KR102816596B1 - Methods for providing risk-minimizing behavior considering traffic and vehicle and road systems supporting the same method - Google Patents

Abstract

The present invention relates to a system supporting a risk minimization operation, and the present invention preferably includes the steps of: obtaining status information of a vehicle in which an abnormality has occurred during driving and traffic information on a road on which the vehicle is driving; calculating lane information of the road; and providing stopping location information at which the vehicle can stop according to the calculated road information and status information. According to various embodiments of the present invention, a safe zone considering the characteristics of the road is provided to an autonomous vehicle, thereby enabling safe stopping in an emergency situation (fallback).

Description

{Methods for providing risk-minimizing behavior considering traffic and vehicle and road systems supporting the same method}

The present invention relates to a system supporting risk minimization operations.

Autonomous vehicles, which have been actively developed recently, are receiving attention not only for the convenience of driving but also as a fundamental alternative for solving various traffic problems in modern society. Accordingly, not only existing automakers or auto parts manufacturers but also various IT companies are actively conducting research and development to commercialize autonomous driving technology based on improved communication and computing technologies.

These autonomous driving systems control steering, acceleration, and deceleration for lane changes along the route, assuming driving within the lane to safely reach the destination within road regulations.

According to the Society of Automotive Engineers (SAE), autonomous vehicles can be classified from Level 0 (Advanced Driver Assistance System) to Level 5 (Automatic Driving System) and Level 3 (Level 5). Autonomous driving systems that do not require driver assistance are classified as Level 3 or higher. Level 3 systems require an emergency response user (FRU, Fallback-Ready User) to respond in emergency situations, while Level 4 or higher systems require the autonomous driving system to be able to respond (fallback) on its own even in the event of an emergency such as a breakdown. Here, the autonomous driving system's response means that in the event of a breakdown, it must perform Minimal Risk Maneuvers (MRM) by itself in the Minimum Risk Condition (MRC) or parking/stopping state.

However, even if MRM should operate or FRU responds, there is a limit to confirming the safety zone based on the vehicle's perception sensor in an emergency situation such as a breakdown/failure. The perception sensor may have malfunctioned, and even if it operates normally, the safety zone may be blocked by surrounding obstacles. For example, in a four-lane road, when the vehicle is located in the first lane, it may be difficult to accurately determine the shoulder situation due to surrounding traffic flow, and there is a need to propose a specific vehicle response method for such situations.

Therefore, the present invention aims to solve the above-described problem.

One of the various tasks of the present invention is to provide a method for providing a vehicle with a safe stopping zone based on vehicle sensors on the road when an accident or emergency occurs.

In addition, one of the various tasks of the present invention is to provide a criterion for determining a method of providing a safety zone based on the traffic conditions of a road on which a vehicle is driving.

In order to solve the problem of the present invention, in various embodiments, a method for providing guidance information for a risk minimization operation based on lane recognition is preferably provided, comprising: a step of obtaining status information of a vehicle in which an abnormal condition has occurred while driving and traffic volume information of a road on which the vehicle is driving; a step of calculating lane information of the road; and a step of providing the vehicle with stopping location information at which the vehicle can stop according to the calculated road information and status information.

It is preferable that the above stopping location information is location information on a road including the driving road or on the shoulder of a road on the road.

It is desirable that the above stopping location information be determined by considering the traffic volume on the road.

It is preferable that the above stopping location information be determined based on lane information of the road on which other vehicles are driving included in the traffic volume of the road.

It is preferable that the step of calculating the lane information calculates the lane information of the road on which the vehicle is driving based on the markings already installed on the road.

It is preferable that the step of calculating the lane information calculates the lane information according to the longitudinal position of the road on which the vehicle is driving based on the left or right markings already installed on the road.

In order to solve the problem of the present invention, a guidance information providing server for lane recognition-based risk minimization operation as various embodiments includes: a processor; a memory for loading a computer program executed by the processor; and a storage for storing the computer program, wherein the computer program includes an operation for obtaining status information of a vehicle in which an abnormality has occurred while driving and traffic volume information of a road on which the vehicle is driving, an operation for calculating lane information of the road, and an operation for providing the vehicle with stopping location information at which the vehicle can stop based on the calculated road information and status information.

