CN118010059A - Path planning system and method based on personalized comfort control - Google Patents
Path planning system and method based on personalized comfort control Download PDFInfo
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Abstract
The invention relates to the technical field of big data, in particular to a path planning system and a path planning method based on personalized comfort control, wherein the system comprises a path information planning module, a path comfort analysis module, a path proposal recommendation proposal generation module and an optimal path proposal recommendation module, the path comfort analysis module is used for preprocessing the generated path planning information, acquiring corresponding path user feedback reports through historical data according to preprocessing results, analyzing proposal comfort conditions corresponding to different path planning information according to feedback reports of different users.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a path planning system and method based on personalized comfort control.
Background
With the continuous development of economy, the holding quantity of resident automobiles is also rapidly increased, a large number of users and wide development space are obtained by navigation software, great convenience is provided for daily travel of people with respect to development of functions of reducing occurrence time, avoiding congestion, reducing charge and the like in a corresponding navigation algorithm, the existing navigation technology only improves travel efficiency of people, excessive analysis is not carried out on road driving experience, and further, personalized differences of different drivers on driving experience cannot be reflected according to travel routes planned by the existing navigation, so that a path planning system and a path planning method based on personalized comfort control are needed.
Disclosure of Invention
The invention aims to provide a path planning system and a path planning method based on personalized comfort control, which are used for solving the problems in the background technology, and the invention provides the following technical scheme:
A path planning method based on personalized comfort control, the method comprising the steps of:
s1, acquiring a current user intention list, extracting a starting point and an ending point recorded in the current user intention list, screening route planning information conforming to traffic through satellites, and generating a travel route selection scheme by combining satellite screening results;
S2, collecting different user feedback reports of schemes of different travel routes through historical data, analyzing comfort feedback conditions of corresponding road sections by combining the feedback reports of different users, and dynamically analyzing comprehensive comfort degrees corresponding to each travel route selection scheme by combining vehicle information of corresponding users and human body states of the corresponding users;
S3, judging the comprehensive comfort condition of the corresponding travel route based on the comfort analysis condition of the corresponding travel route scheme, generating a path recommendation priority sequence according to the analysis result of the comprehensive comfort, and calibrating the generated path recommendation priority sequence by combining the type of the user passing tool;
And S4, matching the optimal recommended scheme based on the current user traffic tool information, and taking the optimal recommended scheme as an optimal path planning method of the current user.
Further, the method in S1 includes the following steps:
step 1001, acquiring an intention list of a current user, extracting a starting point position and an end point position of a travel route preset by the current user by combining the intention list, and mapping the extracted starting point position and end point position into a longitude and latitude coordinate system;
Step 1002, based on the current user preset starting point position and end point position of the travel route, combining satellite screening to pass-conforming path planning information, mapping the complete travel route into a longitude and latitude coordinate system according to the path planning information, generating multiple segments of complete travel routes based on the preset starting point position and end point position of the travel route, and recording as a set A, wherein each segment of complete travel route takes the user preset starting point position as a starting point, the user preset end point position as an end point,
，
Wherein the method comprises the steps ofAnd n represents the number of the generated multiple complete travel routes based on the preset travel route starting point position and the preset travel route ending point position, wherein the path planning information comprises the travel route from the starting point to the ending point, the predicted time from the starting point to the ending point, the mileage from the starting point to the ending point, the road condition information from the starting point to the ending point and the predicted cost from the starting point to the ending point.
According to the invention, the starting point position and the end point position of the current user preset travel route are obtained, the road section information conforming to the traffic is extracted by combining with the satellite, and then the data reference is provided for the subsequent analysis of the user comfort level evaluation corresponding to different road sections.
