CN113655801B - Automatic driving system architecture and tracking control method for intelligent vehicle in park - Google Patents

Abstract

The invention discloses a park intelligent vehicle automatic driving system architecture and a tracking control method, wherein the architecture comprises a switch, a computing platform, a bottom controller, a sensing device, a positioning device, a communication device and a man-machine interaction platform, and the man-machine interaction platform transmits information to the computing platform through the communication device; when the power supply system supplies power normally and completes initialization of parameters of the control system, the switch and the computing platform carry out information interaction, the computing platform is used for receiving a starting control instruction issued by the man-machine interaction platform, loading tracking map information under the condition that the vehicle state is normal, then judging whether the analysis of the vehicle position and the attitude information is accurate, after judging that the analysis is accurate, continuously judging whether the current position point of the vehicle is on an expected tracking track, under the condition that the judgment is 'yes', calculating an expected steering angle and an expected vehicle speed according to the expected tracking track and the current position of the vehicle, and sending the expected steering angle and the expected vehicle speed to the bottom layer controller through a serial port. The invention can realize safe, reliable and low-power consumption automatic driving task of intelligent vehicles in the park.

Description

Automatic driving system architecture and tracking control method for intelligent vehicle in park

Technical Field

The invention relates to the technical field of automatic driving, in particular to a park intelligent vehicle automatic driving system architecture and a tracking control method.

Background

The park scene has the characteristics of simpler road environment, high structuralization degree, more fixed driving route and the like, and is a landing application scene with important intelligent automobile automatic driving technology and minimum difficulty. At present, the park automatic driving technology is successfully applied to limited area scenes such as scenic spot sightseeing instead of walk, warehouse logistics distribution, park environmental sanitation cleaning and the like, and the landing and industrial application of the automatic driving technology are accelerated.

Campus autopilot technology also faces a number of challenges. In the aspect of an automatic driving system architecture, in order to facilitate system upgrading, expandability is an important factor to be considered in the design of the automatic driving system architecture, and along with the continuous improvement of the intelligent degree of a perception decision algorithm of the automatic driving system, the demand on the computing power of a hardware platform is also continuously improved. And the intelligent park vehicle is limited by the requirements of the vehicle volume and the vehicle endurance mileage, and the maximum power supply power of the automatic driving system equipment is restricted, so that the power supply system of the intelligent park vehicle is challenged for providing stable and reliable power for all equipment of the automatic driving system. Meanwhile, the control algorithm is required to reduce the computational power requirement while completing the driving task, and the method provides a challenge for realizing low-power consumption automatic driving in a park environment.

The existing automatic driving system can only carry out positioning through a global satellite navigation positioning system, and the automatic driving scene of a garden often has poor satellite positioning signals due to reasons such as tree shielding. Or for the route without the lane line in the park, the tracking driving capability is continuously kept by the automatic driving technology which cannot be supported by the camera lane line detection.

Disclosure of Invention

It is an object of the present invention to provide a park intelligent vehicle autopilot system architecture and tracking control method that overcomes or at least alleviates at least one of the above-mentioned deficiencies of the prior art.

In order to achieve the purpose, the invention provides a park intelligent vehicle automatic driving system architecture, which comprises a switch, a computing platform, a bottom controller, a sensing device, a positioning device, a communication device and a human-computer interaction platform, wherein the sensing device and the positioning device transmit information to the computing platform through the switch; the man-machine interaction platform transmits information to the computing platform through the communication equipment; the switch is in information interaction with the computing platform, and the underlying controller is in information interaction with the computing platform in a serial port connection mode;

the human-computer interaction platform comprises a tracking start-stop control module, a tracking map selection module and a control mode selection module, wherein the tracking start-stop control module is used for sending a start or stop control instruction, the tracking map selection module is used for sending a selected tracking map information loading instruction, the control mode selection module is used for sending a transverse or longitudinal control mode activation instruction, when a power supply system is normally powered and control system parameters are initialized, the computing platform is used for receiving the start control instruction, loading the tracking map information under the condition that the vehicle state is normal, then judging whether the analysis of the vehicle position and posture information is accurate, continuing judging whether the current position point of the vehicle is on an expected tracking track after judging that the analysis is accurate, and calculating an expected steering angle and an expected vehicle speed according to the expected tracking track and the current position of the vehicle under the condition that the judgment is 'yes', and sent to the underlying controller through a serial port.

Further, power supply system provides three independent power supply lines each other, is upper DC power supply bus, bottom DC power supply bus and AC power supply bus respectively, power supply system includes main power supply, auxiliary power supply line control unit, wherein, the main power supply charges through on-vehicle power supply, the auxiliary power supply charges through the main power supply, power supply line control unit includes:

a working voltage requirement judgment subunit for judging the working voltage requirement D_V；

The power consumption equipment working power requirement judgment subunit is used for judging the judgment result of the subunit according to the working voltage requirement and the normal working power requirement D of the power consumption equipment_PAnd rated power P₁Determining one of the power supply lines, wherein P₁And determining according to the rated power of the main power supply and the secondary power supply.

Further, the secondary power supply is connected with the primary power supply through an upper switch and a charging switch in sequence, voltage-stabilized power supplies a and B in the upper dc power supply bus are respectively connected between the upper switch and the charging switch and between the output terminals of the secondary power supply, the input terminal of the bottom dc power supply bus is connected between the primary power supply and the upper switch through a lower switch, an inverter is arranged between the output terminal of the ac power supply bus and the output terminal of the secondary power supply to output 220V ac power, and the power-on sequence includes:

preferentially closing a lower layer switch to provide 12V direct current for the bottom layer controller; secondly, starting a vehicle-mounted power source to charge a main power source; then closing an upper switch to provide 12V direct current for an upper direct current power supply bus, and closing a charging switch to charge an auxiliary power supply; finally, the inverter is started, and 220v voltage is provided through the alternating current power supply bus.

Further, the power consumption equipment working power requirement judgment subunit is judging D_VUnder the condition of 12V direct current, the power supply line is determined by the following three conditions:

situation one, D_P<P₁The power supply line is the bottom layer direct current power supply bus;

case two, D_P<P₁The power supply line is a stabilized voltage power supply A in the upper layer direct current power supply bus;

case two, D_P≥P₁The power supply line is a stabilized voltage power supply B in the upper layer direct current power supply bus;

the power consumption equipment working power requirement judgment subunit judges D_VIn the case of 220V AC, and D_P≥P₁And the power supply line is the alternating current power supply bus.

Further, the computing platform comprises:

a pre-aiming distance calculation unit for calculating the pre-aiming distance d according to the formula (3)_p：

In the formula, k_ρAdjustment factor, k, for curvature preview_vVehicle speed preview adjustment factor, Con₁A curvature adjusting factor is obtained, v is the current vehicle speed, and rho is the curvature of the current road point;

a pre-aim point selection unit for selecting a pre-aim point according to a desired tracking trajectory, a current position of the vehicle and d_pDetermining a preview point;

the vehicle speed control unit is used for determining the expected vehicle speed and the size of a transverse corner according to the detected obstacle situation on the front tracking track of the vehicle;

and the expected steering angle calculation unit is used for determining the size of the expected steering angle according to the curvature steering angle determined by the curvature of the track corresponding to the current waypoint and the tracking steering angle determined by the aiming point.