The features of each of the above-described embodiments may be implemented in combination in other embodiments as long as they are not contradictory or exclusive to other embodiments.

According to various embodiments of the present invention, a safe zone that takes into account the characteristics of a driving road is provided to an autonomous vehicle, thereby enabling a safe stop in an emergency situation (fallback).

The present invention aims at providing a vehicle with a safe stopping zone by utilizing a vehicle sensor in the event of an accident or emergency. The present invention has the effect of significantly improving road safety.

In addition, the present invention provides a criterion for determining a method of providing a safety zone based on the traffic conditions of a road on which a vehicle is driving, thereby enabling a quick and efficient response in the event of a traffic accident.

The present invention enables better response to road conditions and actively ensures the safety of drivers and other road users in the event of an accident.

The effects of the present invention are not limited to those described above, and other effects not mentioned will be clearly recognized by those skilled in the art from the description below.

Figure 1 is a conceptual diagram illustrating a system that provides a safety zone provision service according to one embodiment of the present invention.
FIG. 2 is a flowchart for explaining a method for providing a safety zone according to one embodiment of the present invention.
Figures 3 to 7 are exemplary diagrams illustrating a safety zone provision scenario according to one embodiment of the present invention.
FIG. 8 is a block diagram illustrating a server providing a method for providing a safe zone according to one embodiment of the present invention.

Hereinafter, specific embodiments of the present invention will be described with reference to the drawings. The following detailed description is provided to help a comprehensive understanding of the methods, devices, and/or systems described herein. However, this is only an example and the present invention is not limited thereto.

In describing embodiments of the present invention, if it is judged that a detailed description of a known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description will be omitted. In addition, the terms described below are terms defined in consideration of their functions in the present invention, and may vary depending on the intention or custom of the user or operator. Therefore, the definitions should be made based on the contents throughout this specification. The terms used in the detailed description are only for describing embodiments of the present invention, and should never be limited. Unless clearly used otherwise, the singular form includes the plural form. In this description, expressions such as "comprises" or "comprising" are intended to indicate certain features, numbers, steps, operations, elements, parts or combinations thereof, and should not be construed to exclude the presence or possibility of one or more other features, numbers, steps, operations, elements, parts or combinations thereof other than those described.

FIG. 1 is a conceptual diagram illustrating a system supporting risk minimization operations according to one embodiment of the present invention.

The following description is made with reference to FIG. 1. A system supporting a risk minimization operation according to one embodiment of the present invention may include a server (300) that communicates with a vehicle (200) and transmits and receives data.

The server (300) collects and stores information transmitted by clients (vehicles (200), users, etc.) capable of network communication based on the cloud, and can provide stored information or additionally provide results according to information processing at the request of the client.

In this embodiment, the server (300) can collect current vehicle status information and provide a series of information necessary for driving the vehicle by communicating with various control devices installed in the vehicle (200) as a client, and for example, can generate and provide control information according to the situation and condition of a specific road.

The current cloud environment is gradually expanding its flexibility by incorporating virtualization technology from the past physical server (300)-based operation method, so it is not limited to a specific server (300) and can be diversified depending on the network implementation method.

The system of this embodiment provides convenience to drivers by utilizing various information and communication technologies such as a telematics system. As communication technologies, cellular (4G, LTE, etc.), WAVE (Wireless Access in Vehicular Environment), and mobile communication-based vehicle/things communication (C-V2X) methods can be utilized.

C-V2X is a vehicle communication technology that allows vehicles to exchange information with other vehicles, traffic vehicle sensors, pedestrians, networks, etc. via cellular mobile communication networks such as LTE and 5G. It combines mobile communication technology with existing V2X that relies on cameras, radar, and vehicle sensors to recognize the surrounding environment, enabling real-time communication with other vehicles and vehicle sensors to recognize unexpected situations.

Through these communication technologies, vehicle-to-vehicle (V2V) communication or vehicle-to-roadside unit (RSU) communication (V2I: Vehicle to Infrastructure) is possible, and in the case of this embodiment, data that is continuously updated and stored in the server (300) can be provided to the vehicle through the above-described communication technologies.

