53results about How to "Improve driving behavior" patented technology

The invention discloses a personal driving behaviour analysis management control system, comprising a data reading terminal, a GPS (global positioning system) positing device and a server, wherein the data reading terminal is used for acquiring vehicle ECU (electronic control unit) operational data, reading automobile travelling working condition data, creating a driver operation behaviour data evaluation analysis model, giving an alarm when finding a dangerous driving behaviour, emergently recording vehicle accident data, carrying out statistic on automobile travelling mileage and fuel consumption and detecting whether vehicle emission exceeds the standard or not; the GPS positioning device is used for vehicle positioning; and the server is used for recording and analyzing driving behaviour data, timely reminding a vehicle maintenance fault by combining OBD (on-board diagnostics) vehicle diagnostic function and exchanging information with a user by virtue of an interconnection platform. The invention extracts safety and economy conditions of a vehicle owner by virtue of multiple behaviour models, provides guiding suggestions and ideas for a vehicle owner and alarms and suggests in the automobile driving process and on an Internet terminal interface, thus the system improves driving behaviour and achieves energy conversation and emission reduction, is safety in control, is economic and environment-friendly.

A lane-keeping method and system for a motor vehicle determines a transverse deviation and an misalignment angle of the motor vehicle relative to a target lane centerline, calculates a reference track for the motor vehicle to follow to return to the centerline using the transverse deviation and the misalignment angle, determines a reference yaw rate using a curvature of the reference track and a longitudinal speed of the vehicle, and compares the reference yaw rate with an actual yaw rate of the vehicle to determine a control deviation. A steering input is then applied to a steering system of the motor vehicle to minimize the control deviation.

The invention discloses a driving behavior analyzing system. The driving behavior analyzing system comprises a driving information collecting module, a vehicle surrounding environment collecting module, a driver fatigue extent measuring module, a data recording and analyzing module, a judgment module, an alarming module and an evaluating module. The driving information collecting module, the vehicle surrounding environment collecting module and the driver fatigue extent measuring module are all connected with the data recording and analyzing module, the other end of the data recording and analyzing module is connected with the judgment module, and the other end of the judgment module is connected with the alarming module and the evaluating module. According to the driving behavior analyzing system, driving data are analyzed to measure the driving behavior of a driver, the driving behavior of the driver is evaluated accordingly, the driving behavior of the driver can be analyzed on thebasis of the driving environment, correct guiding is made for the driver, misguiding is avoided, meanwhile the driving behavior of the driver is improved, and the oil consumption of a vehicle is reduced.

The invention discloses an ADAS intelligent vehicle-mounted terminal-based vehicle insurance management service system. The system comprises an ADAS intelligent vehicle-mounted terminal and a remote server connected through a wireless network, wherein the remote server is connected with a service monitoring platform through a cloud server; the ADAS intelligent vehicle-mounted terminal comprises an image acquisition and processing apparatus, a GPS locating apparatus, an acceleration sensor, a data processing apparatus, a storage memory unit and a wireless transmission apparatus; the remote server comprises a communication gateway, a big data cloud expert system and a storage unit; the big data cloud expert system is used for performing analysis and classified storage on data; and the service monitoring platform is used for performing monitoring management on an operation and maintenance vehicle according to data of the ADAS intelligent vehicle-mounted terminal. The system can detect a dangerous driving behavior of a driver and give an early warning, so that the driving behavior of the driver is improved, the accidents are effectively avoided, and the vehicle insurance claim rate is reduced.

The invention provides a GPS-based risky driving behavior monitoring method. The GPS-based risky driving behavior monitoring method comprises the following steps: step 1, acquiring GPS data, and storing effective GPS data; step 2, analyzing the effective GPS data, and storing the analyzed vehicle speed and vehicle running direction angle and time as a group of data; and step 3, analyzing multiple groups of data acquired continuously, and giving an alarm if risky driving behaviors exist. The method is mainly used for detecting behaviors which easily cause dangers for vehicles including rapid acceleration, rapid brake, sharp turning, speeding and the like, gives an alarm to a user finally, and assists in the user to know his risky driving, and the driving behaviors of the user can be improved effectively.