Further, the longitudinal vehicle speed control is carried out according to the obstacle condition on the tracking track in front of the vehicle detected by the sensing device, and the method specifically comprises the following steps:

in the case of no obstacle, the desired vehicle speed V is calculated from ρ by equation (5)_tar：

In the formula, k_vtFor ensuring that the desired vehicle speed is reduced with increasing curvature by a curvature speed adjustment factor, and k_vt>0；Con₂The constant for avoiding the overlarge target vehicle speed calculated when the curvature is very small is in a value range of 0-0.02; if V_{tar_0}>V_maxThen V is_tar＝V_maxIf | V_{tar_0}-v|>Δv_maxAnd (v + Δ v)_max)<V_maxThen V is_tar＝v+Δv_maxElse, V_tar＝V_{tar_0}，Δv_maxIs V and V_tarThe speed variation limit value v between which the riding comfort can be ensured_maxThe highest vehicle speed;

under the condition of obstacles, V is calculated according to different obstacle avoidance strategies_tarThe method specifically comprises the following steps:

if the distance S between the obstacle in front of the vehicle and the vehicle>(D_{b_min}+ Δ s), then the deceleration parking obstacle avoidance strategy is executed, and V is calculated by equation (6)_tar，

Is a V_tarLower shortest braking distance, a_maxIs the maximum braking deceleration;

in the formula (I), the compound is shown in the specification,

Δ s is the distance between the vehicle and the obstacle when the vehicle is stationaryA minimum safe distance therebetween;

if S is less than or equal to (D)_{b_min}+ Δ s), the obstacle avoidance strategy to be executed is executed, according to the curvature ρ corresponding to the planned lane change track_sCalculating V by equation (5)_tar。

Further, the tracking steering angle θ determined by the preview point is calculated by equation (9)_P：

e_i＝(1-k)δ_P+kδ_x (8)

In the formula, e_iInput deviation for transverse rotation angle control of i-th cycle, e_i-1Is the input deviation of the transverse rotation angle control of the i-1 th period, and is calculated by the formula (8), T is the control period, K_PFor PID control of the proportionality coefficient, K_iControlling the integral coefficient, K, for PID_dFor PID control of differential coefficient, k is in the value range [00.1]]Yaw angle difference weight of, delta_PIs the difference of the pre-collimation angle, delta_xIs the yaw angle difference.

The invention also provides a tracking control method of the automatic driving system of the intelligent vehicle in the park, which comprises the following steps:

step S1, supplying power through a power supply system, sending a starting control instruction to a computing platform through communication equipment by a man-machine interaction platform, and finishing parameter initialization of an automatic driving control system by the computing platform;

step S2, the computing platform judges whether the vehicle state is normal according to the vehicle state information acquired by the bottom controller through the vehicle gateway, if so, the computing platform enters step S3;

step S3, the computing platform loads the tracking map information according to the tracking map information selected by the man-machine interaction platform and conveyed by the switch, and judges whether the analysis of the vehicle position and attitude information is accurate or not according to the vehicle positioning information acquired by the positioning equipment and conveyed by the switch, if so, the step S4 is executed;

step S4, the computing platform judges whether the current position point of the vehicle is on the expected tracking track, if yes, the step S5 is carried out;

step S5, the calculation platform calculates an expected steering angle and an expected vehicle speed according to an expected tracking track and the current position of the vehicle, and sends the expected steering angle and the expected vehicle speed to the underlying controller;

step S6, the computing platform judges whether to adopt manual driving according to the control mode activating instruction of the man-machine interaction platform conveyed by the switch, if so, the computing platform drives by the manual driving, otherwise, the computing platform enters step S7;

and step S7, the computing platform judges whether the human-computer interaction platform sends a parking control instruction or reaches a target parking position, and if so, the computing platform sends a parking instruction to the underlying controller.

Further, the power supply system provides three independent power supply lines which are an upper layer direct current power supply bus, a bottom layer direct current power supply bus and an alternating current power supply bus respectively, the power supply system comprises a main power supply and an auxiliary power supply, wherein the main power supply is charged through a vehicle-mounted power source, the auxiliary power supply is charged through the main power supply, and the power supply line control method of the power supply system specifically comprises the following steps:

step S11, judging the working voltage demand D_V；

Step S12, in the step S11 determining D_VUnder the condition of 12V direct current, the power supply line is determined by the following three conditions:

situation one, D_P<P₁The power supply line is the bottom layer direct current power supply bus;

case two, D_P<P₁The power supply line is a stabilized voltage power supply A in the upper layer direct current power supply bus;

case two, D_P≥P₁The power supply line is a stabilized voltage power supply B in the upper layer direct current power supply bus;

d is judged at the step S11_VIn the case of 220V AC, and D_P≥P₁The power supply line is the alternating current power supply bus;

wherein, P₁The power supply is determined according to the rated power of the main power supply (11) and the secondary power supply (12).

Further, the step S5 specifically includes:

step S51, calculating the pre-aiming distance d according to the formula (3)_p：

In the formula, k_ρAdjustment factor, k, for curvature preview_vVehicle speed preview adjustment factor, Con₁A curvature adjusting factor is obtained, v is the current vehicle speed, and rho is the curvature of the current road point;

step S52, according to the expected tracking track, the current position of the vehicle and d_pDetermining a preview point;

step S53, determining the expected vehicle speed and the magnitude of the lateral rotation angle according to the detected obstacle situation on the tracking track in front of the vehicle, which specifically includes:

in the case of no obstacle, the desired vehicle speed V is calculated from ρ by equation (5)_tar：

In the formula, k_vtA speed adjustment factor for ensuring that the desired vehicle speed decreases with increasing curvature, and k_vt>0；Con₂The constant for avoiding the overlarge target vehicle speed calculated when the curvature is very small is in a value range of 0-0.02; if V_{tar_0}>V_maxThen V is_tar＝V_maxIf | V_{tar_0}-v|>Δv_maxAnd (v + Δ v)_max)<V_maxThen V is_tar＝v+Δv_maxElse, V_tar＝V_{tar_0}，Δv_maxIs V and V_tarThe speed variation limit value v between which the riding comfort can be ensured_maxThe highest vehicle speed;

with an obstacle situationThen, V is calculated according to different obstacle avoidance strategies_tarThe method specifically comprises the following steps:

if the distance S between the obstacle in front of the vehicle and the vehicle>(D_{b_min}+ Δ s), then the deceleration parking obstacle avoidance strategy is executed, and V is calculated by equation (6)_tar，

Is a V_tarLower shortest braking distance, a_maxAn acceleration upper limit value for ensuring riding comfort;

in the formula (I), the compound is shown in the specification,

Δ s is the minimum safe distance between the vehicle and the obstacle when the vehicle is stationary, a_maxIs the maximum braking deceleration;

if S is less than or equal to (D)_{b_min}+ Δ s), a lane change and obstacle avoidance strategy needs to be executed, and according to the curvature ρ corresponding to the planned lane change track_sCalculating V by equation (5)_tar；

Step S54 is a step of determining a tracking steering angle θ from a curvature steering angle determined from the curvature of the trajectory corresponding to the current waypoint and the home point represented by equation (9)_PDetermining the magnitude of the desired steering angle:

e_i＝(1-k)δ_P+kδ_x (8)

in the formula, e_iInput deviation for transverse rotation angle control of i-th cycle, e_i-1Is the input deviation of the transverse rotation angle control of the i-1 th period, and is calculated by the formula (8), T is the control period, K_PFor PID control of the proportionality coefficient, K_iControlling the integral coefficient, K, for PID_dThe differential coefficient is controlled by PID, and k is in the value range of [ 2 ]0 0.1]Yaw angle difference weight of, delta_PIs the difference of the pre-collimation angle, delta_xIs the yaw angle difference.

