CN112959859B - Driving reminding method and device, electronic equipment and storage medium - Google Patents
Driving reminding method and device, electronic equipment and storage medium Download PDFInfo
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- CN112959859B CN112959859B CN202110221090.7A CN202110221090A CN112959859B CN 112959859 B CN112959859 B CN 112959859B CN 202110221090 A CN202110221090 A CN 202110221090A CN 112959859 B CN112959859 B CN 112959859B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C11/00—Tyre tread bands; Tread patterns; Anti-skid inserts
- B60C11/24—Wear-indicating arrangements
- B60C11/246—Tread wear monitoring systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C19/00—Tyre parts or constructions not otherwise provided for
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C19/00—Tyre parts or constructions not otherwise provided for
- B60C2019/006—Warning devices, e.g. devices generating noise due to flat or worn tyres
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Abstract
The embodiment of the application discloses a driving reminding method and device, electronic equipment and a storage medium. The driving reminding method comprises the following steps: acquiring initial pattern depth data of vehicle tires before a journey is started and historical driving data of a user; determining wear limit data of the vehicle tire in the process according to the initial pattern depth data and the historical driving data; and generating stroke reminding information according to the wear limit data, and sending the stroke reminding information to a user. Because the technical means of determining the predicted wear limit data of the vehicle tire in the journey according to the initial pattern depth data of the vehicle tire before the journey and the historical driving data of the user is adopted, the technical problem that the wear condition of the vehicle tire in the journey cannot be accurately determined in the prior art is solved, and the technical effect of improving the driving safety in the journey is further achieved.
Description
Technical Field
The embodiment of the application relates to the technical field of vehicles, in particular to a driving reminding method, a driving reminding device, electronic equipment and a storage medium.
Background
Tires are important parts of automobiles and need to maintain good adhesion during driving. The pattern depth of a tire is an important factor in evaluating the adhesion of the tire. Therefore, in order to ensure the safety of the tire during driving, the owner of the vehicle preferably knows the abrasion of the tire in the travel in advance so as to replace the tire in time.
And in prior art, the vehicle owner usually gets off the vehicle through naked eyes to observe the vehicle tire before driving or in the driving process, but only the general wear condition of the tire can be simply observed, and the pattern depth state which is difficult to distinguish by the naked eyes needs to be detected by means of special equipment, so that the estimation of the vehicle owner on the tire data is not facilitated.
Disclosure of Invention
The embodiment of the application provides a driving reminding method and device, electronic equipment and a storage medium, so as to achieve the purpose of improving driving safety.
In a first aspect, an embodiment of the present application provides a driving reminding method, including:
acquiring initial pattern depth data of vehicle tires before a journey is started and historical driving data of a user;
determining wear limit data for the vehicle tire during the run from the initial pattern depth data and the historical driving data;
and generating stroke reminding information according to the wear limit data, and sending the stroke reminding information to a user.
Optionally, the wear limit data comprises a limit travel length;
correspondingly, determining wear limit data of the vehicle tire in the travel according to the initial pattern depth data and the historical driving data comprises:
and determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on a pre-constructed limit running time model.
Optionally, the route is composed of road segments of at least two road types;
correspondingly, the method for determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on the limit running time model constructed in advance comprises the following steps:
and determining the limit driving time of the vehicle tire on each road section in the travel according to the road type of each road section in the travel, the mileage data of each road section, the initial pattern depth data and the historical driving data based on a pre-constructed limit driving time model.
Optionally, generating a travel prompting message according to the wear limit data, and sending the travel prompting message to a user, includes:
and if the limit running time is less than the predicted running time of the travel, generating tire replacement reminding information and sending the tire replacement reminding information to a user.
Optionally, the wear limit data further comprises a limit travel speed;
correspondingly, the method for determining the wear limit data of the vehicle tire in the travel according to the initial pattern depth data and the historical driving data further comprises the following steps:
and determining the limit running speed of the vehicle tire in the travel according to the travel data based on a pre-constructed limit running speed model.
Optionally, generating a travel prompting message according to the wear limit data, and sending the travel prompting message to a user, includes:
and if the real-time running speed in the travel is greater than the limit running speed, generating tire wear serious reminding information, and sending the tire wear serious reminding information to a user.
Optionally, the method further includes:
acquiring running data after a journey starts; wherein the driving data at least comprises the traveled mileage and the actual travel speed of the trip;
determining updated wear limit data for the vehicle tyre over the remaining travel from the driving data and the initial profile depth data;
and generating stroke updating reminding information according to the updated wear limit data, and sending the stroke updating reminding information to a user.
