WO2025088719A1 - Vehicle driving assistance device - Google Patents

Abstract

A vehicle driving assistance device according to the present invention comprises a control unit. The control unit comprises: a road information acquisition unit that acquires road information on the basis of travel environment information; a minimum road surface friction coefficient detection unit that detects a minimum road surface friction coefficient on the basis of the road information; a driving force calculation unit that calculates a driving force on the basis of a torque of a driving source; a road surface grip force calculation unit that calculates a road surface grip force of a driving wheel on the basis of the minimum road surface friction coefficient detected by the minimum road surface friction coefficient detection unit; a comparison unit that compares the driving force with the road surface grip force; and a travel assistance control unit that executes travel assistance control when the comparison unit determines that the driving force exceeds the road surface grip force. The control unit further comprises a travel segment setting unit that segments a travel route ahead of a host vehicle in accordance with a prescribed travel segment condition, and the minimum road surface friction coefficient detection unit detects the minimum road surface friction coefficient in a travel segment on the basis of the travel environment information.

Description

Vehicle driving support device

The present invention relates to a vehicle driving assistance device.

When a driver is driving their vehicle, changes in road conditions or weather can cause the vehicle to behave in ways that the driver does not anticipate. For example, if part of the road surface is frozen, the vehicle may slip for a moment when passing over the frozen surface.

Furthermore, momentary slippage can occur when tires pass over metal joints at bridge joints, or snow or fallen leaves. In front-wheel drive vehicles, where the driving wheels also serve as steering wheels, if the front wheels slip, it becomes difficult to steer the vehicle.

If slippage occurs while the vehicle is moving, the vehicle's behavior becomes unstable, causing anxiety to the driver and other passengers.

For example, in the technology disclosed in Japanese Patent Publication No. 2023-1303513, in an autonomous driving mode, the driving control unit first checks the tire slip condition from the tire rotation speed and estimates the road friction coefficient. Then, based on this road friction coefficient, it is checked whether the road surface is slippery or not. If it is determined that the road surface is slippery, the driving control unit executes a low friction coefficient driving mode. In this low friction coefficient driving mode, the steering speed is slowed down, the braking timing is set earlier, and the upper limit speed and upper limit acceleration are set low.

When the low-friction coefficient driving mode is in operation, the driving control unit detects the driver's level of anxiety from factors such as the frequency with which the driver moves their eyes. If it determines that the driver is feeling anxious, it further corrects the steering speed and braking timing. This is intended to ease the driver's anxiety.

By the way, road surface conditions change from moment to moment depending on the driving environment. In order to prevent slippage from occurring while a vehicle is moving, it is necessary to predict upcoming changes in the road surface friction coefficient at an early stage.

However, in the technology disclosed in JP 2023-1303513 A, after detecting slippage occurring in the vehicle, the low friction coefficient driving mode is executed. Furthermore, at that time, the degree of anxiety of the driver is judged and the driver's anxiety is alleviated. This makes it easy for a momentary delay in control to occur when preventing slippage. Also, because control to alleviate anxiety is not executed until the driver feels anxiety, a momentary delay in control also occurs in this case.

In view of the above circumstances, the present invention aims to provide a vehicle driving assistance device that can suppress the occurrence of slippage and significantly reduce the anxiety felt by passengers, including the driver.

One aspect of the present invention has a driving environment information acquisition unit that acquires driving environment information ahead of the vehicle, and a control unit, the control unit including a road information acquisition unit that acquires road information based on the driving environment information acquired by the driving environment information acquisition unit, a minimum road friction coefficient detection unit that detects a minimum road friction coefficient based on the road information acquired by the road information acquisition unit, a driving force calculation unit that calculates a driving force based on the torque of a driving source, a road grip calculation unit that calculates the road grip of a driving wheel based on the minimum road friction coefficient detected by the minimum road friction coefficient detection unit, and The vehicle includes a comparison unit that compares the driving force calculated by the power calculation unit with the road grip force calculated by the road grip force calculation unit, and a driving support control unit that executes driving support control when the comparison unit determines that the driving force exceeds the road grip force. The control unit further includes a driving section setting unit that divides the driving route ahead of the vehicle according to predetermined driving section conditions, and the minimum road friction coefficient detection unit detects the minimum road friction coefficient within the driving section set by the driving section setting unit based on the driving environment information acquired by the driving environment information acquisition unit.