The invention forms an automatic driving system architecture capable of providing an expanded space for system upgrading by utilizing the switch through Ethernet communication, realizes reliable and accurate positioning of multiple scenes through combined navigation positioning, provides stable and reliable electric power for all equipment through a dual-power system, and realizes convenient control of a driver on the automatic driving system through a human-computer interaction platform. Based on the automatic driving system architecture design control method, safe, reliable and low-power consumption automatic driving tasks of intelligent vehicles in the park are achieved.

Drawings

Fig. 1 is a schematic diagram of an architecture of an automatic driving system of a smart vehicle in a park according to an embodiment of the present invention.

Fig. 2 is a schematic diagram of a human-computer interaction platform interface provided in an embodiment of the present invention.

Fig. 3 is a schematic diagram of a power supply system of an automatic driving system according to an embodiment of the present invention.

Fig. 4 is a diagram illustrating a connection example of a power supply system of an automatic driving system according to an embodiment of the present invention.

Fig. 5 is a schematic track diagram in the tracking control method of the automatic driving system of the intelligent vehicle in the campus provided in the embodiment of the present invention.

Fig. 6 is a flowchart illustrating a tracking control method of an automatic driving system of an intelligent vehicle in a campus according to an embodiment of the present invention.

Detailed Description

The invention is described in detail below with reference to the figures and examples.

As shown in fig. 1, fig. 2, and fig. 6, the campus intelligent vehicle automatic driving system architecture provided by the embodiment of the present invention includes a switch 1, a computing platform 2, an underlying controller 3, a sensing device 4, a positioning device 5, a communication device 7, and a human-computer interaction platform 8. The perceiving device 4 and the positioning device 5 convey information to the computing platform 2 through the switch 1. The human-computer interaction platform 8 delivers information to the computing platform 2 via the communication device 7. The switch 1 is in information interaction with the computing platform 2, and the underlying controller 3 is in information interaction with the computing platform 2 in a serial port connection mode. All the computing platforms 2, the sensing devices 4, the positioning devices 5, the communication devices 7 and the like related to the external automatic driving system realize the Ethernet communication of the star topology through the switch 1. The display device 6 and the computing platform 2 can be connected by any one of dvi (digital Visual interface), hdmi (high definition multimedia interface), vga (video graphical array) interface. The bottom Controller 3 is connected to a vehicle gateway through a CAN (Controller Area Network) bus to realize data interaction with a vehicle drive-by-wire chassis. The emergency stop button and the mode switching button are input to the floor controller 3 in the form of switching signals. Other surrounding vehicles are connected with the Vehicle-mounted Communication equipment in any one mode of DSRC (Dedicated Short-Range Communication), LTE-V (Long Term Evolution-Vehicle to Evolution, Vehicle networking technology based on wireless cellular Communication) and Wifi (Wireless Communication) to realize the Vehicle-Vehicle Communication function. A vehicle local area network is established by utilizing the wireless router, and the human-computer interaction platform 8 is connected with the local area network through wifi to realize data interaction with the computing platform 2.

The positioning device 5 may include, but is not limited to, a GNSS receiver and an inertial navigation system. The bottom layer controller 3 and the GNSS receiver are connected with the computing platform 2 through serial ports. The GNSS receiver supports the joint positioning and orientation of multi-system signals (Beidou, GPS and GLONASS) and can also be used for single-system positioning and orientation. The positioning equipment related by the invention can realize two positioning modes: one mode is a double-antenna GNSS positioning mode, and is suitable for a satellite signal non-shielding scene; the other mode is a combined positioning mode of a GNSS and an inertial navigation system, and is suitable for scenes that satellite signals are shielded by trees, buildings and the like to cause signal loss. The inertial navigation system delivers information to the exchange 1.

The automatic driving system framework provided by the embodiment of the invention realizes convenient connection among all devices and provides expanded space for upgrading the automatic driving system. All external intelligent networking driving related computing equipment, sensing equipment, positioning equipment, communication equipment and the like realize star topology Ethernet communication through a switch. The external system realizes high-reliability communication with the computing platform through the bottom layer controller so as to finish reading of vehicle bottom layer information and sending of control instructions.

As shown in fig. 2, the human-computer interaction platform 8 includes a tracking start/stop control module 81, a tracking map selection module 82, and a control mode selection module 83, where the tracking start/stop control module 81 is configured to send a start or stop control instruction, the tracking map selection module 82 is configured to send a selected tracking map information loading instruction, and the control mode selection module 83 is configured to send a transverse or longitudinal control mode activation instruction.

The interface provided by the human-computer interaction platform 8 comprises a tracking start-stop control area, a vehicle state display area, a control mode selection area and a tracking state display area.

The tracking start-stop control area corresponds to the start and stop functions of the tracking start-stop control module 81, and in the tracking control process of the vehicle, if the stop function is activated, the vehicle is braked and kept in a parking state; if the starting function is activated, the automatic driving system of the vehicle carries out tracking control.

The vehicle state display area displays the current speed of the vehicle and the actual turning angle of the steering wheel in real time.

The control mode selection region corresponds to the control mode selection module 83 and includes a lateral control switch and a longitudinal control switch, and if the lateral control switch is not activated, the vehicle steering requires the driver to operate, and if the longitudinal control switch is not activated, the vehicle longitudinal driving and braking requires the driver to operate.

The tracking state display area corresponds to a tracking map selection module 82 and comprises tracking map selection, tracking track display and early warning information prompt, and the tracking map selection function is used for selecting an expected tracking track currently executed by the vehicle from the tracking tracks stored in the system; the tracking track display mainly realizes the graphical display of the expected tracking track and displays the corresponding waypoints of the current position of the vehicle on the tracking track in real time; the early warning information prompts that the running state of the vehicle is changed in the processes of power-on initialization and tracking control of the automatic driving system is mainly displayed in real time, and if the initialization fails or normal tracking cannot be performed, the fault reason is displayed.

The selection of various control modes and the observation of the running state of the vehicle and the early warning prompt information of the system can be realized through the man-machine interaction platform. The control method of the automatic driving system can present the running state of the system to passengers through the man-machine interaction platform, and can realize the remote control of vehicles.

When the power supply system 10 supplies power normally and completes initialization of control system parameters, the computing platform 2 is configured to receive the start control instruction, load the tracking map information in a normal vehicle state, determine whether the vehicle position and posture information analysis is accurate, continue to determine whether the current position point of the vehicle is on the expected tracking track after determining that the vehicle position and posture information analysis is accurate, calculate an expected steering angle and an expected vehicle speed according to the expected tracking track and the current position of the vehicle in a yes determination, and send the expected steering angle and the expected vehicle speed to the bottom layer controller 3 through a serial port.

In one embodiment, as shown in fig. 3, to meet the power requirements of the devices included in the autopilot system and provide stable and reliable power for all the devices, the power supply system 10 provides three independent power supply lines, i.e. an upper layer dc power supply bus, a lower layer dc power supply bus and an ac power supply bus, such as the 12V upper layer dc power supply bus, the 12V lower layer dc power supply bus and the 220V ac power supply bus shown in fig. 4.