The invention relates to a vehicle illegal driving risk analysis method based on the Beidou positioning system. The method comprises the steps: obtaining basic information and driving information of a vehicle, wherein the driving information comprises driving track information and / or running state information; uploading the basic information and the driving information of the vehicle to a server, so that the server analyzes the driving behavior of the vehicle, determines the illegal driving condition of the vehicle, and updates the risk score of illegal driving of the vehicle; and judging the risk level of the illegal driving condition of the vehicle according to the score, and generating a vehicle illegal driving risk analysis report. The risk score of illegal driving of the vehicle is accurately calculated, and a user generates the risk analysis report of illegal driving according to the risk score of illegal driving of the vehicle, so that the user can easily discover which aspects the illegal driving exists in, so as to remind and supervise a driver to improve the driving behavior and achieve the early warning and assessment effects on the driving behavior of the driver, thereby facilitating the daily management.

The invention relates to an economic driving assistance system based on a big data cloud platform and an implementation method thereof. The economic driving assistance system comprises a cloud platform, a data transmission terminal, a vehicle internal bus network, a vehicle-mounted controller, a vehicle central control screen and a vehicle-mounted sensor. The implementation method comprises the steps that the vehicle-mounted sensor acquires information, the vehicle-mounted controller collects and processes the information and then transmits the information to the vehicle internal bus network, the data transmission terminal accesses to the vehicle internal bus network to acquire vehicle position information and the above information, the data transmission terminal transmits the information to the cloud platform so as to be stored and used for driving behavior analysis, and the cloud platform performs driving behavior guidance on a driver. The economic driving assistance system can scientifically analyze historical driving behavior data, accurately recognize the current state of the vehicle, correctly guide driving actions of the driver and improve driving behaviors of the driver.

The invention relates to a vehicle traveling data recorder with a driving behavior optimization function. The vehicle traveling data recorder comprises a positioning module, a three-axis acceleration sensor, an MCU (Microprogrammed Control Unit) microprocessor, a CAN (Controller Area Network) bus transmitting and receiving module and a communication module. The vehicle traveling data recorder is characterized in that the CAN bus transmitting and receiving module is connected to a vehicle CAN bus for data communication; the three-axis acceleration sensor is used for acquiring vehicle posture data for auxiliary calculation through the MCU microprocessor so as to judge driving behaviors. Three-dimensional dynamic acceleration values of a vehicle in the running process are acquired through the three-axis acceleration sensor, a speed pulse detection module is connected with a vehicle speed sensor to detect the pulse speed of the vehicle, after a terminal acquires the data, harmful driving behaviors of a driver can be judged and optimized through operation of filtration, integration, calculation, analysis and the like.

The invention relates to a pure electric vehicle energy consumption monitoring optimization method, which comprises the steps of setting a target place where a vehicle needs to arrive, and starting tocollect vehicle operation information after the vehicle is started; determining an actual road condition from the target location to the location of the current vehicle, and simulating the actual road condition information; when the driving cycle number i is larger than or equal to 1, starting energy consumption evaluation; calculating and obtaining real-time energy consumption efficiency in thecurrent energy consumption evaluation period, and displaying the real-time energy consumption efficiency Ei and the energy consumption rate Ei-1 in the (i-1) th energy consumption evaluation period ona vehicle-mounted instrument; giving an optimization suggestion of the driving behavior; and through comparing the residual electric quantity of the battery with the residual demand electric quantity, giving a prompt of whether the driver can normally arrive at the target place. The invention further discloses a pure electric vehicle energy consumption monitoring and optimizing system. The current energy consumption condition can be accurately provided for the driver, suggestions can also be provided for the driving behavior of the driver, and energy conservation and consumption reduction ofthe whole vehicle are achieved.