Schematic diagram of a vehicle driving assistance device Flowchart showing the routine for setting estimated road surface μ Flowchart showing a routine for slip suppression control according to driving conditions Conceptual diagram of basic road surface μ setting map based on road type Weather correction factor setting map concept Conceptual diagram of tire correction coefficient setting map Conceptual diagram of road surface μ correction coefficient setting map based on road surface type FIG. 13 is an explanatory diagram showing a manner in which road surface μ is estimated for each section. FIG. 2 is an explanatory diagram showing the relationship between the driving force of the driving tires and the road grip force.

Below, one embodiment of the present invention will be described with reference to the drawings. It should be noted that the drawings are schematic, and that the relationship between the thickness and width of each component, the thickness ratio of each component, and the like differ from the actual ones, and of course there are parts in which the dimensional relationships and ratios differ between the drawings.

In Figure 1, reference numeral 1 denotes a drive control device. This drive control device 1 is mounted on the host vehicle M (see Figure 5). The host vehicle M is an electric vehicle. In the following description, the host vehicle M will be referred to as the electric vehicle M.

The drive control device 1 has a vehicle integrated control unit 2. This vehicle integrated control unit 2 comprehensively performs various controls related to the drive of the electric vehicle M. A camera control unit 3 and left and right side view cameras 7l, 7r are connected to this vehicle integrated control unit 2. Although not shown, various sensors that obtain information required when driving the electric vehicle M are connected to the vehicle integrated control unit 2. Furthermore, the vehicle integrated control unit 2 and the camera control unit 3 correspond to the control unit of the present invention.

Side view cameras 7l, 7r are attached to the left and right front parts of the vehicle body to capture images of the left and right sides of the vehicle body. From the images captured by each side view camera 7l, 7r, the vehicle integrated control unit 2 detects the moving speed of the road surface and the moving speed of the tires of the drive wheels Fl, Fr at their road contact positions.

In addition, an inverter control unit 5 is connected to the vehicle integrated control unit 2. Although not shown, the vehicle integrated control unit 2 is connected to various control units so that bidirectional communication is possible.

Each of the control units 2, 3, 5, and the navigation system 8 described below, is composed of a microcontroller equipped with a CPU, RAM, ROM, rewritable non-volatile memory (flash memory or EEPROM), and peripheral devices. The ROM stores programs and fixed data necessary for the CPU to execute each process. The RAM is provided as a work area for the CPU, and temporarily stores various data for the CPU. The CPU is also called an MPU (Microprocessor) or a processor. A GPU (Graphics Processing Unit) or a GSP (Graph Streaming Processor) may be used instead of the CPU. Alternatively, a selective combination of the CPU, GPU, and GSP may be used.

The inverter 12 of the electric powertrain 11 is connected to the inverter control unit 5. The electric powertrain 11 includes the inverter 12, a high-voltage battery 13, and a drive motor 14 as a drive source. The inverter 12 is operated by a command signal from the inverter control unit 5. In accordance with the command signal from the inverter control unit 5, the inverter 12 converts direct current (DC) power from the high-voltage battery 13 into alternating current (AC) power and supplies it to the drive motor 14. The inverter control unit 5 controls the driving force of the drive motor 14 by vector control.

The output shaft 21 of the drive motor 14 is connected to the drive shafts 22l, 22r of the left and right drive wheels Fl, Fr via a differential Df. The drive motor 14 drives the drive wheels Fl, Fr with power supplied from the inverter 12 to power the electric vehicle M.

In addition, a camera unit 6 is installed at the front of the electric vehicle M as a driving environment detection unit. The camera unit 6 is equipped with a stereo camera consisting of a main camera 6a and a sub-camera 6b.

This camera unit 6 is connected to the input side of the camera control unit 3. The camera control unit 3 processes the images of the driving environment ahead of the electric vehicle M captured by both cameras 6a, 6b of the camera unit 6 to obtain information about the driving environment ahead.

In addition, the non-volatile memory 3a provided in the camera control unit 3 stores information about the tires currently installed. This tire information is input by the user or the driver when the tires are installed. The tire information includes the type of tire, the replacement time, etc. The type of tire includes whether it is a normal tire or a studless tire, the tire size, etc.