That is, instead of communicating directly with a vehicle, the server (300) communicates with a roadside device (400) installed at a point on the road to increase accessibility and can collect and provide more accurate information about a moving vehicle.

In addition, the server (300) can communicate with various road facilities, for example, signboards (500), and provide safety zone information according to the present embodiment.

In this embodiment, the target vehicle (200) that receives information from the server (300) may be a manually driven vehicle including an advanced driver assistance system (ADAS) or a vehicle capable of driving in which various sensors mounted on the vehicle for autonomous driving are operating normally and, in particular, a device for steering the vehicle is operating normally.

The vehicle (200) is not limited to a vehicle in perfect normal running condition with no physical malfunction elements, and includes a vehicle that causes an emergency stop due to a malfunction that relatively affects autonomous driving or driver driving.

Specifically, a vehicle (200) in which a breakdown has occurred may refer to a vehicle (200) in which some of the various sensors mounted on the vehicle for autonomous driving are operating abnormally, or an emergency situation has occurred in which a device for acceleration or steering of the vehicle is operating abnormally.

At this time, the vehicle (200) may mean a vehicle that requires control according to MRM (Minimal Risk Maneuver) to transition to MRC (Minimal Risk Condition) state due to a failure (Fallback) in some of the components of the autonomous driving or driving control system.

In this case, the vehicle (200) can receive information on a safe zone where emergency parking/stopping is possible from the server (300) depending on the condition of the vehicle and drive toward the safe zone through autonomous driving or manual driving. When the server (300) receives a request for a safe zone from the vehicle (200), it can extract an optimal safe zone from among a plurality of previously stored safe zones through the method described below and provide it to the vehicle (200).

The above-mentioned safe zone refers to a parking area, a space where parking is permitted in accordance with traffic laws, and can refer to an area where parking of vehicles is permitted away from the main road, such as a road shoulder, rest area, or rest stop, or a stopping area, such as a shoulder, where normal vehicle driving is prohibited, but stopping/parking is permitted only in unavoidable cases, such as in the case of a breakdown.

A request for a safe zone may be requested by an emergency response unit (FRU) or by the autonomous driving system.

A request from a Fallback Ready User (FRU) may mean that a passenger or driver, or other FRU, requests a search for a safe zone when an emergency parking/stop is required due to a breakdown that occurs during manual driving or passenger violence during autonomous driving.

A request from an autonomous driving system may mean that, when the driver's control of the vehicle is transferred to the autonomous driving system, the system may request a search for a safe zone at its discretion.

Additionally, the request and provision of a safe zone can also be performed by other vehicles (200') around the vehicle (200) or surrounding vehicle sensors such as roadside devices (400). For example, in the case of a temporary communication failure or failure of the vehicle (200), surrounding vehicles can confirm abnormal driving and transmit this to the server (300) and request a safe zone. The safe zone can be transmitted to the vehicle (200) later through V2V communication.

The suitability for a safe zone is calculated using the distance between the vehicle (200) and the safe zone, the number of lane changes according to lane information, the traffic volume, and the difficulty of driving. A lower suitability score has a higher priority, and the server (300) guides the vehicle (200) to drive to the most optimal safe zone.

In addition, when a vehicle (200) has a breakdown that makes it difficult to change lanes, or when manual driving by the driver is not possible in a breakdown situation, the vehicle can perform a stop in the driving lane or a stop in an adjacent lane as a risk minimization action.

Or, if the current state of the vehicle (200) is such that a lane change is possible, the risk of traffic congestion or secondary accidents can be minimized by providing safety zone information so that the vehicle can stop on the road shoulder by changing lanes.

The server (300) can update information on whether a safe zone is used by collecting data while the vehicle (200) is driving.

The server (300) continuously updates the availability of a predefined safe zone, and when a vehicle (200) requests safe zone information, provides an optimal safe zone candidate group for the vehicle (200) based on the information, and at the same time provides information such as the vehicle's (200) stopping location, route, and breakdown status to service users around the vehicle (200), and can also provide signals for controlling the overall traffic flow to surrounding vehicles.

