CN111731301A

CN111731301A - Vehicle, vehicle machine equipment and driving time optimization processing method thereof

Info

Publication number: CN111731301A
Application number: CN201910219112.9A
Authority: CN
Inventors: 时红仁
Original assignee: Shanghai Pateo Electronic Equipment Manufacturing Co Ltd
Current assignee: Shanghai Pateo Electronic Equipment Manufacturing Co Ltd
Priority date: 2019-03-21
Filing date: 2019-03-21
Publication date: 2020-10-02

Abstract

The application relates to the technical field of vehicle networking, and provides a vehicle, a vehicle equipment and a driving time optimization processing method thereof. According to the traffic condition automatic identification method and device, the traffic condition can be automatically identified, congestion judgment is carried out according to the driving route of the user, and related entertainment items or working items and the like are recommended to the user when the total congestion consumption is combined, so that the driving mood of the user is changed, and the discomfortable emotions such as road rage and the like are avoided.

Description

Vehicle, vehicle machine equipment and driving time optimization processing method thereof

Technical Field

The application relates to the technical field of vehicle networking, in particular to a vehicle machine device and a driving time optimization processing method thereof, and the vehicle machine device and a vehicle applying the driving time optimization processing method.

Background

With the continuous improvement of living standard, automobiles are more and more common in the life of people, and gradually become one of indispensable vehicles in the life of people in cities and villages.

The 2017 year global traffic situation survey report issued by traffic data company Inrix shows that los angeles in the united states becomes the "globally most congested city" for 6 consecutive years. The survey covers 1360 cities in 38 countries worldwide. It is reported that the los angeles drivers are 102 hours full-year stuck on the road, traffic congestion causes annual per-year economic losses to local drivers of $ 2828, and the total loss in los angeles amounts to $ 192 billion. The survey report showed that the first 5 cities that were globally the most congested in 2017 were los angeles, moscow, new york, saint paul and san francisco in that order. However, the investigation does not include countries such as china, japan, korea, india and pakistan. The Inrix first economic agent Greenham-Cukson shows that traffic jam threatens the economic development of the United states, reduces the quality of life of people, and an intelligent transportation system must be developed by investment to effectively solve the challenge.

In summary, traffic congestion is a global problem, but the problem cannot be solved under the current circumstances, so that a user needs to adjust a driving mode and mood by himself to reduce the use experience and the vehicle using safety brought to the user by congestion as much as possible.

In view of the problems of the prior art, those skilled in the art are always seeking solutions.

Disclosure of Invention

The invention aims to provide a vehicle, a vehicle-mounted device and a driving time optimization processing method thereof, which can automatically identify traffic road conditions, carry out congestion judgment according to driving routes of users, and recommend related entertainment items or work items and the like to the users by combining congestion total consumption so as to change driving moods of the users and avoid causing unstable moods such as road rage and the like.

In order to solve the above technical problem, the present application provides a driving time optimization method, as one embodiment, the driving time optimization method includes:

the vehicle-mounted equipment acquires a current travel route;

judging whether the travel route has congestion road conditions or not;

if the congested road conditions exist, calculating the total time consumed by congestion required by the congested road conditions;

calculating available effective time according to the total congestion time;

and recommending corresponding target items to the user according to the effective time so as to optimize the driving time of the user.

As one implementation manner, the car machine device obtains a current travel route through navigation software.

As one embodiment, the step of acquiring, by the car machine device, the current travel route specifically includes:

acquiring the current position of a vehicle and a travel plan of a user;

and determining the current travel route according to the current position of the vehicle and the travel plan.

As one of the implementation manners, the in-vehicle device identifies the current location of the vehicle through the vehicle-mounted positioning module or the intelligent device connected with the vehicle.

As one implementation manner, the car-on-board device obtains a current travel route from voice information received by a microphone and input by a user.

As an implementation manner, the step of calculating the total congestion time required by the congested road condition specifically includes:

and the vehicle equipment acquires the reference consumed time of the congested road condition through the vehicle networking network, and the reference consumed time is used as the total congested time.

the vehicle equipment acquires the road section length of the congested road condition;

and calculating the total time consumption of the congestion required by the vehicle to pass through according to the road section length.

Real-time targeted items include, as one of the embodiments, listening to music, watching movies, learning, listening to news, and/or processing meetings.

