of the smart car;
the intelligent analysis component is arranged near the real-time acquisition component and connected with the real-time acquisition component, and is used for executing the following predicted analysis actions of the passing time length for each residual road section of the current driving route: taking the remaining first road section of the current driving route as a target road section, taking the current time as the target road section to obtain reference time required by corresponding predicted passing time, predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time of the automobile with the same type as the intelligent automobile passing through the target road section respectively corresponding to the reference time within a time interval falling on the reference time, taking the prediction time obtained after the current time extends the predicted passing time as the next road section of the target road section to obtain the reference time required by the corresponding predicted passing time, so as to execute the acquisition of the predicted passing time of the next road section of the target road section, and successively iterating in the above way to obtain each predicted passing time corresponding to each remaining road section of the current driving route;
the duration processing component is connected with the intelligent analysis component and used for receiving each predicted passing duration corresponding to each of the rest road sections of the current driving route, accumulating the predicted passing durations to obtain the duration consumed by the intelligent automobile for driving the rest road sections of the current driving route and outputting the duration as the reference passing duration of the current driving route;
the real-time acquisition component, the intelligent analysis component and the duration processing component perform acquisition and output of the reference passing duration of the current driving route again at regular time intervals;
the step of predicting the predicted passing time length of the intelligent automobile passing through the target road section according to the multiple-pass time lengths respectively corresponding to the fact that the vehicles of the same type as the intelligent automobile pass through the target road section in the time interval of the reference time falling for the latest multiple times comprises the following steps: and taking the arithmetic mean of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section.
2. The system of claim 1, wherein the system further comprises:
the reference clock equipment is respectively connected with the real-time acquisition component, the intelligent analysis component and the duration processing component;
and the reference clock equipment sends an operation triggering instruction to the real-time acquisition component, the intelligent analysis component and the duration processing component at regular time intervals respectively.
3. The system for dynamically updating traffic information for a smart car as recited in claim 1, wherein said system further comprises:
and the central control display instrument is arranged at a central control console of the intelligent automobile, is connected with the duration processing part and is used for receiving and displaying the latest acquired reference passing duration of the current driving route.
4. The system for dynamically updating traffic information of an intelligent vehicle according to any one of claims 1-3, wherein:
the predicted passing time of the intelligent automobile passing through the target road section, which is obtained by taking the arithmetic mean of the remaining passing time obtained by removing the maximum value of the preset proportion from the multi-time passing time, as the prediction, comprises the following steps: the ratio of the removed maximum values occupying the number of the multiple-pass time lengths is half of the preset ratio;
the method comprises the following steps of taking the arithmetic mean of the remaining passing durations obtained after the maximum value of the preset proportion is removed from the multi-time passing duration as the predicted passing duration of the intelligent automobile passing the target road section, wherein the predicted passing duration of the intelligent automobile passing the target road section comprises the following steps: the removed minimum values occupy half of the preset ratio of the number of the multi-pass time periods.
5. The system for dynamically updating traffic information of an intelligent vehicle according to any one of claims 1-3, wherein:
taking the predicted time obtained after the current time extends the predicted passing time as the reference time required by acquiring the corresponding predicted passing time of the next road section of the target road section, so as to execute the acquisition of the predicted passing time of the next road section of the target road section, and thus, successively iterating to acquire each predicted passing time corresponding to each remaining road section of the current driving route respectively comprises the following steps: for the next road section of the target road section, predicting the predicted passing time of the intelligent automobile passing through the next road section according to the multiple-time passing time lengths which are respectively corresponding to the target road section when the automobile with the same type as the intelligent automobile passes through the next road section within the time interval of the reference time corresponding to the next road section for the last multiple times, and taking the predicted time obtained after the reference time corresponding to the next road section is extended to the predicted passing time length of the next road section as the reference time required by obtaining the corresponding predicted passing time length of the next road section so as to obtain the predicted passing time length of the next road section of the target road section;
the step of obtaining the predicted passing time corresponding to each of the remaining road segments of the current driving route through successive iteration by taking the predicted time obtained after extending the predicted passing time at the current time as the reference time required by obtaining the corresponding predicted passing time for the next road segment of the target road segment to obtain the predicted passing time of the next road segment of the target road segment includes: and for the next road section of the target road section, predicting the predicted passing time of the smart car passing the next road section according to the multiple-pass time lengths which correspond to the time intervals when the car of the same type as the smart car passes the next road section for multiple times in the time interval which corresponds to the reference time of the next road section and falls, and taking the predicted time which is obtained after the reference time corresponding to the next road section is extended to the predicted passing time of the next road section as the reference time required by obtaining the corresponding predicted passing time of the third road section after the target road section so as to obtain the predicted passing time of the third road section after the target road section.
