An active lane-changing system for intelligent driving vehicles considering the flow of intelligent vehicle groups

Abstract

The present invention relates to an active lane changing system for an intelligent driving vehicle taking into account the flow of an intelligent vehicle group. The lane changing system comprises a camera, a radar, a wheel speed sensor, an IMU component, a communication module, a GNSS module, an ECU module, an HMI module and a motion execution module. A lane changing comprehensive decision method comprises the steps of obtaining motion information of a vehicle and an environmental vehicle, basic road information, determining a motion gain for lane changing, calculating a corresponding longitudinal minimum safety distance, determining whether the lane changing behavior has a significant impact on the traffic flow, and the like. On the basis of a traditional minimum safety distance model, the present invention considers the impact of road curvature on the minimum safety distance model under different road conditions such as straight roads and curves, comprehensively considers the impact of lane changing behavior on the traffic flow of a target lane, establishes a lane changing system and a comprehensive decision model, provides a practical and feasible decision basis for intelligent networked vehicles when changing lanes, and finally obtains a more comprehensive, more economical and more efficient comprehensive lane changing control method.

Description

Technical Field

[0001] The present invention relates to an active lane-changing system for intelligent driving vehicles taking into account the flow of intelligent vehicle groups, and in particular to an active lane-changing decision system and a lane-changing comprehensive decision method for intelligent vehicle groups. Background Art

[0002] With the rapid development of information and communication technologies such as cloud computing, big data, and the Internet of Things, we have now entered the Internet era of the interconnection of all things. Emerging communication technologies represented by 5G are integrating with all walks of life and continuously promoting the development and change of society. As one of the traditional manufacturing industries, the automobile industry is also constantly transforming and upgrading in the direction of "intelligent manufacturing" and "Internet +".

[0003] Intelligent Connected Vehicle (ICV) is the combination of automotive intelligence technology and networking technology. Networking technology enables smart cars to break through the limitations of the sensing capabilities of sensors installed on the vehicle in many aspects such as environmental perception and behavioral decision-making, and achieve the purpose of information interaction and sharing among people, vehicles, roads, and clouds during vehicle driving, thereby bringing significant improvements to the vehicle in terms of energy saving, safety, and efficiency.

[0004] Lane changing is a common driving behavior in traffic. When the traffic volume is small, reasonable lane changing behavior helps the vehicle to achieve a higher driving speed; when the traffic volume is large, lane changing behavior may seriously affect the speed of the traffic flow and reduce the road capacity. Unreasonable lane changing behavior may even cause serious traffic accidents. Therefore, it is necessary to take the impact of lane changing behavior on traffic flow into account when the vehicle makes a lane changing decision. Summary of the invention

[0005] In order to solve the above technical problems, the present invention designs an active lane changing comprehensive decision model for the influence of lane changing behavior of intelligent vehicle groups on traffic flow based on the minimum safety distance model, thereby ensuring the rationality and feasibility of lane changing and avoiding the influence of unreasonable lane changing behavior on road traffic efficiency; and provides a matching active lane changing decision system for intelligent vehicle groups.

[0006] The present invention provides an active lane changing system for intelligent driving vehicles taking into account the flow of intelligent vehicle groups, characterized in that it includes a camera, a radar, a wheel speed sensor, an IMU component, a communication module, a GNSS module, an ECU module, an HMI module and a motion execution module. The camera, radar, wheel speed sensor, IMU component, communication module, GNSS module, HMI module and motion execution module are all arranged on the vehicle body, connected to the ECU module through the CAN bus on the vehicle to realize data transmission between each other; the camera includes at least 5 monocular cameras, which are respectively arranged at the front side, rear side, left side and right side middle of the vehicle body and the middle of the roof; the radar includes at least 4 laser radars and 6 short-range millimeter-wave radars, which are respectively located at the left front, left rear, right front and right rear corners of the vehicle; the millimeter-wave radars are respectively located at the front, middle and rear of the left and right sides of the vehicle body; the IMU component is used to measure the angular velocity, acceleration, yaw angle and altitude of the vehicle; the GNSS module uses RTK-GNSS (real time kinematic GNSS) technology to determine the absolute position of the vehicle, and can achieve centimeter-level positioning accuracy based on carrier phase difference technology. The absolute position includes the current latitude and longitude and altitude of the vehicle; the ECU module converts the obtained motion information into a control signal to control the driving execution module, the braking execution module and the steering execution module in the motion execution module to perform corresponding operations.