In order to solve the technical problem, the present application further provides a car-mounted device, as one of the implementation manners, the car-mounted device includes a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program, so as to implement the driving time optimization processing method.

In order to solve the technical problem, the present application further provides a vehicle, as one embodiment, the vehicle is configured with the in-vehicle device as described above.

According to the vehicle, the vehicle equipment and the driving time optimization processing method thereof, the vehicle equipment acquires a current travel route, judges whether congestion road conditions exist in the travel route, calculates total congestion time consumption required by the congestion road conditions if the congestion road conditions exist, calculates available effective time according to the total congestion time consumption, and recommends corresponding target items to a user according to the effective time so as to optimize the driving time of the user. According to the traffic condition automatic identification method and device, the traffic condition can be automatically identified, congestion judgment is carried out according to the driving route of the user, and related entertainment items or working items and the like are recommended to the user when the total congestion consumption is combined, so that the driving mood of the user is changed, and the discomfortable emotions such as road rage and the like are avoided.

The foregoing description is only an overview of the technical solutions of the present application, and in order to make the technical means of the present application more clearly understood, the present application may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present application more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.

Drawings

Fig. 1 is a schematic flow chart of an embodiment of a driving time optimization processing method according to the present application.

Fig. 2 is a schematic block diagram of the car machine device according to the present application.

Detailed Description

To further illustrate the technical means and effects of the present application for achieving the intended application purpose, the following detailed description is provided with reference to the accompanying drawings and preferred embodiments for describing specific embodiments, methods, steps, features and effects of the vehicle, the vehicle-mounted device and the driving time optimization method thereof according to the present application.

The foregoing and other technical matters, features and effects of the present application will be apparent from the following detailed description of preferred embodiments, which is to be read in connection with the accompanying drawings. While the present application has been described in terms of specific embodiments and examples for achieving the desired objects and objectives, it is to be understood that the invention is not limited to the disclosed embodiments, but is to be accorded the widest scope consistent with the principles and novel features as defined by the appended claims.

Referring to fig. 1, fig. 1 is a schematic flow chart illustrating an embodiment of a driving time optimization method according to the present application.

The driving time optimization processing method according to the present embodiment may include, but is not limited to, the following steps.

Step S101, the vehicle-mounted equipment acquires a current travel route;

step S102, judging whether the travel route has congestion road conditions or not;

step S103, if congestion road conditions exist, calculating the total time consumed by congestion required by the congestion road conditions; if no congested road conditions exist, the processing is not carried out, or a user common music list is played;

step S104, calculating available effective time according to the total congestion time;

and step S105, recommending corresponding target items to the user according to the effective time so as to optimize the driving time of the user.

It should be particularly noted that the driving time optimization processing method of the embodiment is also applicable to user intelligent terminals such as mobile phones and wearable devices, and only needs to judge the road condition according to the travel of the user and give out related recreation suggestions, so that the driving time optimization processing method can assist the user in adjusting the driving mood and emotion of the congested road condition to a certain extent, and avoid bringing potential danger to the user.

It is easy to understand that, the step of acquiring, by the in-vehicle device according to this embodiment, the current travel route specifically includes: the vehicle-mounted equipment acquires the current travel route through navigation software. The navigation software of the present embodiment may be a navigation software in the in-vehicle device, or a navigation software of a mobile phone connected to the in-vehicle device, which is not limited herein.

In addition, in a preferred embodiment, the step of acquiring, by the vehicle-mounted device, the current travel route specifically includes: acquiring the current position of a vehicle and a travel plan of a user; and determining the current travel route according to the current position of the vehicle and the travel plan. For example, if it is determined that the vehicle is on a certain road, a travel route of the vehicle within a certain time period may be determined.

It should be mentioned that, in the present embodiment, the vehicle-mounted device identifies the current location of the vehicle through the vehicle-mounted positioning module or the intelligent device connected to the vehicle. For example, the user makes a travel plan to Shenzhen on 10 month 1, and on 10 month 2, the in-vehicle device can judge that the user is already in the journey of Shenzhen.

It should be noted that, in the car-in-vehicle device according to this embodiment, the current travel route is acquired from the voice information received by the microphone and input by the user. It is understood that, for example, when the user walks on the a road, finds that the number of vehicles increases, and determines that there may be a congestion ahead, a voice command and a current travel route are sent to the in-vehicle device.

