TWM552127U - System for evaluating driving risk - Google Patents

Description

Evaluation of driving risk system

The present invention relates to a system for assessing the driving risk of a subject, and in particular to a system for evaluating using virtual reality techniques.

Motor vehicles are the main means of transportation for the Chinese people because of their high mobility and economical price. However, with the increase in the number of steam locomotives in China in recent years, the road traffic problems that have arisen have also become more serious. The improvement of driving behavior of Chinese steam locomotives has always been the first problem for law enforcement agencies to improve. In order to promote correct driving behavior, the government will reduce the risk of driving and continuously improve the contents of the motorbike driving test. The purpose is to ensure that qualified drivers can have good driving habits and comply with traffic regulations. However, this method still has its limitations; in the case of locomotives, the practice space for locomotive riding is limited, the subjects are generally under-exercised before being tested, and no qualified coach teaches the correct riding style and road riding. Taking advantage of the concept, the lack of links between traffic regulations and actual driving behavior, the driver can only familiarize with the operation skills of the locomotive after the actual riding process after obtaining the driver's license. In view of this, in order to improve the defects of the prior art, there is a need in the art for a method and system for evaluating driving risk to improve the deficiencies of the prior art.

The novel content is intended to provide a simplified summary of the disclosure in order to provide a basic understanding of the disclosure. This Summary is not an extensive overview of the disclosure, and is not intended to identify key/critical elements of the novel embodiments or the scope of the invention.

One aspect of the present invention relates to a method for assessing a driver's driving risk, mainly using virtual reality technology, taking the user's behavior factor and calculating it with a specific model, thereby assessing the user's driving risk and achieving a reduction. The accident rate guarantees the safety of driving. The method of the present invention comprises the following steps: (a) using a video module to provide a vehicle driving virtual reality video and audio to the subject by a head-mounted audio-visual device, so that the subject is in a vehicle driving virtual In the real world, wherein the vehicle driving virtual reality includes at least one conventional situation and/or at least one emergency situation; (b) using a sensor to receive the subject in the driving virtual reality of the vehicle corresponding to the conventional situation Generating at least a first behavioral factor and/or at least a first behavioral factor and/or a second behavioral factor generated by the emergency context; and (c) utilizing a computing module to generate a first behavioral factor based on the first behavioral factor The risk score is generated and/or a risk perception score is generated based on the second behavior factor.

According to an embodiment of the present invention, the first behavior factor is selected from the group consisting of: an initial behavior, a braking behavior, a vehicle traveling behavior, and a vehicle parking behavior. According to a specific embodiment of the present invention, the step (c) is to generate the anecdotal risk score by comparing the first behavior factor and a first reference behavior. The first reference behavior is pre-stored in a database of the novel system as a benchmark for comparison analysis, and a score corresponding to the first behavior factor of the subject is given to calculate an anecdotal risk score.

According to still another embodiment of the present invention, the step (c) is to first detect the instantaneous velocity, the reaction distance and the reaction time of the subject in a sudden situation, and respectively compare the standard values to generate a corresponding score. Then, the corresponding scores are integrated to generate a risk perception score. In one embodiment, the reaction time comprises a release throttle reaction time and a brake reaction time. According to an embodiment of the present invention, the release throttle reaction time and the brake reaction time are calculated by weighting to obtain the risk perception score. In addition, the weight of the throttle reaction time is higher than the brake reaction time. In a preferred embodiment, the weight ratio of the release throttle reaction time to the brake reaction time is 6:4.

In addition, the method of the present invention includes, in step (a), using a context control module to set the number of times a conventional situation and/or a sudden situation occurs in a vehicle driving virtual reality. In another embodiment, the context control module can further set the location and time at which the conventional context and/or the abrupt situation occurs in the virtual reality. In an embodiment of the present invention, the occurrence of the sudden situation is determined based on the instantaneous speed at which the subject travels on the road in the virtual reality.

In addition, the method of the present invention further includes the following steps: (d) recording, by a recording module, the traveling condition of the subject in the driving virtual reality of the vehicle to generate a recorded video; and (e) utilizing A teaching module plays the recorded video and audio through the head-mounted audio and video device for viewing by the subject.