[0007] The smart car group is a group of smart connected cars with the same or similar destinations; the communication module of the smart connected car uses LTE-V2X technology to realize information interaction between cars and between cars and infrastructure, and its operating frequency band is 5905-5925MHz. The information interaction between cars uses LTE-V-direct technology, which does not require transit through base stations; the information interaction between cars and infrastructure uses LTE-V-cell technology to achieve large bandwidth and large coverage communication; the interaction information includes authentication information, upload information and download information; the authentication information is the authentication information such as the license plate number sent by the vehicle terminal to the cloud server after completing the device registration, the upload information includes the vehicle reporting at a certain frequency including the current speed, position, driving direction, driving intention and other information of the vehicle, and the download information includes traffic events, roadside safety information and movement information of environmental vehicles sent by the cloud server.

[0008] The HMI module includes a user demand input module and a vehicle information feedback module. The user demand input module includes an active input module and an intelligent perception module. The active input module allows the driver to input his or her needs to the vehicle through touch, voice, body sensation, etc.; the intelligent perception module allows the vehicle to perceive the air conditions in the vehicle, the user's psychology, emotional changes and other information through olfactory perception, biological perception, etc., and intelligently perceive the user's needs; the vehicle information feedback module allows the vehicle to inform the user of the current and future operating status of the vehicle through vision, voice, touch, etc.

[0009] The ECU module includes a basic information module of the vehicle, a high-precision electronic map module, a navigation module, a memory and a motion decision module. The basic information module of the vehicle, the high-precision electronic map module, the navigation module and the motion decision module are connected to the memory respectively; the basic information module of the vehicle and the high-precision electronic map module are connected to the navigation module respectively; the navigation module is connected to the motion decision module; the basic information module of the vehicle includes a static information module and a dynamic information module, including information such as the absolute position, relative position, heading, speed and acceleration of the vehicle; the high-precision electronic map module includes a basic map module, a regional map module and a real-time dynamic map module, providing map information including basic road networks and buildings, etc. and dynamic map information including traffic signals around the vehicle, environmental vehicles, etc.; the navigation module includes a global route drawing module and a local route drawing module, completing the drawing of the shortest path from the current position of the vehicle to the destination and the drawing of the route to be followed in the current section; the motion decision module includes a motion decomposition module and a feedback adjustment module; the memory is used to store data.

[0010] The local route drawing module includes a behavior decision module and a trajectory drawing module. The behavior decision module includes a motion gain determination module, a safety determination module and an environmental impact determination module, which respectively determine whether the lane changing behavior can bring better motion effects to the vehicle, whether the distance between the vehicle and the vehicle in front of the original lane, the vehicle in front of the target lane, and the vehicle in the rear of the target lane meets the minimum safety distance requirements, and whether the lane changing behavior has too much impact on the traffic flow of the target lane, and then make a behavior decision of lane changing or lane keeping. The trajectory drawing module draws a motion trajectory that meets the behavior requirements according to the decision made by the behavior decision module.

[0011] The motion decomposition module decomposes the motion trajectory drawn by the trajectory drawing module into the longitudinal and lateral speeds and accelerations of the vehicle at each moment, and transmits them to the motion execution module to complete the corresponding motion operation. The feedback adjustment module completes the adaptive adjustment of the motion state at the next moment according to the difference between the current motion state and the expected motion state.

[0012] Based on the above system, the present invention provides an active lane changing system for intelligent driving vehicles taking into account the flow of intelligent vehicle groups, comprising the following steps:

[0013] Step 1: Obtain the motion information of the vehicle through the IMU component and the wheel speed sensor, and obtain the motion information and relative position information of the vehicles in the adjacent lanes through vehicle-to-vehicle communication, radar, etc. The vehicle-to-vehicle communication realizes information exchange between vehicles through the periodic traffic mode. The motion information includes the current speed and acceleration information of the vehicle and the vehicles in the adjacent lanes, and the relative position information includes the relative position relationship between the adjacent lane vehicles and the vehicle in the longitudinal and lateral directions;

[0014] Step 2: Determine whether the lane-changing behavior can bring better operating benefits to the vehicle, including:

[0015] (1) Based on the motion information obtained in step 1, the motion information of the ego vehicle is compared with that of the vehicles in the adjacent lane. If the average speed and acceleration of the vehicles in the adjacent lane are significantly higher than those of the ego vehicle, a lane change intention is generated. Otherwise, the behavior decision module 29 generates a lane keeping instruction and repeats step 1.