6. A traffic information dynamic updating method for an intelligent automobile is characterized by comprising the following steps:
the real-time acquisition component is arranged in the intelligent automobile and used for acquiring the remaining road sections of the current driving route in real time in the driving process of the intelligent automobile;
using an intelligent analysis component, arranged near and connected with the real-time acquisition component, and used for executing the following predicted analysis actions of the passing time length for each remaining road segment of the current driving route: taking the remaining first road section of the current driving route as a target road section, taking the current time as the target road section to obtain reference time required by corresponding predicted passing time, predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time of the automobile with the same type as the intelligent automobile passing through the target road section respectively corresponding to the reference time within a time interval falling on the reference time, taking the prediction time obtained after the current time extends the predicted passing time as the next road section of the target road section to obtain the reference time required by the corresponding predicted passing time, so as to execute the acquisition of the predicted passing time of the next road section of the target road section, and successively iterating in the above way to obtain each predicted passing time corresponding to each remaining road section of the current driving route;
the use duration processing component is connected with the intelligent analysis component and is used for receiving each predicted passing duration corresponding to each remaining road section of the current driving route, accumulating the predicted passing durations to obtain the duration consumed by the intelligent automobile for driving all the remaining road sections of the current driving route and outputting the duration as the reference passing duration of the current driving route;
the real-time acquisition component, the intelligent analysis component and the duration processing component perform acquisition and output of the reference passing duration of the current driving route again at regular time intervals;
the step of predicting the predicted passing time of the intelligent automobile passing through the target road section according to the multiple passing time lengths corresponding to the fact that the vehicles of the same type as the intelligent automobile pass through the target road section for multiple times recently in the time interval falling to the reference time comprises the following steps: and taking the arithmetic mean of the remaining passing time lengths obtained after the maximum value of the preset proportion is removed from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section.
7. The dynamic traffic information updating method for smart cars according to claim 6, characterized in that the method further comprises:
the reference clock equipment is respectively connected with the real-time acquisition component, the intelligent analysis component and the duration processing component;
and the reference clock equipment sends an operation triggering instruction to the real-time acquisition component, the intelligent analysis component and the duration processing component at regular time intervals.
8. The method of claim 6, wherein the method further comprises:
and the central control display instrument is arranged at a central control console of the intelligent automobile, is connected with the duration processing component and is used for receiving and displaying the latest acquired reference passing duration of the current driving route.
9. The method for dynamically updating traffic information of an intelligent vehicle according to any one of claims 6 to 8, wherein:
taking the arithmetic mean of the remaining passing durations obtained after the maximum value of the preset proportion is removed from the multi-time passing durations as the predicted passing duration of the intelligent automobile passing through the target road section, wherein the predicted passing duration of the intelligent automobile passing through the target road section comprises the following steps: the ratio of the removed maximum values occupying the number of the multiple-pass time lengths is half of the preset ratio;
the method comprises the following steps of taking the arithmetic mean of the remaining passing time lengths obtained by removing the maximum value of the preset proportion from the multi-time passing time length as the predicted passing time length of the intelligent automobile passing through the target road section, wherein the predicted passing time length of the intelligent automobile passing through the target road section comprises the following steps: the removed minimum values occupy half of the preset ratio of the number of the multi-pass time periods.
10. The method for dynamically updating traffic information of an intelligent vehicle according to any one of claims 6 to 8, wherein:
taking the predicted time obtained after extending the predicted passing time at the current time as the reference time required by acquiring the corresponding predicted passing time for the next road section of the target road section, so as to execute the acquisition of the predicted passing time for the next road section of the target road section, and thus, successively iterating to acquire each predicted passing time corresponding to each remaining road section of the current driving route respectively comprises the following steps: for the next road section of the target road section, predicting the predicted passing time of the smart car passing through the next road section according to the multiple-time passing time lengths of the vehicles of the same type as the smart car passing through the target road section in the time interval of the multiple-time passing of the vehicles which pass through the target road section in the time interval of the reference time corresponding to the next road section, wherein the multiple-time passing time lengths are respectively corresponding to the multiple-time passing time lengths, the predicted time obtained after the reference time corresponding to the next road section is extended from the predicted passing time length of the next road section is used as the reference time required by the next road section of the next road section to obtain the corresponding predicted passing time length, and the obtaining of the predicted passing time length of the next road section of the target road section is executed;