Specifically, in step (e), the method further comprises: generating a bird's-eye view map by using the audio-visual module, and displaying the first behavior and/or the location where the second behavior occurs on the bird's-eye view map. Furthermore, the novel The method can also be synchronously taught. In the step (e), the teaching module is further configured to display a normal driving behavior information in the recorded audio and video at the position where the first behavior and/or the second behavior occurs.

Another aspect of the present invention relates to a driving risk assessment system. The evaluation system includes a head-mounted audio-visual device, a video module, a sensor, and a computing module that are communicatively coupled and/or electrically coupled to each other. The head-mounted audio-visual device is worn on the head of the subject and covers the head and ears of the subject. The audio-visual module is configured to provide a vehicle driving virtual reality video and audio to the subject by the head-mounted audio-visual device, so that the subject is in a vehicle driving virtual reality, wherein the vehicle driving virtual reality includes at least one A general situation and/or at least one unexpected situation. The sensor is configured to receive at least one second behavior factor generated by the at least one first behavior factor and/or the sudden situation generated by the subject in a corresponding virtual situation in the vehicle driving virtual reality. The computing module is configured to generate a risk perception score based on the first behavior factor and/or the second behavior factor.

The basic spirit and other novel objects of the present invention, as well as the technical means and implementations of the present invention, can be readily understood by those of ordinary skill in the art.

The main component symbols of this new model are listed below:

100, 200‧‧‧ system

108, 208‧‧‧ head-mounted audio and video equipment

110, 210‧‧‧ communication unit

111‧‧‧ transceiver module

113‧‧‧Video Module

115‧‧‧ alignment module

117‧‧‧Computation Module

119‧‧‧Database

150, 250‧‧‧ sensor

155‧‧‧Base station

180, 280‧‧‧ arithmetic device

220‧‧‧ display

230‧‧‧ Speaker

252‧‧‧ throttle grip

254‧‧‧煞车握把

312-318, 418-432, 550-556‧‧‧ steps

The above and other objects, features, advantages and embodiments of the present invention will be more apparent and understood. The description of the drawings is as follows: FIG. 1A is a driving risk assessment system 100 according to an embodiment of the present disclosure. schematic diagram; 1B is a block diagram of a driving risk assessment system module according to an embodiment of the present disclosure; FIG. 2 is a schematic diagram of a driving risk assessment system 200 according to another embodiment of the present disclosure.

3 is a flowchart of the driving risk assessment method according to an embodiment of the present disclosure; FIG. 4 is a partial flowchart of the driving risk assessment method according to an embodiment of the present disclosure; The figure is a partial flow chart of the driving risk assessment method according to another embodiment of the present disclosure.

The various features and elements in the figures are not drawn to scale, and are in the In addition, similar elements/components are referred to by the same or similar element symbols throughout the different drawings.

In order to make the description of the present disclosure more detailed and complete, the following description of the embodiments of the present invention and the specific embodiments thereof are set forth. The features of various specific embodiments, as well as the method steps and sequences thereof, are constructed and manipulated in the embodiments. However, other specific embodiments may be utilized to achieve the same or equivalent function and sequence of steps.

Unless otherwise defined in the specification, the meaning of the scientific and technical terms used herein is the same as that of ordinary skill in the art. In the absence of conflict with context, the singular noun used in this specification covers the plural of the noun, and the plural noun used also covers the singular of the noun. In addition, in the scope of the present specification and the patent application, the expressions "at least one" and "one or more" have the same meaning, and both represent one, two, three or more. What is more, in the scope of this specification and the patent application, "selected from the following groups: A, B and C", "A, B and / or C" means that only A, only There are B, only C, A and B, B and C, A and C, and A, B and C.