In a second aspect, an embodiment of the present application further provides a driving reminding device, including:
the data acquisition module is used for acquiring initial pattern depth data of the vehicle tire before the travel starts and historical driving data of a user;
a wear determination module to determine wear limit data for the vehicle tire during the trip based on the initial pattern depth data and the historical driving data;
and the wear reminding module is used for generating stroke reminding information according to the wear limit data and sending the stroke reminding information to a user.
Optionally, the wear limit data comprises a limit travel length;
accordingly, the wear determination module is specifically configured to:
and determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on a pre-constructed limit running time model.
Optionally, the route is composed of road segments of at least two road types;
accordingly, the wear determination module is specifically configured to:
and determining the limit running time of the vehicle tire on each road section in the travel according to the road type of each road section in the travel, the mileage data of each road section, the initial pattern depth data and the historical driving data based on a pre-constructed limit running time model.
Optionally, the wear-out reminding module is specifically configured to:
and if the limit running time is less than the predicted running time of the travel, generating tire replacement reminding information and sending the tire replacement reminding information to a user.
Optionally, the wear limit data further includes a limit travel speed;
accordingly, the wear determination module is further specifically configured to:
and determining the limit running speed of the vehicle tire in the travel according to the travel data based on a pre-constructed limit running speed model.
Optionally, the wear-out reminding module is specifically configured to:
and if the real-time running speed in the travel is greater than the limit running speed, generating tire wear serious reminding information, and sending the tire wear serious reminding information to a user.
Optionally, the apparatus further includes a wear update reminding module, specifically configured to:
acquiring running data after a journey starts; wherein the driving data at least comprises the traveled mileage and the actual travel speed of the trip;
determining updated wear limit data for the vehicle tyre over the remaining travel from the driving data and the initial profile depth data;
and generating stroke updating reminding information according to the updated wear limit data, and sending the stroke updating reminding information to a user.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a driving reminder method as described in any of the embodiments of the present application.
In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a driving reminding method according to any embodiment of the present application.
One of the above technical solutions has the following advantages or beneficial effects: because the technical means of determining the predicted wear limit data of the vehicle tire in the journey according to the initial pattern depth data of the vehicle tire before the journey and the historical driving data of the user is adopted, the technical problem that the wear condition of the vehicle tire in the journey cannot be accurately determined in the prior art is solved, and the technical effect of improving the driving safety in the journey is achieved.
Drawings
Fig. 1 is a flowchart of a driving reminding method in a first embodiment of the present application;
fig. 2 is a flowchart of a driving reminding method in the second embodiment of the present application;
fig. 3 is a schematic structural diagram of a driving reminding device in a third embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device in the fourth embodiment of the present application.
Detailed Description
Embodiments of the present application are described below with reference to the accompanying drawings.
Example one
Fig. 1 is a flowchart of a driving reminding method in a first embodiment of the present application, and this embodiment is applicable to a case of improving driving safety in a trip based on a vehicle tire wear condition. The method may be performed by a driving alert apparatus, which may be implemented in software and/or hardware, and may be configured in an electronic device, for example, the electronic device may be a device with communication and computing capabilities, such as an in-vehicle device or a mobile device self-contained by a user. As shown in fig. 1, the method specifically includes:
The trip refers to a next pre-travel trip planned by a user driving the vehicle, and in the embodiment of the present application, a source of obtaining the trip data is not limited, and for example, the trip data may be obtained through a starting position in a navigation system on the vehicle-mounted device, or may be automatically input by the user according to an actual trip plan. The initial pattern depth data of the vehicle tire before the trip is started refers to the current residual pattern depth data of the tire on the vehicle before the trip is performed, and in the embodiment of the present application, the obtaining source of the initial pattern depth data is not limited, and for example, the initial pattern depth data may be obtained through actual measurement or determined according to the record of replacing the tire and the vehicle running record. The historical driving data of the user refers to driving habit related data determined according to the historical driving record of the user, the historical driving record can be determined through a pre-stored record associated with the unique identity of the user, and exemplarily, the historical driving data can comprise the historical driving speed of the user and is used for representing the driving average speed of the user; the historical driving data also includes braking data of the user for characterizing the sudden braking frequency of the user.
For example, when a user is about to start a trip, the wear of the vehicle tire during the trip needs to be predicted in advance. The user can use the measuring tool to measure the initial pattern depth data of the current vehicle tire, the measured initial pattern depth data is input into the driving reminding device, and the driving reminding device obtains historical driving data according to the identity of the user when receiving the initial pattern depth data.
And step 102, determining wear limit data of the vehicle tire in the process according to the initial pattern depth data and the historical driving data.