The invention provides a driver relative risk evaluation method based on benchmark analysis. The driver relative risk evaluation method includes the steps: by installing a GPS data collector on a motor vehicle, obtaining natural driving behavior data of a driver; based on the vehicle operation parameters, extracting key events, and determining dangerous driving behaviors of a driver; classifying the driving behaviors with different danger degrees by adopting a clustering analysis method; and calculating comprehensive risk indexes of the individual drivers relative to other drivers by utilizinga benchmark analysis method, and meanwhile, obtaining dangerous driving behavior weight distribution reflecting individual differences of the drivers. According to the driver relative risk evaluationmethod, the traditional absolute risk is replaced by the relative risk of the driver, so that the absolute risk quantification of various dangerous driving behaviors is avoided. Relative risk evaluation is carried out on dynamic driving behaviors of individual drivers, and technical support can be provided for safe driving intelligent reminding and feedback of the drivers, personalized insuranceevaluation based on the driving behaviors and road traffic safety management.

The invention discloses a scenario-based driving behavior evaluating method. The method comprises the following steps that: S1, a data acquisition unit for an ECU (Electronic Control Unit) of a vehicle collects the vehicle working condition data and vehicle performance data, and then the collected data is synchronized to an intelligent cloud platform in real time through a wireless network; S2, the intelligent cloud platform analyzes the recorded data for the driving travel same as the travel route by a big data analysis method; and S3, the intelligent cloud platform receives the data transmitted from an intelligent mobile terminal, the data is stored in the platform, and the driving travel of the time is accurately analyzed by a big data analysis method according to the historical travel data. The method is high in accuracy, can accurately evaluate the degree of proper driving actions of a driver in different situations and objectively reflect the driving skill level of the driver, and meanwhile, is high in computational efficiency, and can quickly evaluate the driving behavior of the driver and feedback the evaluation result in time.

The invention discloses a driving recorder which comprises a CPU processor and further comprises a GPS data receiver and a photographic sensor which are connected with the CPU processor. The CPU processor is further connected with an SD memory card and a display; both a memory output module and an NADA flash memory module are arranged between and connected with the CPU processor and the display. According to the invention, the problem that driving recorders in the prior art can not analyze a variety of indexes of driving behaviors is overcome; a variety of relevant parameters like illegal speeding, rapid acceleration, rapid braking, an instable vehicle speed, idling time and swinging states in the process of driving can be detected by using the driving recorder and detection results are combined with a wheelpath detected by the GPS data receiver and are displayed on an image screen, which enables a driver to clearly spot aberrant behaviors in the process of driving, and therefore, the driver is reminded that he should improve his driving behaviors.

The invention provides a reinforcement-learning-based optimization method for an ecological driving behavior at an urban road intersection. The method comprises the following steps: establishing a simulation platform by using a cellular automata model; placing a vehicle on the simulation platform for reinforcement learning; after reinforcement learning on the vehicle, obtaining a Q matrix; and optimizing the driving behavior of the vehicle by using the obtained Q matrix to realize ecological driving. With the evaluation method based on reinforcement learning and the microscopic simulation platform, the influences on vehicle exhaust emission and traffic characteristics by the ecological driving behavior are studied to provide useful information for improvement of the strategy of the vehicleecological driving.

The embodiment of the invention provides a driving behavior real-time reminding method and device, an electronic device and a storage medium. The method comprises: obtaining vehicle state parameters and driver state parameters in the driving process; analyzing the vehicle state parameters and the driver state parameters to generate corresponding analysis results; judging whether violation behaviors are included in the driving process or not according to the analysis result; and when the violation behavior is included in the driving process, generating a warning prompt according to the specificcontent of the violation behavior. The method has the advantages that the driver state and the driving parameters are evaluated, suggested and reminded in real time, the vehicle state parameters andthe driver state parameters in the driving process are comprehensively assessed through the management platform, the driving behavior of the driver is practically improved, and the good driving behavior habit of the driver is cultivated.

