CN119359139A - Various data scoring systems and scoring methods based on multi-dimensional fusion of vehicle control - Google Patents
Various data scoring systems and scoring methods based on multi-dimensional fusion of vehicle control Download PDFInfo
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Abstract
The invention discloses a system and a method for scoring various data based on vehicle control multidimensional fusion, wherein the system comprises a data acquisition module for acquiring driving data through a truck sensor, the data processing module receives, cleans, sorts and analyzes the data, the driving behavior data is obtained after the data is standardized by a preset algorithm, and the scoring module distributes scores based on the data and the weights to form a result. The feedback module feeds the scores back to a driver and a vehicle management department, and the driver can check the scores and the improvement suggestions through the vehicle-mounted terminal or the mobile phone APP. All modules are connected by signals in turn, so that high-efficiency data flow and processing are realized.
Description
Technical Field
The invention relates to the technical field of Internet of vehicles, in particular to a system and a method for scoring various data based on vehicle control multi-dimensional fusion.
Background
If the driving behavior of the truck is not standard, the energy consumption of the truck is often increased, and the safety risk is increased. Therefore, a set of system capable of scientifically and accurately evaluating the driving behavior of the truck is developed, and the system has great significance in improving the driving skill of a driver, reducing the energy consumption of the vehicle and guaranteeing the driving safety. In the past, many motorcades set fuel consumption base lines according to experience to manage drivers, and fuel consumption is affected by a plurality of comprehensive factors. The same vehicle is driven on the same route, and the fuel consumption difference caused by different driving habits can exceed 10%. In order to pursue low fuel consumption, many drivers have quite high-grade low-rotation-speed conditions during running, and the vehicles can run out of low fuel consumption, but the vehicles are extremely damaged, and particularly the service lives of the vehicles are greatly shortened when the vehicles run at high-grade low-rotation-speed conditions for a long time.
Therefore, it is important to study the driving behavior of the driver to ensure the safe running of the vehicle, and intelligent driving behavior analysis is imperative.
SUMMARY OF THE PATENT FOR INVENTION
The invention aims to provide a system for scoring various data based on vehicle control multi-dimensional fusion and a use method thereof, so as to solve the problems in the background art.
In order to solve the technical problems, the invention provides a technical scheme that the system for scoring various data based on vehicle control multidimensional fusion comprises a data acquisition module, a data processing module, a scoring module and a feedback module, wherein the data acquisition module is used for acquiring various data in the running process of a truck, the data acquisition is realized through a sensor arranged on the truck, the sensor is connected with the data acquisition module through a signal, the data processing module is used for receiving various data acquired by the data acquisition module, cleaning, sorting and analyzing the various data, and carrying out standardized processing on the various data through an algorithm preset in the data processing module so as to obtain driving behavior data, the scoring module scores the various data based on driving behavior data and weight distribution and forms a scoring result, the feedback module is used for feeding the scoring result back to a driver and a vehicle management department, the driver checks own driving scoring and improving advice through a vehicle-mounted terminal or a mobile phone APP, and the data acquisition module, the data processing module, the scoring module and the feedback module are sequentially connected with each other through signals.
Furthermore, the feedback module can utilize the vehicle-mounted T-BOX to carry out voice broadcast driving behavior data improvement suggestion.
The scoring method of the scoring system of each item of data based on the multidimensional fusion of vehicle control, which is implemented based on the autonomous vehicle networking system of the emergency lane, comprises the following steps:
The method comprises the following steps that S1, a data acquisition module acquires various data in real time through a vehicle body sensor and uploads the data to a data processing module;
The data comprise GPS time, longitude and latitude, GPS time difference, standard mileage difference, standard oil consumption difference, standard speed, acceleration, current gear of a vehicle, engine speed, accelerator opening percentage difference, coolant temperature ℃, brake signal state, altitude, running gradient, calculated gradient value, engine output torque, engine fuel consumption rate and steering wheel rotation angle;
S2, the data processing module cleans, sorts and analyzes all data, performs standardized processing on all data through a preset algorithm, and accordingly obtains driving behavior data, and then uploads the driving behavior data to the scoring module;
the standardized index is a standard threshold, and different thresholds are configured for different vehicle types;
s3, the scoring module performs weight distribution based on the driving behavior data, and scores the driving behavior according to the weight ratio of each index in the driving behavior data so as to obtain a scoring result;
The weight ratio of each index is used for determining whether the index participates in grading;
the weight ratio of the index comprises three grades of high, medium and bottom,
The weight ratio of the high-grade index sequentially comprises super-safe vehicle speed, super-economic rotation speed, super-economic vehicle speed, large accelerator, sudden brake, insufficient brake pre-judgment and overlong idle speed from approximately small;
when the brake pre-judgment and the sudden braking occur simultaneously, the system reports the sudden braking;
the weight ratio of the medium-level index sequentially comprises the following steps of too low rotating speed, short-time accelerator fluctuation, unreasonable neutral gear sliding and in-situ oil rolling,
The weight ratio of the bottom grade index is approximately smaller and sequentially comprises that the cold vehicle runs, the gear increasing rotating speed is too low, the gear decreasing rotating speed is too low, and the gear pre-judgment is unreasonable;
S4, the feedback module feeds back the scoring result to a driver and a vehicle management department;
S5, a driver checks own driving scores and improvement suggestions through a vehicle-mounted terminal or a mobile phone APP;
And S6, the vehicle management department carries out rewarding and punishment management on the driver according to the grading result.