[0016] (2) The adjacent lane with a higher driving speed, acceleration and greater following distance is temporarily set as the target lane. The following distance calculation formula is:

[0017] d rel =v H ·τ+L

[0018] Where τ is the following distance, L is the vehicle length, and v H is the average lane speed.

[0019] Step 3: If the lane-changing intention is generated in step 2 and the target lane is determined, the basic information of the current road is determined through communication between the vehicle and the roadside unit (RSU), and the calculation of the longitudinal minimum safety distance is completed, and this is used as the safety condition for the lane-changing behavior; the longitudinal minimum safety distance includes the longitudinal minimum safety distance between the vehicle and the vehicle in front of the target lane, the longitudinal minimum safety distance between the vehicle and the vehicle behind the target lane, and the longitudinal minimum safety distance between the vehicle and the vehicle in front of the original lane;

[0020] If the longitudinal distance between the vehicle and any of the vehicles in front of the target lane, behind the target lane, or in front of the original lane is less than the corresponding longitudinal minimum safety distance, the vehicle cannot change lanes, and the behavior decision module 29 generates a lane keeping instruction and repeats step 1.

[0021] Step 4: If the longitudinal distances between the ego vehicle and the vehicle in front of the target lane, the vehicle behind the target lane, and the vehicle in front of the original lane all meet the minimum safety distance condition in step 3, the calculation of the target lane traffic flow with or without lane changing behavior is completed, and it is further determined whether the minimum fluctuation of the traffic flow is met. If the traffic flow fluctuation caused by the lane changing is less than the set threshold condition value, it is considered that the decision condition for lane changing is met, and the behavior decision module 29 generates a lane changing instruction; otherwise, a lane keeping instruction is generated, and step 1 is repeated.

[0022] Step 5: If the traffic flow fluctuation calculated in step 4 meets the corresponding conditions, the lane change decision is considered feasible, the behavior decision module 29 issues a lane change instruction, and the trajectory drawing module 30 draws a reasonable lane change trajectory. At the same time, the ego vehicle transmits the lane change intention to other vehicles in the smart car group in the event-triggered traffic mode.

[0023] The corresponding minimum longitudinal safety distance for the current road condition in step 3 is as follows, where M represents the vehicle, L represents the d represents the front vehicle in the target lane, F d represents the vehicle behind the target lane, L 0 Represents the front car in the original lane:

[0024] When the current road is a straight road, the minimum longitudinal safety distance includes:

[0025] (1) The ego vehicle M and the front vehicle L in the target lane d The minimum longitudinal safety distance is:

[0026]

[0027] Among them, a M (τ), are the accelerations of the vehicle and the vehicle in front of the target lane, respectively, v M (0) are the initial velocities of the vehicle and the vehicle in front of the target lane, L is the vehicle length, t c It indicates the time when the lane-changing vehicle collides with the target lane after completing the adjustment of the longitudinal distance and longitudinal speed, t adj Indicates the time required for the vehicle to adjust the longitudinal distance and longitudinal speed before starting the lane change operation in order to successfully perform the lane change operation, t c +t adj is the time when the collision occurs, T is the total lane change time;

[0028] (2) The ego vehicle M and the vehicle F behind in the target lane d The minimum longitudinal safety distance is:

[0029]

[0030] Among them, a M (τ), are the accelerations of the ego vehicle and the vehicle behind the target lane, v M (0) are the initial velocities of the ego vehicle and the vehicle behind in the target lane, respectively;

[0031] (3) Vehicle M and vehicle L in the original lane 0 The minimum longitudinal safety distance is:

[0032]

[0033] Among them, a M (τ), are the accelerations of the vehicle and the vehicle in front of the original lane, v M (0) are the initial velocities of the vehicle and the front vehicle in the original lane respectively;