In this embodiment, the server (300) can also perform control that takes into account the overall road situation along with individual driving guidance of the above target vehicles.

For example, the server (300) can receive vehicle status information and assign driving lanes to each vehicle to alleviate traffic congestion caused by increased traffic volume.

The vehicle (200) can perform a risk minimization operation to minimize the risk due to a breakdown, and can stop in a safe zone depending on the type of risk minimization operation.

Hereinafter, a method for setting a specific stopping area on the shoulder of a road as a safe zone that can minimize risk by using a server (300) according to this embodiment will be described with reference to the drawings.

Referring to FIG. 2, FIG. 2 is a flowchart for explaining a method for providing status information of a safety zone providing system according to one embodiment of the present invention.

First, the server (300) obtains status information of vehicles on the road and traffic volume information on the road on which the vehicles are driving in order to provide a safe zone (S100).

For example, the server (300) can receive status information directly from a vehicle via a network or can collect information collected by a roadside device (400) via a network.

Status information is information related to the current driving of the vehicle, and can be a series of information such as the current location, vehicle speed, whether it is autonomous driving, and whether a breakdown has occurred.

Or, it may include information related to vehicle control, such as more detailed vehicle control status and vehicle specifications.

For example, information about the vehicle being received may include information about the controllability of the lateral direction (Lateral Control), the powertrain for deceleration and acceleration, and the controllability of the brakes based on the driving direction as an operable module among various modules for autonomous driving.

Additionally, the server (300) can obtain traffic volume information on the driving road.

Based on traffic density and traffic volume information on the road on which you wish to change lanes, you can calculate whether lanes can be changed, the time required to change lanes, and the distance required to change lanes.

For example, the traffic density on the lane to be changed can be obtained through a sensor inside the vehicle or a roadside device (400).

Alternatively, it can be determined based on V2X information provided by surrounding vehicles (200') (such as BSM information providing location/speed of each vehicle).

BSM (Basic Safety Message) information is a key data element that provides key information related to the vehicle. This information is mainly used as part of the V2X (Vehicle-to-Everything) communication system and can play a key role in autonomous vehicles and modern traffic management systems. BSM provides the exact location of the vehicle. It can be used to identify the current location of the vehicle through GPS coordinates and to determine the relative location to surrounding vehicles and infrastructure.

In addition, the current speed information of the vehicle can also be transmitted through the BSM. In addition, the direction of movement and heading (azimuth) information of the vehicle can also be included. The acceleration information of the vehicle is used to detect sudden acceleration or sudden deceleration situations, and information about the size and shape of the vehicle (e.g. sedan, SUV, truck, etc.) can also be included in the BSM.

For example, traffic density can be indirectly assessed by comparing the speed of surrounding vehicles to the speed limit.

The following server calculates lane information on the road on which the vehicle is driving (S200).

In this embodiment, lane information may be information defining which lane the vehicle is currently driving on among the driving roads.

Lane information can be derived based on lanes acquired through sensors mounted on the vehicle, such as camera sensors.

Referring to Fig. 3, a camera that collects images of the left and right areas (210) of a vehicle (200) is used to detect lanes in the image, and based on the detected lanes, it is determined in which lane the vehicle is ultimately located.

Lane recognition information is efficiently classified through a lane information classification method based on sensors and cameras mounted on a vehicle (200). For example, the camera can obtain information on its own lane and adjacent lanes, or information on two lanes adjacent to its own lane. Based on the obtained information, the vehicle (200) classifies lane recognition information into three categories.

Lane recognition information can be classified into 1) adjacent lane, 2) adjacent lane one lane across, 3) third lane or more, and if the camera or the autonomous vehicle's onboard sensors can only recognize adjacent lanes, the system can also classify only adjacent lanes and lanes one lane across or more.

In this embodiment, when driving on the right side of the road based on the direction of travel, information on the right lane in particular can play an important role in this decision.

Technically, the vehicle (200) can receive an image acquired from a camera and detect one or more lane markings as objects within the image and a lane pattern and lane color of each lane marking.