The system has the beneficial effects that the system can carry out scientific and accurate assessment on the driving behavior of the driver by collecting key data in the driving process of the truck in real time and combining an advanced algorithm and a scoring mechanism. The system has the functions of real-time data processing and instant feedback, and can rapidly transmit the scoring result to drivers and vehicle management departments, so that problems can be timely identified and corresponding improvement measures can be taken. In addition, the system can flexibly customize scoring rules according to different driving behaviors and scenes, so that the evaluation result is ensured to have more pertinence and guiding value. The system is compatible with trucks and drivers of various models, and has wide applicability and good market popularization potential.
Drawings
Fig. 1 is a flow chart of a scoring method of each data scoring system based on vehicle control multi-dimensional fusion in the second embodiment;
Fig. 2 is a data display diagram of the driving behavior analysis algorithm in the second embodiment.
Detailed Description
The patent of the invention is further described below with reference to the accompanying drawings.
Example 1
The invention discloses a vehicle control multi-dimensional fusion-based scoring system for various data, which comprises a data acquisition module, a data processing module, a scoring module and a feedback module, wherein the data acquisition module is used for acquiring various data in the running process of a truck, the data acquisition is realized through a sensor arranged on the truck, the sensor is connected with the data acquisition module through a signal, the data processing module is used for receiving the various data acquired by the data acquisition module, cleaning, sorting and analyzing the various data, and carrying out standardized processing on the various data through an algorithm preset in the data processing module so as to obtain driving behavior data, the scoring module scores the various data based on driving behavior data and weight distribution and forms a scoring result, the feedback module is used for feeding the scoring result back to a driver and a vehicle management department, the driver checks own driving scoring and improvement suggestion through a vehicle-mounted terminal or a mobile phone APP, and the data acquisition module, the data processing module, the scoring module and the feedback module are connected with each other through signals in sequence.
Furthermore, the feedback module can utilize the vehicle-mounted T-BOX to carry out voice broadcast driving behavior data improvement suggestion.
Example two
Referring to fig. 1, a scoring method of each item of data scoring system based on vehicle control multi-dimensional fusion implemented based on an emergency lane autonomous internet of vehicles system includes the following steps:
The method comprises the following steps that S1, a data acquisition module acquires various data in real time through a vehicle body sensor and uploads the data to a data processing module;
The data comprise GPS time, longitude and latitude, GPS time difference, standard mileage difference, standard oil consumption difference, standard speed, acceleration, current gear of a vehicle, engine speed, accelerator opening percentage difference, coolant temperature ℃, brake signal state, altitude, running gradient, calculated gradient value, engine output torque, engine fuel consumption rate and steering wheel rotation angle;
S2, the data processing module cleans, sorts and analyzes all data, performs standardized processing on all data through a preset algorithm, and accordingly obtains driving behavior data, and then uploads the driving behavior data to the scoring module;
the standardized index is a standard threshold, and different thresholds are configured for different vehicle types;
such as an over-economy vehicle speed threshold, an over-safe vehicle speed threshold, a large throttle threshold, and a short throttle fluctuation amplitude.