The power supply system 10 includes a main power supply 11, a subsidiary power supply 12, and a power supply line control unit, wherein the main power supply 11 is charged by an in-vehicle power source 13, and the in-vehicle power source 13 may be an engine or a drive motor. The subsidiary power supply 12 is charged by the main power supply 11.

The power supply system 10 needs to take into account the power range D for the proper operation of all the power-requiring devices of the autopilot system_PVoltage requirement D_VAnd voltage stabilization requirement D_SThe power supply system is designed to meet the requirements of all the power-supply-required equipment in three aspects. In view of this, the power supply line control unit includes an operating voltage demand judgment subunit and an electric device operating power demand judgment subunit.

The working voltage requirement judgment subunit is used for judging a working voltage requirement D_V. Power consumption equipment working power demand judgment sub-sheetThe element is used for judging the judgment result of the subunit according to the working voltage requirement and the normal working power requirement D of the electric equipment_PAnd rated power P₁Determining one of the power supply lines, wherein P₁The determination is made based on the rated power levels of the main power supply 11 and the subsidiary power supply 12.

In one embodiment, the secondary power source 12 is connected to the primary power source 11 through an upper switch 14 and a charging switch 15 in this order, and the upper switch 14 and the charging switch 15 are connected in series. The stabilized voltage power supply A and the stabilized voltage power supply B in the upper layer direct current power supply bus are respectively connected between the upper layer switch 14 and the charging switch 15 and between the input end of the secondary power supply 12, the input end of the bottom layer direct current power supply bus is connected between the main power supply 11 and the upper layer switch 14 through the lower layer switch 16, an inverter 17 is arranged between the output end of the alternating current power supply bus and the output end of the secondary power supply 12, and 220V alternating current is output.

External computing equipment, sensing equipment, positioning equipment and communication equipment related to automatic driving have large power requirements, so that the vehicle-mounted power source 13 needs to be started to supply power to the main power source 11 before power supply. To ensure that the secondary power source 12 maintains sufficient power capacity during operation, it also needs to be charged.

The 12V upper layer dc power supply bus can be powered by the main power supply 11 and the secondary power supply 12 respectively, and when the upper layer switch 14 is closed, the main power supply 11 provides 12V dc power through the regulated power supply a. The secondary power supply 12 provides 12V direct current directly through a regulated power supply B. When the upper level switch 14 is open, the secondary power supply 12 can continue to provide 12 vdc to the upper level dc supply bus. The 12V upper layer direct current power supply bus mainly supplies power for related equipment of automatic driving and Internet of vehicles, such as positioning equipment, sensing equipment, a computing platform, a router and the like.

The bottom layer controller 3 mainly realizes high-reliability communication between related equipment of the intelligent vehicle automatic driving system and a computing platform, finishes reading of vehicle bottom layer information and sending of control instructions, has the highest functional importance level, is most sensitive to electromagnetic interference, and has the highest power supply priority. The 12V bottom power supply bus is connected with a main power supply 11 through a bottom switch 16 to supply power to the bottom controller 3. The power supply circuit of the bottom controller 3 alone reduces the influence of the state of the upper power supply circuit on the bottom, and improves the reliability of bottom control.

The 220V alternating current power supply mainly supplies power for debugging equipment (notebook computer electric energy) and the like, and the starting priority is lowest. The 220V alternating current power supply bus is connected with the secondary power supply 12 through the inverter 7, and the requirement of equipment contained in the automatic driving system on 220V alternating current can be met.

Thus, the power supply system 10 power-up sequence includes:

preferentially closing a lower layer switch 16 to provide 12V direct current for the lower layer controller 3; secondly, starting the vehicle-mounted power source 13 to charge the main power source 11; then closing the upper switch 14 to provide 12V direct current for the upper direct current power supply bus, and closing the charging switch 15 to charge the secondary power supply 12; finally, the inverter 7 is started and a voltage of 220v is supplied via the ac supply bus. The setting of the operation sequence mainly aims at the power supply system provided by the invention, the closing priority of the power switch is established by considering the importance degree of the equipment functions and the problem of mutual electromagnetic interference, and all the equipment can be ensured to work stably and reliably.

The automatic driving system requires power supply equipment comprising a computing platform, a bottom layer controller, positioning equipment, sensing equipment, vehicle-mounted communication equipment, a human-computer interaction platform, display equipment and a switch. The power supply system that designs in this patent needs the electric power demand that satisfies each equipment, and the electric power demand of each equipment in the autopilot system is as follows:

the designed power supply system needs to meet the power requirement, the voltage requirement and the voltage stabilization requirement of each device in the automatic driving system at the same time. From the power range, the power requirement is high when a computing platform (industrial personal computer), vehicle-mounted communication equipment (LTE/DSRC) and display equipment (display) work normally, and an independent power supply needs to be designed for supplying power to ensure stable and reliable power supply; from the voltage requirement perspective, the power supply system needs to provide 12V direct current and 220V alternating current voltage simultaneously; from steady voltage demand angle, no steady voltage demand is held in bottom controller (singlechip), bottom controller (radiator fan) and vehicle communication equipment (LTE/DSRC), and other equipment are higher to the power quality requirement, need pass through steady voltage.

In one embodiment, the power-consumption-equipment working power requirement judging subunit judges D_VUnder the condition of 12V direct current, the power supply line is determined by the following three conditions:

situation one, D_P<P₁The power supply line is the bottom layer direct current power supply bus;

case two, D_P<P₁The power supply line is a stabilized voltage power supply A in the upper layer direct current power supply bus;

case two, D_P≥P₁The power supply line is a stabilized voltage power supply B in the upper layer direct current power supply bus;

the power consumption equipment working power requirement judgment subunit judges D_VIn the case of 220V AC, and D_P≥P₁And the power supply line is the alternating current power supply bus.

Wherein P is₁The determination can be made according to the rated power of the main power supply and the secondary power supply. If the primary power source is the vehicle starting power source, then typically P, considering that the primary power source is required to provide a greater amount of power when the vehicle is started₁Taking the smaller value, and the value range is 20W-30W.

According to the above principles, the specific power supply manner of each device included in the architecture of the automatic driving system proposed by the present invention is shown in fig. 4.

1) The 12V bottom power supply bus can meet the requirements of a bottom controller (a single chip microcomputer) and a bottom controller (a cooling fan) on power range and voltage supply, and the single chip microcomputer is provided with a peripheral voltage stabilizing circuit, so that the requirement of no voltage stabilization is required on a power supply;

2) the 12V upper layer direct current power supply bus can meet the requirements of positioning equipment, sensing equipment, a computing platform, a display, a switch and a router on three aspects of power range, voltage supply and voltage stability;

3) the 220V alternating current power supply bus can meet the requirements of communication equipment and a man-machine interaction platform in three aspects of power range, voltage supply and voltage stability.

In one embodiment, the computing platform 2 comprises a preview distance computing unit, a preview point selecting unit, a vehicle speed control unit and a desired steering angle computing unit, wherein:

the pre-aiming distance calculation unit is used for calculating the pre-aiming distance d according to the formula (3)_p：

In the formula, k_ρAdjustment factor, k, for curvature preview_vVehicle speed preview adjustment factor, Con₁And v is the current vehicle speed, and p is the current waypoint curvature.