As can be appreciated, the "computing device" typically has at least some form of storage unit and communication unit. The storage medium comprises an electrical, non-electrical, removable and non-removable medium, and the appropriate medium or technology can be used to enable the above media to store desired information (eg, computer readable) Instructions, data structures, application modules, and other materials). The storage medium includes but is not limited to: random access memory RAM, read only memory (ROM), and electronically erasable readable memory (Electrically-Erasable Programmable Read-Only Memory) , EEPROM), flash memory, or other memory technology, CD-ROM, digital multi-function video (DVD), or other optical storage, magnetic tape, tape, Disk storage, and other magnetic storage devices, or any other medium that can be used to store the required information and be accessible to the processor. In general, communication components can be used to implement computer readable instructions, data, structures, application modules and other data into various data signals and can be transmitted through any communication medium. By way of illustration and not limitation, communication media includes wired media (such as a wired network or direct wired connection) and wireless media (such as sonic, infrared, radio, microwave, spread spectrum, and other wireless media technologies). In addition, this article Computer-readable media refers to any available media that can be accessed by the computing device, such as the storage media described above, communication components, or a combination of both. By way of example and not limitation, the "computing device" may be a desktop computer, a server computer, a handheld or laptop device, a personal digital assistant, a multi-computing device system, a system based on a micro-operating device, or an on-board Boxes, programmable consumer electronics, mobile phones (especially smart phones), network computers, mini computers, host computers, distributed computing environments containing any of the above systems or devices, and the like.

The term "subject" as used herein refers to an individual suitable for the present novel method and system for assessing driving risk. In a specific embodiment, the individual is a human.

The term "behavioral factor" as used herein refers to an individual who is evaluated by the present method for assessing driving risk, which is related to the driving behavior induced by the normal situation and/or the sudden situation in the test content.

1 is a schematic diagram of a system 100 for performing the present method of assessing driving risk, in accordance with an embodiment of the present invention. In order to accurately assess the potential risk of the subject in driving on the road, the newcomer proposed a novel driving risk method for the first time, which integrates computer graphics, human-machine interface technology, sensing technology, psychology, ergonomics and labor. Wisdom and other technologies use virtual reality to test the driving behavior of individuals in driving simulation scenarios, and compare, analyze and calculate the anecdotal risk and risk perception ability of the data subject in the driving process, in addition to being a personal path. In addition to driving risk assessment, this method can also be used to improve the correct driving attitude and driving skills of the subjects, reduce the risk of accidents and improve traffic safety.

The new evaluation driving risk system utilizes near-eye display technology to transmit virtual images and sound effects to the subject, giving them an immersive feel. The driving risk system 100 includes a head-mounted audio-visual device 108, a sensor 150, a base station 155, and an arithmetic device 180 that are communicatively coupled to each other. The computing device 180 described herein can be any type of electronic computing system and is well known to those skilled in the art. Solution, whether the electronic computing system is a complex computer device that can be simultaneously logged in and used by multiple users or a workstation or handheld device that is only used by a single user, the novel method or system is equally applicable to these electronic computing system. Moreover, the novel method or system is equally applicable regardless of whether the electronic computing system is a stand-alone or member of a complex network.

Specifically, the computing device 180 of the present invention is an electronic device including a processing unit (eg, a central processing unit (CPU)); in order to be able to implement the method proposed by the present invention, the computing device 180 may also be provided with an appropriate communication unit. For connecting the computing device 180 to a network or other device, so that it can exchange information with the head-mounted audio-video device 108, the base station 155, and/or the sensor 150. As can be understood, the computing device 180 generally includes a memory and a storage unit. The memory includes volatile memory and non-volatile memory for storing instructions to be executed, and the storage unit is used for Store databases and various electronic files or information. The volatile memory means that when the power is interrupted, the data stored in the memory disappears as the power is interrupted. Such memory includes but is not limited to random access memory, such as dynamic random access memory (DRAM). (eg, Synchronous Dynamic Random Access Memory Third Generation (DDR 3); or Static Random Access Memory (SRAM). Conversely, non-volatile memory means stored in the power supply when it is interrupted. The data does not disappear; such memory includes, but is not limited to, read-only memory or flash memory.

In the embodiment of the present invention, the head-mounted audio-video device 108 and the computing device 180 are connected through a wired physical device, but the configuration of the two components is not limited thereto. For example, the head-mounted audio-visual device 108 can also be communicatively coupled to the computing device 180 in a wireless manner. Moreover, as shown in the figure, the system 100 detects the action behavior of the subject operating sensor 150 through the base station 155, and then transmits the information back to the computing device 180. In addition, a speaker may be disposed in the head-mounted audio-visual device 108, or a headset may be additionally coupled to the audio-visual device 108.