It is to be noted that, in the embodiment, the step of calculating the total congestion time required for the congested road condition specifically includes: and the vehicle equipment acquires the reference consumed time of the congested road condition through the vehicle networking network, and the reference consumed time is used as the total congested time.

It should be particularly noted that, the step of calculating the total congestion time required by the congested road condition in the embodiment specifically includes: the vehicle equipment acquires the road section length of the congested road condition; and calculating the total time consumption of the congestion required by the vehicle to pass through according to the road section length. For example, it may be calculated by dividing the length of the road section by the estimated speed.

It is readily understood that the real-time objective items of the present embodiment include listening to music, watching movies, learning, listening to news, and/or processing a work meeting.

According to the traffic condition automatic identification method and device, the traffic condition can be automatically identified, congestion judgment is carried out according to the driving route of the user, and related entertainment items or working items and the like are recommended to the user when the total congestion consumption is combined, so that the driving mood of the user is changed, and the discomfortable emotions such as road rage and the like are avoided.

Referring to fig. 2, the present application further provides a car-mounted device, as an implementation manner, the car-mounted device includes a memory 20 and a processor 21, where the memory 20 stores a computer program, and the processor 21 is configured to execute the computer program, so as to implement the driving time optimization processing method described above.

Specifically, the processor 21 according to this embodiment is configured to obtain a current travel route;

the processor 21 is configured to determine whether a congested road condition exists on the travel route;

if the congested road condition exists, the processor 21 is configured to calculate total congestion time required by the congested road condition;

the processor 21 is configured to calculate an available effective time according to the total congestion time;

the processor 21 is configured to recommend a corresponding target item to the user according to the effective time, so as to optimize the driving time of the user.

It is easily understood that the processor 21 in this embodiment is used to obtain the current travel route through the navigation software. The navigation software of the present embodiment may be a navigation software in the in-vehicle device, or a navigation software of a mobile phone connected to the in-vehicle device, which is not limited herein.

In addition, in a preferred embodiment, the processor 21 is configured to obtain a current location of the vehicle and a travel plan of the user; and determining the current travel route according to the current position of the vehicle and the travel plan. For example, if it is determined that the vehicle is on a certain road, a travel route of the vehicle within a certain time period may be determined.

It should be noted that the processor 21 in this embodiment is configured to identify a current location of the vehicle through a vehicle-mounted positioning module or an intelligent device connected to the vehicle. For example, the user makes a travel plan to Shenzhen on 10 month 1, and on 10 month 2, the in-vehicle device can judge that the user is already in the journey of Shenzhen.

It should be noted that the processor 21 according to this embodiment is configured to obtain the current travel route from the voice information received by the microphone and input by the user. It is understood that, for example, when the user walks on the a road, finds that the number of vehicles increases, and determines that there may be a congestion ahead, a voice command and a current travel route are sent to the in-vehicle device.

It should be noted that, in this embodiment, the processor 21 is configured to obtain the reference consumed time that has passed through the congested road condition through an internet of vehicles network, and use the reference consumed time as a total congestion consumed time.

It should be particularly noted that, in this embodiment, the processor 21 is configured to obtain a road segment length of the congested road condition; and calculating the total time consumption of the congestion required by the vehicle to pass through according to the road section length. For example, it may be calculated by dividing the length of the road section by the estimated speed.

The application further provides a vehicle, and as one embodiment of the vehicle, the vehicle is provided with the vehicle equipment as shown in fig. 2 and the embodiment of the vehicle.

In this embodiment, the in-vehicle device may be connected to a mobile phone or a cloud server, and may be connected to various internet of things, such as a car networking network, and specifically, may support a 3G communication network, a 4G communication network, a 5G communication network, a WIFI network, and the like.

It should be noted that the 5G communication network technology of the present embodiment may be a technology oriented to a scene, and the present application utilizes the 5G technology to play a key supporting role for a vehicle (especially an intelligent networked automobile), and simultaneously implements connection of people, objects or vehicles, and may specifically adopt the following three typical application scenarios.