The vehicle (200) can also calculate lane information based on the classification result (L, R) of left or right and calculate the number of lane changes to reach the road shoulder.

However, in some cases, when it is difficult for a lane to obtain information on all driving lanes on the road, it is possible to obtain lane information by linking with an external source.

In other words, a vehicle can obtain lane information by receiving external information in addition to the vehicle's own sensing results.

Referring to Fig. 4, a vehicle can obtain lane information based on location information based on V2I (Vehicle-to-Infrastructure) through communication with external infrastructure.

For example, a vehicle can provide its current location sensed through GPS or other means to an external infrastructure, and can also calculate lane information based on the sensing information relative to the total number of lanes on the road corresponding to the location.

Or, the location of a vehicle (200) in motion can be accurately identified through a server (300) roadside device (400), and based on this location information, the number of lanes (L, R) remaining on the left and right sides of the vehicle (200) can be identified and transmitted to the vehicle (200) through V2I (Vehicle-to-Infrastructure) communication.

The vehicle (200) can use the transmitted information to calculate the number of lanes remaining to the shoulder of the road, the number of lane changes required, and the distance and time it will take to stop at the side of the road after a lane change.

Alternatively, it is possible to directly derive lane information based on the location of a vehicle requested directly from an external infrastructure and provide the derived lane information to the vehicle.

Furthermore, referring to FIG. 5, the vehicle (200) can derive lane information based on external installed fixed facilities, for example, roadside sign facilities (34-1, 34-2).

Road facilities such as a median strip, guardrail, and delineator can indicate the left and right end locations of a road. A vehicle (200) can accurately determine the location of the lane in which it is driving by utilizing these facilities. For example, the location of a median strip can indicate the center of a road or the end of a right lane, and a guardrail can indicate the location of a lane adjacent to the edge of a road or a shoulder.

The vehicle (200) estimates the current lane position by measuring the distance between the vehicle and road sign facilities using sensors such as mounted cameras, radars, and lidars. These sensors provide high-resolution data on the surrounding environment and collect visual information necessary to identify lines, signs, and other facilities on the road surface.

In addition, traffic safety facilities and road facilities can be used to estimate lane positions. These facilities can clearly identify major road structures such as the beginning and end of lanes, intersection locations, and lane change points, thereby enabling the calculation of vehicle driving lane information.

The above vehicle (200) can estimate the current location of the vehicle based on the sensed road marking facilities and calculate lane information based on the sensing information compared to the total number of driving lanes based on the location.

At this time, the lane information of the driving road may include the number of right lanes located on the right based on the direction of travel.

In this embodiment, control for stopping in a safe zone can be performed depending on the condition of the vehicle, so for example, in a country where right-hand traffic is the standard, stopping can be performed on the shoulder of the road located on the right side of the road.

Therefore, the number of right lanes located on the right side based on the direction of travel of the vehicle can be obtained as lane information.

Conversely, in countries where left-hand traffic is the standard, the lane information of a driving road may also include the number of left lanes located on the left side based on the direction of travel.

Alternatively, in a city driving situation, not a highway, for example, in a one-way traffic situation, it is possible to obtain the value including the number of left lanes, as stopping on the left is also possible in countries where right-hand traffic is the standard.

Additionally, the server (300) can also use surrounding vehicles to obtain the above-described lane information depending on traffic conditions.

When the number of surrounding vehicles increases depending on traffic conditions, it may be difficult to accurately recognize lane information on the current driving road of the vehicle (200) using a camera.

Referring to FIG. 6, when the camera view of the vehicle (200) is obstructed by another vehicle (200') located in the lane next to the right area (210), it is also possible to additionally calculate lane number information through another vehicle (200') in the lane next to it recognized by the camera.

For example, if another vehicle (20'0) located in the right lane has accurate lane information, the other vehicle (200') can share the lane information with the vehicles (200) using V2V (Vehicle-to-Vehicle) communication. This can be particularly useful when information provided from the infrastructure center or edge is insufficient or inaccurate. For example, if another vehicle (200') in the vicinity has information about a lane that is temporarily closed due to road construction, the other vehicle (200') can transmit this information to the vehicle (200) via V2V. This can allow the vehicle (200) to establish a more accurate lane change plan, which can contribute to overall road safety and efficient traffic flow.