In addition, the present invention further discloses a system for performing the present method for evaluating driving risk. Referring to FIG. 2, the system 200 of the present embodiment includes a head-mounted audio-video device 208, a sensor 250, and an arithmetic device 280. To simulate the situation of locomotive ride, the appearance of the head-mounted audio-visual device 208 is designed to be the shape of a locomotive helmet, and the sensor 250 is in the shape of a locomotive. Specifically, the head-mounted audio-video device 208 includes a communication unit 210, a display 220, and a speaker 230, which can surely isolate external noise when worn. In the process of performing the novel method, the head-mounted audio-video device 208 is The communication unit 210 is communicatively coupled to the sensor 250 and the computing device 280. The speaker 230 is disposed inside the head-mounted audio-visual device 208, preferably on both sides of the head-mounted audio-visual device 208, and the display 220 is disposed on the front side of the head-mounted audio-video device 208. In addition to the instrument panel, the sensor 250 is provided with a throttle grip 252, a brake grip 254 and a directional light button (not shown), and the like to detect the behavior of the subject driving in the sensor 250. A gyroscope and/or a directional sensor can be provided. In addition, it should be understood by those of ordinary skill in the art that the system of the present invention can also integrate commercially available virtual reality hardware devices (for example, HTC VIVE) and computing devices to perform the present invention to assess the risk of driving of the subject. Methods.

FIG. 1B is a schematic diagram of a module of a computing module system in the driving risk system 100 shown in FIG. 1A. In order to perform the method proposed by the present invention, the computing device 180 of the novel system is mainly loaded with four modules, which are a transceiver module 111, a video module 113, a comparison module 115, and a calculation module 117. The transceiver module 111 is configured to transmit/receive information to the sensor 150, the base station 155, and the head-mounted AV module 108 that operate the new evaluation method. The audio and video module 113 is used to transmit the virtual reality video and audio required to perform the new evaluation method to the head-mounted audio and video device 108. The comparison module 115 is configured to compare the first behavior factor and/or the second behavior factor received by the transmissive sensor 150 with the setting parameters pre-stored in the database 119, and obtain respective data information for calculation. Module 117 analyzes the calculation of anecdotal risk and risk perception capabilities.

Please refer to FIG. 1A, FIG. 1B and FIG. 3 at the same time. The method for estimating the driving risk of the testee is specifically described as follows: First, the subject wears the audio-visual device 108 on the head, and the subject's eyes are The cover is wrapped in the head-mounted audio-visual device 108, and the subject is held by the sensor 150 to perform a driving risk test. Then, the driving risk assessment method of the method is started. The driving risk assessment method of the present invention is to use the audio-visual module 113 to perform the test on the locomotive virtual reality (ie, the vehicle driving virtual reality video and audio) and the related sound effects via the transceiver module 111. The display 120 and the speaker 130 of the head-mounted audio-visual device 108 are provided to the subject, and the subject is placed in the vehicle driving virtual reality (step 312).

In step 314, the new test time is about 5-10 minutes, and the test content is mainly to simulate the actual situation that the subject may actually ride in the urban road. The novel method can provide a plurality of different road detection units (for example, different cities, regions, weather, etc.) for testing, wherein the virtual reality of each detection unit includes at least one conventional situation or a sudden situation. The conventional scenario is to simulate a situation of a general riding locomotive, for example, an urban traffic road containing traffic signs. Furthermore, the sudden situation is that the vehicle suddenly changes lanes, the door suddenly opens, the goods fall, the weather suddenly changes, the pedestrian or dog rushes out, the road area water, the road obstacles, the roadside vehicles start, the unattended side-by-side parking, the road Side construction site, reverse locomotive, front truck cargo drop, front vehicle parallel, forward vehicle change lane, vehicle left turn or vehicle right turn. In step 316, the subject simulates locomotive ride by the sensor 150, such as acceleration, turning, deceleration, changing direction lights, etc., and the behavior is detected by the new sensor 150, and then transmitted through the base station. 155 is transmitted to the computing device 180, and after processing and analyzing, the corresponding visual effect is transmitted to the subject through the audio-visual module 112. Specifically, the present invention differs from the prior art in that the driving behavior of the subject is mainly divided into two categories: one, the first behavior factor generated relative to the conventional situation, and, second, the first generated relative to the sudden situation. The second behavior is for further comparison calculation analysis. Next, the computing device 180 receives the first line from the subject through the transceiver module 111. After the factor and the second behavior factor, the behaviors are again generated by the comparison module 115 and the calculation module 117 to generate an accident risk score and a risk perception score (step 318).