The first is eMBB (enhanced Mobile Broadband), so that the user experience rate is 0.1-1 gpbs, the peak rate is 10gbps, and the traffic density is 10Tbps/km 2;

for the second ultra-reliable low-delay communication, the main index which can be realized by the method is that the end-to-end time delay is in the ms (millisecond) level; the reliability is close to 100%;

the third is mMTC (mass machine type communication), and the main index which can be realized by the application is the connection number density, 100 ten thousand other terminals are connected per square kilometer, and the connection number density is 10^6/km 2.

Through the mode, the characteristics of the super-reliable of this application utilization 5G technique, low time delay combine for example radar and camera etc. just can provide the ability that shows for the vehicle, can realize interdynamic with the vehicle, utilize the interactive perception function of 5G technique simultaneously, and the user can do an output to external environment, and the unable light can detect the state, can also do some feedbacks etc.. Further, the method and the device can also be applied to cooperation of automatic driving, such as cooperation type collision avoidance and vehicle formation among vehicles, so that the vehicle speed is integrally formed and the passing efficiency is improved.

In addition, the communication enhancement automatic driving perception capability can be achieved by utilizing the 5G technology, and the requirements of passengers in the automobile on AR (augmented reality)/VR (virtual reality), games, movies, mobile office and other vehicle-mounted information entertainment and high precision can be met. According to the method and the device, the downloading amount of the 3D high-precision positioning map at the centimeter level can be 3-4 Gb/km, the data volume of the map per second under the condition that the speed of a normal vehicle is limited to 120km/h (kilometer per hour) is 90 Mbps-120 Mbps, and meanwhile, the real-time reconstruction of a local map fused with vehicle-mounted sensor information, modeling and analysis of dangerous situations and the like can be supported.

It should be noted that the method and the device can also be applied to an automatic driving layer, can assist in realizing partial intelligent cloud control on the urban fixed route vehicles by utilizing a 5G technology, and can realize cloud-based operation optimization and remote display and control under specific conditions on unmanned vehicles in parks and ports.

In the present application, the above-mentioned system and method CAN be used in a vehicle system having a vehicle TBOX, i.e. the vehicle is a vehicle system that CAN have a vehicle TBOX, and CAN be further connected to a CAN bus of the vehicle.

In this embodiment, the CAN may include three network channels CAN _1, CAN _2, and CAN _3, and the vehicle may further include one ethernet network channel, where the three CAN network channels may be connected to the ethernet network channel through two in-vehicle networking gateways, for example, where the CAN _1 network channel includes a hybrid power assembly system, where the CAN _2 network channel includes an operation support system, where the CAN _3 network channel includes an electric dynamometer system, and the ethernet network channel includes a high-level management system, the high-level management system includes a human-vehicle-road simulation system and a comprehensive information collection unit that are connected as nodes to the ethernet network channel, and the in-vehicle networking gateways of the CAN _1 network channel, the CAN _2 network channel, and the ethernet network channel may be integrated in the comprehensive information collection unit; the car networking gateway of the CAN _3 network channel and the Ethernet network channel CAN be integrated in a man-car-road simulation system.

Further, the nodes connected to the CAN _1 network channel include: the hybrid power system comprises an engine ECU, a motor MCU, a battery BMS, an automatic transmission TCU and a hybrid power controller HCU; the nodes connected with the CAN _2 network channel are as follows: the system comprises a rack measurement and control system, an accelerator sensor group, a power analyzer, an instantaneous oil consumption instrument, a direct-current power supply cabinet, an engine water temperature control system, an engine oil temperature control system, a motor water temperature control system and an engine intercooling temperature control system; the nodes connected with the CAN _3 network channel are as follows: electric dynamometer machine controller.

The preferable speed of the CAN _1 network channel is 250Kbps, and a J1939 protocol is adopted; the rate of the CAN _2 network channel is 500Kbps, and a CANopen protocol is adopted; the rate of the CAN _3 network channel is 1Mbps, and a CANopen protocol is adopted; the rate of the Ethernet network channel is 10/100Mbps, and a TCP/IP protocol is adopted.

In this embodiment, the car networking gateway supports a 5G technology V2X car networking network, which may also be equipped with an IEEE802.3 interface, a DSPI interface, an eSCI interface, a CAN interface, an MLB interface, a LIN interface, and/or an I2C interface.