Further, the method in S2 includes the following steps:
Step 2001, based on the elements in the set A, collecting feedback reports of different users corresponding to the complete travel routes through historical data, counting user feedback reports related to an nth complete travel route in the generated multiple complete travel routes, and recording the counting result in a table M;
2002, extracting a curve corresponding to an nth complete travel route in a longitude and latitude coordinate system, and cutting off the curve in combination with road condition information to generate a multi-section path curve, wherein the road condition information is a database preset value, the road condition information packet can be cut off by taking a traffic light as a reference point, a road intersection point as a reference point and the appearance of a road as the reference point, and the path curve represents one section of the corresponding curve of the corresponding complete travel route;
Randomly extracting one curve of the multi-section path curves, and marking an a-th curve of the multi-section path curves as a curve And combine the data extraction curves/>, in table MThe user feedback report, corresponding to the one involved in the complete travel route, is noted as set B,
，
Wherein the method comprises the steps ofRepresenting an mth user feedback report related to a section corresponding to an a-th curve in the multi-section path curves;
step 2003, combining the analysis results in step 2002, calculating the comfort feedback condition of the corresponding user for the section corresponding to the a-th curve in the multi-section path curves, and marking as ，
，
Wherein the method comprises the steps of、/>And/>All represent the proportionality coefficient which is the preset value of the database,/>Representing the comprehensive flatness of the section corresponding to the a-th curve,/>The method comprises the steps of representing the operability of a section corresponding to an a curve, wherein the operability represents road meeting, the operability is obtained by inquiring a corresponding user feedback report, the operability is divided into a first level, a second level and a third level, wherein the first level represents the road meeting difficulty level easily, the second level represents the road meeting difficulty level moderately, the third level represents the road meeting difficulty level difficultly, the meeting difficulty level feeds back the meeting difficulty level by judging the maximum distance value between meeting vehicles, and when the maximum distance value between meeting vehicles is in a section/>When the maximum distance value between vehicles is in the interval/>, the maneuverability is determined to be the first levelWhen the maximum distance value between vehicles is in the interval/>, judging that the maneuverability is two-stageWhen the operation is performed, the operability is determined to be three-level,/>、/>And/>Are all the preset values of the database,Representing the congestion degree of a road section corresponding to an a-th curve, wherein the congestion degree is obtained by inquiring a user feedback report, the congestion degree is divided into a first level, a second level, a third level, a fourth level and a fifth level, the first level represents smooth, the second level represents basically smooth, the third level represents slightly smooth, the fourth level represents moderate congestion, the fifth level represents severe congestion, the congestion degree of the corresponding road section is judged by analyzing the driving mileage per minute of a traveling vehicle, and when the driving mileage per minute of the corresponding vehicle is monitored, the congestion degree of the corresponding road section is judgedWhen the corresponding vehicle is monitored to drive the mileage per minute, the congestion degree is judged to be the first levelWhen the corresponding vehicle is monitored to run the mileage per minute, the congestion degree is judged to be the second levelWhen the congestion degree is judged to be three-level, and when the running mileage of the corresponding vehicle per minute is monitored to be in the intervalWhen the corresponding vehicle is monitored to run the mileage per minute, the congestion degree is judged to be four-levelIf yes, judging the congestion degree as five-level,/>、/>、/>、/>And/>Are all the preset values of the database,
Wherein the method comprises the steps of，
Wherein the method comprises the steps of、/>/>All represent the proportionality coefficient which is the preset value of the database,/>Representing the flatness of the section corresponding to the a-th curve, wherein the flatness is obtained by detecting through a measuring instrument,/>Feedback value of tire pressure in vehicle information representing that the w-th user runs through a road section corresponding to the a-th curve,/>Representing a human body state feedback value of a w user driving through a road section corresponding to the a curve, wherein the human body comfort feedback value is obtained through feedback of pressure sensor data corresponding to the main driving seat configuration of the user,
A first plane rectangular coordinate system is constructed by taking a point o as an origin, taking a time node as an x axis and taking a feedback value as a y axis,
Marking coordinate points corresponding to tire pressure feedback values in the running of a road section corresponding to an a curve at different time nodes of a w user in a first plane rectangular coordinate system, sequentially connecting two adjacent coordinate points, and generating a fitting curve，
A second plane rectangular coordinate system is constructed by taking the point o1 as an origin, taking a time node as an x1 axis and taking a feedback value as a y1 axis,
In a second plane rectangular coordinate system, marking coordinate points corresponding to human body state feedback values in the running process of a road section corresponding to an a curve at different time nodes of a w user, and sequentially connecting two adjacent coordinate points to generate a fitting curve，
Then，/>Wherein t represents the number of time nodes,/>Representing a tire pressure feedback standard value which is a database preset value,/>Representing a human body state feedback standard value, wherein the human body state feedback standard value is a database preset value;
Step 2004, cycling steps 2002-2003 to obtain comfort feedback conditions of different users for the section corresponding to the a-th curve in the multi-section path curves, and analyzing the comprehensive comfort level of the n-th complete travel route by combining the comfort feedback conditions, and marking as ，
，
Wherein the method comprises the steps ofAnd/>All represent the proportionality coefficient which is the preset value of the database,/>The comfort feedback condition of the jth user for the section corresponding to the (a) curve in the multi-section path curve is represented, i represents the number of comfort feedback users for the section corresponding to the (a) curve in the multi-section path curve, and i is represented by the number of the feedback users for the comfort feedback of the section corresponding to the (a) curve in the multi-section path curveRepresenting the number of users feedback for the comfort level of the nth complete route of the multiple complete routes,/>Representing the time of the nth user's passage through the nth complete travel route of the multiple complete travel routes,/>A comprehensive score representing the nth complete travel route of the multiple complete travel routes, wherein the comprehensive score is obtained through corresponding user comfort feedback report inquiry;
step 2005, looping step 2001-step 2004 result in a comprehensive comfort level corresponding to the different complete travel routes.
According to the invention, the comprehensive comfort level analysis report is generated by analyzing the comprehensive comfort level conditions of the corresponding road sections in each path planning information and combining the feedback information of different users and the feedback information of the users with the same path, so that the data reference is provided for the subsequent generation of the priority recommendation sequence by combining the comfort level feedback conditions of each road section and the comprehensive comfort level corresponding to the complete path planning.