The pre-aiming point selection unit is used for selecting a pre-aiming point according to a desired tracking track, the current position of the vehicle and d_pAnd determining a preview point.

The vehicle speed control unit is used for determining the expected vehicle speed and the size of the transverse corner according to the detected obstacle situation on the front tracking track of the vehicle. According to the obstacle situation on the tracking track in front of the vehicle detected by the sensing equipment (4), longitudinal vehicle speed control is carried out, and the method specifically comprises the following steps:

in the case of no obstacle, the desired vehicle speed V is calculated from ρ by equation (5)_tar：

In the formula, k_vtFor ensuring that the desired vehicle speed is reduced with increasing curvature by a curvature speed adjustment factor, and k_vt>0；Con₂The constant for avoiding the overlarge target vehicle speed calculated when the curvature is very small is in a value range of 0-0.02; if V_{tar_0}>V_maxThen, thenV_tar＝V_maxIf | V_{tar_0}-v|>Δv_maxAnd (v + Δ v)_max)<V_maxThen V is_tar＝v+Δv_maxElse, V_tar＝V_{tar_0}，Δv_maxIs V and V_tarThe speed variation limit value v between which the riding comfort can be ensured_maxIs the highest vehicle speed.

Under the condition of obstacles, V is calculated according to different obstacle avoidance strategies_tarThe method specifically comprises the following steps:

if the distance S between the obstacle in front of the vehicle and the vehicle>(D_{b_min}+ Δ s), then the deceleration parking obstacle avoidance strategy is executed, and V is calculated by equation (6)_tar，

Is a V_tarLower shortest braking distance, a_maxIs the maximum braking deceleration;

in the formula (I), the compound is shown in the specification,

Δ s is the minimum safe distance between the vehicle and the obstacle when the vehicle is stationary;

if S is less than or equal to (D)_{b_min}+ Δ s), the obstacle avoidance strategy to be executed is executed, according to the curvature ρ corresponding to the planned lane change track_sCalculating V by equation (5)_tar。

And the expected steering angle calculation unit is used for determining the size of the expected steering angle according to the curvature steering angle determined by the curvature of the track corresponding to the current waypoint and the tracking steering angle determined by the pre-aiming point.

The tracking steering angle theta determined by the preview point is calculated by the equation (9)_P：

e_i＝(1-k)δ_P+kδ_x (8)

In the formula, e_iInput deviation for transverse rotation angle control of i-th cycle, e_i-1Is the input deviation of the transverse rotation angle control of the i-1 th period, and is calculated by the formula (8), T is the control period, K_PFor PID control of the proportionality coefficient, K_iControlling the integral coefficient, K, for PID_dFor PID control of differential coefficient, k is in the value range [00.1]]Yaw angle difference weight of, delta_PIs the difference of the pre-collimation angle, delta_xIs the yaw angle difference.

The embodiment of the invention also provides a tracking control method of the automatic driving system of the intelligent vehicle in the park, which comprises the following steps:

step S1, stable and reliable electric power is provided for all equipment through the power supply system 10, the human-computer interaction platform 8 sends a starting control instruction to the computing platform 2 through the communication equipment 7, and the computing platform 2 completes parameter initialization of the automatic driving control system.

In step S2, the computing platform 2 determines whether the vehicle status is normal according to the vehicle status information obtained by the underlying controller 3 through the vehicle gateway 9, and if so, the process goes to step S3. The normal vehicle state refers to meeting the requirement of starting control of an automatic driving system, the conditions comprise that the current vehicle speed is 0, a transmission is engaged into a forward gear, a parking brake is in a release state and the like, and tracking map information is loaded under the condition that the vehicle state is judged to be normal; otherwise, the system displays the prompt message 'abnormal vehicle state' through the man-machine interaction platform.

Step S3, the computing platform 2 loads the tracking map information according to the tracking map information selected by the human-computer interaction platform 8 conveyed by the switch 1, and judges whether the vehicle position and attitude information analysis is accurate according to the vehicle positioning information acquired by the positioning equipment 5 conveyed by the switch 1, if so, the step S4 is executed. Specifically, whether the GNSS receiver receives correction data of a differential base station is judged, and if the GNSS receiver does not receive the differential correction data, a system displays a prompt message of 'vehicle non-differential positioning' through a human-computer interaction platform; if the difference correction data is received, step S4 is executed.

In step S4, the computing platform 2 determines whether the current position point of the vehicle is on the expected tracking track, and if so, it goes to step S5. And if the current position of the vehicle is not on the expected tracking track waypoint, displaying a prompt message 'the vehicle deviates from the expected track' through a man-machine interaction platform.

Specifically, tracking map information is loaded according to an expected tracking track selected by a man-machine interaction platform, and meanwhile, the current position point (x) of the vehicle is judged by utilizing the current position information of the vehicle road acquired by the positioning equipment_a,y_a,ψ_a) The conditions that need to be met on the desired tracking trajectory are: at least one waypoint (x) can be found on the tracking track_i,y_i,γ_i) The following requirements are met:

in the formula, X_ThIs a longitudinal error threshold, Y_ThIs a lateral error threshold, θ_ThIs a heading angle error threshold.

The value of the error threshold is related to the precision of the positioning system, and when the vehicle positioning system is differential positioning and the satellite signal is not shielded, the error threshold can be calculated as follows:

for example, X_ThAnd Y_ThIs determined according to the length L and the width B of the outline dimension of the vehicle, X_Th＝0.05*L，Y_Th＝0.1*B，θ_ThCan be based on the maximum steering angle theta of the steering wheel_maxDetermination of theta_Th＝0.1*θ_max。

In step S5, the computing platform 2 calculates a desired steering angle and a desired vehicle speed according to the desired tracking track and the current position of the vehicle, and sends them to the bottom layer controller 3.

Specifically, tracking control is started according to an expected tracking track and the current position of the vehicle, a calculation platform calculates an expected steering angle according to the transverse deviation between the current position and a pre-aiming point on the tracking track, an expected vehicle speed is calculated according to the road curvature and the vehicle power constraint, and meanwhile, the calculation platform sends the expected steering angle and the expected vehicle speed to a bottom layer controller through a serial port; and the bottom layer controller executes control quantity conversion calculation to convert the expected vehicle speed into an expected driving or braking force demand, and simultaneously sends the expected driving or braking force demand and the expected steering angle to a vehicle CAN bus through a vehicle gateway to realize the control of driving, braking and steering actuating mechanisms in a vehicle chassis.

Step S6, the computing platform 2 determines whether to adopt manual driving according to the control mode activation instruction of the human-computer interaction platform 8 conveyed by the switch 1, if so, that is: the driver has the intention of taking over the vehicle, if the driver actively rotates a steering wheel, steps on an accelerator pedal or a brake pedal, the vehicle exits from an automatic driving mode, and the driver directly controls the vehicle; otherwise, the process proceeds to step S7.

Step S7, the computing platform 2 judges whether the stop function of the tracking start control area in the human-computer interaction platform 8 is activated, if the stop function is activated, the vehicle automatic driving system executes a stop instruction; if the stopping function is not activated, whether the vehicle reaches a preset expected stopping point on the tracking track is further judged, if the vehicle reaches the expected stopping point, the automatic driving system of the vehicle executes a stopping instruction, otherwise, the step S6 is continuously executed until the vehicle reaches the expected stopping position.