Since the wear rate of the vehicle tire is influenced by the driving speed of the vehicle, the sudden braking frequency and the like, the wear limit data supported by the current vehicle tire can be predicted according to the initial pattern depth data and the historical driving data of the user. Specifically, the worn pattern depth data that can wear the tire of the vehicle at most at present can be determined from the initial pattern depth data, the data such as the historical driving speed and the historical sudden braking frequency of the user can be determined from the historical driving data of the user, the limit driving distance supported by the current worn pattern depth data is determined from the historical driving speed and the sudden braking frequency, and the limit driving distance is used for representing the maximum safe driving distance of the vehicle tire when the user drives at the historical driving speed and the historical sudden braking frequency. For example, the influence degrees of the driving speeds and the sudden braking frequencies of different levels on the pattern depth data are predetermined, the influence degrees of the corresponding levels are determined according to the historical driving speeds and the historical sudden braking frequencies, and the wear limit data of the vehicle tires are determined according to the influence degrees.
In one possible embodiment, the wear limit data includes a limit travel length;
accordingly, determining wear limit data for a vehicle tire over a trip based on the initial pattern depth data and historical driving data, comprising:
and determining the limit running time of the vehicle tire in the process according to the initial pattern depth data and the historical driving speed in the historical driving data based on a pre-constructed limit running time model.
The limit driving time model is determined by the following formula:
h represents the depth of a worn pattern, the depth of the worn pattern is the difference between initial pattern depth data and limit pattern depth data, and the limit pattern depth data is determined according to attribute information of the vehicle tire; a represents a ratio value of pattern wear speed affected by vehicle running speed; x represents a unit wear consumption value of a pattern depth during running; v represents a historical driving speed; t represents the limit travel period.
The maximum driving time duration refers to the longest safe driving time duration supported by the current vehicle tire when a user drives according to historical driving data, and if the time duration that the user drives the vehicle according to the historical driving data exceeds the maximum driving time duration, the residual pattern depth of the vehicle tire is insufficient to ensure good adhesion, so that great hidden danger is caused to the driving safety of the vehicle.
And constructing a limit running duration model in advance according to the worn pattern depth, the wear influence of the normal running of the vehicle on the pattern depth and the wear influence of the running speed of the vehicle on the pattern depth. Specifically, the normal vehicle running can cause abrasion to the pattern depth of the vehicle tire, the speed during running can affect the pattern depth abrasion speed in different degrees, and the faster the vehicle speed is, the greater the abrasion to the pattern depth is. Therefore, a ratio value of the influence of the vehicle running speed on the pattern wear speed is introduced when a limit running time model is constructed, the ratio value is used for representing the influence degree of the vehicle speed on the pattern deep wear, and the specific size of the ratio value can be determined according to the actual test condition. For example, when the ratio value is determined, the wear condition of the tire pattern depth of the vehicle in the same external environment can be measured under different vehicle speeds by a control variable method aiming at the same vehicle, so that the relationship between the vehicle speed and the wear condition can be determined, and the ratio value can be obtained. Illustratively, the magnitude of the ratio value may be set to 0.02.
The specific wear consumption value refers to the wear consumption of the tire per a preset running length of the vehicle running on a standard road surface. Illustratively, the magnitude of the specific wear consumption value is set to 0.1. The historical driving speed is obtained from historical driving data, represents the average driving speed of the user, and can be determined according to the ratio of the total driving travel length of the user to the total driving time length. The wear pattern depth is used to indicate the depth at which the vehicle tire pattern can be worn away while ensuring safe driving of the vehicle. Illustratively, the initial pattern depth data of the vehicle tire pattern before the stroke starts is 5mm, the limit pattern depth data is 1mm, the wear pattern depth is 4mm, the limit pattern depth data indicates that when the vehicle tire pattern depth is 1mm, the adhesion force of the tire is difficult to ensure the safe driving of the vehicle, the tire should be replaced in time, the limit pattern depth data can be determined according to the attribute information of the vehicle tire, and the limit pattern depth data of tires of different brands and models are different. The limit driving time represents the maximum time that the vehicle tire pattern can travel when worn from the initial pattern depth to the limit pattern depth.
For example, when it is determined that the user has a pre-running stroke, the initial tread depth data is collected to be 5mm, and the worn tread depth H is determined to be 4mm when the limit tread depth data is determined to be 1mm according to the attribute information of the tire. The value a of the ratio of the pattern wear speed affected by the vehicle running speed was determined to be 0.02 according to a predetermined test. The specific wear consumption value X of the running course pattern depth was determined to be 0.1 according to a predetermined test. Meanwhile, the historical driving speed of the user is determined to be 80km/h according to the historical driving data of the user. Then
Indicating that the pattern will be severely worn after a maximum of 25 hours of travel at a current vehicle speed of 80km/h.
And 103, generating stroke reminding information according to the wear limit data, and sending the stroke reminding information to a user.