Specifically, referring to FIG. 7, the vehicle (200) can identify another vehicle (200') that is the cause of the obscured area and estimate the current vehicle's lane number information (R=R'+1) based on the lane number information (R') recognized by the vehicle through V2V communication with the vehicle.

The next server (300) provides the vehicle with information on a possible stopping location (S300).

The stopping location information may be a potential stopping area, which is an area within the road that defines a safe zone where lane recognition and lane changes are possible through sensors.

In addition to the vehicle directly detecting the stop location information, the communication module can also operate to receive the stop location information from an external source, preferably a server (300) according to the present invention or a vehicle sensor.

Specifically, the stopping location information can be determined according to the type of risk minimization action.

In this embodiment, the type of risk minimization maneuver (MRM (Minimal Risk Maneuver) type) can be determined by identifying internal environmental factors such as a failure state of autonomous driving or the severity of a failure state, or external environmental factors such as a safe zone situation.

MRM types can be categorized according to stopping situations, and in the case of traffic lane stops, they can be categorized into straight stop, in-lane stop, and adjacent lane stop.

Straight-line stop means that the vehicle (10) is stopped by braking in the direction in which it is currently traveling, which is the most urgent or serious situation in which a breakdown is occurring. Therefore, lateral steering (lateral control), acceleration control, and lane change control are not required, and deceleration control for braking is performed.

Stopping in a lane means that the vehicle (10) stops while braking is performed in the direction of maintaining the lane in which the vehicle (10) is currently driving. Therefore, acceleration control and lane change control are not necessary, and lateral steering to maintain the lane and deceleration control for braking are performed.

Adjacent lane stop means that the vehicle (10) moves from the lane in which the vehicle (10) is currently driving to another safer lane and performs braking to stop the vehicle (10). In adjacent lane stop, acceleration control for leaving the current lane, lane change control for moving to another lane, lateral steering for moving to and maintaining the lane, and deceleration control for braking are performed.

In addition to this, a stop type can be distinguished in which a safe zone is available by searching for it through an external server (300) or a road side unit (RSU) under the condition of detecting a safe zone.

It can be divided into road shoulder stop and parking lane stop for stopping in a safe road shoulder or parking/stopping area.

In this embodiment, the server (300) can provide a specific location of the shoulder of the road to a vehicle capable of stopping on the shoulder of the road based on the lane information obtained as the stopping location information.

In the case of shoulder stops, if the shoulder of the road is as wide as the road (lane), for example, if it is more than 2m, it can be categorized as a full-shoulder stop, otherwise it can be categorized as a half-shoulder stop.

The above-determined MRM type can be dynamically changed according to changes in the internal and external environments, and the MRM operation is executed according to the determined type. When the vehicle (10) stops in the final determined type, the vehicle (10) at that time becomes a MRC (Minimal Risk Condition) in which the risk is minimized.

Specifically, in this embodiment, the stopping location information on the shoulder of the road can be determined based on the necessity and possibility of changing lanes by considering the number of lanes on the driving road.

First, the stop location information can be determined by considering the distance the vehicle can drive based on the current speed and the stopping time according to the longitudinal movement required to stop based on the received status information.

At this time, the stopping time can consider the lane change time according to the lateral driving according to the number of lane changes to reach the road shoulder based on the acquired lane information.

That is, the final stopping location information is determined by considering the stopping time, which is calculated by taking into account the stopping time in the longitudinal direction and the time required for changing lanes in the lateral direction.

At this time, in this embodiment, the stop location information can further determine the traffic volume of the road area.

Self-driving cars can cause traffic congestion by making abnormal lane changes to stop on the shoulder of a road even when they are in a breakdown state.

Therefore, the server (300) can determine a safe zone through the current traffic situation.

For example, when traffic congestion is light, it is relatively easy to change lanes, but when traffic congestion is heavy, as in Fig. 5, it is difficult to change lanes. Therefore, when traffic congestion is light, it is possible to determine a nearby safe zone, but when traffic congestion is heavy, it is also possible to determine a safe zone far away so that you can go straight and then stop.

