Flight support node acquisition system and method based on multi-source heterogeneous data fusion

Abstract

The present invention discloses a flight support node acquisition system and method based on multi-source heterogeneous data fusion, including aircraft and flight support special vehicles, information tracking and support node data acquisition system, data storage center, data parsing processing analysis system and aviation support node comprehensive display module, the position information tracking and support node data acquisition system includes a position information tracking module and a support node data acquisition module, the support node data acquisition module collects aircraft action events, flight support special vehicle position data, support data and transmits them to the data parsing processing analysis system for data processing and sorting out aviation support node data. The present invention monitors the position of airport aircraft and flight support special vehicles in real time based on multi-source data fusion technology, can accurately and automatically collect the time node of flight support, improve the airport operation management capability, and improve the airport transportation volume and safety assurance capability.

Description

Technical Field

[0001] The present invention relates to flight support node data processing, and in particular to a flight support node collection system and method based on multi-source heterogeneous data fusion. Background Art

[0002] With the rapid development of the civil aviation industry, airports are generally facing capacity saturation or overload operation. Passenger and cargo traffic are growing faster and faster, and the efficiency of ground support for aircraft is becoming increasingly prominent. After the flight arrives on the ground, the airport operation center and related departments need to quickly obtain the status of the aircraft approach node to ensure that the flight support is fast, efficient and safe. Under the existing resource allocation conditions, ensuring flight punctuality and improving service quality have become key steps to ensure the safe and efficient operation of the airport.

[0003] The flight support link mainly refers to the ground support nodes involved in the entire process from flight landing to take-off. The support nodes mainly include passenger elevator operation, shuttle bus operation, in-flight catering operation, aviation fuel filling operation, cabin cleaning operation, cargo and mail loading and unloading operation, clean water and sewage operation, etc. This node is also called a milestone event. For its schematic diagram, see Figure 5 The completion of each link is inseparable from the corresponding support vehicles, mainly including more than ten kinds of special vehicles such as passenger elevators, food trucks, cleaning trucks, and refueling trucks, as shown by the flight support of the aircraft at the apron.

[0004] At present, there are two main ways to collect information about airport flight ground support nodes in my country: manual collection and collection based on video analysis technology. However, there are the following disadvantages in manually inputting information about flight ground support nodes: (1) it increases the workload of airport flight support staff, which in turn affects the quality of work; (2) the real-time nature of the data is poor; (3) the false alarm rate and missed alarm rate are high, and the data is of poor reference value; (4) it is easily affected by weather conditions, such as cold weather, heavy rain and other severe weather conditions. The technical means of using cameras to collect video data and then identify flight support nodes through video analysis still has many disadvantages, mainly manifested in: (1) it is easily affected by weather, such as rain, snow, haze and other bad weather will affect the quality of video data; (2) affected by the camera configuration, cameras of different models and precisions have a greater impact on the collected data, and the collected data results are inconsistent; (3) the installation location and layout of remote camera positions are difficult to set up; (4) relying solely on video data collected by cameras, it is impossible to fully cover all nodes in the flight support process; and only through the technical means of video data analysis, the node collection of flight support can only automatically obtain about 60-70% of the node information, and cannot completely replace manual work. Summary of the invention

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to provide a flight support node acquisition system and method based on multi-source heterogeneous data fusion, which can replace manual operations and reduce the limitations of video analysis technology. At the same time, it can improve the airport operation management capabilities, perceive the airport operation status and adjust the working mode, actively and proactively achieve airport operation resource load balancing, and improve the airport's transportation volume and safety assurance capabilities.

[0006] The purpose of the present invention is achieved through the following technical solutions:

[0007] A flight support node collection system based on multi-source heterogeneous data fusion includes an aircraft, a flight support special vehicle, a position information tracking and support node data collection system, a data storage center, a data parsing and processing analysis system, and an aviation support node comprehensive display module. The position information tracking and support node data collection system includes a position information tracking module and a support node data collection module. The position information tracking module is used to collect aircraft position data and transmit it to the data storage center and the data parsing and processing analysis system. The data parsing and processing analysis system determines whether the aircraft is located in the apron according to its position data; the support node data collection module is used to collect aircraft action events, flight support special vehicle position data, and support data and transmit them to the data storage center and the data parsing and processing analysis system. The aircraft action events include opening and closing cabin doors. The support data of flight support special vehicles includes type information, position information, and support service data. The data parsing and processing analysis system performs data processing based on the data of the support node data collection module and classifies and sorts the support node data according to the support nodes to obtain the aviation support node data. The aviation support node comprehensive display module displays the aviation support node data.