Further, the method in S3 includes the following steps:
Step 3001, obtaining comprehensive comfort degree analysis results corresponding to different complete travel routes in step 2005, generating a path recommendation priority sequence according to the sequence of the comprehensive comfort degree from small to large, marking as a sequence C,
，
Wherein the method comprises the steps ofRepresenting the comprehensive comfort level corresponding to the kth complete travel route;
Step 3002, binding the best passing tool based on the corresponding element in the sequence C, extracting the kth element in the sequence C, counting the passing tools related to the user corresponding to the kth element, obtaining the passing tool corresponding to the highest occurrence frequency of the passing tools by combining the counting result as the best passing tool of the corresponding complete travel route, combining the feedback result of the corresponding user comfort degree identical to the nth complete travel route, dividing the elements in the sequence C,
Extracting the elements with the same optimal passing tool in the sequence C, adjusting the sequence of the elements in the sequence C by combining the feedback result of the comfort degree of the corresponding user, generating a sequence set D according to the adjustment result,
，
Wherein the method comprises the steps ofAnd f represents the number of types of passing tools, wherein the number of types of passing tools is a database preset value, the sequences corresponding to each element in the sequence set D are ordered according to the order from large to small according to the comprehensive comfort level, and if the comprehensive comfort levels are the same in the corresponding sequences, the elements with the large number of adoption times are preferentially selected by taking the number of adoption times corresponding to the complete travel route as a reference.
According to the method, elements in the priority sequence are further divided, the traffic tools which do not need users are combined for classification, and the optimal traffic tools are matched according to the corresponding path planning, so that data reference is provided for the follow-up analysis of the recommendation of the optimal path planning of the current user.
Further, the method in S4 includes the following steps:
Step 4001, acquiring current user traffic tool information, and extracting a sequence set conforming to the current user traffic tool information by combining the analysis result in step 3002;
Step 4002, based on the analysis result in step 4001, taking the first element in the sequence set conforming to the current user traffic tool information as the optimal path planning method of the current user.
A path planning system based on personalized comfort control, the system comprising the following modules:
And a path information planning module: the path information planning module is used for acquiring a current user intention list, extracting a starting point and an ending point recorded in the current user intention list, screening path planning information conforming to traffic through satellites, and generating a travel route selection scheme by combining satellite screening results;
Path comfort analysis module: different user feedback reports of schemes of different travel routes are acquired through historical data, the feedback reports of different users are combined to analyze comfort feedback conditions of corresponding road sections, and the comprehensive comfort degree corresponding to each travel route selection scheme is comprehensively analyzed by combining vehicle dynamic information of corresponding users and comfort dynamic feedback values of corresponding users;
The path scheme recommendation scheme generation module: the route scheme recommendation scheme generation module is used for judging the comprehensive comfort condition of the corresponding travel route based on the comfort analysis condition of the corresponding travel route scheme, generating a route recommendation priority sequence according to the analysis result of the comprehensive comfort, and calibrating the generated route recommendation priority sequence by combining the type of a user passing tool;
the optimal path scheme recommending module: the optimal path scheme recommending module is used for matching an optimal recommended scheme based on the traffic tool information of the current user, and taking the optimal recommended scheme as an optimal path planning method of the current user.
Further, the path information planning module includes a path query unit and a path generation unit:
the path query unit is used for acquiring an intention list of a current user, and extracting a starting point position and an end point position of a travel route preset by the current user by combining the intention list;
the path generation unit is used for generating path planning information conforming to traffic by combining satellites based on the analysis result of the path inquiry unit.
Further, the path comfort level analysis module comprises a data acquisition unit, a road section comfort level analysis unit and a comprehensive comfort level calculation unit:
the data acquisition unit is used for acquiring feedback reports of different users of the corresponding complete travel route through historical data based on the analysis result of the path generation unit;
the road section comfort level analysis unit is used for calculating the comfort level feedback condition of the corresponding path by combining the analysis result of the data acquisition unit;
The comprehensive comfort level calculating unit is used for further comprehensively analyzing the comprehensive comfort level corresponding to the corresponding complete travel route by combining the analysis result of the road section comfort level analyzing unit.
Further, the path scheme recommendation scheme generating module includes a priority sequence generating unit and a sequence calibrating unit:
the priority sequence generating unit is used for setting a sequence rule by combining the analysis result of the comprehensive comfort level calculating unit and generating a priority sequence by combining the sequence mechanism;
the sequence calibration unit is used for carrying out sequence calibration on the priority sequence based on the analysis result of the priority sequence generation unit and combining a traffic tool adopted by the corresponding user.
Further, the best path scheme recommending module comprises a scheme matching unit and a best path planning confirming unit:
The scheme matching unit is used for combining the current user to adopt a traffic tool, and combining the analysis result of the sequence calibration unit to match the route planning scheme conforming to the current user;
the optimal path planning confirming unit is used for confirming an optimal path planning method based on the analysis result of the scheme matching unit.
According to the invention, by acquiring all feasible routes from the starting point to the end point, calculating the driving comfort level of the corresponding road section based on the feedback condition of the corresponding user of each road section, and matching the optimal route planning by combining the current user passing tool, so that the optimal route planning information is matched for the current user, the driving feeling of the current user is effectively met, and meanwhile, the journey of the current user is more comfortable.