The invention realizes information interaction among all sensing devices (cameras, laser radars and the like), positioning devices, communication devices and a computing platform through one switch, can ensure that all devices are not interfered with each other, has the main advantages of stronger flexibility, convenient mounting of new devices, no influence on normal work of an original system due to the connection and disconnection of the new devices, and can provide an expansion space for system upgrading. Aiming at the problem of unreliability of the algorithm in the development and test process, the scheme provided by the invention can fully ensure the safety and can ensure the availability of the original vehicle control under the condition that the automatic driving control system is broken down or fails.

In one embodiment, the power supply system 10 provides three independent power supply lines, namely, an upper layer DC power supply bus, a lower layer DC power supply bus and an AC power supply bus. The power supply system 10 comprises a main power supply 11 and a secondary power supply 12, wherein the main power supply 11 is charged through a vehicle-mounted power source 13, the secondary power supply 12 is charged through the main power supply 11, and the power supply line control method of the power supply system 10 specifically comprises the following steps:

step S11, judging the working voltage demand D_V；

Step S12, in the step S11 determining D_VUnder the condition of 12V direct current, the power supply line is determined by the following three conditions:

situation one, D_P<P₁The power supply line is the bottom layer direct current power supply bus;

case two, D_P<P₁The power supply line is a stabilized voltage power supply A in the upper layer direct current power supply bus;

case two, D_P≥P₁The power supply line is a stabilized voltage power supply B in the upper layer direct current power supply bus;

d is judged at the step S11_VIn the case of 220V AC, and D_P≥P₁And the power supply line is the alternating current power supply bus.

Wherein, P₁The determination is made based on the rated power levels of the main power supply 11 and the subsidiary power supply 12.

The electric energy of the automatic driving equipment is provided by two sets of battery packs, the electric energy of the upper layer direct current power supply bus is respectively supplied by two sets of stabilized voltage power supplies and the main power supply 12 and the auxiliary power supply 12, the reliability of the upper layer control equipment and the balance of power distribution are ensured, the influence of the state of the upper layer power supply circuit on the bottom layer is reduced by the independent power supply circuit of the bottom layer controller, and the reliability of the bottom layer control is improved.

In one embodiment, step S5 specifically includes:

step S51, tracking the upper path point P along the advancing direction of the vehicle_j(x_j,y_j) With the actual position P obtained by the vehicle positioning system_a(x_a,y_a) The corresponding waypoint when the distance is minimum is positioned as the current waypoint P_i(x_i,y_i) The calculation is as follows:

calculating the pre-aiming distance d according to the formula (3)_p：

In the formula, k_ρAdjust a factor for curvature preview, and k_ρ>0，k_vThe vehicle speed preview adjusting factor is usually selected from the range of 1.0-4.0, Con₁Is a constant term, and Con₁>And 0, the value of which is in the range of 0-0.02, and the function of the method is to avoid the overlarge pre-aiming distance calculated when the curvature is very small, v is the current vehicle speed, and rho is the curvature of the current waypoint.

Step S52, tracking the upper path point P along the advancing direction of the vehicle_j(x_j,y_j) And the current waypoint P_i(x_i,y_i) A distance D between_ijDistance d from the pre-aiming_pThe corresponding waypoint when the absolute value of the difference is minimum is the preview point P_{i_P}(x_{i_P},y_{i_P})。

In the formula (I), the compound is shown in the specification,

step S53, determining the expected vehicle speed and the magnitude of the lateral rotation angle according to the detected obstacle situation on the tracking track in front of the vehicle, which specifically includes:

(I) in the case of no obstacle, the desired vehicle speed V is calculated by equation (5) based on ρ_tar：

In the formula, k_vtAdjusting a factor for a curvature speedAnd k is_vt>0, the expected vehicle speed can be ensured to be reduced along with the increase of the curvature; con₂Is a constant term, and Con₂>0, the value range of which is 0-0.02, and the main function of the vehicle speed control method is to avoid calculating an overlarge target vehicle speed when the curvature is very small. If V_{tar_0}>V_maxThen V is_tar＝V_maxIf | V_{tar_0}-v|>Δv_maxAnd (v + Δ v)_max)<V_maxThen V is_tar＝v+Δv_maxElse, V_tar＝V_{tar_0}，Δv_maxIs V and V_tarThe speed variation limit value v between which the riding comfort can be ensured_maxIs the highest vehicle speed.

(II) under the condition of obstacles, calculating V according to different obstacle avoidance strategies_tarThe method specifically comprises the following steps:

if the distance S between the obstacle in front of the vehicle and the vehicle>(D_{b_min}+ Δ s), then the deceleration parking obstacle avoidance strategy is executed, and V is calculated by equation (6)_tar，

Is a V_tarLower shortest braking distance, a_maxIs the maximum braking deceleration;

in the formula (I), the compound is shown in the specification,

Δ s is the minimum safe distance between the vehicle and the obstacle when the vehicle is stationary;

if S is less than or equal to (D)_{b_min}+ Δ s), the obstacle avoidance strategy to be executed is executed, according to the curvature ρ corresponding to the planned lane change track_sCalculating V by equation (5)_tar；

Step S54, the desired steering angle θ_tarConsists of two parts, one part is a curvature steering angle theta determined by the curvature of the track corresponding to the current road point_ρThe other part is tracking steering determined by the pre-aiming point and tracking the selected tracking trackAngle theta_P。

Curvature rho corresponding to tracking track where current waypoint is located_iThe curvature steering angle theta is calculated as follows, stored in the tracking map:

θ_ρ＝(1+Kv²)ρ_iL (7)

in the formula, K is a stability factor, and L is the wheelbase of the front axle and the rear axle of the vehicle.

Tracking steering angle theta determined by the point of preview_PThe vehicle can achieve the purpose of course tracking. First, the yaw angle of the vehicle is defined as the angle between the longitudinal axis of the vehicle and the coordinate axis x, as shown by α in FIG. 5_xAs shown. The preview angle is the angle between the line from the center of the vehicle to the preview point and the coordinate axis x, as shown by alpha in FIG. 5_pAs shown. It is desirable to minimize the difference between the heading angle and the yaw angle, as shown by δ in FIG. 5, for lateral control of the vehicle_PShown, defined as the difference in the boresight angles. Meanwhile, in order to further improve the tracking accuracy, it is also necessary to reduce the yaw angle of the vehicle and the heading angle ψ of the preview point as much as possible_pThe difference between them, e.g. delta in fig. 5_xShown, defined as the yaw angle difference. Comprehensively considering the preview angle difference and the preview angle difference, the input deviation of the transverse rotation angle control is calculated by the following formula:

e_i＝(1-k)δ_P+kδ_x (8)

in the formula, k is the yaw angle difference weight, and the value range of the k is [00.1 ].

The tracking steering angle theta is obtained by adopting a PID control method and taking the deviation angle described in the formula (8) as the input of a controller_PThe calculation formula is as follows:

in the formula, e_iInput deviation for transverse rotation angle control of i-th cycle, e_i-1Is the input deviation of the transverse rotation angle control of the i-1 th period, and is calculated by the formula (8), T is the control period, K_PFor PID control of the proportionality coefficient, K_iControlling the integral coefficient, K, for PID_dControlling differential coefficients for PIDK is in the value range of [00.1]]The yaw angle difference weight of (a) is to be noted that the selection of the appropriate proportional, integral and derivative coefficients is different under different driving conditions.