The invention relates to the technical field of vehicle oil consumption management, and provides an Internet of Vehicles server, a vehicle and a vehicle oil consumption prompting method based on driving data. The vehicle oil consumption prompting method comprises the steps: collecting driving data related to the vehicle oil consumption in the driving process of the vehicle; performing big data arrangement and learning on the driving data, and performing analysis according to the big data arrangement and learning to obtain corresponding driving behavior description; and integrating the drivingbehavior description with the vehicle oil consumption condition to obtain an oil consumption saving suggestion, and prompting the oil consumption saving suggestion to a user to adopt a corresponding driving behavior. Thus, according to the method, the driving behavior of a vehicle driver can be improved, accurate oil consumption use suggestions can be given to the driver according to the driving habits of controlling the accelerator size, gear selection, brake frequency and the like of the driver, the driver is helped to reduce the oil consumption, the cost is reduced for the driver, the environment can be protected, and the user experience is improved.

The invention discloses a vehicle risk comprehensive evaluation method based on transition probability, which comprises the following steps of: 1) data acquisition and processing, 2) index classification determination: according to the influence of indexes on risks, dividing the indexes into A-class indexes with large influence on risks and B-class indexes with small influence on risks, the A-class indexes comprising an anti-collision early warning index and a fatigue driving alarm index, and 3) constructing a vehicle driving risk assessment model for the preprocessed Internet of Vehicles alarm data. Through the above steps, the invention provides the vehicle risk comprehensive evaluation method based on the transition probability, which is good in evaluation accuracy, good in use effect and high in applicability.

The invention discloses an intelligent man-machine interaction type vehicle accelerator pedal device. The device comprises a pedal rotary shaft system, a control shaft system, a sliding polished shaft system and a clutch shaft system. The pedal rotary shaft system, the control shaft system, the sliding polished shaft system and the clutch shaft system are arranged on a pedal support. The pedal rotary shaft system is used for achieving work states of a common accelerator pedal, the control shaft system transmits power to the clutch shaft system through the sliding polished shaft system, a cylindrical cam, idler wheels and a transmission rod in the clutch shaft system drive a pressing plate to move axially so that the plate-type cam of the control shaft system can achieve feedback control of pedal force after the pressing plate and a friction plate are combined and locked, and an adjusting mechanism in the sliding polished shaft system can adjust the axial position of a sliding gear so that the common accelerator pedal can work when a control motor fails. Besides, control of rotation speed and power of an engine and running speed can be achieved through the common accelerator pedal, running states and road condition information can be fed back to drivers through an accelerator pedal in a tactile feedback mode, man-machine interaction is achieved, and the drivers are assisted in improving driving behaviors.

The invention discloses a driving behavior analysis method. The driving behavior analysis method comprises the steps that current driving data relevant with vehicle oil consumption is acquired in the vehicle driving process; according to a preset analysis rule, the driving data is analyzed to obtain an analysis result; according to the analysis result, a driving behavior description corresponding to the driving data is generated. The invention further discloses a driving behavior analysis device. The driving behaviors of a driver can be analyzed, so that the driver conveniently adjusts the driving behaviors according to the analysis result to reduce the vehicle oil consumption.

The invention relates to an automobile acceleration pedal device with a tactile feedback function. The device comprises a pedal support, a pedal rotating shaft system, a control motor shaft system, a planetary gear mechanism and a control push rod mechanism, wherein the pedal rotating shaft system, the control motor shaft system, the planetary gear mechanism and the control push rod mechanism are installed on the pedal support. The pedal support is fixedly combined with bodywork of the automobile. The pedal rotating shaft system is composed of an angular displacement sensor, a pedal rotating shaft, an acceleration pedal and a reset spring. The control motor shaft system is mainly composed of a control motor and an output shaft. The planetary gear mechanism is mainly composed of a sun wheel, two planetary wheels, a planet support and a gear ring. The control push rod mechanism is mainly composed of a push rod, a fulcrum bar, a mandril, a buffer spring and a friction plate. According to the automobile acceleration pedal device with the tactile feedback function, free conversion of a common acceleration pedal mode and an active feedback type acceleration pedal mode can be achieved, and a driver can select the working modes according to individual needs.