Drawings
FIG. 1 is a flow chart of a personalized comfort control based path planning method of the present invention;
Fig. 2 is a block diagram of a path planning system based on personalized comfort control of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: referring to fig. 1, in this embodiment:
A path planning method based on personalized comfort control, the method comprising the steps of:
s1, acquiring a current user intention list, extracting a starting point and an ending point recorded in the current user intention list, screening route planning information conforming to traffic through satellites, and generating a travel route selection scheme by combining satellite screening results;
The method in S1 comprises the following steps:
step 1001, acquiring an intention list of a current user, extracting a starting point position and an end point position of a travel route preset by the current user by combining the intention list, and mapping the extracted starting point position and end point position into a longitude and latitude coordinate system;
Step 1002, based on the current user preset starting point position and end point position of the travel route, combining satellite screening to pass-conforming path planning information, mapping the complete travel route into a longitude and latitude coordinate system according to the path planning information, generating multiple segments of complete travel routes based on the preset starting point position and end point position of the travel route, and recording as a set A, wherein each segment of complete travel route takes the user preset starting point position as a starting point, the user preset end point position as an end point,
，
Wherein the method comprises the steps ofAnd n represents the number of the generated multiple complete travel routes based on the preset travel route starting point position and the preset travel route ending point position, wherein the path planning information comprises the travel route from the starting point to the ending point, the predicted time from the starting point to the ending point, the mileage from the starting point to the ending point, the road condition information from the starting point to the ending point and the predicted cost from the starting point to the ending point.
S2, collecting different user feedback reports of schemes of different travel routes through historical data, analyzing comfort feedback conditions of corresponding road sections by combining the feedback reports of different users, and dynamically analyzing comprehensive comfort degrees corresponding to each travel route selection scheme by combining vehicle information of corresponding users and human body states of the corresponding users;
the method in S2 comprises the steps of:
Step 2001, based on the elements in the set A, collecting feedback reports of different users corresponding to the complete travel routes through historical data, counting user feedback reports related to an nth complete travel route in the generated multiple complete travel routes, and recording the counting result in a table M;
2002, extracting a curve corresponding to an nth complete travel route in a longitude and latitude coordinate system, and cutting off the curve in combination with road condition information to generate a multi-section path curve, wherein the road condition information is a database preset value, the road condition information packet can be cut off by taking a traffic light as a reference point, a road intersection point as a reference point and the appearance of a road as the reference point, and the path curve represents one section of the corresponding curve of the corresponding complete travel route;
Randomly extracting one curve of the multi-section path curves, and marking an a-th curve of the multi-section path curves as a curve And combine the data extraction curves/>, in table MThe user feedback report, corresponding to the one involved in the complete travel route, is noted as set B,
，
Wherein the method comprises the steps ofRepresenting an mth user feedback report related to a section corresponding to an a-th curve in the multi-section path curves;
step 2003, combining the analysis results in step 2002, calculating the comfort feedback condition of the corresponding user for the section corresponding to the a-th curve in the multi-section path curves, and marking as ，
，
Wherein the method comprises the steps of、/>And/>All represent the proportionality coefficient which is the preset value of the database,/>Representing the comprehensive flatness of the section corresponding to the a-th curve,/>The method comprises the steps of representing the operability of a section corresponding to an a curve, wherein the operability represents road meeting, and is obtained by inquiring a corresponding user feedback report, wherein the meeting difficulty level is fed back to the meeting difficulty level by judging the maximum distance value between the meeting vehicles, the operability is divided into one level, two levels and three levels, wherein the one level represents the road meeting difficulty level is easy, the two levels represent the road meeting difficulty level is medium, and the three levels represent the road meeting difficulty level is difficult, i.e./>Representing the congestion degree of the road section corresponding to the a-th curve, wherein the congestion degree is obtained by inquiring a user feedback report, the congestion degree is divided into a first level, a second level, a third level, a fourth level and a fifth level, the first level represents smooth, the second level represents basically smooth, the third level represents slightly smooth, the fourth level represents moderate congestion, the fifth level represents severe congestion, the congestion degree of the corresponding road section is judged by analyzing the driving mileage per minute of a traveling vehicle,
Wherein the method comprises the steps of，
Wherein the method comprises the steps of、/>/>All represent the proportionality coefficient which is the preset value of the database,/>Representing the flatness of the section corresponding to the a-th curve, wherein the flatness is obtained by detecting through a measuring instrument,/>Representing the tire pressure feedback value in the vehicle information of the w-th user driving through the section corresponding to the a-th curve (the vehicle information comprises the tire pressure feedback value and the starting time, but only the influence of the tire pressure feedback value on the flatness is considered in the application),/>Representing a human body state feedback value of a w user driving through a road section corresponding to the a curve, wherein the human body comfort feedback value is obtained through feedback of pressure sensor data corresponding to the main driving seat configuration of the user,
A first plane rectangular coordinate system is constructed by taking a point o as an origin, taking a time node as an x axis and taking a feedback value as a y axis,
Marking coordinate points corresponding to tire pressure feedback values in the running of a road section corresponding to an a curve at different time nodes of a w user in a first plane rectangular coordinate system, sequentially connecting two adjacent coordinate points, and generating a fitting curve，