The final calculated desired steering angle is calculated by:

θ_tar＝θ_ρ+θ_P (10)。

finally, it should be pointed out that: the above examples are only for illustrating the technical solutions of the present invention, and are not limited thereto. Those of ordinary skill in the art will understand that: modifications can be made to the technical solutions described in the foregoing embodiments, or some technical features may be equivalently replaced; such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (9)

1. A park intelligent vehicle automatic driving system architecture is characterized by comprising a switch (1), a computing platform (2), a bottom layer controller (3), a sensing device (4), a positioning device (5), a communication device (7) and a human-computer interaction platform (8), wherein the sensing device (4) and the positioning device (5) transmit information to the computing platform (2) through the switch (1); the human-computer interaction platform (8) transmits information to the computing platform (2) through the communication equipment (7); the switch (1) is in information interaction with the computing platform (2), and the underlying controller (3) is in information interaction with the computing platform (2) in a serial port connection mode;

the human-computer interaction platform (8) comprises a tracking start-stop control module (81), a tracking map selection module (82) and a control mode selection module (83), wherein the tracking start-stop control module (81) is used for sending a start or stop control instruction, the tracking map selection module (82) is used for sending a selected tracking map information loading instruction, the control mode selection module (83) is used for sending a transverse or longitudinal control mode activation instruction, when a power supply system (10) is normally powered and control system parameter initialization is completed, the computing platform (2) is used for receiving the start control instruction, loading the tracking map information under the condition that the vehicle state is normal, then judging whether the vehicle position and attitude information analysis is accurate, and after judging that the vehicle position and attitude information analysis is accurate, continuously judging whether the current position point of the vehicle is on the expected tracking track, under the condition that the tracking position is judged to be 'yes', calculating an expected steering angle and an expected vehicle speed according to an expected tracking track and the current position of the vehicle, and sending the expected steering angle and the expected vehicle speed to the underlying controller (3) through a serial port; the power supply system (10) provides three independent power supply lines which are an upper direct current power supply bus, a bottom direct current power supply bus and an alternating current power supply bus respectively, the power supply system (10) comprises a main power supply (11), an auxiliary power supply (12) and a power supply line control unit, wherein the main power supply (11) is charged through a vehicle-mounted power source (13), the auxiliary power supply (12) is charged through the main power supply (11), the auxiliary power supply (12) is sequentially connected with the main power supply (11) through a charging switch (15) and an upper switch (14), a stabilized voltage power supply A in the upper direct current power supply bus is connected between the upper switch (14) and the charging switch (15), and when the upper switch (14) is closed, the main power supply (11) provides 12V direct current through the stabilized voltage power supply A; a stabilized voltage power supply B in the upper layer direct current power supply bus is connected to the output end of the secondary power supply (12), and when the upper layer switch (14) is switched off, the secondary power supply (12) continues to provide 12V direct current for the upper layer direct current power supply bus; the input end of the bottom layer direct current power supply bus is connected between the main power supply (11) and the upper layer switch (14) through a lower layer switch (16) to supply power for the bottom layer controller (3); establish inverter (17) between the output of AC power supply bus and the output of secondary power source (12), output 220V alternating current, the power supply line control unit includes:

a working voltage requirement judgment subunit for judging the working voltage requirement D_V；

The power consumption equipment working power requirement judgment subunit is used for judging the judgment result of the subunit according to the working voltage requirement and the normal working power requirement D of the power consumption equipment_PAnd rated power P₁Determining one of the power supply lines, wherein P₁The power supply is determined according to the rated power of the main power supply (11) and the secondary power supply (12).

2. The campus intelligent vehicle autopilot system architecture of claim 1 wherein the power-up sequence comprises:

preferentially closing a lower layer switch (16) to provide 12V direct current for the lower layer controller (3); secondly, starting a vehicle-mounted power source (13) to charge a main power source (11); then closing an upper switch (14) to provide 12V direct current for an upper direct current power supply bus, and closing a charging switch (15) to charge the secondary power supply (12); finally, the inverter (7) is started and a 220v voltage is provided through the AC power supply bus.

3. The campus intelligent vehicle autopilot system architecture of claim 2 wherein the powered device operating power requirement determination subunit is determining D_VUnder the condition of 12V direct current, the power supply line is determined by the following three conditions:

situation one, D_P＜P₁The power supply line is a stabilized voltage power supply A in the bottom layer direct current power supply bus and the upper layer direct current power supply bus;

case two, D_P≥P₁The power supply line is a stabilized voltage power supply B in the upper layer direct current power supply bus;

the power consumption equipment working power requirement judgment subunit judges D_VIn the case of 220V AC, and D_P≥P₁The power supply line is the AC power supply bus, D_PFor the power range of normal operation of the power-requiring apparatus, P₁Is a power value determined according to the rated power of the main power supply (11) and the secondary power supply (12).

4. The campus intelligent vehicle autopilot system architecture of any one of claims 1 to 3 wherein the computing platform (2) comprises:

a pre-aiming distance calculation unit for calculating the pre-aiming distance d according to the formula (3)_p：

In the formula, k_ρAdjustment factor, k, for curvature preview_vFor pre-aiming adjustment factor, Con, of vehicle speed₁A curvature adjusting factor is obtained, v is the current vehicle speed, and rho is the curvature of the current road point;

a pre-aim point selection unit for selecting a pre-aim point according to a desired tracking trajectory, a current position of the vehicle and d_pDetermining a preview point;

the vehicle speed control unit is used for determining the magnitude of the expected vehicle speed according to the detected obstacle situation on the front tracking track of the vehicle;

and the expected steering angle calculation unit is used for determining the size of the expected steering angle according to the curvature steering angle determined by the curvature of the track corresponding to the current waypoint and the tracking steering angle determined by the aiming point.

5. The automatic driving system architecture of intelligent vehicles on campus of claim 4, wherein, according to the obstacle situation on the tracking track in front of the vehicle detected by said sensing device (4), the longitudinal speed control is carried out, specifically including:

in the case of no obstacle, the desired vehicle speed V is calculated from ρ by equation (5)_tar：

In the formula, k_vtA speed adjustment factor for ensuring that the desired vehicle speed decreases with increasing curvature, and k_vt＞0；Con₂The constant for avoiding the overlarge target vehicle speed calculated when the curvature is very small is in a value range of 0-0.02; if V_{tar_0}＞V_maxThen V is_tar＝V_maxIf | V_{tar_0}-v|＞Δv_maxAnd (v + Δ v)_max)＜V_maxThen V is_tar＝v+Δv_maxElse, V_tar＝V_{tar_0}，Δv_maxIs V and V_tarCan ensure the riding comfortLimit of linear speed variation, v_maxThe highest vehicle speed;

under the condition of obstacles, V is calculated according to different obstacle avoidance strategies_tarThe method specifically comprises the following steps:

if the distance S > (D) between the obstacle in front of the vehicle and the vehicle_{b_min}+ Δ s), then the deceleration parking obstacle avoidance strategy is executed, and V is calculated by equation (6)_tar，

Is a V_tarLower shortest braking distance, a_maxIs the maximum braking deceleration;

in the formula (I), the compound is shown in the specification,

Δ s is the minimum safe distance between the vehicle and the obstacle when the vehicle is stationary;

if S is less than or equal to (D)_{b_min}+ Δ s), a lane change and obstacle avoidance strategy needs to be executed, and according to the curvature ρ corresponding to the planned lane change track_sCalculating V by equation (5)_tar。

6. The campus intelligent vehicle autopilot system architecture of claim 5 wherein the tracking steering angle θ determined by the pre-pointing point is calculated by equation (9)_P：

e_i＝(1-k)δ_P+kδ_x (8)

In the formula, e_iInput deviation for transverse rotation angle control of i-th cycle, e_i-1Is the input deviation of the transverse rotation angle control of the i-1 th period, and is calculated by the formula (8), T is the control period, K_PFor PID control of the proportionality coefficient, K_iControlling the integral coefficient, K, for PID_dFor PID control of differential coefficient, k is a value range of [0, 0.1]]Yaw angle difference weight of, delta_PIs the difference of the pre-collimation angle, delta_xIs the yaw angle difference.

