Mobility recognition system using artificial intelligence

Abstract

The present invention relates to a mobility recognition system using AI. According to the present invention, a mobility recognition system using AI is provided, comprising: a first CCTV mounted on a street light installed at set intervals along a road and detecting mobility approaching as it travels based on artificial intelligence; a second CCTV mounted on the street light and detecting people around a pedestrian walkway based on artificial intelligence; a first VMS mounted on the street light and displaying safety information for a mobility driver; a second VMS mounted on the street light and displaying safety information for a pedestrian; and a control unit that controls the real-time change of the content and color of the safety information displayed on each of the first VMS and the second VMS based on mobility and person detection information through the first and second CCTVs. According to the present invention, by installing two VMSs with different target objects on a street light and providing information about each other to each target, mobility drivers and pedestrians can safely travel without the risk of accidents.

Description

Technology Field

[0001] The present invention relates to a mobility recognition system using AI, and more specifically, to a mobility recognition system using AI that enables mobility drivers and pedestrians to quickly verify information about each other and safely travel without the risk of accidents. Background Technology

[0002] Over the years, humans have developed technologies for various modes of transportation and devoted significant effort to solving issues related to traffic safety. As a result, today's world is equipped with advanced mobility technologies and is undergoing continuous innovation. Faster and more efficient modes of transportation, Intelligent Transport Systems (ITS), and Cooperative Intelligent Transport Systems (C-ITS) all enhance mobility and safety. Furthermore, technologies such as 'AI EDGE' enable immediate and automatic emergency response in accident-prone areas like highways. Convolutional Neural Networks (CNN)-based object recognition technology is also being utilized in advanced transportation fields, such as autonomous driving and traffic accident prevention.

[0003] To date, transportation development has generally aimed to enhance mobility and safety. However, future transportation must focus more specifically on protecting and supporting "transportation vulnerable groups," such as children, the elderly, and people with disabilities. Many developed countries have already adjusted transportation development to be pedestrian-friendly for these groups and implemented systems and infrastructure accordingly. Examples include "barrier-free" initiatives, "school zones" for child protection, and "silver zones" for the elderly. Among these, protecting child pedestrians must be the top priority.

[0004] Despite the implementation of systems related to the safety of vulnerable road users, it has been found that traffic accidents involving vulnerable road users have not been completely eradicated in Korea. Currently, technologies and systems designed to protect children near school zones are primarily limited to "painting road infrastructure yellow" and "installing cameras to crack down on traffic violations and speeding." These measures provide only a superficial sense of protection and fail to address micro-level variables, such as children's jaywalking and visual obstructions within school zones.

[0005] Given that school zones are occupied by children at various times of the day, more practical and direct solutions are needed. To truly protect children in school zones, it is essential to develop measures and devices that address these micro-variables.

[0006] Recently, due to the increased use of personal mobility (PM) devices such as electric scooters and electric bicycles, a large volume of PM traffic is entering the roads. If a pedestrian and a moving PM driver collide without recognizing each other, both parties suffer serious injuries. In other words, mobility drivers feel as though pedestrians are suddenly appearing from unexpected places, making driving quite frightening; similarly, pedestrians feel significant fear when crossing and passing due to the unexpected approach of mobility devices.

[0007] Therefore, it is necessary to develop a mobility recognition detector that enables pedestrians to detect the approach of various forms of mobility, such as personal mobility devices (PMs) and automobiles.

[0008] The technology forming the background of the present invention is disclosed in Korean Published Patent No. 10-2021-0064971 (published June 3, 2021). The problem to be solved

[0009] The present invention aims to provide a mobility recognition system using AI that enables mobility drivers and pedestrians to quickly verify information about each other, thereby allowing them to travel safely without the risk of accidents. means of solving the problem

[0010] The present invention provides a mobility recognition system using AI, comprising: a first CCTV mounted on a street light installed at set intervals along a road and detecting mobility approaching as it travels based on artificial intelligence; a second CCTV mounted on the street light and detecting people around a pedestrian walkway based on artificial intelligence; a first VMS mounted on the street light and displaying safety information for a mobility driver; a second VMS mounted on the street light and displaying safety information for a pedestrian; and a control unit that controls the real-time change of the safety information display content and display color for each of the first VMS and the second VMS based on mobility and person detection information through the first and second CCTVs.