Furthermore, various maps are stored in this non-volatile memory 3a. The maps include a basic road surface μ setting map (see FIG. 4A) that is read in when setting the estimated μ initial value, a weather correction coefficient setting map (see FIG. 4B), and a tire correction coefficient setting map (see FIG. 4C). Furthermore, a road surface μ correction coefficient map (see FIG. 4D) is stored in the non-volatile memory 3a.

As shown in Figure 4A, the basic road surface μ map stores basic road surface μ data that is preset for each road type. Road types include paved roads (concrete road surface, asphalt road surface), unpaved roads (gravel road, dirt road), etc. The basic road surface μ for unpaved roads is set lower than that for paved roads.

As shown in Figure 4B, the weather correction coefficient setting map has correction coefficients (however, correction coefficients ≦ 1) set according to the weather. The correction coefficients are set to decreasing values in the following order: sunny > cloudy > rain > snow.

As shown in FIG. 4C, the tire correction coefficient setting map has correction coefficients (however, correction coefficients≦1) set according to tire type. The correction coefficient for normal tires is set higher than that for studless tires. Also, the higher the aspect ratio of the tire, the higher the correction coefficient is set.

As shown in Figure 4D, the road surface μ correction coefficient setting map has road surface μ correction coefficients set according to the road surface type. Even on paved roads, the road surface μ is lower on snowy or rainy roads than on dry roads. The road surface μ correction coefficient setting map is set with the percentage by which the road surface μ is lowered for each road surface type, determined in advance through experiments, etc.

Furthermore, a navigation system 8 is connected to the camera control unit 3. Furthermore, a GNSS (Global Navigation Satellite System) receiver 9 and a road information transmission/reception unit 10 are connected to this navigation system 8.

The navigation system 8 acquires information on the vehicle's position (latitude, longitude, altitude) based on positioning signals received by a GNSS receiver 9 from multiple positioning satellites. The navigation system 8 has a memory unit in which road map data is stored. This road map data includes static information and dynamic information. Static information includes road information such as paved roads and unpaved roads. Dynamic information includes weather information that changes in real time.

Weather information includes weather conditions such as sunny/rainy/snowy, sunshine, amount of rainfall, amount of snowfall, temperature, humidity, air pressure, etc. Weather information may be obtained from meteorological information provided on a website.

The navigation system 8 plots the vehicle's estimated position based on the positioning signal received by the GNSS receiver 9 on road map data, and estimates the vehicle's current position on the road map and the direction of travel. The navigation system 8 then creates a driving route on the road map that connects the destination input by the driver or other person and the vehicle's position.

Furthermore, the navigation system 8 can access the cloud server 103 from the road information transmitting/receiving unit 10 via the base station 101 and the network 102. The navigation system 8 acquires the latest road map data (static information, dynamic information) for the area around the vehicle from the cloud server 103. The camera unit 6 and the navigation system 8 correspond to the driving environment information acquisition unit of the present invention.

The navigation system 8 also acquires road information around the vehicle based on road map data. This acquired road information is then sent to the camera control unit 3.

The camera control unit 3 sets the division conditions for dividing the driving route set on the road map into distances. These driving division conditions are set based on road information ahead of the vehicle position obtained by the navigation system 8, and driving environment information ahead of the vehicle obtained from images captured by the camera unit 6. Note that these division conditions are constantly updated. Therefore, while the electric vehicle M is traveling on the divided road, the driving route ahead is divided into driving sections.

The camera control unit 3 divides the driving route from the front of the vehicle to a preset distance according to the set driving section conditions. The camera control unit 3 then sets the smallest minimum road surface μmin within the driving section. The camera control unit 3 sets this minimum road surface μmin for each driving section.

When the electric vehicle M enters a road segment, the vehicle integrated control unit 2 controls the driving force P of the drive wheels Fl and Fr based on the minimum road surface μmin set within that road segment.

Meanwhile, when the electric vehicle M is traveling, if the driving force P applied by the drive motor 14 to the tires of the drive wheels Fl, Fr (referred to as "drive tires") exceeds the grip force from the road surface acting on the drive tires (referred to as "road surface grip force") Ft (P>Ft), slippage occurs. As shown in FIG. 7, the driving force P of the drive tires (front wheels in the figure) in the electric vehicle M is expressed as follows:
P = T / r ... (1)
Here, T is the torque, and r is the effective radius of the driving tire.