[0008] In order to better realize the flight support node collection system of the present invention, the position information tracking module includes ADS-B equipment, secondary radar and surface surveillance radar. The ADS-B equipment is installed in the aircraft, and the secondary radar and surface surveillance radar are installed near the airport apron. The ADS-B equipment is used to collect data including the position, altitude, heading, ground speed, vertical speed, and call sign of the aircraft. The secondary radar and surface surveillance radar are used to collect information including the aircraft number, altitude, direction, and the position of the aircraft and the apron; the support node data collection module includes sensor equipment, Beidou / GPRS positioning vehicle terminal and ACARS ground receiver. The sensor equipment and Beidou / GPRS positioning vehicle terminal are deployed in special vehicles for flight support, and the ACARS ground receiver is deployed at a corresponding position near the airport or apron.

[0009] Preferably, the location information tracking module also includes an aircraft motion sensor system, which includes a door opening and closing sensor, a brake sensor, a landing gear sensor, and a wheel block sensor. The sensor equipment includes an infrared ranging sensor, a laser ranging sensor, and a gravity sensor. The ACARS ground receiver interacts and communicates with the flight support special vehicle and the aircraft respectively.

[0010] Preferably, the location information tracking and support node data collection system is located at the physical layer of the system, the data storage center is located at the data layer of the system, the data parsing and analysis system is located at the data processing layer of the system, and the aviation support node comprehensive display module is located at the application layer of the system.

[0011] Preferably, the flight support special vehicles include fresh water filling vehicles, sewage collection vehicles, refueling vehicles, cargo, mail and luggage vehicles, catering vehicles, cleaning vehicles, and bridge / passenger elevator vehicles; the cabin door opening and closing sensors include passenger door sensors and cargo door sensors.

[0012] A flight support node collection method based on multi-source heterogeneous data fusion, the method is as follows:

[0013] A. Obtain the position data of the aircraft through monitoring equipment including ADS-B equipment, secondary radar and surface surveillance radar; the secondary radar and surface surveillance radar cover the apron, and determine whether the aircraft has taxied into the apron by combining the aircraft position data and the apron position information. The secondary radar and surface surveillance radar verify the status of the aircraft having taxied into the apron; if it is determined that the aircraft has taxied into the apron, proceed to step B;

[0014] B. Collect the vehicle location data of the flight support special vehicle based on the Beidou / GPRS positioning vehicle terminal and the ACARS ground receiver, analyze the vehicle location data of the flight support special vehicle and determine whether the corresponding flight support special vehicle has entered the apron and entered the flight support state; if the flight support special vehicle has entered the flight support state, collect the support mission information in combination with the ACARS ground receiver, the sensor equipment in the flight support special vehicle and the Beidou / GPRS positioning vehicle terminal, and the support mission information includes the support mission name and the start and end time of the support mission;

[0015] C. Combine the support mission information of all flight support special vehicles to form aviation support node data, and the aviation support node data is displayed through the aviation support node comprehensive display module.

[0016] In order to better implement the flight support node collection method of the present invention, the multi-source heterogeneous data fusion method of the aircraft position data in step A, the vehicle position data in step B, and the support mission information collected is as follows:

[0017] First, data preprocessing is performed on data of the same type, then feature extraction is performed on data of the same type, and then data of the same type is fused and the fused data is output.

[0018] Preferably, the data preprocessing method in the flight support node collection method of the present invention is as follows:

[0019] Data preprocessing includes data denoising, abnormal data cleaning, and redundancy processing. Redundancy processing uses correlation analysis processing, and the method is as follows:

[0020] Calculate the correlation coefficient between attributes X and Y to estimate the correlation between the two attributes, that is:

[0021]

[0022] Where m is the number of attributes, x and y are the values ​​of attributes X and Y respectively. and are the means of attributes X and Y, respectively, and σ X and σ Y are the standard deviations of X and Y, respectively, and is the sum of the XY cross products, where -1 ≤ R X,Y ≤1, and R X,Y The closer to 0, the smaller the correlation between X and Y; if R X,Y is 0, then X and Y are independent;

[0023] The correlation between the attributes is obtained through the above correlation analysis. If the correlation between two attributes is large, one attribute is removed from the two attributes, and the remaining attribute is used to replace the two original attributes with large correlation to reduce the redundancy of the data.