The travel reminding information is used for reminding the user of safe driving. Because the adhesive force of the tire is greatly reduced when the tire pattern of the vehicle is worn to the limit pattern depth, and the driving safety is seriously influenced, the determined wear limit data is compared with the travel data of the current travel, if the tire pattern depth data is predicted to be worn to the limit pattern depth before the travel is finished, travel reminding information is generated and sent to a user, so that the user is reminded to replace the vehicle tire, and the driving safety in the travel is ensured.
In one possible embodiment, generating the trip alert information based on the wear limit data and sending the trip alert information to the user includes:
and if the limit running time is less than the expected running time of the journey, generating tire replacement reminding information, and sending the tire replacement reminding information to a user.
Wherein the predicted travel time period of the trip is determined based on the total length of the trip and the historical driving speed of the user. Illustratively, if the total length of the pre-travel route is determined to be 400km by the navigation system, the user's historical driving speed is 80km/h, and the expected travel time period is 5 hours. On the basis of the above-described embodiment, the maximum driving time period is 25 hours, which is longer than the expected driving time period, and it means that the pattern depth of the vehicle tire is not worn to the maximum pattern depth after the vehicle has traveled the pre-driving travel, and the adhesion of the tire can still be ensured. If the limit running time is less than the expected running time, the situation that tire patterns are seriously worn can be shown in the process of running the pre-running travel, the adhesion of the tire in the travel is difficult to guarantee, a user is reminded to check and replace the tire of the vehicle before the travel is started, and the safety of travel driving is improved from the perspective of tire safety.
The technical scheme has the following advantages or beneficial effects: because the preset limit running time model is adopted, and the technical means of determining the predicted limit running time of the vehicle tire in the journey according to the initial pattern depth data of the vehicle tire before the journey and the historical driving data of the user is adopted, the technical problem that the abrasion condition of the tire in the journey cannot be accurately determined in the prior art is solved, and the technical effect of improving the driving safety in the journey is further achieved.
Example two
Fig. 2 is a flowchart of a driving reminding method in an embodiment two of the present application, and the embodiment two is further supplemented on the basis of the embodiment one, and the wear limit data includes a limit driving speed in addition to the limit driving time length, as another possible implementation manner. As shown in fig. 2, the method includes:
And step 202, based on a pre-constructed limit running time model, determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data.
In one possible embodiment, the journey consists of segments of at least two road types;
correspondingly, the method for determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on the pre-constructed limit running time model comprises the following steps:
and determining the limit driving time of the vehicle tire on each road section in the travel according to the road type of each road section, the mileage data of each road section, the initial pattern depth data and the historical driving data in the travel based on a pre-constructed limit driving time model.
Wherein, the unit abrasion consumption value X of the pattern depth in the driving process is determined by the following formula:
X＝D×R；
wherein D represents the basic unit abrasion consumption value of the pattern depth in the driving process; r represents the wear rate of different road types.
Since different road conditions wear the vehicle tires differently, for example, the degree of wear of the vehicle tires is different for town roads and country roads. The road type of the road segment in the travel is determined according to the position information in the travel. The division of the road type may be determined according to a predetermined division rule and position information in the navigation system, and the division rule may be divided according to a friction coefficient of a road surface. Exemplary road types include, but are not limited to, freeway types, town road types, winding road types, country road types, and the like.
The user's pre-driving travel may simultaneously include road segments of at least two road types, for example, the total length of the user's pre-driving travel is 400km, the road segment of the first 100km is a town road type and is marked as a first road segment, and the road segment of the last 300km is a winding mountain road type and is marked as a second road segment. Since different road types have different degrees of wear on vehicle tires, it is necessary to determine the limit driving time period for each road segment.
Since the specific wear consumption value X of the pattern depth during running referred to in the above embodiments refers to the wear consumption of the vehicle tire per preset running distance when the vehicle runs on a standard road surface, but in the embodiment of the present application, the probability of the road type is introduced, and therefore, the specific wear consumption value X of the pattern depth during running is newly determined by determining the degree of wear of the vehicle tire pattern by different road types. The basic unit wear consumption value D of the pattern depth during the driving process represents the wear consumption of the tire when the vehicle drives on a standard road surface for each preset distance length, wherein the standard road surface may refer to a road surface with a friction coefficient as a preset reference value, and the preset reference value of the friction coefficient may be obtained by testing according to actual conditions, which is not limited herein. The wear ratios R of different road types indicate the degree of influence of different road types on the pattern depth, and for example, the wear conditions of the tire pattern depths of vehicles in different road types can be measured by a control variable method at the same vehicle speed for the same vehicle when determining the wear ratios, so that the relationship between the road types and the wear conditions can be determined to obtain the wear ratios. Illustratively, the abrasion ratio of the expressway type is 0.9, the abrasion ratio of the town road type is 1.1, and the abrasion ratio of the winding road type is 1.5, so that it is known that the friction coefficient of the winding road is larger than that of the town road, the friction coefficient of the town road is larger than that of the expressway, and the abrasion ratio of the standard road surface is 1, and the friction coefficient thereof should be located between the town road and the expressway.