The new behavioral perception analysis excludes car and road related factors, and mainly analyzes the behaviors such as human error, negation, and negligence factors to give corresponding scores. The behavioral awareness analysis mainly uses the first behavior factor and the second behavior factor collected by the computing device 180 to compare the reference data stored in the database 119, and then analyzes the risk by using the computing module. Scores and risk perception scores give the subject a driving risk result.

Specifically, based on the first behavioral factor, the anecdotal risk is calculated by Equation 1:

Among them, R: anecdotal risk score, R 20%

F _i : percentage of the i-th trigger driving behavior record factor, i=1, 2, 3...N

N: number of user triggers, N 0

First, the first behavior factor is an analysis relative to the conventional situation, mainly for whether the user follows the provisions of the road traffic regulations and maintains good driving behavior under normal conditions. Therefore, the database 111 of the system 100 is pre-stored. The first reference behavior, as a benchmark for the comparison analysis of the system, compares the actual driving behavior (ie, the first behavior factor) and the first reference behavior of the subject in the test, and generates corresponding first behavior data information, In the above formula, the probability of anecdotal risk is calculated. Specifically, the first behavioral factor of the method is evaluated for the following behavior categories, including but not limited to, initial behavior, braking behavior, vehicle travel behavior, and vehicle parking behavior. For example, in the judgment of the initial behavior, the method can be given according to the degree to which the vehicle starts to drive the throttle. The corresponding score, for example, as the starting throttle is driven, the percentage of the risk of anecdotes increases. Then, it is also possible to evaluate whether the subject has a viewing mirror and a start direction light when the vehicle starts moving. In addition, in the evaluation of the braking behavior, for example, the speed of the braking operation is reduced by more than 20 kilometers per second or less. In the vehicle travel behavior, it can be evaluated whether the vehicle's driving process maintains the front and rear or left and right safety distance, reverse overtaking, occupying a straight lane left turn, green light preemptive start, grab yellow light through the intersection, indecent pedestrians, talking on the phone, night When there are no headlights, traffic stops, etc., there is no left and right view, crossing the double white line and so on. The novel classifies and analyzes the various first behavior factors generated by the subject corresponding to each behavior category, and gives corresponding scores.

According to an embodiment of the present invention, the evaluation method of the present invention divides the probability of accident into three intervals (20-40%/40-70%/70-99%), which are low risk interval, medium risk interval and high risk interval respectively. And give each section a commentary to explain the probability of anecdote. .

Furthermore, the sudden situation is related to the driving behavior of the subject during the measurement, and occurs in conjunction with certain driving behaviors of the first behavior factor. In the present embodiment, the setting of the sudden situation of the present invention is based on the instantaneous speed of the vehicle on which the subject is traveling on a specific road as a reference value for inducing the sudden situation. For example, if the vehicle speed is higher than a preset value during the detection process, the computing device 180 of the present invention is configured to execute the audio-visual module 113 to generate at least one sudden situation in the virtual reality. For example, the emergency situation includes, but is not limited to, a sudden change of lane of the vehicle, a sudden opening of the door, falling of the cargo, pedestrian or dog rushing out, road area water, road obstacles, roadside vehicles starting, not paying attention to side-by-side parking, Roadside construction site, reverse locomotive, front truck cargo drop, front vehicle parallel, forward vehicle change lane, vehicle left turn or vehicle right turn. The calculation of the risk perception score is calculated based on parameters such as the reaction distance of the subject in an emergency, the speed of the driving moment, the time of releasing the throttle, and the time of pressing the brake.

In a specific embodiment, when the vehicle speed of the subject is greater than 36 km/h (ie, the instantaneous speed), a sudden situation in which the reaction distance is 40 meters is triggered; and when the vehicle speed of the subject is 10- 20 km / h, triggering the reaction time of a sudden situation with a reaction distance of 10 meters, and so on. In addition, if the instantaneous speed of the subject is less than 10 km, the sudden situation will not be triggered because the driving speed is slow.