[0024] Preferably, the special vehicles for flight support include fresh water filling vehicles, sewage collection vehicles, refueling vehicles, cargo, mail and luggage vehicles, catering vehicles, cleaning vehicles, and bridge / passenger elevator vehicles.

[0025] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0026] (1) The present invention monitors the location of airport aircraft and flight support special vehicles in real time based on multi-source data fusion technology, and configures corresponding sensors on special vehicles to accurately and automatically collect the time nodes of flight support, thereby reducing the errors in manual data entry, improving the airport's operation management capabilities, and improving the airport's transportation volume and safety assurance capabilities.

[0027] (2) The present invention collects real-time location data of aircraft and vehicles through ADS-B receiving equipment, field monitoring radar, multi-point positioning, secondary radar, Beidou / GPS positioning vehicle-mounted terminal, automatically collects flight node support node data through ACARS equipment and various types of sensor equipment, and after fusing the collected multi-source heterogeneous data, visualizes the data of flight support nodes. This technical means can effectively reduce the limitations of video acquisition node technology, improve the accuracy and coverage of node acquisition, and enhance the automation level of airport flight support node acquisition.

[0028] (3) The present invention uses multi-source heterogeneous data fusion technology to process, analyze and visualize flight support node data, which is economical and efficient, realizes the automation of airport flight nodes, effectively saves the personnel cost of manual data collection, greatly improves the efficiency of node collection and improves the accuracy of node data.

[0029] (4) The present invention innovatively utilizes various types of sensor equipment to install different sensor equipment on special vehicles that provide support for different flights. The sensor data information can be used to collect flight support nodes that cannot be collected by video.

[0030] (5) The present invention innovatively realizes air-ground collaborative integration by processing and analyzing the flight's ADS-B data, secondary radar and scene surveillance radar data, and achieves automation and intelligence of flight support node collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a principle structure block diagram of the flight support node collection system in the embodiment;

[0032] Figure 2 This is a schematic diagram of the system architecture of the flight support node collection system in the embodiment;

[0033] Figure 3 This is a schematic diagram of data transmission, storage and display of the flight support node collection system in the embodiment;

[0034] Figure 4 This is a schematic diagram of the workflow of the flight support node collection method in the embodiment;

[0035] Figure 5 This is a display diagram of the flight support node in the embodiment;

[0036] Figure 6 It is a flow chart of multi-source heterogeneous data fusion of the flight support node collection method in the embodiment;

[0037] Figure 7 This is a display effect diagram of the comprehensive display module of the aviation support node. DETAILED DESCRIPTION

[0038] The present invention is further described in detail below in conjunction with embodiments:

[0039] Example

[0040] like Figure 1 to Figure 7 As shown, a flight support node collection system based on multi-source heterogeneous data fusion includes an aircraft, a flight support special vehicle, a position information tracking and support node data collection system, a data storage center, a data parsing and processing analysis system, and an aviation support node comprehensive display module. The position information tracking and support node data collection system includes a position information tracking module and a support node data collection module. The position information tracking module is used to collect aircraft position data and transmit it to the data storage center and the data parsing and processing analysis system. The data parsing and processing analysis system determines whether the aircraft is located in the apron according to its position data; the support node data collection module is used to collect aircraft action events, flight support special vehicle position data, and support data and transmit them to the data storage center and the data parsing and processing analysis system. The aircraft action events include opening and closing cabin doors. The support data of flight support special vehicles includes type information, position information, and support service data. The data parsing and processing analysis system processes data according to the data of the support node data collection module and classifies and organizes the support node data according to the support nodes to obtain the aviation support node data. The aviation support node comprehensive display module displays the aviation support node data.