Specifically, for different road types, the unit abrasion consumption value X with corresponding pattern depth in the running process is provided, so that the accuracy of determining the total travel limit running duration is improved. For example, if the base unit wear consumption value D of the course pattern depth is 0.1, the unit wear consumption value X of the course pattern depth corresponding to the town road type is 0.1 × 1.1=0.11, the unit wear consumption value X of the course pattern depth corresponding to the expressway type is 0.1 × 0.9=0.09, and the unit wear consumption value X of the course pattern depth corresponding to the mountain road type is 0.1 × 1.5= 0.15.
And predicting the limit running time length on each road section in the travel based on the unit abrasion consumption value X of the pattern depth in the running process of different road types. Illustratively, based on the above example, the limit travel time period for traveling on the first road segment is
Approximately equal to 22 hours; determining the depth of wear of the profile on the first road section is necessary when determining the limit length of travel on the second road section, for example, on the basis of the estimated length of travel on the first road section, which is the length of travel estimated on the first road section
When hours, the predicted wear depth h1= t1 × a × X × V =1.25 × 0.02 × 0.11 × 80=0.22mm on the first road segment, and further, the limit travel time period for traveling on the second road segment is
And (4) hours.
Illustratively, when the travel is composed of at least two road types of road sections, the historical driving speeds of the users on different road types are determined according to the historical driving data of the users, and then the limit driving duration on each road section in the travel is determined according to the corresponding historical driving speed so as to ensureThe accuracy of determining the limit driving time is verified. For example, in case that it is determined that the user's historical driving speed on town roads is 80km/h and the historical driving speed on mountain roads is 60km/h based on the user's historical driving data, on the basis of the above-described example,
approximately equal to 22 hours; the limit travel time of the second road section is
And (4) hours.
And step 203, determining the limit running speed of the vehicle tire in the running process according to the running data based on the limit running speed model constructed in advance.
Wherein the limit travel speed model is determined by the following formula:
where L denotes a maximum speed limit value of the travel section, R denotes a wear rate of different road types, and M denotes a limit travel speed on the travel section.
Since the degree of wear of a vehicle tire is affected by the vehicle running speed, the degree of wear of the tire pattern increases sharply when the vehicle speed is greater than a certain threshold value. The threshold value may be determined by a limit travel speed model, i.e., the limit travel speed.
And constructing a limit driving speed model in advance according to the highest speed limit value of the driving road section and the wear rate of different road types to the pattern depth. Specifically, the maximum speed limit values of different road sections are provided, and the wear rates of the road sections of different road types to tire patterns are different, so that a limit driving speed model is constructed based on the maximum speed limit values of the driving road sections and the wear rates of the different road types, the limit driving speed obtained based on the limit driving speed model not only considers the limit of the maximum speed limit of the road, but also considers the wear condition of the road to the patterns, and the reminding accuracy of a user is improved.
Illustratively, based on the above example, the first road segment is an urban road, and the maximum speed limit value of the urban road type is 100km/h according to the maximum speed limit requirement of the urban road, then the limit driving speed on the first road segment is obtained
Approximately equal to 90km/h; the second road section is a winding mountain road, the highest speed limit value of the winding mountain road type is 80km/h according to the highest speed limit requirement of the winding mountain road, and the ultimate driving speed on the second road section is obtained
Approximately equal to 53km/h. Specifically, the maximum speed limit value of each road section may be determined according to an actual speed limit value in the navigation system, for example, for a town road type, due to construction or existence of school and other factors, the sub-road section in the first road section has different maximum speed limit values, so that when actually determining, the limit driving speed is determined according to the actual maximum speed limit value of each road section, so as to ensure accuracy of determining the limit driving speed.
And step 204, if the limit running time is less than the expected running time of the journey, generating tire replacement reminding information, and sending the tire replacement reminding information to a user.
Specifically, before the running starts, the travel reminding information is generated according to the determined limit running duration, and the travel reminding information is sent to the user. When the travel is composed of road sections of at least two road types, the comparison result of the limit running time on each road section and the predicted running time running according to the historical driving speed is respectively determined, if the limit running time on each road section is greater than the predicted running time, the fact that the tire of the vehicle is not worn to the limit wearing depth is shown, and the driving safety can be guaranteed.