The road grip force F is
F=μ・Wf…(2)
Here, μ is the road friction coefficient, Wf is the vehicle weight applied to the driving tires (front wheels), and in FIG. 7, W is the total vehicle weight, and Wr is the vehicle weight applied to the driven tires (rear wheels).

Therefore, if the road grip force F is set based on the minimum road surface μmin, and the driving force P is set so that the relationship P≦F is always maintained, the electric vehicle M can continue to run without causing slippage.

The camera control unit 3 sets the minimum road surface μmin for each driving segment in accordance with the estimated road surface μ setting routine shown in FIG. 2.

The camera control unit 3 first acquires vehicle position information estimated by the navigation system 8 (step S1). Next, the camera control unit 3 searches for a driving route ahead of the vehicle position from road map data based on the vehicle position, and acquires driving environment information on the driving route (step S2). This driving environment information includes road information acquired based on images captured by the camera unit 6, and static and dynamic information stored in the road map data. The processing in step S2 corresponds to the road information acquisition section of the present invention.

Then, the camera control unit 3 sets the driving segment conditions based on the driving environment information (step S3). The driving segment conditions are classified based on the travel distance from the position when the driving route was classified in the previous calculation, the preset time pitch, the lane after the electric vehicle M changes lanes, the road type (paved road, unpaved road, etc.), the sunlight on the road (sunny, shaded), the road surface condition (dry, wet), the snow surface condition (uncleared, cleared), etc. Furthermore, the driving segment conditions are used to select which condition is used for the driving segment. Figure 6 shows an example in which the driving segment is set as a condition for classifying the driving segment as paved road or unpaved road. This driving segment condition can be changed successively.

Then, the camera control unit divides the driving route on which the electric vehicle M is traveling according to the set driving section conditions (step S4). Note that the processing in steps S3 and S4 corresponds to the driving section setting unit of the present invention.

When the driving section condition is set to paved road or unpaved road, the driving route shown in Figure 6 is divided into sections: driving section A where the electric vehicle M is currently driving is paved road, the next driving section B is unpaved road, and the next driving section C is paved road. Note that this driving section is determined within a range where the road conditions can be recognized based on the images captured by the camera unit 6.

Then, the camera control unit 3 refers to the basic road surface μ map (FIG. 4A) based on the classified road type, and sets the basic road surface μ corresponding to the acquired road type (step S5). The basic road surface μ map stores the road surface μ set for each road type, which is obtained in advance through experiments, etc.

Current weather information around the vehicle's position is also obtained from dynamic information in road map data or weather information provided on a website (step S6). Then, based on this weather information, the weather correction coefficient is set by referring to the weather correction coefficient setting map (Figure 4B) (step S7).

Furthermore, the camera control unit 3 sets the tire correction coefficient by referring to the tire correction coefficient setting map (Figure 4C) based on the tire information of the electric vehicle M pre-stored in the non-volatile memory 3a (step S8).

Then, the camera control unit 3 multiplies the basic road surface μ set for each driving segment by the average value of the weather correction coefficient and the tire correction coefficient, or whichever is lower, to set the estimated road surface μ initial value (step S9). Note that when setting this estimated road surface μ initial value, the cloud server 103 may be accessed to retrieve information on other vehicles in the driving segment (e.g., slip information and road surface μ information), and this other vehicle information may be incorporated into the estimated road surface μ initial value.

Then, the camera control unit 3 sets the distribution of road surface types within the driving section (step S10). For example, driving sections A and B shown in Figure 6 are paved roads, but the road surface can be of any type, such as asphalt or concrete, and the road surface μ differs depending on the type. Also, as shown in driving section C, even on paved roads, there are some areas in the shade where snow has piled up or the road has become icy. Furthermore, on unpaved roads such as driving section B shown in Figure 6, even if the majority of the road is gravel, there are also some areas where the dirt road is exposed, the gravel is unevenly distributed, and the road is muddy. In this way, the road surface μ differs depending on the condition of the road surface, whether the road type is paved or unpaved.

This road surface type distribution is based on the image of the road ahead captured by the camera unit 6, and is determined by dividing one frame of image data into road surface types using image recognition that utilizes AI (artificial intelligence), for example. This road surface type is information that acquires the current changes in the road surface in real time.