the step of obtaining the predicted passing time corresponding to each of the remaining road sections of the current driving route by successive iteration by using the predicted time obtained after extending the predicted passing time at the current time as the reference time required for obtaining the corresponding predicted passing time of the next road section of the target road section to perform obtaining the predicted passing time of the next road section of the target road section includes: and for the next road section of the target road section, predicting the predicted passing time of the intelligent automobile passing through the next road section according to the multiple-time passing time length which corresponds to the fact that the automobile with the same type as the intelligent automobile passes through the next road section within the time interval which corresponds to the reference time of the next road section for multiple times recently, and taking the predicted time obtained after the reference time corresponding to the next road section is extended to the predicted passing time length of the next road section as the reference time required by acquiring the corresponding predicted passing time length of the third road section after the target road section so as to acquire the predicted passing time length of the third road section after the target road section.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211473591.5A CN115512549A (en) | 2022-11-23 | 2022-11-23 | Traffic information dynamic updating system and method for intelligent automobile |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211473591.5A CN115512549A (en) | 2022-11-23 | 2022-11-23 | Traffic information dynamic updating system and method for intelligent automobile |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115512549A true CN115512549A (en) | 2022-12-23 |
Family
ID=84513698
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211473591.5A Pending CN115512549A (en) | 2022-11-23 | 2022-11-23 | Traffic information dynamic updating system and method for intelligent automobile |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115512549A (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103489048A (en) * | 2013-10-17 | 2014-01-01 | 李慧兵 | RFID (Radio Frequency Identification Device) data-based route travel time predicting method |
| TW201413219A (en) * | 2012-09-26 | 2014-04-01 | Hon Hai Prec Ind Co Ltd | System and method for vehicle navigation |
| CN106382939A (en) * | 2015-12-20 | 2017-02-08 | 杭州后博科技有限公司 | System and method for predicating driving time on navigation path based on historical data |
| CN107917714A (en) * | 2016-10-09 | 2018-04-17 | 腾讯科技（深圳）有限公司 | Duration method of estimation and device in navigation procedure |
| CN109059952A (en) * | 2018-10-11 | 2018-12-21 | 国家卫星海洋应用中心 | A kind of stroke duration prediction method and device |
| CN112797994A (en) * | 2019-11-14 | 2021-05-14 | 阿里巴巴集团控股有限公司 | Method for determining estimated arrival time of route, and related device and server |
| CN114822061A (en) * | 2022-03-30 | 2022-07-29 | 阿里巴巴（中国）有限公司 | Arrival time estimation method and device, electronic equipment and computer program product |
| CN115218912A (en) * | 2021-12-10 | 2022-10-21 | 广州汽车集团股份有限公司 | Navigation duration estimation method and device, vehicle and equipment |
-
2022
- 2022-11-23 CN CN202211473591.5A patent/CN115512549A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW201413219A (en) * | 2012-09-26 | 2014-04-01 | Hon Hai Prec Ind Co Ltd | System and method for vehicle navigation |
| CN103489048A (en) * | 2013-10-17 | 2014-01-01 | 李慧兵 | RFID (Radio Frequency Identification Device) data-based route travel time predicting method |
| CN106382939A (en) * | 2015-12-20 | 2017-02-08 | 杭州后博科技有限公司 | System and method for predicating driving time on navigation path based on historical data |
| CN107917714A (en) * | 2016-10-09 | 2018-04-17 | 腾讯科技（深圳）有限公司 | Duration method of estimation and device in navigation procedure |
| CN109059952A (en) * | 2018-10-11 | 2018-12-21 | 国家卫星海洋应用中心 | A kind of stroke duration prediction method and device |
| CN112797994A (en) * | 2019-11-14 | 2021-05-14 | 阿里巴巴集团控股有限公司 | Method for determining estimated arrival time of route, and related device and server |
| CN115218912A (en) * | 2021-12-10 | 2022-10-21 | 广州汽车集团股份有限公司 | Navigation duration estimation method and device, vehicle and equipment |
| CN114822061A (en) * | 2022-03-30 | 2022-07-29 | 阿里巴巴（中国）有限公司 | Arrival time estimation method and device, electronic equipment and computer program product |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104169990B (en) | Method for providing the parking information on free parking space | |
| KR101769723B1 (en) | Movement support apparatus, movement support method, and driving support system | |
| EP2604980B1 (en) | Evaluation Indication System, Evaluation Indication Method and Computer-Readable Storage Medium | |
| WO2016026865A1 (en) | Route planning device and associated method | |
| US20080077316A1 (en) | Traffic State Predicting Apparatus | |
| WO2015051289A1 (en) | System and method for vehicle energy estimation, adaptive control and routing | |
| KR20040108548A (en) | Traffic information management system | |
| GB2541511A (en) | Rapid traffic parameter estimation | |
| CN101795919A (en) | Fuel economy driving assistance apparatus | |
| CN110969834A (en) | Processing method, processing device, computer equipment, storage medium and vehicle dispatching system | |
| CN115523934A (en) | Vehicle track prediction method and system based on deep learning | |
| US8983758B2 (en) | Traffic information management device, traffic information management method, and traffic information management program | |
| CN111737601A (en) | Method, device and equipment for recommending travel strategy and storage medium | |
| CN113970338A (en) | Travel mode recommendation method, related method, device and system | |
| CN115512549A (en) | Traffic information dynamic updating system and method for intelligent automobile | |
| JP3380882B2 (en) | Traffic signal control method and control device | |
| US20240053161A1 (en) | Method for Predicting a Velocity Profile of a Vehicle | |
| US11650067B2 (en) | System and method for reducing route time using big data | |
| CN114781243A (en) | ETA prediction and model training method, device, medium and product | |
| CN111854777B (en) | Updating method of navigation route driving time, navigation method, navigation system and vehicle | |
| CN114298432A (en) | Data processing method, device, equipment and computer storage medium | |
| JPH08129697A (en) | Recommended route guide device | |
| CN114330786A (en) | Vehicle reservation method, device and equipment based on automatic driving and storage medium | |
| CN111681430A (en) | Method for predicting number of stop lines of signal lamp intersection in future in real time | |
| CN112292579A (en) | Method for providing data for a vehicle |
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: 20221223 |
|
| RJ01 | Rejection of invention patent application after publication |