The key to assessing the second behavioral factor is the response time of the subject to release the throttle and press the brakes in the event of an emergency, and give the corresponding score. In the method of the present invention, the transceiver module 111 is used to receive the second behavior factor generated by the sensor transmitted by the sensor 150 for the sudden situation, and then the comparison module 115 is used to compare the second behavior factor. The parameters produce a second behavioral score. Next, calculate the hazard perception score by formula 2: the risk perception score calculation formula:

Where H: risk perception score, 0 H 100

A _i : the i-th release throttle time corresponding score, i=1, 2, 3...N

B _i : the i-th pressing time corresponding to the braking time, i=1, 2, 3...N

N: total number of user triggers, N=0, 1, 2, 3, 4, 5

A%: percentage of weight lost by releasing the throttle

B%: Percentage of weight by pressing the throttle

According to an embodiment of the present invention, in order to evaluate the driver's risk perception ability, different weight ratios can be given for the throttle operation behavior, and the risk perception score of the new model is obtained by weighting calculation. number. In an embodiment, the weight of the throttle reaction time is higher than the weight of the brake reaction time. For example, the weight ratio of the throttle reaction time and the brake reaction time is 55:45, 60:40, 70:30, and 75:25; however, the present invention is not limited thereto.

In an embodiment of the present invention, when the subject is in the test, in the virtual reality of driving the vehicle, when the instantaneous speed of driving is greater than 36 kilometers per hour, the audio-visual module 113 of the computing device 180 is executed to generate a burst. In the virtual reality of vehicle driving in the detection process, the response time (T) of the subject to release the throttle is five points between 3 seconds and 4 seconds, and the reaction time (T) of the subject to press the brake is between 3 Five points are obtained from seconds to 4 seconds, and the scores are weighted to obtain a second behavioral risk perception score, that is, (5×0.6+5*0.4)*1=5.

The proposed method for assessing the driving risk of the subject can simultaneously assess the anecdotal risk and risk perception of the driving. In a non-limiting embodiment, when the user changes the lane three times in the process of being tested, the direction light is not advanced, the speeding behavior in the four-time vehicle array or the general driving, and four sudden situations, wherein The speeding behavior in a vehicle array or in general driving occurs in a specific road section and meets the starting emergency situation condition factor. At the end of the game, there are 7 accidental violations and 4 sudden situations, and the probability of detecting the accident is detected. The score percentage should be 55% (calculation 20% + 3 × 5% + 4 × 5% = 55%) and the total risk perception score should be 60 points (assuming a weight ratio of 60: 40, calculation method (60%) ×(20+10+5+15)+40%×(20+10+5+10))/4)×5=60), in which the probability of accident is caused by the driver’s driving violation during the test period. Increasingly, the risk perception score will change according to the perceived ability of the subject in the face of each sudden situation; and the percentage of the probability of shooting 55% can be interpreted as "more impulsive on the way to cycling, as a force to drive, can not Full compliance with road traffic safety rules, it is easy to cause the danger of yourself and his car to occur or increase, be cautious Italian Caution Cycling slows down. The score of 60 for the risk perception can be interpreted as "in the face of a dangerous emergency, your perceived reaction time is just right, you can identify the danger and take appropriate measures."

In an embodiment, the method of the present invention can set the normal situation and/or the number of occurrences of the sudden situation and the location of the occurrence in the virtual reality video of the vehicle through a context control module (not shown). For example, in a single detection unit of the new driving risk test (ie, a test process of about 10 minutes), at most five burst situations are generated in the vehicle driving virtual reality. Those of ordinary skill in the art should be able to understand the number and frequency of sudden situation settings, which can be adjusted according to actual needs. In addition, the system 100 of the present invention can also generate different emergencies in different sections and/or regions in the virtual reality of the test process, and the settings can be performed by executing the novel context control module. For example, at a road turn, set a sudden change of lanes or emergency braking in front of the vehicle.

FIG. 4 is a partial flow chart of driving risk assessment according to an embodiment of the present invention. The flow of the new driving risk assessment is in principle the same as in the third figure, so the same step flow will not be repeated here. It should be noted that the driving risk assessment method of the present invention may further include generating a warning message to the audio and video device through the audio and video module. For example, based on the dynamic calculation results of the new system in the process under test, it is possible to know the driving behavior of the subject during the test, if the subject violates the road traffic safety condition (ie, the first behavior factor) As a result, the risk of accidents increases, and the probability of a traffic accident is high. Therefore, the new system can generate a warning message to the subject. If there is no improvement, the probability of an accident is increased, and the detection can be directly interrupted.