In this embodiment, for example, the IEEE802.3 interface may be used to connect to a wireless router to provide a WIFI network for the entire vehicle; the DSPI (provider manager component) interface is used for connecting a Bluetooth adapter and an NFC (near field communication) adapter and can provide Bluetooth connection and NFC connection; the eSCI interface is used for connecting the 4G/5G module and communicating with the Internet; the CAN interface is used for connecting a vehicle CAN bus; the MLB interface is used for connecting an MOST (media oriented system transmission) bus in the vehicle, and the LIN interface is used for connecting a LIN (local interconnect network) bus in the vehicle; the IC interface is used for connecting a DSRC (dedicated short-range communication) module and a fingerprint identification module. In addition, the application can merge different networks by mutually converting different protocols by adopting the MPC5668G chip.

In addition, the vehicle TBOX system, Telematics-BOX, of the present embodiment is simply referred to as a vehicle TBOX or a Telematics.

Telematics is a synthesis of Telecommunications and information science (information) and is defined as a service system that provides information through a computer system, a wireless communication technology, a satellite navigation device, and an internet technology that exchanges information such as text and voice, which are built in a vehicle. In short, the vehicle is connected to the internet (vehicle networking system) through a wireless network, and various information necessary for driving and life is provided for the vehicle owner.

In addition, Telematics is a combination of wireless communication technology, satellite navigation system, network communication technology and vehicle-mounted computer, when a fault occurs during vehicle running, the vehicle is remotely diagnosed by connecting a service center through wireless communication, and the computer built in the engine can record the state of main parts of the vehicle and provide accurate fault position and reason for maintenance personnel at any time. The vehicle can receive information and check traffic maps, road condition introduction, traffic information, safety and public security services, entertainment information services and the like through the user communication terminal, and in addition, the vehicle of the embodiment can be provided with electronic games and network application in a rear seat. It is easy to understand that, this embodiment provides service through Telematics, can make things convenient for the user to know traffic information, the parking stall situation that closes on the parking area, confirms current position, can also be connected with the network server at home, in time knows electrical apparatus running condition, the safety condition and guest's condition of visiting etc. at home.

The vehicle according to this embodiment may further include an Advanced Driver Assistance System (ADAS) that collects environmental data inside and outside the vehicle at the first time using the various sensors mounted on the vehicle, and performs technical processing such as identification, detection, and tracking of static and dynamic objects, so that a Driver can recognize a risk that may occur at the fastest time, thereby attracting attention and improving safety. Correspondingly, the ADAS of the present application may also employ sensors such as radar, laser, and ultrasonic sensors, which can detect light, heat, pressure, or other variables for monitoring the state of the vehicle, and are usually located on the front and rear bumpers, side view mirrors, the inside of the steering column, or on the windshield of the vehicle. It is obvious that various intelligent hardware used by the ADAS function can access the V2X car networking network by means of an ethernet link to implement communication connection and interaction.

The host computer of the present embodiment vehicle may comprise suitable logic, circuitry, and/or code that may enable operation and/or functional operation of the five layers above the OSI model (Open System Interconnection, Open communication systems Interconnection reference model). Thus, the host may generate and/or process packets for transmission over the network, and may also process packets received from the network. At the same time, the host may provide services to a local user and/or one or more remote users or network nodes by executing corresponding instructions and/or running one or more applications. In various embodiments of the present application, the host may employ one or more security protocols.

In the present application, the network connection used to implement the V2X car networking network may be a switch, which may have AVB functionality (Audio Video brightening, meeting the IEEE802.1 set of standards), and/or include one or more unshielded twisted pair wires, each of which may have an 8P8C module connector.

In a preferred embodiment, the V2X vehicle networking network specifically comprises a vehicle body control module BCM, a power bus P-CAN, a vehicle body bus I-CAN, a combination instrument CMIC, a chassis control device and a vehicle body control device.

In this embodiment, the body control module BCM may integrate the functions of the car networking gateway to perform signal conversion, message forwarding, and the like between different network segments, i.e., between the power bus P-CAN and the body bus I-CAN, for example, if a controller connected to the power bus needs to communicate with a controller connected to the body bus I-CAN, the body control module BCM may perform signal conversion, message forwarding, and the like between the two controllers.

The power bus P-CAN and the vehicle body bus I-CAN are respectively connected with a vehicle body control module BCM.