A second plane rectangular coordinate system is constructed by taking the point o1 as an origin, taking a time node as an x1 axis and taking a feedback value as a y1 axis,
In a second plane rectangular coordinate system, marking coordinate points corresponding to human body state feedback values in the running process of a road section corresponding to an a curve at different time nodes of a w user, and sequentially connecting two adjacent coordinate points to generate a fitting curve，
Then，/>Wherein t represents the number of time nodes,/>Representing a tire pressure feedback standard value which is a database preset value,/>Representing a human body state feedback standard value, wherein the human body state feedback standard value is a database preset value;
Step 2004, cycling steps 2002-2003 to obtain comfort feedback conditions of different users for the section corresponding to the a-th curve in the multi-section path curves, and analyzing the comprehensive comfort level of the n-th complete travel route by combining the comfort feedback conditions, and marking as ，
，
Wherein the method comprises the steps ofAnd/>All represent the proportionality coefficient which is the preset value of the database,/>The comfort feedback condition of the jth user for the section corresponding to the (a) curve in the multi-section path curve is represented, i represents the number of comfort feedback users for the section corresponding to the (a) curve in the multi-section path curve, and i is represented by the number of the feedback users for the comfort feedback of the section corresponding to the (a) curve in the multi-section path curveRepresenting the number of users feedback for the comfort level of the nth complete route of the multiple complete routes,/>Representing the time of the nth user's passage through the nth complete travel route of the multiple complete travel routes,/>A comprehensive score representing the nth complete travel route of the multiple complete travel routes, wherein the comprehensive score is obtained through corresponding user comfort feedback report inquiry;
step 2005, looping step 2001-step 2004 result in a comprehensive comfort level corresponding to the different complete travel routes.
S3, judging the comprehensive comfort condition of the corresponding travel route based on the comfort analysis condition of the corresponding travel route scheme, generating a path recommendation priority sequence according to the analysis result of the comprehensive comfort, and calibrating the generated path recommendation priority sequence by combining the type of the user passing tool;
the method in S3 comprises the following steps:
Step 3001, obtaining comprehensive comfort degree analysis results corresponding to different complete travel routes in step 2005, generating a path recommendation priority sequence according to the sequence of the comprehensive comfort degree from small to large, marking as a sequence C,
，
Wherein the method comprises the steps ofRepresenting the comprehensive comfort level corresponding to the kth complete travel route;
Step 3002, binding the best passing tool based on the corresponding element in the sequence C, extracting the kth element in the sequence C, counting the passing tools related to the user corresponding to the kth element, obtaining the passing tool corresponding to the highest occurrence frequency of the passing tools by combining the counting result as the best passing tool of the corresponding complete travel route, combining the feedback result of the corresponding user comfort degree identical to the nth complete travel route, dividing the elements in the sequence C,
Extracting the elements with the same optimal passing tool in the sequence C, adjusting the sequence of the elements in the sequence C by combining the feedback result of the comfort degree of the corresponding user, generating a sequence set D according to the adjustment result,
，
Wherein the method comprises the steps ofAnd f represents the number of types of passing tools, wherein the number of types of passing tools is a database preset value, the sequences corresponding to each element in the sequence set D are ordered according to the order from large to small according to the comprehensive comfort level, and if the comprehensive comfort levels are the same in the corresponding sequences, the elements with the large number of adoption times are preferentially selected by taking the number of adoption times corresponding to the complete travel route as a reference.
And S4, matching the optimal recommended scheme based on the current user traffic tool information, and taking the optimal recommended scheme as an optimal path planning method of the current user.
The method in S4 includes the steps of:
Step 4001, acquiring current user traffic tool information, and extracting a sequence set conforming to the current user traffic tool information by combining the analysis result in step 3002;
Step 4002, based on the analysis result in step 4001, taking the first element in the sequence set conforming to the current user traffic tool information as the optimal path planning method of the current user.
In this embodiment: a path planning system (as shown in fig. 2) based on personalized comfort control is disclosed, the system is used for realizing specific scheme content of a method, and the system comprises the following modules:
And a path information planning module: the path information planning module is used for acquiring a current user intention list, extracting a starting point and an ending point recorded in the current user intention list, screening path planning information conforming to traffic through satellites, and generating a travel route selection scheme by combining satellite screening results;
Path comfort analysis module: different user feedback reports of schemes of different travel routes are acquired through historical data, the feedback reports of different users are combined to analyze comfort feedback conditions of corresponding road sections, and the comprehensive comfort degree corresponding to each travel route selection scheme is comprehensively analyzed by combining vehicle dynamic information of corresponding users and comfort dynamic feedback values of corresponding users;
The path scheme recommendation scheme generation module: the route scheme recommendation scheme generation module is used for judging the comprehensive comfort condition of the corresponding travel route based on the comfort analysis condition of the corresponding travel route scheme, generating a route recommendation priority sequence according to the analysis result of the comprehensive comfort, and calibrating the generated route recommendation priority sequence by combining the type of a user passing tool;
the optimal path scheme recommending module: the optimal path scheme recommending module is used for matching an optimal recommended scheme based on the traffic tool information of the current user, and taking the optimal recommended scheme as an optimal path planning method of the current user.