[0011] In addition, the control unit can display safety information for pedestrians, including the type, speed, and distance of approaching mobility detected through the first CCTV, on the second VMS in real time, and safety information for mobility drivers, including the type and number of pedestrians detected through the second CCTV, on the first VMS in real time.

[0012] In addition, the types of mobility mentioned above include vehicles, motorcycles, bicycles, and personal mobility (PM), and the types of pedestrians mentioned above may include children and other general pedestrians.

[0013] In addition, the control unit can simultaneously change the display colors of the first and second VMSs according to the approach distance of the mobility.

[0014] In addition, the control unit may compare the approach distance of the mobility with a preset multi-stage threshold distance to change the display colors of the first and second VMSs stepwise according to the approach distance, and may change the saturation of the display colors by additionally considering the driving speed of the mobility.

[0015] In addition, the mobility recognition system using the AI ​​described above may further include a floor light installed on the bottom of the street light and simultaneously controlled by the control unit to have the same color as the first and second VMS.

[0016] In addition, the control unit may switch the first and second VMSs to a standby screen of a preset low-power mode if mobility is not recognized by the first CCTV for a set period during daytime hours.

[0017] In addition, the first VMS can be coupled to enable rotation and angle tilting relative to the street light.

[0018] In addition, if mobility is not recognized by the first CCTV for a set period during nighttime hours, the control unit can rotate the first VMS, which is previously set to face the road, toward the pedestrian walkway, perform angle tilting so that the screen faces the ground, and then turn on the streetlight of a set color to switch from the existing VMS mode to the streetlight mode.

[0019] In addition, if mobility is detected by the first CCTV while the street light mode is in operation, the position and state of the first VMS can be restored to switch to the VMS mode. Effects of the invention

[0020] According to the present invention, two VMSs with different target objects are installed on streetlights installed along a road, and by providing information about each other to each target, mobility drivers and pedestrians can quickly check information about each other and safely travel without the risk of accidents. Brief explanation of the drawing

[0021] FIG. 1 is a diagram illustrating the configuration of a mobility recognition system using AI according to an embodiment of the present invention. FIG. 2 is a drawing showing an example of the installation of a street light according to an embodiment of the present invention. FIG. 3 is a diagram showing an example of displaying information by illuminating a VMS for a mobility driver and a VMS for a pedestrian when mobility approach is detected in an embodiment of the present invention. Figures 4a and 4b are drawings showing examples of information display through a VMS for mobility drivers. FIGS. 5a to 5c are drawings showing examples of information display through a pedestrian VMS. FIG. 6 is a diagram exemplarily showing the first and second VMSs operating in a low-power mode when mobility is not accessed during daytime hours in an embodiment of the present invention. FIG. 7 is a diagram exemplarily showing the first VMS switching to street light mode when mobility is not approaching during nighttime hours in an embodiment of the present invention. FIG. 8 is a diagram showing in detail the mode switching operation of the first VMS in an embodiment of the present invention. FIG. 9 is a diagram showing the first VMS being switched to VMS mode when a vehicle approach is detected while the first VMS is operating in street light mode during nighttime hours in an embodiment of the present invention. Specific details for implementing the invention

[0022] Then, with reference to the attached drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily implement the invention. However, the present invention may be embodied in various different forms and is not limited to the embodiments described herein. Furthermore, in order to clearly explain the present invention in the drawings, parts unrelated to the explanation have been omitted, and similar parts throughout the specification have been given similar reference numerals.

[0023] Throughout the specification, when a part is described as being "connected" to another part, this includes not only cases where they are "directly connected," but also cases where they are "electrically connected" with other components interposed between them. Furthermore, when a part is described as "including" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0024] FIG. 1 is a diagram illustrating the configuration of a mobility recognition system using AI according to an embodiment of the present invention, and FIG. 2 is a diagram showing an example of the installation of a street light according to an embodiment of the present invention.

[0025] A mobility recognition system (100) according to an embodiment of the present invention can be mounted on and operated on a street light (10). The street light (10) can be installed at set intervals (e.g., 30m intervals) along a road as shown in FIG. 2. FIG. 2 illustrates a case where multiple street lights (10) are installed along a road with severe blind spots caused by vehicles parked on the shoulder of the road, within and near a child protection zone. Here, the installation location and method of the street lights are not necessarily limited to FIG. 2.