[0034] When the current road is a curve, the minimum longitudinal safety distance includes:

[0035] (1) The ego vehicle M and the front vehicle L in the target lane d The minimum longitudinal safety distance is:

[0036]

[0037] Where R is the radius of curvature of the outer lane, H is the lane width, l 2 (0) is the vehicle L in the target lane at the initial moment d The arc length along the inner lane to the vehicle M, for l 2 (0) The corresponding central angle of the circle;

[0038] (2) The ego vehicle M and the vehicle F behind in the target lane d The minimum longitudinal safety distance is:

[0039]

[0040] (3) Vehicle M and vehicle L in the original lane 0 The minimum longitudinal safety distance is:

[0041]

[0042] Among them l 1 (0) is the initial moment of the self-vehicle M and the front vehicle L in the original lane 0 Distance along the outside lane.

[0043] The traffic flow of the lane with or without the lane change target lane described in step 4 is respectively:

[0044] (1) When there is no lane-changing behavior, the traffic volume in the target lane is:

[0045]

[0046] In the formula, v H is the average speed of the target lane, T is the total duration of the statistical period, t 2 is the time interval between two adjacent vehicles,

[0047] (2) When there is a lane change, the traffic flow in the target lane is:

[0048]

[0049] In the formula, v L is the current speed of the vehicle, a is the acceleration of the vehicle, t 1 ,t 2 are the duration of the first half and the second half of the lane change, T 1 is the total time required to complete the lane change, T 1 =t acc +t lat , where the time required for the vehicle to accelerate to the target speed is t lat The time required for the vehicle to change lanes.

[0050] The minimum fluctuation of vehicle flow in step 4 is:

[0051] J c =β (δ-1) ·(nn c )

[0052] In the formula, β is the traffic flow fluctuation influence coefficient, which is a positive number less than 1, and δ is the number of times the lane change intention is generated but the lane change operation is not executed in step 2. When the lane change intention is generated multiple times but the lane change behavior is not successfully executed, the lane change motivation is stronger and the influence of traffic flow fluctuation gradually decreases.

[0053] Beneficial effects of the present invention:

[0054] The present invention proposes an active lane changing system for intelligent driving vehicles taking into account the traffic flow of intelligent vehicle groups. The motion information of environmental vehicles is obtained by vehicle-to-vehicle communication in the intelligent vehicle group, the influence of lane changing behavior on the traffic flow of the target lane is analyzed, and a traffic flow influence model is proposed. Meanwhile, different road conditions are taken into consideration. In the cases of straight roads and curves, the influence of road curvature on the minimum safe distance model is comprehensively considered. The above two models are combined to establish a comprehensive lane changing decision model, which provides a practical decision basis for intelligent connected vehicles when they have the intention to change lanes. Finally, a more comprehensive and reasonable lane changing control method is obtained, while frequent and unreasonable lane changing behaviors of vehicles are avoided, the safety of vehicle driving is ensured, and the efficiency of road traffic is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Schematic diagram of the overall structure of the lane changing system of the present invention;

[0056] Figure 2 Schematic diagram of the distribution of cameras of the lane changing system of the present invention;

[0057] Figure 3 Schematic diagram of the distribution of the lane changing system radar of the present invention;

[0058] Figure 4 It is a structural schematic diagram of the HMI module in the lane changing system of the present invention;

[0059] Figure 5 It is a structural schematic diagram of a high-precision electronic map module in the lane changing system of the present invention;

[0060] Figure 6 It is a structural schematic diagram of a behavior decision module in the lane changing system of the present invention;

[0061] Figure 7 A logical schematic diagram of the lane-changing comprehensive decision-making method of the present invention;

[0062] Figure 8 This is a schematic diagram of a straight lane changing scenario of the present invention;

[0063] Fig. 9 This is a schematic diagram of a lane-changing scene on a curve according to the present invention;

[0064] Fig.10 It is a schematic diagram of a collision between a vehicle and an adjacent vehicle in a straight lane change situation of the present invention;

[0065] Fig.11 It is a schematic diagram of a collision between a vehicle and an adjacent vehicle in a lane change situation on a curve according to the present invention;

[0066] Fig.12 A relationship diagram between the minimum safe distance between the vehicle and the neighboring vehicle and the lane changing time in the case of lane changing on a straight road according to the present invention;