S3, the scoring module performs weight distribution based on the driving behavior data, and scores the driving behavior according to the weight ratio of each index in the driving behavior data so as to obtain a scoring result;
The weight ratio of each index is used for determining whether the index participates in grading;
the weight ratio of the index comprises three grades of high, medium and bottom;
The weight ratio of the high-grade index sequentially comprises super-safe vehicle speed, super-economic rotation speed, super-economic vehicle speed, large accelerator, sudden brake, insufficient brake pre-judgment and overlong idle speed from approximately small;
when the brake pre-judgment and the sudden braking occur simultaneously, the system reports the sudden braking;
The weight ratio of the medium-level index sequentially comprises the following steps of too low rotating speed, short-time accelerator fluctuation, unreasonable neutral gear sliding and in-situ oil rolling from approximately small;
The weight ratio of the bottom grade index is approximately smaller and sequentially comprises that the cold vehicle runs, the gear increasing rotating speed is too low, the gear decreasing rotating speed is too low, and the gear pre-judgment is unreasonable;
for example, in the weight ratio of each index, the super-economic vehicle speed is divided into a super-economic vehicle speed mileage ratio of 65% and a super-economic vehicle speed average vehicle speed of 35%, and the conventional large accelerator is divided into a large accelerator mileage ratio of 65% and a large accelerator average opening degree of 35%;
as shown in fig. 2, the driving behavior analysis algorithm specifically includes:
The method comprises the steps of determining a supereconomic vehicle speed, namely determining a current v threshold value, determining a threshold value, namely, v= [ Vmax-Vmin ] 0.8+Vmin ], general cargo, namely, v <88km/h, v, 88< = v <95km/h,88, 5< = v, and speed limiting 89, wherein the speed limiting 89 is according to 88, the speed limiting 89 is according to 95 (can not be recognized whether the speed limiting is calculated according to the speed limiting), and determining a throttle opening of the vehicle to be more than 0%, determining an actual torque percentage of the engine to be more than 20%, and determining a duration of the engine to be more than 60s (default), wherein after an event is met, the duration of the vehicle is configurable, if any parameter continuous 2s does not meet the requirement, the vehicle speed threshold value is ended for the duration of the vehicle speed of the vehicle to be configurable 7;
the ultra-safe vehicle speed is judged, wherein the dangerous defaulting is greater than 80km/h, the general cargo defaulting is greater than 100km/h, the duration is & >10s (the duration can be uniformly configured), the vehicle speed is terminated after the event is established and the continuous 2s of the vehicle speed is insufficient, and the vehicle speed configuration in a certain vehicle range can be supported;
The pre-judging of the brake is insufficient, namely 1s, the accelerator is provided, the brake is not provided, the speed is more than 50km/h, 2s-5s, the accelerator is provided, the brake is provided (a brake switch=1 or a brake stroke is more than 5%), and the acceleration is less than-0.56 m/s2 (the brake and the acceleration judging meets the establishment and the end of an event);
Flat road braking, vehicle speed >30km/h, brake switch=1 or brake stroke >5%, accelerator opening=0, acceleration < -0.56m/s2, gradient >0.8%6 duration >1s7, any one of which is not satisfied with interruption);
the sudden braking is that the initial speed is more than 40km/h, the final speed is the lowest cut-off is 30km/h, the acceleration is less than y' a (a is 1.0 as default), and specific rules are shown in the formula of-braking process brake=1 or braking travel is more than 5% accelerator opening=0;
The idle speed is too long, the vehicle speed=0, 500rpm < the rotating speed <1100rpm, the accelerator opening=0, the water temperature >10 degrees (the abnormal water temperature vehicle cancels the water temperature judgment), the duration >600s (default), the ambient temperature, after the event is established, any field is continuous for 2s and does not meet the requirement, the end is reached, and the duration is configurable;
super-economic rotation speed driving, wherein the whole-course speed is more than 20km/h; current speed > upper limit economic speed (1 + gradient) - - - - - - - - - - - - - - - - - - - - - - - - - -. Assigning 0, and assigning 5% to a slope > 5%; throttle >0%, engine actual torque percentage >20%, duration >60s_ (default), after the event is met, any field is finished after 2s is not met, and the duration is configurable
The economic rotation speed driving is that the whole-course speed is more than 20kmh, any one of the following conditions can be met (current rotation speed < = (lower limit economic rotation speed-50) and accelerator=0%, (lower limit economic rotation speed-50) < current rotation speed < upper limit economic rotation speed (1+gradient), current rotation speed > = upper limit economic rotation speed (1+gradient) and accelerator=0%, - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -, 5% and 5% is assigned, and the index is a statistical index, and is non-event;