[0026] The streetlights on which the system proposed in this invention is installed and operated are not limited to ordinary streetlight facilities, but may encompass facilities such as poles installed along roadsides.

[0027] As shown in FIGS. 1 and 2, a mobility recognition system (100) using AI according to an embodiment of the present invention includes a first CCTV (110), a second CCTV (120), a first VMS (130), a second VMS (140), and a control unit (150), and may further include a floor light (160) and a solar light (170).

[0028] In an embodiment of the present invention, the first CCTV (110) and the first VMS (130) may be installed facing the road side, and the second CCTV (120) and the second VMS (140) may be installed facing the pedestrian walkway side.

[0029] Here, the first and second CCTVs (110, 120) can recognize and detect objects of interest within the video by analyzing the video based on artificial intelligence. The first CCTV (110) is for detecting mobility on the road (e.g., vehicles, motorcycles, bicycles, personal mobility (PM)), and the second CCTV (120) is for detecting people on the sidewalk (e.g., children, general pedestrians).

[0030] In an embodiment of the present invention, the first and second CCTVs (110, 120) may use a deep learning-based YOLO (You Look Only Once) algorithm for object detection and classification within an image. YOLO divides the image into a grid and uses a method of predicting the presence and class of an object in each grid cell. Due to these characteristics, YOLO can detect objects at a high speed, making it suitable for real-time applications.

[0031] The first and second VMS (Variable Message Signs) (130, 140) may correspond to traffic information display boards installed in public places such as roads or buildings to display traffic-related information. Here, the first VMS (130) may correspond to a VMS for mobility drivers, and the second VMS (140) may correspond to a VMS for pedestrians. VMS typically uses LED technology to display information and can transmit variable messages, allowing information to be updated according to various situations.

[0032] Referring again to FIG. 1, the first CCTV (110) can detect approaching mobility based on artificial intelligence. And, the second CCTV (120) can detect people around the pedestrian walkway based on artificial intelligence. The first CCTV (110) can determine various information such as the type of mobility recognized at the site, speed, and distance from streetlights through AI EDGE technology applied within the camera.

[0033] Figure 1 illustrates an exemplary situation in which a vehicle approaches and a pedestrian attempts to cross the road, where a blind spot exists due to vehicles parked on the shoulder of the road, such as within a child protection zone or school zone. In this case, it is difficult to secure a clear view between the vehicle and the pedestrian, and there is a risk of an accident.

[0034] In this situation, the first CCTV (110) installed on the street light (10) can detect the type, distance, and speed of mobility based on deep learning-based image analysis, and the second CCTV (120) can detect the type and number of pedestrians based on deep learning-based image analysis.

[0035] In an embodiment of the present invention, the types of detectable mobility may include vehicles, motorcycles, bicycles, and personal mobility (hereinafter PM), and the types of pedestrians may include children and other general pedestrians.

[0036] As such, in an embodiment of the present invention, the image recognition camera is configured with a total of two cameras, one for pedestrian detection and one for mobility detection, and can quickly recognize mobility and pedestrians approaching within the section, and can analyze what type of mobility it is and whether the pedestrian is an adult or a child. Information about pedestrians waiting to cross is transmitted to the driver of the approaching mobility through the first VMS (130) for the mobility driver, and information about the approaching mobility can be transmitted to the pedestrians waiting to cross through the second VMS (140) for pedestrians.

[0037] The first VMS (130) is installed facing the road and can display safety information for the mobility driver (e.g., the number and type of pedestrians detected around the pedestrian walkway). At this time, the first VMS (130) can be installed at an angle facing the direction of approach of the mobility.

[0038] The second VMS (140) is installed facing the pedestrian walkway and can display safety information for pedestrians (e.g., type of approaching mobility, distance, speed).

[0039] In an embodiment of the present invention, the first VMS (130) and the second VMS (140) can be manufactured in a form that can be attached to a street light by modifying a small VMS with dimensions of 30 to 60 cm in width and 30 cm in height. For example, the first VMS (130) for mobility drivers can be manufactured with dimensions of 60 cm in width and 30 cm in height, and the second VMS (140) for pedestrians can be manufactured with dimensions of 30 cm in width and 30 cm in height.