The invention discloses a driving behavior analysis device and method. The device comprises an obtaining module, which is used for obtaining traffic information of an automobile in the driving process from a vehicle-mounted driving assistance system; an analysis module, which is connected with the obtaining module and is used for carrying out statistic analysis on the traffic information to obtain vehicle following habits of a driver according to the vehicle following distance, to obtain lane changing habits of the driver according to lane departure times and duration time, to obtain over-speed driving habits of the driver according to over-speed range and duration time and to obtain vehicle following and speed-up driving habits of the driver according to forward collision warning times; and an evaluation module, which is used for comparing the driving habits of the driver obtained by the analysis module with preset good driving habits to obtain bad driving habits of the driver. According to the driving behavior analysis device and method, the driving habits of the driver can be analyzed based on the driving environment, and the driver can be correctly guided, thereby preventing misguiding and meanwhile, improving the driving behavior of the driver.

The invention discloses a driving risk factor quantification method based on a driving behavior portrait. The method comprises: firstly, preprocessing original data collected by a vehicle sensor; secondly, selecting a sampling time interval and a sampling time continuous duration for the preprocessed vehicle sensor data by using a clustering algorithm; thirdly, performing driving behavior variableselection, feature extraction of each behavior and the like on the data obtained through clustering, and energy features are extracted; and finally, establishing a driving risk factor quantificationsystem by combining with a Sigmoid function according to the extracted features. The problem that driving risk quantification is difficult is solved. The driving behavior of the driver is quantified based on the data received by the vehicle-mounted sensor equipment, the driving behavior of the driver can be improved, and an enterprise judges a good driver and assists a vehicle insurance company toidentify the risk so as to carry out differential pricing on vehicle insurance premium.

The invention discloses a detecting and monitoring system and method for safe driving of an automobile. The detecting and monitoring system comprises a plurality of safe driving behavior detecting devices separately connected with an input end of a vehicle driving computer, and an output end of the vehicle driving computer is connected with display screens and a dashboard. A personal headshot anddriving behavior data of a driver are automatically stored and analyzed by the vehicle driving computer and then displayed on the display screens and the dashboard. A license plate of one vehicle onelicense is input into the vehicle driving computer by a vehicle management department and displayed on the display screens, and the display screens at least include a front display screen and a rear display screen separately installed inside or outside the vehicle and conveniently viewed from the outside of a vehicle. The relevant data monitored by the safe driving behavior detecting devices can be outputted and displayed on the display screens and the dashboard after being automatically stored and analyzed by the vehicle driving computer, so that the situation that the whole people coordinatewith the traffic control department to supervise the driving behavior of drivers can be realized. The awareness of safe driving for all the people is improved, traffic accidents are reduced, and licenses are prevented from being altered or replaced after theft of the vehicle.

The invention relates to a vehicle driving behavior improving system. The vehicle driving behavior improving system is provided with an environmental perception module, a knowledge base module, a driving behavior algorithm module and a vehicle control system. According to environment information and knowledge information from the environmental perception module, an original brake pedal signal, an original accelerator pedal signal and an original steering wheel angle signal are optimized by the driving behavior algorithm module, optimized signals are obtained and compared with the original signals, an actual brake pedal signal, an actual accelerator pedal signal and an actual steering wheel angle signal are obtained and input into a brake system, a transmission system and a steering system correspondingly. According to brake torque, driving torque and a steering angle which are obtained from the brake system, the transmission system and the steering system correspondingly, a vehicle is controlled by the vehicle control system.

The embodiment of the invention provides a method and device for optimizing a driving behavior. The method for the optimizing the driving behavior comprises the steps of determining an optimization power control device state parameter of a vehicle according to a pre-stored driving model and a vehicle speed of the vehicle if it is detected that average fuel consumption of the vehicle within a preset mileage is higher than a preset value, wherein the driving model comprises a corresponding relation between a preset vehicle speed and a preset optimization power control device state parameter; anddetermining an optimized driving behavior for the vehicle according to the optimization power control device state parameter and a current power control device state parameter of the vehicle. The device for optimizing the driving behavior is used for executing the method for optimizing the driving behavior. According to the method and device for optimizing the driving behavior, provided by the embodiment of the invention, the driving behavior of a driver can be optimized so as to reduce the fuel consumption of the vehicle.