The path information planning module comprises a path inquiring unit and a path generating unit:
the path query unit is used for acquiring an intention list of a current user, and extracting a starting point position and an end point position of a travel route preset by the current user by combining the intention list;
the path generation unit is used for generating path planning information conforming to traffic by combining satellites based on the analysis result of the path inquiry unit.
The path comfort level analysis module comprises a data acquisition unit, a road section comfort level analysis unit and a comprehensive comfort level calculation unit:
the data acquisition unit is used for acquiring feedback reports of different users of the corresponding complete travel route through historical data based on the analysis result of the path generation unit;
the road section comfort level analysis unit is used for calculating the comfort level feedback condition of the corresponding path by combining the analysis result of the data acquisition unit;
The comprehensive comfort level calculating unit is used for further comprehensively analyzing the comprehensive comfort level corresponding to the corresponding complete travel route by combining the analysis result of the road section comfort level analyzing unit.
The path scheme recommendation scheme generation module comprises a priority sequence generation unit and a sequence calibration unit:
the priority sequence generating unit is used for setting a sequence rule by combining the analysis result of the comprehensive comfort level calculating unit and generating a priority sequence by combining the sequence mechanism;
the sequence calibration unit is used for carrying out sequence calibration on the priority sequence based on the analysis result of the priority sequence generation unit and combining a traffic tool adopted by the corresponding user.
The optimal path scheme recommending module comprises a scheme matching unit and an optimal path planning confirming unit:
The scheme matching unit is used for combining the current user to adopt a traffic tool, and combining the analysis result of the sequence calibration unit to match the route planning scheme conforming to the current user;
the optimal path planning confirming unit is used for confirming an optimal path planning method based on the analysis result of the scheme matching unit.
Example 2: setting the starting point set by the current user as A, the end point as B, screening the complete routes conforming to A to B through satellites to obtain 3 routes which are respectively marked as a scheme C1, a scheme C2 and a scheme C3,
Analysis was performed based on scheme C1: extracting a complete route in the scheme C1, analyzing that the corresponding route is combined with a satellite to obtain 4 branches, mapping the complete route in the scheme C1 into a longitude and latitude coordinate system, cutting off a curve corresponding to the complete route in the longitude and latitude coordinate system to obtain a curve 1, a curve 2, a curve 3 and a curve 4,
Analysis was performed based on curve 1: combining the feedback report of the road section statistical approach user corresponding to the curve 1, analyzing the comfort feedback condition of the corresponding user by combining the feedback report, and recording the comfort feedback condition of the road section corresponding to the nth user approach curve 1 as，
，
Comprehensively analyzing comfort degree by combining user feedback reports identical to current user routes and recording as，
The analysis is circulated to obtain comprehensive comfort degree values of the scheme C2 and the scheme C3, which are respectively recorded asAndWherein/>，
And counting the passing tools of the corresponding users according to the corresponding complete routes to obtain the current passing tool which is also the car, and taking the scheme C1 as the recommended route of the current user.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
It is noted that relational terms such as first and second, and the like are 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. Moreover, 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.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A path planning method based on personalized comfort control, characterized in that the method comprises the following steps:
s1, acquiring a current user intention list, extracting a starting point and an ending point recorded in the current user intention list, screening route planning information conforming to traffic through satellites, and generating a travel route selection scheme by combining satellite screening results;
S2, collecting different user feedback reports of schemes of different travel routes through historical data, analyzing comfort feedback conditions of corresponding road sections by combining the feedback reports of different users, and dynamically analyzing comprehensive comfort degrees corresponding to each travel route selection scheme by combining vehicle information of corresponding users and human body states of the corresponding users;
S3, judging the comprehensive comfort condition of the corresponding travel route based on the comfort analysis condition of the corresponding travel route scheme, generating a path recommendation priority sequence according to the analysis result of the comprehensive comfort, and calibrating the generated path recommendation priority sequence by combining the type of the user passing tool;
And S4, matching the optimal recommended scheme based on the current user traffic tool information, and taking the optimal recommended scheme as an optimal path planning method of the current user.
2. The path planning method based on personalized comfort control according to claim 1, wherein the method in S1 comprises the steps of:
step 1001, acquiring an intention list of a current user, extracting a starting point position and an end point position of a travel route preset by the current user by combining the intention list, and mapping the extracted starting point position and end point position into a longitude and latitude coordinate system;
Step 1002, based on the current user preset starting point position and end point position of the travel route, combining satellite screening to pass-conforming path planning information, mapping the complete travel route into a longitude and latitude coordinate system according to the path planning information, generating multiple segments of complete travel routes based on the preset starting point position and end point position of the travel route, and recording as a set A, wherein each segment of complete travel route takes the user preset starting point position as a starting point, the user preset end point position as an end point,
，
Wherein the method comprises the steps ofAnd n represents the number of the generated multiple complete travel routes based on the preset travel route starting point position and the preset travel route ending point position, wherein the path planning information comprises the travel route from the starting point to the ending point, the predicted time from the starting point to the ending point, the mileage from the starting point to the ending point, the road condition information from the starting point to the ending point and the predicted cost from the starting point to the ending point.