7. The tracking control method of the park intelligent vehicle automatic driving system is characterized by comprising the following steps:

step S1, supplying power through a power supply system (10), sending a starting control instruction to a computing platform (2) by a man-machine interaction platform (8) through a communication device (7), and finishing parameter initialization of an automatic driving control system by the computing platform (2);

step S2, the computing platform (2) judges whether the vehicle state is normal according to the vehicle state information acquired by the bottom controller (3) through the vehicle gateway (9), if so, the computing platform enters step S3;

step S3, the computing platform (2) loads the tracking map information according to the tracking map information selected by the human-computer interaction platform (8) conveyed by the switch (1), judges whether the vehicle position and attitude information analysis is accurate according to the vehicle positioning information acquired by the positioning equipment (5) conveyed by the switch (1), and if so, the step S4 is carried out;

step S4, the computing platform (2) judges whether the current position point of the vehicle is on the expected tracking track, if so, the step S5 is carried out;

step S5, the computing platform (2) computes a desired steering angle and a desired vehicle speed according to a desired tracking track and the current position of the vehicle, and sends the steering angle and the vehicle speed to the underlying controller (3);

step S6, the computing platform (2) judges whether to adopt manual driving according to the control mode activating instruction of the man-machine interaction platform (8) transmitted by the switch (1), if so, the man-machine interaction platform is driven by the man, otherwise, the step S7 is entered;

and step S7, the computing platform (2) judges whether the human-computer interaction platform (8) sends a parking control instruction or reaches a target parking position, and if so, sends a parking instruction to the underlying controller (3).

8. The park intelligent vehicle autopilot system tracking control method of claim 7, the power supply system (10) provides three independent power supply lines which are an upper layer direct current power supply bus, a bottom layer direct current power supply bus and an alternating current power supply bus respectively, the power supply system (10) comprises a primary power source (11) and a secondary power source (12), wherein the main power supply (11) is charged by an in-vehicle power source (13), the subsidiary power supply (12) is charged by the main power supply (11), the secondary power supply (12) is connected with the main power supply (11) through a charging switch (15) and an upper layer switch (14) in sequence, a stabilized voltage power supply A in the upper layer direct current supply bus is connected between the upper layer switch (14) and the charging switch (15), when the upper layer switch (14) is closed, the main power supply (11) provides 12V direct current through the stabilized voltage power supply A; a stabilized voltage power supply B in the upper layer direct current power supply bus is connected to the output end of the secondary power supply (12), and when the upper layer switch (14) is switched off, the secondary power supply (12) continues to provide 12V direct current for the upper layer direct current power supply bus; the input end of the bottom layer direct current power supply bus is connected between the main power supply (11) and the upper layer switch (14) through a lower layer switch (16) to supply power for the bottom layer controller (3); an inverter (17) is arranged between the output end of the alternating current power supply bus and the output end of the secondary power supply (12) to output 220V alternating current, and the power supply line control method of the power supply system (10) specifically comprises the following steps:

step S11, judging the working voltage demand D_V；

Step S12, in the step S11 determining D_VUnder the condition of 12V direct current, the power supply line is determined by the following three conditions:

situation one, D_P＜P₁The power supply line is a stabilized voltage power supply A in the bottom layer direct current power supply bus and the upper layer direct current power supply bus;

case two, D_P≥P₁The power supply line is a stabilized voltage power supply B in the upper layer direct current power supply bus;

d is judged at the step S11_VIn the case of 220V AC, and D_P≥P₁Said supply ofThe electric line is the alternating current power supply bus;

wherein D is_PFor the power range of normal operation of the power-requiring apparatus, P₁Is a power value determined according to the rated power of the main power supply (11) and the secondary power supply (12).

9. The tracking control method for the automatic driving system of the intelligent vehicle on the campus of claim 8, wherein the step S5 specifically includes:

step S51, calculating the pre-aiming distance d according to the formula (3)_p：

In the formula, k_ρAdjustment factor, k, for curvature preview_vFor pre-aiming adjustment factor, Con, of vehicle speed₁A curvature adjusting factor is obtained, v is the current vehicle speed, and rho is the curvature of the current road point;

step S52, according to the expected tracking track, the current position of the vehicle and d_pDetermining a preview point;

step S53, determining the expected vehicle speed and the magnitude of the lateral rotation angle according to the detected obstacle situation on the tracking track in front of the vehicle, which specifically includes:

in the case of no obstacle, the desired vehicle speed V is calculated from ρ by equation (5)_tar：

In the formula, k_vtA speed adjustment factor for ensuring that the desired vehicle speed decreases with increasing curvature, and k_vt＞0；Con₂The constant for avoiding the overlarge target vehicle speed calculated when the curvature is very small is in a value range of 0-0.02; if V_{tar_0}＞V_maxThen V is_tar＝V_maxIf | V_{tar_0}-v|＞Δv_maxAnd (v + Δ v)_max)＜V_maxThen V is_tar＝v+Δv_maxElse, V_tar＝V_{tar_0}，Δv_maxIs V and V_tarThe speed variation limit value v between which the riding comfort can be ensured_maxThe highest vehicle speed;

under the condition of obstacles, V is calculated according to different obstacle avoidance strategies_tarThe method specifically comprises the following steps:

if the distance S > (D) between the obstacle in front of the vehicle and the vehicle_{b_min}+ Δ s), then the deceleration parking obstacle avoidance strategy is executed, and V is calculated by equation (6)_tar，

Is a V_tarLower shortest braking distance, a_maxIs the maximum braking deceleration;

in the formula (I), the compound is shown in the specification,

Δ s is the minimum safe distance between the vehicle and the obstacle when the vehicle is stationary;

if S is less than or equal to (D)_{b_min}+ Δ s), a lane change and obstacle avoidance strategy needs to be executed, and according to the curvature ρ corresponding to the planned lane change track_sCalculating V by equation (5)_tar；

Step S54 is a step of determining a tracking steering angle θ from a curvature steering angle determined from the curvature of the trajectory corresponding to the current waypoint and the home point represented by equation (9)_PDetermining the magnitude of the desired steering angle:

e_i＝(1-k)δ_P+kδ_x (8)

in the formula, e_iInput deviation for transverse rotation angle control of i-th cycle, e_i-1Is the input deviation of the transverse rotation angle control of the i-1 th period, and is calculated by the formula (8), T is the control period, K_PFor PID control of the proportionality coefficient, K_iControlling the integral coefficient, K, for PID_dFor PID control of differential coefficient, k is a value range of [0, 0.1]]Yaw angle difference weight of, delta_PIs the difference of the pre-collimation angle, delta_xIs the yaw angle difference.

Images