The speed is too low, the whole speed is more than 20km/h, the current speed is less than the speed threshold (speed threshold=lower economic speed- ō) (ō is default 50), the throttle is more than 0%, the actual torque percentage of the engine is more than 60%, the actual torque is changed to be more than 20%, the duration is more than 10s, after the event is met, any field is finished when the continuous 2s is not met, and the duration is configurable;
The gear pre-judgment is unreasonable, namely the vehicle speed is more than 20km/h, the gear A is more than A+1 (the duration of the gear 2s < A+1 is less than 10 s), the gear A is more than A, and the gear A is not neutral;
the gear-increasing rotating speed is too low, the vehicle speed is more than 20km/h, the rotating speed before gear-increasing is less than max economic rotation, the rotating speed after gear-increasing is less than min economic rotation speed- ō (ō: default 50) (the current rotating speed is less than max economic rotation speed, 3 continuous gear increases appear subsequently, the last point is less than min economic rotation speed-50 rpm, the total time is less than 6 seconds, and the event is true);
The speed of the gear is over low, the speed of the vehicle is more than 20km/h, the speed of the gear is less than the min economic speed-50 rpm and 1 before the gear is reduced, the speed of the gear is less than the min economic speed + ō (ō: default 100) after the gear is reduced, (the current speed is less than the min economic speed-50 rpm, 3 continuous gear reduction occurs subsequently, the last point is less than the min economic speed +100rpm, the total time is less than 6 seconds, and the event is true) (the shift process points are eliminated, and the number of points is not more than 3)
Unreasonable neutral gear sliding, namely judging a vehicle with abnormal brake stroke (accelerator >0 and brake=1 for more than 1 s) by adopting brake stroke, wherein the brake stroke is >5%, and increasing a scene neutral gear sliding time 2s < t <7s;
Neutral coasting, vehicle speed >1km/h, accelerator opening <6%, 0< engine actual torque percentage <15%, rotational speed <800rpm, duration >5s, any of which does not satisfy the interruption;
the conventional big throttle is used for judging the speed of the vehicle to be more than 20km/h, judging the torque of the throttle to be more than 80% of the throttle opening and more than 80% of the torque, and keeping the duration to be more than 60s (default), wherein after an event is established, the continuous speed of the vehicle for 2s or the continuous opening of the throttle for 2s is insufficient and is terminated, and the duration can be configured;
The throttle control instability is standard deviation, namely the throttle opening standard deviation is that the throttle opening is judged to be more than 0% of time or the mileage ratio is more than 20% when the fueling running is needed, and the throttle standard deviation calculation of the data of the throttle opening is carried out, wherein the throttle standard deviation calculation opening ratio is not in accordance with the standard deviation assignment 0;
Throttle control instability-throttle stability level: throttle stability level, y= -1.4839x+109.35, (standard deviation <9, 9 standard deviation >40, 40);
Short-time accelerator fluctuation, namely, judging the vehicle speed to be more than 50km/h, judging the gear, namely, judging the event process to be not neutral gear, keeping the gear unchanged, judging the accelerator (greatly fluctuating), namely, judging the accelerator change amplitude I of I (containing third second data) in 3s to be more than 65%, and alternately changing the accelerator to be larger/smaller for more than 3 times, wherein the initial interval of the change is less than 13s, the event termination condition, the interval > =13 s, or the continuous 2s of the vehicle speed does not meet the requirement, or the gear is changed;
In-situ bombing oil, namely, vehicle speed=0, rotating speed >1500rpm, throttle >10%, duration >3s, and stopping when the vehicle speed is continuous for 2s or the throttle opening is continuous for 2s or the rotating speed is continuous for 2s is insufficient after an event is established;
The cold vehicle runs at a speed of >0, a speed of >10km/h, an accelerator of >50%, a temperature of-40 DEG < water temperature <20 DEG, a duration of >10s, and an event end of the journey or the accelerator of <20% & continuous 10s or the water temperature of >20 DEG & continuous 10s;
The ascending cruising is used by CC activation (cruise state cannot be identified and is replaced by accelerator opening=0), the speed is more than 50km/h, the actual torque percentage of the engine is more than 85%, the duration time is more than 10s, and after an event is established, the continuous speed for 2s or the continuous torque for 2s is insufficient, and then the vehicle is stopped;
S4, the feedback module feeds back the scoring result to a driver and a vehicle management department;
S5, a driver checks own driving scores and improvement suggestions through a vehicle-mounted terminal or a mobile phone APP;
And S6, the vehicle management department carries out rewarding and punishment management on the driver according to the grading result.