And if the limit running time on the target road section is less than the expected running time, generating tire replacement reminding information and sending the information to a user. For example, the tire replacement reminding information is generated according to the position of the target road segment on the journey, for example, after the target road segment is located 100km after the beginning of the journey, the tire replacement reminding information may be: after the automobile runs for 100km, the tire is seriously worn and is recommended to be replaced in advance; or the tire replacement reminding message may be: when the current travel can run for 4 hours at most, please decelerate to reduce the tire wear, and find nearby car repair shops to check and replace the tire.
The tire replacement reminding information is generated through the limit running time, the tire loss condition in the journey is determined, a user is reminded of replacing the tire in time, and the driving safety in the journey is improved.
And step 205, if the real-time running speed in the travel is greater than the limit running speed, generating tire wear serious reminding information, and sending the tire wear serious reminding information to a user.
Specifically, before the journey starts, journey reminding information is generated according to the determined limit running speed, and the journey reminding information is sent to a user. For example, the travel reminder information may be: in order to avoid severe tire wear, it is recommended to keep running at 90km/h for the first 100km in the trip and at 53km/h for the last 300km in the trip.
In the actual running process, the tire abrasion serious reminding information is generated according to the comparison result of the real-time running speed and the limit running speed of the vehicle in the journey, so that the timeliness and the accuracy of the driving reminding of the user are guaranteed. Illustratively, when the real-time running speed of the user on the first road section is more than 90km/h, the tire wear severity reminding information is generated: when the current speed exceeds 90km/h, the tire is seriously worn, and the vehicle speed is recommended to be reduced to below 90 km/h.
The tire wear serious reminding information is generated through the limit running speed, so that the tire wear condition in the journey can be monitored in real time, a user is reminded of paying attention to the speed of the vehicle, and the safety of driving in the journey is improved.
In one possible embodiment, the method further comprises:
acquiring driving data after a journey is started; wherein the driving data at least comprises the traveled mileage and the actual travel speed of the trip;
determining updated wear limit data of the vehicle tire in the remaining travel according to the driving data and the initial pattern depth data;
and generating stroke updating reminding information according to the updated wear limit data, and sending the stroke updating reminding information to a user.
In the above embodiment, the determination of the limited travel time period is based on the historical driving speed in the historical driving data of the user, and since there may be a certain deviation between the actual travel speed of the user and the historical driving speed during the actual travel of the trip, in order to ensure accurate determination of the wear condition of the vehicle tire during the trip, the wear data of the completed trip is calculated based on the travel data after the trip is started, and the wear limit data of the remaining trip is updated and determined. For example, the determination may be updated according to a preset run length, and/or the wear limit data may be updated after a road type change. The update determination is made, for example, every 100km traveled, or after the end of the first link.
Specifically, after the first road segment is finished, the driving data after the travel is started is obtained, and the driving data comprises the traveled mileage of 100km, the actual travel speed change data of the travel, and the remaining traveled mileage of 300km. The actual travel speed variation data of the trip includes travel time within each speed interval range, and the division of the speed interval ranges may be determined according to the actual prediction accuracy. For example, the division of the speed interval range may be 50km/h or less in the first interval, 51km/h-60km/h in the second interval, 61km/h-70km/h in the third interval, 71km/h-80km/h in the fourth interval, 81km/h-90km/h in the fifth interval, and 91km/h or more in the sixth interval, and the associated speed standard value is predetermined for each speed interval, for example, the first interval speed standard value is 50km/h, the second interval speed standard value is 55km/h, the third interval speed standard value is 65km/h, the fourth interval speed standard value is 75km/h, the fifth interval speed standard value is 85km/h, and the sixth interval speed standard value is 90km/h, and the specific determination of the speed standard value may be determined according to the actual prediction accuracy, and is not limited herein.
And determining the actual wear depth in the first road section according to the running time, the associated speed standard value and the initial pattern depth data in each speed interval range, further determining the updated limit running duration of the remaining travel according to the actual wear depth, generating tire replacement reminding information according to the comparison result of the updated limit running duration and the predicted running duration, and sending the tire replacement reminding information to a user.
Illustratively, based on the above example, if the actual travel speed variation data of the user on the trip in the first road section is that the duration of the third interval is 0.5 hour, the duration of the fourth interval is 1 hour, and the duration of the fifth interval is 0.5 hour, then the actual wear depth of the vehicle driven by the user on the first road section is the sum of the wear depths in the speed intervals: h = t × a × X × 0v =0.5 × 10.02 × 0.11 × 65+1 × 0.02 × 0.11 × 75+0.5 × 0.02 × 0.11 × 85=0.33mm, and further, the limit travel time period on the second road segment next is determined according to the actual wear depth:
and (4) hours. And if the updated limit running time is less than the predicted running time of the remaining travel, generating tire replacement reminding information and sending the tire replacement reminding information to a user.