3. The path planning method based on personalized comfort control according to claim 2, wherein the method in S2 comprises the steps of:
Step 2001, based on the elements in the set A, collecting feedback reports of different users corresponding to the complete travel routes through historical data, counting user feedback reports related to an nth complete travel route in the generated multiple complete travel routes, and recording the counting result in a table M;
Step 2002, extracting a curve corresponding to an nth complete travel route in a longitude and latitude coordinate system, and cutting off the curve in combination with road condition information to generate a plurality of sections of path curves, wherein the road condition information is a database preset value, and the path curves represent one section of corresponding curves of the corresponding complete travel route;
Randomly extracting one curve of the multi-section path curves, and marking an a-th curve of the multi-section path curves as a curve And combine the data extraction curves/>, in table MThe user feedback report, corresponding to the one involved in the complete travel route, is noted as set B,
，
Wherein the method comprises the steps ofRepresenting an mth user feedback report related to a section corresponding to an a-th curve in the multi-section path curves;
step 2003, combining the analysis results in step 2002, calculating the comfort feedback condition of the corresponding user for the section corresponding to the a-th curve in the multi-section path curves, and marking as ，
，
Wherein the method comprises the steps of、/>And/>All represent the proportionality coefficient which is the preset value of the database,/>Representing the comprehensive flatness of the section corresponding to the a-th curve,/>The method comprises the steps of representing the operability of a road section corresponding to an a curve, wherein the operability represents road meeting, and is obtained by inquiring corresponding user feedback reports, and the operability is divided into a first level, a second level and a third level, wherein the first level represents the difficulty level of the road meeting, the second level represents the difficulty level of the road meeting to be medium, and the third level represents the difficulty level of the road meeting, namely/>The congestion degree of the road section corresponding to the a curve is represented, the congestion degree is obtained by inquiring a user feedback report, wherein the congestion degree is divided into a first level, a second level, a third level, a fourth level and a fifth level, the first level represents smooth, the second level represents basically smooth, the third level represents slightly smooth, the fourth level represents moderate congestion, the fifth level represents serious congestion,
Wherein the method comprises the steps of，
Wherein the method comprises the steps of、/>/>All represent the proportionality coefficient which is the preset value of the database,/>Representing the flatness of the section corresponding to the a-th curve, wherein the flatness is obtained by detecting through a measuring instrument,/>Feedback value of tire pressure in vehicle information representing that the w-th user runs through a road section corresponding to the a-th curve,/>Representing a human body state feedback value of a w user driving through a road section corresponding to the a curve, wherein the human body comfort feedback value is obtained through feedback of pressure sensor data corresponding to the main driving seat configuration of the user,
A first plane rectangular coordinate system is constructed by taking a point o as an origin, taking a time node as an x axis and taking a feedback value as a y axis,
Marking coordinate points corresponding to tire pressure feedback values in the running of a road section corresponding to an a curve at different time nodes of a w user in a first plane rectangular coordinate system, sequentially connecting two adjacent coordinate points, and generating a fitting curve，
A second plane rectangular coordinate system is constructed by taking the point o1 as an origin, taking a time node as an x1 axis and taking a feedback value as a y1 axis,
In a second plane rectangular coordinate system, marking coordinate points corresponding to human body state feedback values in the running process of a road section corresponding to an a curve at different time nodes of a w user, and sequentially connecting two adjacent coordinate points to generate a fitting curve，
Then，/>Wherein t represents the number of time nodes,/>Representing a tire pressure feedback standard value which is a database preset value,/>Representing a human body state feedback standard value, wherein the human body state feedback standard value is a database preset value;
Step 2004, cycling steps 2002-2003 to obtain comfort feedback conditions of different users for the section corresponding to the a-th curve in the multi-section path curves, and analyzing the comprehensive comfort level of the n-th complete travel route by combining the comfort feedback conditions, and marking as ，
，
Wherein the method comprises the steps ofAnd/>All represent the proportionality coefficient which is the preset value of the database,/>The comfort feedback condition of the jth user for the section corresponding to the (a) curve in the multi-section path curve is represented, i represents the number of comfort feedback users for the section corresponding to the (a) curve in the multi-section path curve, and i is represented by the number of the feedback users for the comfort feedback of the section corresponding to the (a) curve in the multi-section path curveRepresenting the number of users feedback for the comfort level of the nth complete route of the multiple complete routes,/>Representing the time of the nth user's passage through the nth complete travel route of the multiple complete travel routes,/>A comprehensive score representing the nth complete travel route of the multiple complete travel routes, wherein the comprehensive score is obtained through corresponding user comfort feedback report inquiry;
step 2005, looping step 2001-step 2004 result in a comprehensive comfort level corresponding to the different complete travel routes.