[0041] Preferably, the location information tracking module includes an ADS-B device and a secondary radar and a surface surveillance radar. The ADS-B device is installed in the aircraft, and the secondary radar and the surface surveillance radar are installed near the airport apron. The ADS-B device is used to collect data including the position, altitude, heading, ground speed, vertical speed, and call sign of the aircraft. The secondary radar and the surface surveillance radar are used to collect information including the aircraft number, altitude, direction, and location of the aircraft and the apron. Preferably, the security node data acquisition module includes a sensor device, a Beidou / GPRS positioning vehicle terminal, and an ACARS ground receiver. The sensor device and the Beidou / GPRS positioning vehicle terminal are arranged in the flight support special vehicle (the Beidou / GPS positioning vehicle terminal can collect data information including the license plate number, vehicle type, current driving status, vehicle speed, direction, executed tasks, driver, driver status, warning status, etc. of the flight support special vehicle), and the ACARS ground receiver is arranged at a corresponding position near the airport or apron. ACARS ground receiver (English full name Aircraft Communications Addressing and Reporting System, abbreviation: ACARS, Chinese full name Aircraft Communications Addressing and Reporting System) is a digital data link system that transmits short messages (messages) between aircraft and ground stations via radio or satellite. On the aircraft, the ACARS ground receiver consists of an avionics computer called ACARS Management Unit (MU) and a Control Display Unit (CDU). MU is used to send and receive VHF radio digital messages from the ground. On the ground, the ACARS ground receiver consists of a network of multiple radio transceivers, which can receive (or send) data link messages. The ACARS ground receiver automatically detects and reports changes in the aircraft during the main flight phases (out of the gate; off the ground; on the ground; into the gate, referred to as OOOI in the industry). These OOOI events are confirmed by the ACARS management unit through the output signals of various sensors on the aircraft (such as the switch sensors on the door, parking brake and landing gear). At the beginning of each flight phase, ACARS sends a digital message to the ground, which includes the name of the flight phase and the time it occurs.

[0042] Preferably, the location information tracking module also includes an aircraft motion sensor system, which includes a door opening and closing sensor, a brake sensor, a landing gear sensor, and a wheel stop sensor. The sensor equipment includes an infrared ranging sensor, a laser ranging sensor, and a gravity sensor. The ACARS ground receiver interacts and communicates with the flight support special vehicle and the aircraft respectively.

[0043] See also Figure 2 When the flight support node collection system of this embodiment is combined into an overall system, the location information tracking and support node data collection system is located at the physical layer of the system, the data storage center is located at the data layer of the system, the data parsing and analysis system is located at the data processing layer of the system, and the aviation support node comprehensive display module is located at the application layer of the system.

[0044] Preferably, the special vehicles for flight support include fresh water filling vehicles, sewage collection vehicles, refueling vehicles, cargo, mail and luggage vehicles, catering vehicles, cleaning vehicles, and bridge / passenger elevator vehicles; and the door opening and closing sensors include passenger door sensors and cargo door sensors.

[0045] A flight support node collection method based on multi-source heterogeneous data fusion, the method is as follows:

[0046] A. Obtain the position data of the aircraft through monitoring equipment including ADS-B equipment, secondary radar and surface surveillance radar; the secondary radar and surface surveillance radar cover the apron, and determine whether the aircraft has taxied into the apron by combining the aircraft position data and the apron position information. The secondary radar and surface surveillance radar verify the status of the aircraft having taxied into the apron; if it is determined that the aircraft has taxied into the apron, proceed to step B;

[0047] B. Based on the Beidou / GPRS positioning vehicle terminal and ACARS ground receiver, the vehicle location data of flight support special vehicles are collected. Flight support special vehicles include fresh water vehicles, sewage collection vehicles, refueling vehicles, cargo and mail luggage vehicles, catering vehicles, cleaning vehicles, and bridge / passenger elevator vehicles. The vehicle location data of flight support special vehicles are analyzed to determine whether the corresponding flight support special vehicles enter the apron and enter the flight support state; if the flight support special vehicle enters the flight support state, the support mission information is collected in combination with the ACARS ground receiver, the sensor equipment in the flight support special vehicle, and the Beidou / GPRS positioning vehicle terminal. The support mission information includes the name of the support mission and the start and end time of the support mission.