At this time, the traffic situation can be calculated as a relative grade through the speed of vehicles and traffic density, and the server (300) can determine the final stopping location information by reflecting the grade of the traffic situation as a weight in the stopping time synthesized by the time required for stopping in the longitudinal direction and the time according to the distance for changing lanes in the lateral direction.

Longitudinal time can be calculated as the time taken to stop at an approximate deceleration rate (e.g. 0.5 m/s2) corresponding to natural deceleration such as engine braking, based on the current vehicle speed, for example.

Additionally, the lateral movement speed for the vehicle to change lanes can be set to, for example, below a threshold speed. The threshold speed allows the lane change time to be sufficiently long so that surrounding vehicles can recognize the lane change and avoid collisions.

In addition, the vehicle may limit lane changes when the vehicle in front is expected to stop or decelerate rapidly to avoid collisions with the vehicles in front and behind during lane changes, and may use turn signals to indicate its intention to change lanes to maintain a safe distance from the vehicle behind, providing sufficient time for the vehicle behind to recognize and react. Considering the reaction time until the vehicle behind begins to decelerate, the vehicle may initiate deceleration and lane changes after the reaction time.

The next server (300) calculates the stopping time required with traffic volume information applied as a weight and possible candidate stopping points within a certain distance ahead of the vehicle's current location.

For example, the server (300) can calculate the closest location as the first stopping location information. The goal is for the vehicle to stop at the closest location to its current location, which is useful in situations where response time is important, and may be preferred when the vehicle needs to stop quickly. However, there is a risk that the surrounding environment's risk factors may not be sufficiently considered, and a less safe stopping point may be selected.

The server (300) determines a safe zone based on the width of the road shoulder determined in comparison with the design speed in the stopping location information, and can provide a safe zone ahead of the minimum critical distance when the current driving speed of the vehicle is the design speed as the stopping location information.

According to various embodiments of the present invention, a safe zone that takes into account the characteristics of a driving road can be provided to an autonomous vehicle, thereby enabling safe stopping in an emergency situation (fallback).

Below, the configuration of the server (300) according to the present embodiment will be described with reference to FIG. 8.

The server (300) according to some embodiments of the present invention may be implemented in the form of a computing device. For example, at least one of each module constituting the authentication server (300) may be implemented on a general-purpose computing processor and thus may include a processor (308), an input/output I/O (302), a memory device (304), an interface (306), a storage (312), and a bus (314). The processor (308), the input/output I/O (302), the memory device (304), the storage (312), and/or the interface (306) may be coupled to each other via the bus (314). The bus (314) corresponds to a path through which data is moved.

Specifically, the processor (308) may include at least one of a CPU (Central Processing Unit), an MPU (Micro Processor Unit), an MCU (Micro Controller Unit), a GPU (Graphics Processing Unit), a microprocessor, a digital signal processor, a microcontroller, an application processor (AP), and logic devices capable of performing functions similar thereto.

The input/output I/O device (302) may include at least one of a keypad, a keyboard, a touchscreen, and a display device. The memory device (304) may store data and/or programs, etc.

The interface (306) may perform a function of transmitting data to or receiving data from a communication network. The interface (306) may be wired or wireless. For example, the interface (1040) may include an antenna or a wired/wireless transceiver, etc. Although not shown, the memory device (304) may further include a high-speed DRAM and/or SRAM, etc. as an operating memory for improving the operation of the processor (308).

The internal storage (312) stores programming and data configurations that provide the functionality of some or all of the modules described herein. For example, it may include logic to perform selected aspects of the fraud detection condition setting and detection methods described above.

The memory device (304) loads a program or application with a set of instructions including each step of performing the above-described fraud detection method stored in the storage (312) and enables the processor to perform each step.

Furthermore, although not shown, the roadside device (400) may be implemented as a computing device including a processor that performs the operations described above.