[0040] The first CCTV (110) can provide mobility detection information to the control unit (150), and the second CCTV (120) can provide person detection information to the control unit (150).

[0041] The control unit (150) may be installed in the form of a control box on the street light (10), or it may be installed outside the street light and connected to a network. The control unit (150) may be connected to each unit (110~140, 160, 170) via a wired or wireless network and can control the operation of each unit (110~140, 160, 170).

[0042] The control unit (150) can variably control the safety information display content and display color for each of the first VMS (130) and the second VMS (140) in real time based on mobility and person detection information obtained from the first and second CCTVs (110, 120).

[0043] The first VMS (130) can display the type and number of pedestrians currently detected as safety information for mobility drivers, and the second VMS (140) can display the type, distance, and speed of mobility currently approaching the streetlight as safety information for pedestrians.

[0044] As such, according to the present invention, by notifying pedestrians of the approach of various mobility and notifying mobility drivers of the presence of pedestrians, two-way communication between drivers and pedestrians is enabled, and accidents between mobility and pedestrians can be prevented.

[0045] FIG. 3 is a diagram showing an example of displaying information by illuminating a VMS for a mobility driver and a VMS for a pedestrian when mobility approach is detected in an embodiment of the present invention.

[0046] The left figure of FIG. 3 illustrates a situation where mobility is not approaching and the first and second VMSs (130, 140) are operating in a deactivated or power-saving state, while the right figure illustrates a situation where mobility is approaching and the first and second VMSs (130, 140) are lit up in colors corresponding to the approach distance of mobility. At this time, the approach distance of mobility may correspond to the detected distance of mobility based on the street light (10).

[0047] As shown in FIG. 3, the control unit (150) can simultaneously change the display colors of the first and second VMS (130, 140) according to the approach distance of the detected mobility. For example, when the approach distance of the mobility reaches the first threshold distance (e.g., within 30m), it may be displayed as 'green', when it reaches the second threshold distance (within 20m), it may be displayed as 'orange', and when it reaches the third threshold distance (within 10m), it may be displayed as 'red'. Here, the maximum threshold distance (e.g., 30m) among the multi-stage threshold distances may be determined by the installation spacing of the streetlights.

[0048] Additionally, the control unit (150) can simultaneously control the floor light (160) installed on the bottom of the street light to have the same color as the first and second VMS (130, 140). In this way, the control unit (150) can synchronize the display color and lighting timing of the first VMS (130), the second VMS (140), and the floor light (160).

[0049] FIGS. 4a to 5c show examples of information display of the first and second VMS (130, 140). FIGS. 4a and 4b are drawings showing examples of information display through a VMS for mobility drivers, and FIGS. 5a to 5c are drawings showing examples of information display through a VMS for pedestrians.

[0050] First, FIGS 4a and FIGS 4b show examples of safety information display for a mobility driver via the first VMS (130) for a situation where one child is waiting to cross and two pedestrians are waiting to cross, respectively.

[0051] In this way, the control unit (150) can display safety information for mobility drivers, including the type and number of pedestrians detected through the second CCTV (120), on the first VMS (130) in real time. In addition, the first VMS (130) can display the type of person as a combination of an icon and text to improve visibility.

[0052] Next, FIGS. 5a, FIGS. 5b, and FIGS. 5c each show examples of pedestrian safety information display via the second VMS (140) regarding situations where a vehicle, bicycle, and PM are approaching.

[0053] In this way, the control unit (150) can display pedestrian safety information, including the type, speed, and distance of approaching mobility detected through the first CCTV (110), on the second VMS (140) in real time. In addition, the second VMS (140) can display the type of mobility as a combination of icons and text to improve visibility.

[0054] In addition, the information displayed through the first VMS (130) and the second VMS (140) can be varied in real time in response to the detection information.

[0055] And, in all cases of FIGS. 4a to 5c, the control unit (150) can compare the approach distance of the mobility with a preset multi-stage threshold distance (e.g., 30m, 20m, 10m) and change the display colors of the first and second VMS (130, 140) stepwise according to the approach distance.