The combination instrument CMIC is connected with a power bus P-CAN, and the combination instrument CMIC is connected with a vehicle body bus I-CAN. Preferably, the combination meter CMIC of the present embodiment is connected to different buses, such as a power bus P-CAN and a vehicle body bus I-CAN, and when the combination meter CMIC needs to acquire controller information that is hung on any bus, it is not necessary to perform signal conversion and message forwarding through a vehicle body control module BCM, so that gateway pressure CAN be reduced, network load CAN be reduced, and the speed of acquiring information by the combination meter CMIC CAN be increased.

The chassis control device is connected with the power bus P-CAN. The vehicle body control device is connected with a vehicle body bus I-CAN. In some examples, the chassis control device and the body control device CAN respectively broadcast data such as information to the power bus P-CAN and the body bus I-CAN, so that other vehicle-mounted controllers and other devices hung on the power bus P-CAN or the body bus I-CAN CAN acquire the broadcast information, and communication between the vehicle-mounted devices such as different controllers is realized.

In addition, the V2X car networking network of the vehicle of the embodiment may use two CAN buses, i.e., a power bus P-CAN and a car body bus I-CAN, and use the car body control module BCM as a gateway, and a structure that the combination meter CMIC is connected to both the power bus P-CAN and the car body bus I-CAN, so that an operation that information of the chassis control device or the car body control device is forwarded to the combination meter CMIC through the gateway when the combination meter CMIC is hung on one of the two buses in the conventional manner CAN be omitted, thereby reducing the pressure of the car body control module BCM as a gateway, reducing network load, and more conveniently sending information of vehicle-mounted devices hung on the plurality of buses, e.g., the power bus P-CAN and the car body bus I-CAN, to the combination meter CMIC for display and with strong information transmission real-time.

The application can be realized by the following principle and user scene:

1. vehicle passing through congested road section

2. The voice assistant of the vehicle-mounted device prompts that the road ahead is congested and the time of two songs is approximately congested, and recommends to play songs, or directly and automatically plays songs, and certainly, if the passengers have babies, the voice assistant can also play cradle songs and the like to sooth the moods of the babies;

3. when the user does not start navigation, the user can explore the road section five kilometers ahead of the current road, and when the user uses navigation, the user can obtain the planned path information and more accurately obtain the road section for calculation;

4. when the vehicle runs to the congested road section, the passing time is calculated according to the road speed of the real-time road condition, the number of songs is calculated according to the time, for example, one song in 4 minutes, then, the user can be informed of the time of two songs being congested or the time of 15 minutes being congested, and a knowledge lecture, a real-time radio station, an interest program of the user and the like are recommended.

Although the present application has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the application, and all changes, substitutions and alterations that fall within the spirit and scope of the application are to be understood as being included within the following description of the preferred embodiment.

Claims

1. A driving time optimization processing method is characterized by comprising the following steps:

the vehicle-mounted equipment acquires a current travel route;

judging whether the travel route has congestion road conditions or not;

calculating available effective time according to the total congestion time;

2. The travel time optimization processing method according to claim 1, wherein the vehicle-mounted device obtains a current travel route through navigation software.

3. The method for optimizing travel time according to claim 1, wherein the step of obtaining, by the vehicle-mounted device, the current travel route specifically includes:

acquiring the current position of a vehicle and a travel plan of a user;

4. The travel time optimization processing method according to claim 3, wherein the vehicle-mounted device identifies the current position of the vehicle through a vehicle-mounted positioning module or an intelligent device connected with the vehicle.

5. The method for optimizing travel time according to claim 1, wherein the in-vehicle device obtains a current travel route from voice information input by a user and received by a microphone.

6. A driving time optimization processing method according to any one of claims 1 to 5, wherein the step of calculating the total congestion time required for the congested road condition specifically includes:

7. A driving time optimization processing method according to any one of claims 1 to 5, wherein the step of calculating the total congestion time required for the congested road condition specifically includes:

8. A driving time optimization process according to any one of claims 1 to 5 wherein real-time objective events include listening to music, watching movies, learning, listening to news and/or processing meetings.

9. A vehicle-mounted device, characterized in that the vehicle-mounted device comprises a memory and a processor, the memory stores a computer program, and the processor is used for executing the computer program to realize the travel time optimization processing method according to any one of claims 1-8.

10. A vehicle, characterized in that it is equipped with the in-vehicle machine apparatus as claimed in claim 9.