[0048] After analyzing the functional attributes of flight support special vehicles, sensor equipment is installed on special vehicles to collect node information data of flight support special vehicles, and ACARS ground equipment is installed on the top of the airport air traffic control building or in an appropriate location to obtain node data information of flight OOOI events and door opening and closing. Sensor equipment and ACARS ground equipment are located in the physical layer of the system, and the node data information of flight support special vehicles and flight OOOI events and door opening and closing are located in the data layer of the system.

[0049] C. Combine the support mission information of all flight support special vehicles to form aviation support node data, which is displayed through the aviation support node comprehensive display module (visual display of flight node data, use high-precision airport surface geographic information data according to the needs of flight node real-time data, and finally visualize the flight support node data information, see Figure 7 ). All data information of the flight support node is transmitted to the data storage center through the network for storage, and the data is parsed, processed, analyzed and managed by the data parsing and analysis system located in the data processing layer combined with high-precision airport surface geographic information data. Multi-source heterogeneous data has the characteristics of data distributed in different systems or platforms, the amount of data on each data platform is very large, and the data quality of different platforms is inconsistent. Structured data refers to highly organized and neatly formatted data, also known as quantitative data, which can be represented by data or a unified structure; while unstructured data refers to data that is not highly organized and neatly formatted.

[0050] According to a preferred embodiment of the flight support node collection method of this embodiment, the multi-source heterogeneous data fusion method collected by the aircraft position data in step A, the vehicle position data in step B, and the support mission information is as follows:

[0051] First, data preprocessing is performed on data of the same type, then feature extraction is performed on data of the same type, and then data of the same type is fused and the fused data is output.

[0052] When performing data preprocessing, the data preprocessing in this embodiment can be performed in the following manner:

[0053] Data preprocessing includes data denoising, abnormal data cleaning, and redundancy processing. Redundancy processing uses correlation analysis processing, and the method is as follows:

[0054] Calculate the correlation coefficient between attributes X and Y to estimate the correlation between the two attributes, that is:

[0055]

[0056] Where m is the number of attributes, x and y are the values ​​of attributes X and Y respectively. and are the means of attributes X and Y, respectively, and σ X and σ Y are the standard deviations of X and Y, respectively, and is the sum of the XY cross products, where -1 ≤ R X,Y ≤1, and R X,Y The closer to 0, the smaller the correlation between X and Y; if R X,Y is 0, then X and Y are independent;

[0057] The correlation between the attributes is obtained through the above correlation analysis. If the correlation between two attributes is large, one attribute is removed from the two attributes, and the remaining attribute is used to replace the two original attributes with large correlation to reduce the redundancy of the data.

[0058] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A flight support node acquisition system based on multi-source heterogeneous data fusion, including aircraft and flight support special vehicles, characterized in that: It also includes a position information tracking and support node data collection system, a data storage center, a data parsing and processing analysis system, and an aviation support node comprehensive display module. The position information tracking and support node data collection system includes a position information tracking module and a support node data collection module. The position information tracking module is used to collect aircraft position data and transmit it to the data storage center and the data parsing and processing analysis system. The data parsing and processing analysis system determines whether the aircraft is located on the apron based on the aircraft's position data. The support node data acquisition module is used to collect aircraft action events, location data of flight support special vehicles, and support data and transmit them to the data storage center and the data parsing and processing analysis system. The support node data acquisition module includes sensor equipment. The aircraft action events include opening and closing cabin doors. The support data of flight support special vehicles include type information, location information, and support service data. The data parsing and processing analysis system processes data according to the data of the support node data acquisition module and classifies and organizes the support node data according to the support nodes to obtain aviation support node data. The aviation support node comprehensive display module displays the aviation support node data; the position information tracking module also includes an aircraft action sensor system. The aircraft action sensor system includes a cabin door opening and closing sensor, a brake sensor, a landing gear sensor, and a wheel block sensor. The sensor equipment includes an infrared ranging sensor, a laser ranging sensor, and a gravity sensor; the ACARS ground receiver interacts and communicates with the flight support special vehicles and the aircraft respectively.