[0056] FIGS. 4a to 5c show the streetlights and mobility being approached by a pedestrian being lit in red when the physical distance is 10m, yellow when it is 20m, and green when it is 30m. Additionally, the VMS (130, 140) is shown lit in a preset strong saturation when the speed of the mobility is 30km / h or higher, in a preset medium saturation when the speed range is 30km / h to 20km / h, and in a preset weak saturation when the speed range is 20km / h to 10km / h. At this time, the VMS (130) for mobility, the VMS (140) for pedestrians, and the ground light (160) change to the same color and saturation according to the distance and speed of the approaching mobility.

[0057] In this way, the control unit (150) can change the saturation of the display color by additionally considering the driving speed of the mobility. For example, by comparing the speed of the mobility with a multi-stage range (30 km / h or more, 30-20 km / h, 20-10 km / h), the saturation value can be strengthened as it falls into a higher speed range. That is, the higher the driving speed of the mobility, the higher the saturation value of the display color can be adjusted.

[0058] In this way, the present invention enables pedestrians and drivers to exchange information with each other through two different types of VMS (130, 140), and unlike the unidirectional information reception system characteristic of existing VMS, pedestrians and drivers can simultaneously obtain information about each other.

[0059] That is, the mobility driver can know the type and number of pedestrians through the mobility driver VMS (130), and the pedestrian can know information about the type, speed, and distance of the mobility through the pedestrian VMS (140), and can also intuitively check through color and saturation.

[0060] In addition, pedestrians can effectively make a decision on whether to cross the road through the color of the pedestrian VMS and the information displayed thereon. Since pedestrians look at the VMS (140) that is lit up due to the entry of mobility, they can recognize the entry of mobility. Depending on the color, they can think about whether they should cross now or not.

[0061] The VMS (140) can serve as a new safety indicator to recognize the entry of mobility for pedestrians who normally cross naturally without thinking, thereby causing the pedestrian to stop briefly and wait for the mobility to pass. In other words, when the pedestrian VMS (140) operates, the pedestrian recognizes the entry and passage of mobility and stops crossing briefly to wait, allowing mobility to pass smoothly without worrying about the pedestrian's sudden entry. A pedestrian who recognizes the entry of mobility and waits until mobility completes passage will be able to pass safely without worrying about colliding with mobility after it passes.

[0062] FIG. 6 is a diagram exemplarily showing the first and second VMSs operating in a low-power mode when mobility is not accessed during daytime hours in an embodiment of the present invention.

[0063] The left figure of Fig. 6 shows the operation of a mobility access situation during daytime hours (e.g., 06:00–18:00), and the right figure shows the operation transition when mobility access is not detected for a certain period of time.

[0064] As shown in FIG. 6, the control unit (150) can switch the first and second VMSs (130, 140) to a standby screen of a preset low-power mode when mobility is not detected by the first CCTV (110) for a set time (e.g., 5 minutes) during daytime hours (e.g., 06:00 to 18:00), that is, when mobility is not approaching for more than 5 minutes. This reduces power waste when mobility is not detected.

[0065] FIG. 7 is a diagram exemplarily showing the first VMS switching to street light mode when mobility is not approaching during nighttime hours in an embodiment of the present invention.

[0066] As shown in FIG. 7, if mobility is not detected by the first CCTV (110) for a set time (e.g., 5 minutes) during the night time (e.g., 18:00 to 06:00 the next day), the control unit (150) can switch from the existing VMS mode to the street light mode by rotating and tilting the first VMS (130), which is set to face the road, and then lighting it with a street light of a set color (e.g., white, orange light).

[0067] After the daytime when there is heavy traffic, there is relatively less traffic during the nighttime hours from 18:00 to 06:00 the next day. Therefore, when the approach of a mobility vehicle is not detected for 5 minutes, the VMS (130) for mobility vehicle drivers attached to the streetlight can be automatically switched to the streetlight, allowing it to function as a night-only streetlight used for safety. This 'VMS ↔ Streetlight switching' function eliminates power waste caused by unnecessary VMS lighting and enables efficient traffic safety. Furthermore, it can prevent various other criminal behaviors that may occur on the street.

[0068] To this end, the first VMS (130) can be coupled to enable rotation and angle tilting relative to the street light (10). The mode switching operation of the first VMS (130) is described in more detail as follows.