The system can carry out scientific and accurate assessment on the driving behavior of a driver by collecting key data in the driving process of the truck in real time and combining an advanced algorithm and a scoring mechanism. The system has the functions of real-time data processing and instant feedback, and can rapidly transmit the scoring result to drivers and vehicle management departments, so that problems can be timely identified and corresponding improvement measures can be taken. In addition, the system can flexibly customize scoring rules according to different driving behaviors and scenes, so that the evaluation result is ensured to have more pertinence and guiding value. The system is compatible with trucks and drivers of various models, and has wide applicability and good market popularization potential.
The foregoing is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art should be able to substitute or change the technical solution and the inventive conception of the present invention within the scope of the present invention.
Claims (5)
1. The system is characterized by comprising a data acquisition module, a data processing module, a scoring module and a feedback module, wherein the data acquisition module is used for acquiring various data in the running process of a truck, the data acquisition is realized through a sensor arranged on the truck, the sensor is connected with the data acquisition module through a signal, the data processing module is used for receiving the various data acquired by the data acquisition module, cleaning, sorting and analyzing the various data, and carrying out standardized processing on the various data through an algorithm preset in the data processing module so as to obtain driving behavior data, the scoring module scores the various data based on driving behavior data and weight distribution and forms a scoring result, the feedback module is used for feeding the scoring result back to a driver and a vehicle management department, the driver checks own driving scoring and improvement suggestion through a vehicle-mounted terminal or a mobile phone APP, and the data acquisition module, the data processing module, the scoring module and the feedback module are sequentially connected through signals.
2. The system for scoring various data based on vehicle control multidimensional fusion as recited in claim 1 wherein said feedback module utilizes an onboard T-BOX to voice broadcast driving behavior data improvement advice.
3. The scoring method of the scoring system for each item of data based on the vehicle control multi-dimensional fusion is characterized by comprising the following steps:
The method comprises the following steps that S1, a data acquisition module acquires various data in real time through a vehicle body sensor and uploads the data to a data processing module;
The data comprise GPS time, longitude and latitude, GPS time difference, standard mileage difference, standard oil consumption difference, standard speed, acceleration, current gear of a vehicle, engine speed, accelerator opening percentage difference, coolant temperature ℃, brake signal state, altitude, running gradient, calculated gradient value, engine output torque, engine fuel consumption rate and steering wheel rotation angle;
S2, the data processing module cleans, sorts and analyzes all data, performs standardized processing on all data through a preset algorithm, and accordingly obtains driving behavior data, and then uploads the driving behavior data to the scoring module;
the standardized index is a standard threshold, and different thresholds are configured for different vehicle types;
s3, the scoring module performs weight distribution based on the driving behavior data, and scores the driving behavior according to the weight ratio of each index in the driving behavior data so as to obtain a scoring result;
The weight ratio of each index is used for determining whether the index participates in grading;
S4, the feedback module feeds back the scoring result to a driver and a vehicle management department;
S5, a driver checks own driving scores and improvement suggestions through a vehicle-mounted terminal or a mobile phone APP;
And S6, the vehicle management department carries out rewarding and punishment management on the driver according to the grading result.
4. The scoring method of the system for scoring various data based on multi-dimensional fusion of vehicle control according to claim 3, wherein in step S3, the weight ratio of the index comprises three levels of high, medium and bottom,
The weight ratio of the high-grade index sequentially comprises super-safe vehicle speed, super-economic rotation speed, super-economic vehicle speed, large accelerator, sudden brake, insufficient brake pre-judgment and overlong idle speed from approximately small;
the standardized index is a standard threshold, and different thresholds are configured for different vehicle types;
the weight ratio of the medium-level index sequentially comprises the following steps of too low rotating speed, short-time accelerator fluctuation, unreasonable neutral gear sliding and in-situ oil rolling,
The weight ratio of the bottom grade index is approximately smaller and sequentially comprises that the cold vehicle runs, the gear increasing rotating speed is too low, the gear decreasing rotating speed is too low, and gear pre-judgment is unreasonable.
5. The scoring method of the system for scoring various data based on vehicle control multidimensional fusion as recited in claim 4, wherein in step S3, the system reports sudden braking when the braking pre-judgment and sudden braking occur simultaneously in the weight ratio of the medium-level index.
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