Specifically, please refer to FIG. 4, which is the same as the calculation of the above-mentioned anecdotal risk score, based on the first behavioral factor of the subject, through the comparison analysis, to generate the probability of the anecdotal risk. In steps 420 to 424, when the subject's driving behavior is improper and/or the traffic rules are violated, the risk of the accident is raised to a preset value. At present, the risk assessment method of the present invention utilizes the audio-visual module 113 to provide a warning information to the subject to pay attention to his driving behavior, and teach the subject to correct driving behavior from the test. In a non-limiting embodiment, the method may further include a plurality of anecdotal risk presets. In an embodiment, the default risk of the incident risk is 10-99%, such as 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99% . In a preferred embodiment, the default risk of the incident is 20%, 40%, 70%, 99%. For example, when the risk probability of the accident is higher than 30%, the computing device 180 of the system 100 transmits an alert message to the audio-visual device 108, for example, a red-light picture appears on the vehicle driving virtual reality screen. Then, when the risk of accidents is higher than 50%, or even 70%, as the risk of anecdotes increases, the frequency of the red picture or its color depth can be increased. Finally, when the risk of the incident is higher than 90%, the computing device 180 of the system 100 generates an interruption detection screen (for example, a car accident) through the audio-visual module 113 to the audio-visual device 108, and interrupts the detection by the subject.

In contrast, in steps 430 to 432, if the driving behavior of the subject is good after the detection process, the probability of the risk of the accident is kept constant after the analysis of the system 100, that is, the probability of the accident is lower than the preset value. At the time, the test is continued.

FIG. 5 is a partial flow chart of evaluating driving risk assessment according to another embodiment of the present invention. In addition to using the technical means of providing warning information or interrupt detection as shown in Fig. 4, the novel method teaches the subject to perform good driving behavior. After the end of this new test, the method includes the use of a recording module (not shown) records the vehicle traveling condition of the subject in the driving virtual reality of the vehicle to generate a recorded video and audio; and then, through the audio-visual device by using a teaching module (not shown) 108 Play recorded audio and video for the subject to view their driving behavior.

Specifically, as shown in steps 550-552 of the figure, the teaching module of the present invention is configured to display a list of unqualified behaviors to the subject through the audio-visual device 108, so that the subject is informed of the process under test. Improper driving behavior. For example, the list of failed behaviors shown includes a name that indicates improper driving behavior (eg, slowing down, crossing a double yellow line, etc.), and the corresponding location at which it occurred.

Moreover, the subject can view the entire and/or part of the unqualified behavior by clicking on the sensor 150 (step 554), that is, the novel teaching module is executed to play the subject through the audio-visual device 108. Recording audio and video corresponding to the selected specific behavior to the subject. The list of non-conforming behaviors is generated based on the first behavior and/or the second behavior by the comparison module 115. Those of ordinary skill in the art should understand that the categories of behavior can be categorized to indicate that some of the specific behaviors are unqualified (ie, dangerous behaviors).

Moreover, the method of the present invention can also display a bird's-eye view map to the user via the audio-visual module 113 via the audio-visual module 113 (step 556). In a preferred embodiment, the bird's-eye view map indicates the subject's driving trajectory (ie, the path of travel) and the location at which the failed behavior occurs. The location where the non-conformity behavior occurs is a scene where a violation behavior and/or improper driving (ie, a first behavior factor) occurs, and the subject can select a specific behavior point to view the unqualified behavior by the sensor 150. . Or, the location where the unqualified behavior occurs is where the sudden situation induces the second behavior to occur. In addition, in another embodiment, the method of the present invention may further comprise the process of using the teaching module to record the unqualified behavior in recording audio and video, and simultaneously telling the normal driving behavior information to the subject.

In addition, the above-mentioned unqualified behavior is merely an example, and the method of the present invention also covers the first behavior and/or the second behavior when the virtual reality video is driven by the teaching module, so that the subject can repeatedly watch the individual. Complete driving behavior.

In addition, the new method includes data exchange with a third-party server, subsequent big data analysis and statistics, calculation of traffic accident probability and risk perception capability, continuous training of the system, and optimization of the anecdotal risk performed by the system. evaluation method.