Next, the camera control unit 3 refers to a road surface μ correction coefficient map (FIG. 4D) for each road surface type identified by the AI and sets a road surface μ correction coefficient corresponding to the road surface type (step S11). In this road surface μ correction coefficient map, the correction coefficient for each road surface type is determined in advance through experiments, etc. and set.

Then, the camera control unit 3 corrects the set initial estimated road surface μ value with the road surface μ correction coefficient, and sets the estimated road surface μ for each road surface type (step S12).

Next, the minimum estimated road surface μ is selected from among the estimated road surface μ set within the driving segment (step S13). The selected minimum estimated road surface μ is set as the minimum road surface μmin (step S14). Road surface information for the driving segment including this minimum road surface μmin is sent as road information to the vehicle integrated control unit 2 (step S15), and the routine is exited. Note that the processing in steps S13 and S14 corresponds to the minimum road surface friction coefficient detection unit of the present invention.

The vehicle integrated control unit 2 reads road surface information for each driving section from the camera control unit 3 and detects whether or not slippage has occurred when the electric vehicle M is actually driven. The detection of whether or not slippage has occurred for each driving section executed by the vehicle integrated control unit 2 is specifically performed according to the slip detection routine for each driving section shown in FIG. 3.

The driving force of the drive motor 14 of the electric vehicle M is controlled by vector control. Vector control separates the current flowing through the motor into a current component that generates torque (torque current component) and a current component that generates magnetic flux in the rotor (magnetic flux current component), and controls each independently. The vehicle integrated control unit 2 first calculates the driving force P to be applied to the drive wheels Fl and Fr based on the torque current component (step S21). The processing in step S21 corresponds to the driving force calculation section of the present invention.

Next, the vehicle integrated control unit 2 reads the vehicle weight Wf applied to the tires of the drive wheels Fl and Fr (step S22). This vehicle weight Wf is pre-stored in the non-volatile memory 3a. In addition, the vehicle integrated control unit 2 reads the minimum road surface μmin for the driving section in which the vehicle is currently traveling (step S23).

Then, the road grip force F of the driving tires is calculated based on the vehicle weight Wf and the minimum road surface μmin (F = μmin · Wf: step S24). Note that the process in step S24 corresponds to the road grip force calculation unit of this specification.

Then, the vehicle integrated control unit 2 compares the driving force P with the road grip force F (step S25). Note that the process in step S25 corresponds to the comparison section of the present invention.

If P>F (step S25: YES), it predicts that slip will occur. If P≦F (step S25: NO), the vehicle integrated control unit 2 determines that the possibility of slip occurring is low. If it predicts slip occurring, the vehicle integrated control unit 2 executes driving support control (step S28). In step S24, the road grip force F is calculated based on the minimum road surface μmin, so that if P>F, it is possible to quickly predict the occurrence of slip.

If the vehicle integrated control unit 2 determines that the possibility of slippage is low, it detects the moving speed of the road surface and the moving speed of the tires of the drive wheels Fl and Fr at their road contact positions based on the images captured by the left and right side view cameras 7l and 7r (step S26).

The vehicle integrated control unit 2 determines whether or not slip has occurred based on the road surface movement speed and the movement speed of the tires of the drive wheels Fl and Fr at the road contact position (step S27). As described above, when P>F, it is possible to predict the occurrence of slippage early. However, even if the minimum road surface μmin is set, unexpected slippage may actually occur depending on the driving conditions.

Therefore, the vehicle integrated control unit 2 verifies whether or not slippage has actually occurred. Then, if the difference between the moving speed on the road surface and the moving speed at the tire's road contact position is less than the slip determination speed set for determining the occurrence of slippage (step S27: NO), the vehicle integrated control unit 2 determines that no slippage has occurred and exits the routine.

On the other hand, if the moving speed at the road contact position of the tires of the drive wheels Fl and Fr is faster than the moving speed of the road surface and the difference is equal to or greater than the slip determination speed (step S27: YES), the vehicle integrated control unit 2 determines that slip has occurred. If it determines that slip has occurred, the vehicle integrated control unit 2 executes driving assistance (step S28). The processing in step S28 corresponds to the driving assistance control unit of the present invention.