According to the present invention, according to various embodiments of the present invention, a safe zone considering the characteristics of a driving road is provided to an autonomous vehicle, thereby enabling safe stopping in a fallback situation. In addition, when a breakdown situation occurs, risk can be minimized by providing information on a shoulder of a road where stopping is possible based on a vehicle sensor on the road. In addition, the present invention can prevent secondary accidents by sharing guidance information on a safe zone based on a vehicle sensor. In addition, the present invention can continuously update and provide safe zone information at a transmission cycle according to the speed of the vehicle, thereby enhancing stability.

Although various embodiments of the present invention have been described in detail above, those skilled in the art will understand that various modifications can be made to the above-described embodiments without departing from the scope of the present invention. Therefore, the scope of the rights of the present invention should not be limited to the described embodiments, but should be determined not only by the claims described below but also by equivalents of the claims.

Claims (12)

In a method for providing guidance information for risk minimization operation based on lane recognition,
A step for obtaining status information of a vehicle in which an abnormal condition occurs while driving and traffic volume information on a road on which the vehicle is driving;
A step of calculating lane information of the above driving road; and
Including a step of providing a vehicle with stop location information based on the above-mentioned generated road information and status information,
The steps for producing information by the above method are:
The number of lanes of the vehicle is calculated by using the distance between the vehicle and the roadside sign facility located on the left or right side based on the direction of travel of the road.
The step of providing the above stopping location information is:
Using the number of lanes calculated above, the number of lane changes until stopping at the location according to the stopping location information is provided.
A method for providing guidance information for a risk minimization operation, characterized in that the above stopping location information is determined as a position that can be reached within the stopping time required based on longitudinal time considering deceleration during natural deceleration and transverse time considering a speed below the critical speed based on the calculated number of lanes. In paragraph 1,
A method for providing guidance information for risk minimization operation, characterized in that the above stopping location information is location information on a road including the driving road or on the shoulder of a road on the road. In paragraph 1,
A method for providing guidance information for risk minimization operation, characterized in that the above stopping location information is determined by considering the traffic volume on the road. In the third paragraph,
A method for providing guidance information for risk minimization operation, characterized in that the above stopping location information is determined based on information on the lane of a road on which other vehicles are driving included in the traffic volume of the road. In paragraph 4,
A method for providing guidance information for minimizing risk, characterized in that the step of calculating the lane information calculates the lane information of the road on which the vehicle is driving based on the markings already installed on the road. In paragraph 5,
A method for providing guidance information for minimizing risk, characterized in that the step of calculating the lane information calculates lane information according to the longitudinal position of the road on which the vehicle is driving based on the left or right markings already installed on the road. processor,
a memory for loading a computer program executed by said processor, and
Including storage for storing the above computer program,
The above computer program,
In a method for providing guidance information for risk minimization operation based on lane recognition,
An operation for obtaining status information of a vehicle in which an abnormal condition has occurred while driving and traffic information on the road on which the vehicle is driving.
An operation for calculating lane information of the above driving road, and
Includes an operation of providing a vehicle with stop location information based on the above-described road information and status information,
The operation of producing information by the above method is as follows:
The number of lanes of the vehicle is calculated by using the distance between the vehicle and the roadside sign facility located on the left or right side based on the direction of travel of the road.
The action of providing the above stopping location information is:
Using the number of lanes calculated above, the number of lane changes until stopping at the location according to the stopping location information is provided.
A computing device characterized in that the above stopping location information is determined as a position that can be reached within the stopping time required based on the longitudinal time considering the deceleration during natural deceleration and the transverse time considering a speed below the critical speed based on the calculated number of lanes. In paragraph 7,
A computing device characterized in that the above stopping location information is location information on a road including the driving road or on the shoulder of a road on the road. In paragraph 7,
A computing device, characterized in that the above stopping location information is determined by considering the traffic volume on the road. In Article 9,
A computing device characterized in that the above stopping location information is determined based on lane information of a driving road of another vehicle included in the traffic volume of the road. In Article 10,
A computing device characterized in that the operation of calculating the lane information calculates the lane information of the road on which the vehicle is driving based on the markings installed on the road. In Article 11,
A computing device characterized in that the operation of calculating the lane information calculates lane information according to the longitudinal position of the road on which the vehicle is driving based on the left or right markings installed on the road.

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