As can be imagined, another aspect of the present invention relates to a computer storable medium (eg, a program module). The computer storable medium has computer readable instructions stored thereon, and when executed, the instructions can be used to perform the method for assessing driving risk as described in the various aspects/embodiments of the present invention. Taking a program module as an example, the computing device, the sensor, and/or the audio-visual device for performing the method separately store one or all of the program modules to cooperate to complete the evaluation driving risk. method. Alternatively, one or all of the program modules may be stored in a device or location other than one or more of the computing device, the sensor, and/or the audiovisual device, and through appropriate transmission mechanisms (eg, communication components) when needed. ) transmitted to the devices/components.

In another aspect, an aspect of the present invention is directed to a system for performing the above-described method of dynamically assessing driving risk. For example, the system can include an arithmetic device, a sensor, and a video device. In some embodiments, the system further includes a third party server in communication with the computing device. The structure and function of the various devices/elements included in the system are as described above.

In summary, the method for estimating driving risk and the system for implementing the method proposed by the present invention integrate the virtual reality technology and the calculation method proposed by the present invention, and can effectively estimate the subject may have an accident in the actual road. risks of. Using the results obtained by this new model, in addition to being tested In addition to the reference, the method or system can be used to improve driving driving attitudes and behaviors, and to effectively grasp the driving skills.

The specific embodiments of the present invention are disclosed in the above embodiments, and are not intended to limit the present invention. Those of ordinary skill in the art to which the present invention pertains, without departing from the spirit and scope of the present invention, Various changes and modifications may be made thereto, and the scope of protection of the present invention is defined by the scope of the accompanying claims.

100‧‧‧ Driving Risk Assessment System

108‧‧‧ head-mounted audio and video equipment

150‧‧‧ sensor

155‧‧‧Base station

180‧‧‧ arithmetic device

Claims (13)

A driving risk assessment system for assessing a driver's driving risk includes: a head-mounted audio-visual device; and a video-audio module communicatively coupled with the head-mounted audio-visual device for driving a vehicle to virtual reality Video and audio are provided to the subject by the head-mounted audio-visual device to place the subject in a vehicle driving virtual reality, wherein the vehicle driving virtual reality includes at least one conventional situation and/or at least one burst a sensor, in communication with the audio-visual module, for receiving at least a first behavior factor and/or the emergency situation generated by the subject in a virtual reality of the vehicle driving relative to a normal situation Generating at least a second behavior factor; and a computing module communicatively coupled to the sensor and the head-mounted audio-visual device for generating an anecdotal risk score and/or the second behavior based on the first behavior factor The factor produces a risk perception score. The system of claim 1, wherein the first behavioral factor is selected from the group consisting of: an initial behavior, a braking behavior, a vehicle traveling behavior, and a vehicle parking behavior. The system of claim 1, wherein the computing module generates the anecdotal risk score by comparing the first behavior factor with a first reference behavior. The system of claim 1, wherein the computing module generates the risk perception score based on a reaction distance, an instantaneous speed, and/or a reaction time corresponding to the second behavior factor. The system of claim 4, wherein the reaction time comprises a release throttle reaction time and a brake reaction time. The system of claim 5, wherein the release throttle reaction time and the brake reaction time are calculated by weighting to obtain the risk perception score. The system of claim 6, wherein the weight of the throttle response time is higher than the brake reaction time. The system of claim 7, wherein the ratio of the throttle throttle reaction time to the brake reaction time is 6:4. The system of claim 1, further comprising a context control module in communication with the audio-visual module, wherein the context control module is configured to set the normal situation and/or the emergency situation in the vehicle driving virtual reality The number of occurrences in . The system of claim 1, wherein the occurrence of the sudden situation is based on an instantaneous speed of the subject traveling on the road in the virtual reality of driving the vehicle. The system of claim 1, further comprising a recording module and a teaching module, wherein the recording module is configured to communicate with the computing module and/or the audio and video module, wherein the recording module is configured to record the subject in the vehicle Driving the travel condition in the virtual reality to generate a recorded audio and video; and the teaching module plays the recorded video and audio through the head-mounted audio-visual device for the subject to view. The system of claim 11, wherein the audio-visual module is operable to generate a bird's-eye view map and display the first behavior and/or the location at which the second behavior occurs on the bird's-eye view map. The system of claim 12, further comprising a teaching module communicatively coupled to the audio-visual module, and the teaching module is configured to record the first behavior and/or the second behavior in the recorded audio and video , showing a message of normal driving behavior.