Here, the driving support control executed by the vehicle integrated control unit 2 is a control for suppressing the occurrence of slippage. Examples of driving support control include limiting the upper acceleration value of the electric vehicle M, lengthening the lower limit of the distance from the preceding vehicle, and setting a high collision prevention brake intervention threshold value for the electric vehicle M with respect to the preceding vehicle. The vehicle integrated control unit 2 executes at least one of these controls, or a combination of two or more of them.

In addition, the driving support control executed by the vehicle integrated control unit 2 may be a control that only notifies the driver of the occurrence of slippage, instead of the above-mentioned control. The control that notifies the driver of the occurrence of slippage is performed, for example, by applying a reaction force or vibration to the accelerator pedal and the brake pedal.

By applying a reaction force and vibration to the accelerator pedal and brake pedal, the driver will not press the accelerator pedal or brake pedal more than necessary. This makes it possible to prevent slipping. The means for applying the reaction force and vibration is provided by providing a pressure actuator to the accelerator pedal and brake pedal, and the vehicle integrated control unit 2 operates this pressure actuator.

Then, the vehicle integrated control unit 2 updates the road map data stored in the navigation system 8 (step S29). The road surface information for the current driving section is updated. The road surface information to be updated includes the driving section where slippage was detected, the time at which it occurred, and the minimum road surface μmin measured at that time, etc.

Furthermore, the vehicle integrated control unit 2 transmits this road surface information to the cloud server 103 via the network 102 (step S30) and exits the routine. The cloud server 103 stores the received vehicle information as vehicle information for the driving section in which the electric vehicle M has traveled, and provides it to other vehicles.

In this way, in this embodiment, the driving route on which the electric vehicle M travels is divided into predetermined driving section conditions. Then, the minimum road surface μmin in the driving section is detected, and the road grip force F is calculated based on this minimum road surface μmin. Therefore, if the electric vehicle M travels in a driving section with the relationship P≦F, it is possible to prevent slippage from occurring.

Furthermore, even if it is estimated that P≦F, there is still a possibility that slippage will actually occur. Therefore, in this embodiment, when it is estimated that P≦F, it is checked whether or not slippage has actually occurred based on the images captured by the side view cameras 7l, 7r. Then, if slippage is detected, driving assistance is executed, so that slippage is suppressed and higher driving stability can be obtained. As a result, the anxiety felt by the occupants, including the driver, can be significantly reduced.

The electric vehicle M may be a four-wheel drive vehicle. The estimated road surface μ setting routine shown in FIG. 2 may be executed by the vehicle integrated control unit 2. Furthermore, when the vehicle integrated control unit 2 detects the occurrence of slippage, it may notify the driver by voice or by displaying an image on a monitor.

Claims (5)

A driving environment information acquisition unit that acquires driving environment information ahead of the host vehicle;
A control unit,
The control unit is
a road information acquisition unit that acquires road information based on the traveling environment information acquired by the traveling environment information acquisition unit;
a minimum road friction coefficient detection unit that detects a minimum road friction coefficient based on the road information acquired by the road information acquisition unit;
a driving force calculation unit that calculates a driving force based on a torque of a driving source;
a road grip calculation unit that calculates a road grip of a driving wheel based on the minimum road friction coefficient detected by the minimum road friction coefficient detection unit;
a comparison unit that compares the driving force calculated by the driving force calculation unit with the road grip force calculated by the road grip force calculation unit;
a driving assistance control unit that executes driving assistance control when the comparison unit determines that the driving force exceeds the road surface grip force,
The control unit is
A driving section setting unit that divides a driving route ahead of the vehicle in accordance with a predetermined driving section condition,
The minimum road friction coefficient detection unit detects the minimum road friction coefficient within the driving section set by the driving section setting unit based on the driving environment information acquired by the driving environment information acquisition unit. The vehicle driving assistance device according to claim 1, characterized in that the driving segment conditions are at least one of a travel distance from a position when the driving route was segmented in the previous calculation, a preset time pitch, a lane after the vehicle changes lanes, a road type, sunlight on the road, road surface conditions, and snow surface conditions. 3. The vehicle driving support device according to claim 2, wherein the driving section conditions are changeable. 2. The vehicle driving support device according to claim 1, wherein the driving support control executed by the driving support control unit is a control for suppressing slippage. 5. The vehicle driving assistance device according to claim 1, wherein the control unit transmits the road information acquired by the road information acquisition unit to a cloud server via a network.

Images