The wear limit data of the remaining travel is updated and determined according to the actual running speed of the vehicle, so that the determination accuracy and the determination accuracy of the tire wear condition are ensured, and the driving safety is improved.
The technical scheme has the following advantages or beneficial effects: because the maximum driving time of the tire in the journey is determined according to the initial pattern depth data of the vehicle tire before the journey and the historical driving speed of the user, the maximum driving speed of the tire in the journey is determined according to the maximum speed limit value of the road section in the journey and the wear rate of the tire of different road types, and the driving of the user is reminded according to the maximum driving time and the maximum driving speed, the technical problem that the wear condition of the tire in the journey cannot be accurately determined in the prior art is solved, the user is reminded to drive on different roads by using reasonable vehicle speed, the tire is replaced at proper time, the wear condition of the pattern of the wheel is reduced, and the technical effect of improving the driving safety in the journey is achieved.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a driving reminding device in a third embodiment of the present application, and this embodiment is applicable to a case of improving driving safety in a trip based on a vehicle tire wear condition. As shown in fig. 3, the apparatus includes:
a data acquisition module 310, configured to acquire initial pattern depth data of a vehicle tire before a trip starts and historical driving data of a user;
a wear determination module 320 for determining wear limit data for a vehicle tire in the trip based on the initial tread depth data and the historical driving data;
and the wear reminding module 330 is configured to generate stroke reminding information according to the wear limit data, and send the stroke reminding information to a user.
The technical scheme has the following advantages or beneficial effects: because the technical means of determining the predicted wear limit data of the vehicle tire in the journey according to the initial pattern depth data of the vehicle tire before the journey and the historical driving data of the user is adopted, the technical problem that the wear condition of the vehicle tire in the journey cannot be accurately determined in the prior art is solved, and the technical effect of improving the driving safety in the journey is further achieved.
Optionally, the wear limit data comprises a limit travel length;
accordingly, the wear determination module 320 is specifically configured to:
and determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on a pre-constructed limit running time model.
Optionally, the route is composed of road segments of at least two road types;
accordingly, the wear determination module 320 is specifically configured to:
and determining the limit running time of the vehicle tire on each road section in the travel according to the road type of each road section in the travel, the mileage data of each road section, the initial pattern depth data and the historical driving data based on a pre-constructed limit running time model.
Optionally, the wear-out reminding module 330 is specifically configured to:
and if the limit running time is less than the predicted running time of the travel, generating tire replacement reminding information and sending the tire replacement reminding information to a user.
Optionally, the wear limit data further comprises a limit travel speed;
accordingly, the wear determination module 320 is further specifically configured to:
and determining the limit running speed of the vehicle tire in the travel according to the travel data based on a pre-constructed limit running speed model.
Optionally, the wear-out reminding module 330 is specifically configured to:
and if the real-time running speed in the travel is greater than the limit running speed, generating tire wear serious reminding information, and sending the tire wear serious reminding information to a user.
Optionally, the apparatus further includes a wear update reminding module 340, specifically configured to:
acquiring driving data after a journey is started; wherein the driving data at least comprises a traveled mileage and a trip actual driving speed;
determining updated wear limit data of the vehicle tire in the remaining travel according to the driving data and the initial pattern depth data;
and generating stroke updating reminding information according to the updated wear limit data, and sending the stroke updating reminding information to a user.
The driving reminding device provided by the embodiment of the application can execute the driving reminding method provided by any embodiment of the application, and has corresponding functional modules and beneficial effects for executing the driving reminding method.
Example four
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present application. FIG. 4 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present application. The electronic device 12 shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in FIG. 4, electronic device 12 is embodied in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory device 28, and a bus 18 that couples various system components including the system memory device 28 and the processing unit 16.
The system storage 28 may include computer system readable media in the form of volatile storage, such as Random Access Memory (RAM) 30 and/or cache storage 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Storage 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in storage 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally perform the functions and/or methodologies of the embodiments described herein.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system storage device 28, for example, implements a driving reminding method provided by the embodiment of the present application, including:
acquiring initial pattern depth data of vehicle tires before a journey is started and historical driving data of a user;
determining wear limit data of the vehicle tire in the travel according to the initial pattern depth data and the historical driving data;
and generating stroke reminding information according to the wear limit data, and sending the stroke reminding information to a user.
EXAMPLE five
The fifth embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the driving reminding method provided in the embodiment of the present application, and the method includes:
acquiring initial pattern depth data of vehicle tires before a journey starts and historical driving data of a user;
determining wear limit data of the vehicle tire in the travel according to the initial pattern depth data and the historical driving data;
and generating stroke reminding information according to the wear limit data, and sending the stroke reminding information to a user.