[0069] FIG. 8 is a diagram showing in detail the mode switching operation of the first VMS in an embodiment of the present invention. As shown in FIG. 8 (a), when switching from VMS mode to street light mode, the control unit (150) can switch from the existing VMS mode to street light mode by horizontally rotating the first VMS (130) toward the pedestrian walkway, then tilting the screen so that it faces the ground, and then illuminating it with street light.

[0070] In addition, as shown in FIG. 8(b), when mobility is detected by the first CCTV (110) while the street light mode is in operation, the control unit (150) can restore the position and state of the first VMS and switch to VMS mode. In this case, the operation should be reversed from FIG. 8(a).

[0071] For example, when a vehicle approaches within a range of 30m while the streetlight mode is in operation, it switches back from streetlight mode to VMS mode for mobility drivers to provide the same mobility information to pedestrians.

[0072] FIG. 9 is a diagram showing the first VMS being switched to VMS mode when a vehicle approach is detected while the first VMS is operating in streetlight mode during nighttime hours in an embodiment of the present invention. As shown in FIG. 9, when in streetlight mode, the first VMS (130) can perform a lighting function at night by illuminating the streetlight light downwards, and then, when a vehicle approach is detected, it can return to its original state and display relevant information.

[0073] According to the present invention as described above, by installing two VMSs with different target objects on streetlights installed along a road and providing information about each other to each target, mobility drivers and pedestrians can quickly check information about each other and safely travel without the risk of accidents.

[0074] The present invention has been described with reference to embodiments illustrated in the drawings, but this is merely illustrative, and those skilled in the art will understand that various modifications and equivalent alternative embodiments are possible therefrom. Accordingly, the true technical scope of protection of the present invention should be determined by the technical spirit of the appended claims. Explanation of the symbols

[0075] 100: Mobility Recognition System 110: 1st CCTV 120: 2nd CCTV 130: 1st VMS 140: 2nd VMS 150: Control unit 160: Floor light 170: Solar

Claims

Claim 1 A first CCTV mounted on a streetlamp installed at set intervals along the road, which detects approaching mobility based on artificial intelligence as it travels; a second CCTV mounted on the streetlamp, which detects people around the pedestrian walkway based on artificial intelligence; a first VMS mounted on the streetlamp, which displays safety information for mobility drivers and is coupled to allow rotation and angle tilting relative to the streetlamp; and a second VMS mounted on the streetlamp, which displays safety information for pedestrians. A mobility recognition system using AI that includes a control unit that controls the display content and display color of safety information for each of the first VMS and the second VMS in real time based on mobility and person detection information through the first and second CCTVs, wherein if mobility is not recognized by the first CCTV for a set period during nighttime hours, the control unit rotates the first VMS, which is previously set to face the road, toward the pedestrian walkway, performs angle tilting so that the screen faces the ground, and then turns on the streetlight with a set color light to switch from the existing VMS mode to a streetlight mode. Claim 2 A mobility recognition system using AI according to claim 1, wherein the control unit displays safety information for pedestrians, including the type, speed, and distance of approaching mobility detected through the first CCTV, in real time on the second VMS, and displays safety information for mobility drivers, including the type and number of pedestrians detected through the second CCTV, in real time on the first VMS. Claim 3 A mobility recognition system using AI according to claim 2, wherein the types of mobility include vehicles, motorcycles, bicycles, and personal mobility (PM), and the types of pedestrians include children and other general pedestrians. Claim 4 In claim 1, the control unit is a mobility recognition system using AI that simultaneously and collectively changes the display colors of the first and second VMS according to the approach distance of the mobility. Claim 5 In claim 4, the control unit compares the approach distance of the mobility with a preset multi-stage threshold distance to change the display colors of the first and second VMS stepwise according to the approach distance, and additionally considers the driving speed of the mobility to change the saturation of the display colors using AI. Claim 6 A mobility recognition system using AI according to claim 4, further comprising a floor light installed on the bottom part of the street light and simultaneously controlled by the control unit to have the same color as the first and second VMS. Claim 7 A mobility recognition system using AI according to claim 1, wherein if mobility is not recognized by the first CCTV for a set period of time during daytime hours, the first and second VMSs are switched to a standby screen of a preset low-power mode. Claim 8 delete Claim 9 delete Claim 10 A mobility recognition system using AI according to claim 1, wherein when mobility is recognized by the first CCTV during operation of the street light mode, the position and state of the first VMS are restored and switched to the VMS mode.

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