4. A path planning method based on personalized comfort control according to claim 3, wherein the method in S3 comprises the steps of:
Step 3001, obtaining comprehensive comfort degree analysis results corresponding to different complete travel routes in step 2005, generating a path recommendation priority sequence according to the sequence of the comprehensive comfort degree from small to large, marking as a sequence C,
，
Wherein the method comprises the steps ofRepresenting the comprehensive comfort level corresponding to the kth complete travel route;
Step 3002, binding the best passing tool based on the corresponding element in the sequence C, extracting the kth element in the sequence C, counting the passing tools related to the user corresponding to the kth element, obtaining the passing tool corresponding to the highest occurrence frequency of the passing tools by combining the counting result as the best passing tool of the corresponding complete travel route, combining the feedback result of the corresponding user comfort degree identical to the nth complete travel route, dividing the elements in the sequence C,
Extracting the elements with the same optimal passing tool in the sequence C, adjusting the sequence of the elements in the sequence C by combining the feedback result of the comfort degree of the corresponding user, generating a sequence set D according to the adjustment result,
，
Wherein the method comprises the steps ofAnd f represents the number of types of passing tools, wherein the number of types of passing tools is a database preset value, the sequences corresponding to each element in the sequence set D are ordered according to the order from large to small according to the comprehensive comfort level, and if the comprehensive comfort levels are the same in the corresponding sequences, the elements with the large number of adoption times are preferentially selected by taking the number of adoption times corresponding to the complete travel route as a reference.
5. The path planning method based on personalized comfort control according to claim 4, wherein the method in S4 comprises the steps of:
Step 4001, acquiring current user traffic tool information, and extracting a sequence set conforming to the current user traffic tool information by combining the analysis result in step 3002;
Step 4002, based on the analysis result in step 4001, taking the first element in the sequence set conforming to the current user traffic tool information as the optimal path planning method of the current user.
6. A path planning system based on personalized comfort control, the system comprising the following modules:
And a path information planning module: the path information planning module is used for acquiring a current user intention list, extracting a starting point and an ending point recorded in the current user intention list, screening path planning information conforming to traffic through satellites, and generating a travel route selection scheme by combining satellite screening results;
Path comfort analysis module: different user feedback reports of schemes of different travel routes are acquired through historical data, the feedback reports of different users are combined to analyze comfort feedback conditions of corresponding road sections, and the comprehensive comfort degree corresponding to each travel route selection scheme is comprehensively analyzed by combining vehicle dynamic information of corresponding users and comfort dynamic feedback values of corresponding users;
The path scheme recommendation scheme generation module: the route scheme recommendation scheme generation module is used for judging the comprehensive comfort condition of the corresponding travel route based on the comfort analysis condition of the corresponding travel route scheme, generating a route recommendation priority sequence according to the analysis result of the comprehensive comfort, and calibrating the generated route recommendation priority sequence by combining the type of a user passing tool;
the optimal path scheme recommending module: the optimal path scheme recommending module is used for matching an optimal recommended scheme based on the traffic tool information of the current user, and taking the optimal recommended scheme as an optimal path planning method of the current user.
7. The path planning system based on personalized comfort control according to claim 6, wherein the path information planning module comprises a path query unit and a path generation unit:
the path query unit is used for acquiring an intention list of a current user, and extracting a starting point position and an end point position of a travel route preset by the current user by combining the intention list;
the path generation unit is used for generating path planning information conforming to traffic by combining satellites based on the analysis result of the path inquiry unit.
8. The personalized comfort control-based path planning system of claim 7, wherein the path comfort analysis module comprises a data acquisition unit, a road segment comfort analysis unit, and a comprehensive comfort calculation unit:
the data acquisition unit is used for acquiring feedback reports of different users of the corresponding complete travel route through historical data based on the analysis result of the path generation unit;
the road section comfort level analysis unit is used for calculating the comfort level feedback condition of the corresponding path by combining the analysis result of the data acquisition unit;
The comprehensive comfort level calculating unit is used for further comprehensively analyzing the comprehensive comfort level corresponding to the corresponding complete travel route by combining the analysis result of the road section comfort level analyzing unit.
9. The path planning system based on personalized comfort control according to claim 8, wherein the path plan recommendation generation module comprises a priority sequence generation unit and a sequence calibration unit:
the priority sequence generating unit is used for setting a sequence rule by combining the analysis result of the comprehensive comfort level calculating unit and generating a priority sequence by combining the sequence mechanism;
the sequence calibration unit is used for carrying out sequence calibration on the priority sequence based on the analysis result of the priority sequence generation unit and combining a traffic tool adopted by the corresponding user.
10. The personalized comfort control based path planning system according to claim 9, wherein the best path scenario recommendation module comprises a scenario matching unit and a best path scenario confirmation unit:
The scheme matching unit is used for combining the current user to adopt a traffic tool, and combining the analysis result of the sequence calibration unit to match the route planning scheme conforming to the current user;
the optimal path planning confirming unit is used for confirming an optimal path planning method based on the analysis result of the scheme matching unit.
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