2. The flight support node acquisition system based on multi-source heterogeneous data fusion according to claim 1 is characterized in that: The location information tracking module includes ADS-B equipment, secondary radar and surface surveillance radar. The ADS-B equipment is installed in the aircraft, and the secondary radar and surface surveillance radar are installed near the airport apron. The ADS-B equipment is used to collect data including aircraft position, altitude, heading, ground speed, vertical speed, and call sign. The secondary radar and surface surveillance radar are used to collect information including aircraft number, altitude, direction, and aircraft and apron location information; the support node data acquisition module also includes Beidou / GPRS positioning vehicle-mounted terminal and ACARS ground receiver. The sensor equipment and Beidou / GPRS positioning vehicle-mounted terminal are deployed in special vehicles for flight support, and the ACARS ground receiver is deployed at a corresponding location near the airport or apron.

3. The flight support node acquisition system based on multi-source heterogeneous data fusion according to claim 2 is characterized in that: The location information tracking and support node data collection system is located at the physical layer of the system, the data storage center is located at the data layer of the system, the data parsing and analysis system is located at the data processing layer of the system, and the aviation support node comprehensive display module is located at the application layer of the system.

4. The flight support node acquisition system based on multi-source heterogeneous data fusion according to claim 1 is characterized in that: The special vehicles for flight support include fresh water filling vehicles, sewage collection vehicles, refueling vehicles, cargo, mail and luggage vehicles, catering vehicles, cleaning vehicles, and bridge / passenger elevator vehicles; the cabin door opening and closing sensors include passenger door sensors and cargo door sensors.

5. A flight support node collection method using the flight support node collection system of claim 1, characterized in that: The method is as follows: A. Obtain the position data of the aircraft through monitoring equipment including ADS-B equipment, secondary radar and surface surveillance radar; the secondary radar and surface surveillance radar cover the apron, and determine whether the aircraft has taxied into the apron by combining the aircraft position data and the apron position information. The secondary radar and surface surveillance radar verify the status of the aircraft having taxied into the apron; if it is determined that the aircraft has taxied into the apron, proceed to step B; B. Collect the vehicle location data of flight support special vehicles based on Beidou / GPRS positioning vehicle terminals and ACARS ground receivers, analyze the vehicle location data of flight support special vehicles and determine whether the corresponding flight support special vehicles have entered the apron and entered the flight support state; If the flight support special vehicle enters the flight support state, the support mission information is collected in combination with the ACARS ground receiver, the sensor equipment in the flight support special vehicle, and the Beidou / GPRS positioning vehicle terminal. The support mission information includes the name of the support mission and the start and end time of the support mission; C. Combine the support mission information of all flight support special vehicles to form aviation support node data, and the aviation support node data is displayed through the aviation support node comprehensive display module.

6. The flight support node acquisition method based on multi-source heterogeneous data fusion according to claim 5 is characterized by: The method for fusing the multi-source heterogeneous data collected from the aircraft position data in step A, the vehicle position data in step B, and the support mission information is as follows: First, data preprocessing is performed on data of the same type, then feature extraction is performed on data of the same type, and then data of the same type is fused and the fused data is output.

7. The flight support node acquisition method based on multi-source heterogeneous data fusion according to claim 6 is characterized by: The data preprocessing method is as follows: Data preprocessing includes data denoising, abnormal data cleaning, and redundancy processing. Redundancy processing uses correlation analysis processing, and the method is as follows: Calculate the correlation coefficient between attributes X and Y to estimate the correlation between the two attributes, that is: Where m is the number of attributes, x and y are the values ​​of attributes X and Y respectively. and are the means of attributes X and Y, respectively, and σ X and σ Y are the standard deviations of X and Y, respectively, and is the sum of the XY cross products, where -1 ≤ R X,Y ≤1, and R X,Y The closer to 0, the smaller the correlation between X and Y; if R X,Y is 0, then X and Y are independent; The correlation between the attributes is obtained through the above correlation analysis. If the correlation between two attributes is large, one attribute is removed from the two attributes, and the remaining attribute is used to replace the two original attributes with large correlation to reduce the redundancy of the data.

8. The flight support node acquisition method based on multi-source heterogeneous data fusion according to claim 5 is characterized by: The special vehicles for flight support include fresh water vehicles, sewage collection vehicles, refueling vehicles, cargo, mail and luggage vehicles, catering vehicles, cleaning vehicles, and bridge / passenger elevator vehicles.

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