The computer storage media of embodiments of the present application may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (9)
1. A driving reminding method is characterized by comprising the following steps:
acquiring initial pattern depth data of vehicle tires before a journey starts and historical driving data of a user;
determining wear limit data of the vehicle tyre in the travel according to the initial pattern depth data and the historical driving data;
generating stroke reminding information according to the wear limit data, and sending the stroke reminding information to a user;
wherein the wear limit data comprises a limit travel time period;
correspondingly, determining wear limit data of the vehicle tire in the travel according to the initial pattern depth data and the historical driving data comprises: determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on a pre-constructed limit running time model;
the limit running time model is constructed according to the depth of a worn pattern, the wear influence of the normal running of the vehicle on the depth of the pattern and the wear influence of the running speed of the vehicle on the depth of the pattern;
wherein the limit travel time period model is determined by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
representing the depth of the worn pattern, wherein the depth of the worn pattern is the difference between the initial pattern depth data and the limit pattern depth data, and the limit pattern depth data is determined according to the attribute information of the vehicle tire;
a ratio value representing a pattern wear speed affected by a vehicle running speed;
a unit wear loss value representing a pattern depth during running;
represents a historical driving speed;
representing a limit driving time length;
wherein the unit wear consumption value of the running course pattern depth
The determination is made by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
a basic unit wear consumption value representing a pattern depth during running;
indicating the wear rate for different road types.
2. The method of claim 1, wherein the trip is comprised of segments of at least two road types;
correspondingly, the method for determining the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on the pre-constructed limit running time model comprises the following steps:
and determining the limit running time of the vehicle tire on each road section in the travel according to the road type of each road section in the travel, the mileage data of each road section, the initial pattern depth data and the historical driving data based on a pre-constructed limit running time model.
3. The method of claim 1, wherein generating trip alert information based on the wear limit data and sending the trip alert information to a user comprises:
and if the limit running time is less than the predicted running time of the travel, generating tire replacement reminding information and sending the tire replacement reminding information to a user.
4. The method of claim 1, wherein the wear limit data further comprises a limit travel speed;
correspondingly, determining wear limit data of the vehicle tire in the travel according to the initial pattern depth data and the historical driving data, further comprising:
and determining the limit running speed of the vehicle tire in the travel according to the travel data based on a pre-constructed limit running speed model.
5. The method of claim 4, wherein generating travel reminder information from the wear limit data and sending the travel reminder information to a user comprises:
and if the real-time running speed in the travel is greater than the limit running speed, generating tire wear serious reminding information, and sending the tire wear serious reminding information to a user.
6. The method of claim 1, further comprising:
acquiring driving data after a journey is started; wherein the driving data at least comprises the traveled mileage and the actual travel speed of the trip;
determining updated wear limit data for the vehicle tyre over the remaining travel from the driving data and the initial profile depth data;
and generating stroke updating reminding information according to the updated wear limit data, and sending the stroke updating reminding information to a user.
7. A driving warning device, comprising:
the data acquisition module is used for acquiring initial pattern depth data of the vehicle tire before the travel starts and historical driving data of a user;
a wear determination module to determine wear limit data for the vehicle tire during the trip based on the initial pattern depth data and the historical driving data;
the wear reminding module is used for generating stroke reminding information according to the wear limit data and sending the stroke reminding information to a user;
wherein the wear limit data comprises a limit travel length;
correspondingly, the wear determining module is specifically configured to determine the limit running time of the vehicle tire in the travel according to the initial pattern depth data and the historical driving speed in the historical driving data based on a pre-constructed limit running time model;
the limit running time model is constructed according to the depth of a worn pattern, the wear influence of normal running of the vehicle on the depth of the pattern and the wear influence of the running speed of the vehicle on the depth of the pattern;
wherein the limit travel time period model is determined by the following formula:
wherein the content of the first and second substances,
representing the depth of the worn pattern, wherein the depth of the worn pattern is the difference between the initial pattern depth data and the limit pattern depth data, and the limit pattern depth data is determined according to the attribute information of the vehicle tire;
a ratio value representing a pattern wear speed affected by a vehicle running speed;
a unit wear consumption value representing a pattern depth during running;
represents a historical driving speed;
representing a limit driving time length;
wherein the unit wear consumption value of the running course pattern depth
The determination is made by the following formula:
wherein the content of the first and second substances,
a basic unit wear consumption value representing a pattern depth during running;
indicating the wear rate for different road types.
8. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the driving reminder method of any of claims 1-6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a driving reminder method according to any one of claims 1 to 6.
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