The invention discloses a scenario-based driving behavior evaluating method. The method comprises the following steps that: S1, a data acquisition unit for an ECU (Electronic Control Unit) of a vehicle collects the vehicle working condition data and vehicle performance data, and then the collected data is synchronized to an intelligent cloud platform in real time through a wireless network; S2, the intelligent cloud platform analyzes the recorded data for the driving travel same as the travel route by a big data analysis method; and S3, the intelligent cloud platform receives the data transmitted from an intelligent mobile terminal, the data is stored in the platform, and the driving travel of the time is accurately analyzed by a big data analysis method according to the historical travel data. The method is high in accuracy, can accurately evaluate the degree of proper driving actions of a driver in different situations and objectively reflect the driving skill level of the driver, and meanwhile, is high in computational efficiency, and can quickly evaluate the driving behavior of the driver and feedback the evaluation result in time.

The invention discloses an intelligent license plate fixing system and method, and belongs to the technical field of automobile alarm devices. The intelligent license plate fixing system comprises anintelligent license plate fixing device, a cloud platform and a client. The intelligent license plate fixing device comprises a license plate fixing frame, a main control MCU, a communication module,a positioning module, a pressure sensing module and an acceleration sensor. The cloud platform is used for receiving and storing the vehicle driving data, performing background analysis and automatically judging the vehicle driving state. The client is used for checking the driving process by the vehicle owner and setting the accident level according to the driving behavior habit of the vehicle owner. The intelligent license plate fixing system can monitor the driving process in real time, helps a driver to improve the driving behavior, and has good application and popularization value.

The invention discloses a joint optimization method for vehicle speed planning and energy management of a fuel cell vehicle, and the method comprises the following steps: S1, building a vehicle dynamics model through combining vehicle key technical parameters and a vehicle power system power topological structure; s2, performing convex processing on a fuel cell system model, a motor system model and a power cell system model in the vehicle dynamics model; s3, establishing a traffic signal timing model in combination with the traffic signal lamp information; s4, based on the vehicle dynamics model and the traffic signal timing model, solving the vehicle speed planning problem of the fuel cell vehicle passing through the multiple signal lamps by using a double-layer dynamic planning algorithm, and generating an optimal vehicle speed track; s5, solving an energy management problem of the vehicle under the optimal vehicle speed track generated in the step S4 by using a convex optimization algorithm; the problem of combined optimization of vehicle speed planning and energy management of the fuel cell vehicle in a multi-continuous-signal-lamp scene is solved.

The invention discloses a scene-based driver assistant system realizing method, which comprises the following steps: S1, vehicle condition data and vehicle performance data are acquired through a vehicle ECU (electronic control unit) data acquisition device and the acquired data is transmitted to a mobile driver assistant terminal via a wireless network; S2, geographic coordinate data of a vehicle is acquired through the mobile driver assistant terminal during driving, and is synchronized, together with the data acquired in the S1, to a cloud intelligent platform via the wireless network; and S3, the cloud intelligent platform analyzes out information required for driving assistance from mass data by virtue of a big data analytical algorithm. The realizing method is scientific and effective, takes mass data about historical driving journey as a journey route selection reference frame, and effectively meets the requirement of a driver for route selection. Meanwhile, the method is highly accurate, can accurately identify different driving scenes, accurately judges next driving scene for the vehicle, and correctly directs the driver to do proper driving action.

The present invention relates to a method for detecting a driving behavior causing excessive wear of a clutch of a vehicle. The method comprises the following steps: acquiring engine speed information, wheel speed information, and clutch pedal information; calculating an actual transmission ratio of a power system of the vehicle based on the engine rotating speed information and the wheel rotating speed information; calculating a reference transmission ratio based on the engine speed information and the clutch pedal information; and in the event that the actual gear ratio deviates from the reference gear ratio by more than a predetermined degree, concluding that there is a driving behaviour causing excessive wear of a clutch of the vehicle. The invention also relates to a device for detecting the driving behavior causing excessive wear of the clutch of the vehicle. The invention also relates to a method and a device for detecting the excessive wear state of the clutch of the vehicle. The invention also relates to the vehicle and a computer readable storage medium.