[0067] Fig.13 A relationship diagram between the minimum safe distance between the vehicle and the neighboring vehicle and the curve radius in the case of changing lanes on a curve according to the present invention;

[0068] Fig.14 A graph showing the relationship between the vehicle flow rate and the lane-changing vehicle acceleration with and without lane-changing in the present invention;

[0069] Fig.15 A relationship diagram of the vehicle flow rate and the difference between the current speed and the expected speed of the lane-changing vehicle when there is / is not a lane-changing in the present invention;

[0070] 1. Camera 2. Radar 3. Wheel speed sensor 4. IMU component

[0071] 5. Communication module 6. GNSS module 7. ECU module 8. HMI module

[0072] 9. Motion execution module 10. LiDAR 11. Millimeter wave radar

[0073] 12. Basic vehicle information module 13. High-precision electronic map module 14. Navigation module

[0074] 15. Memory 16. Motion decision module 17. Drive execution module

[0075] 18. Braking execution module 19. Steering execution module 20. Static information module

[0076] 21. Dynamic information module 22. Basic map module 23. Regional map module

[0077] 24. Real-time dynamic map module 25. Global route drawing module

[0078] 26. Local route drawing module 27. User demand input module

[0079] 28. Vehicle information feedback module 29. Behavior decision module 30. Trajectory drawing module

[0080] 31. Motion decomposition module 32. Feedback adjustment module 33. Traffic sign module

[0081] 34. Mobile obstacle module 35. Fixed obstacle module

[0082] 36. Motion gain determination module 37. Safety determination module

[0083] 38. Environmental impact determination module 39. Active input module 40. Intelligent perception module. DETAILED DESCRIPTION

[0084] Combination Figure 1-6 As shown:

[0085] The present invention provides an active lane-changing system for intelligent driving vehicles taking into account the flow of intelligent vehicle groups, characterized in that it includes a camera 1, a radar 2, a wheel speed sensor 3, an IMU component 4, a communication module 5, a GNSS module 6, an ECU module 7, an HMI module 8 and a motion execution module 9. The camera 1, the radar 2, the wheel speed sensor 3, the IMU component 4, the communication module 5, the GNSS module 6, the HMI module 8 and the motion execution module 9 are all arranged on the vehicle body and connected to the ECU module 7 through the CAN bus on the vehicle;

[0086] The camera 1 includes at least 5 monocular cameras, which are respectively arranged at the front side, rear side, left side, right side middle part and roof middle part of the vehicle body. The monocular camera uses the S-Cam 4 series camera produced by ZF company, which is used to realize the functions of object type recognition, road indication information recognition, light source type recognition, etc.

[0087] The radar 2 includes at least four laser radars 10 and six short-range millimeter-wave radars 11. The laser radars 10 use the Iris laser radars produced by Luminar, which are respectively located at the left front, left rear, right front, and right rear corners of the vehicle; the millimeter-wave radars 11 use the 77GHz short-range millimeter-wave radar SRR520 produced by Continental, which are respectively located at the front, middle, and rear of the left and right sides of the vehicle body;

[0088] The wheel speed sensor 3 uses a differential two-wire Hall sensor TLE4941-1C produced by Infineon to estimate the current vehicle speed;

[0089] The IMU component 4 uses the ADIS16448 10-DOF inertial sensor produced by ADI, including a three-axis gyroscope, a three-axis accelerometer, a three-axis magnetometer and a barometer, which are used to measure the angular velocity, acceleration, yaw angle and altitude of the vehicle; the gyroscope is used to measure the angular velocity of the vehicle around the three axes of the vehicle coordinate system XYZ, the accelerometer is used to measure the acceleration of the vehicle along the three axes of XYZ, the magnetometer is used to measure the yaw angle of the vehicle relative to the three axes of XYZ, and the barometer is used to measure the altitude of the vehicle;

[0090] The communication module 5 uses LTE-V2X technology based on the cellular mobile communication system, and its operating frequency band is 5905-5925MHz. It is equipped with the 9150C-V2X chipset produced by Qualcomm. When communicating between vehicles, LTE-V-direct technology is used to achieve direct information interaction between vehicles. In other cases, LTE-V-cell technology is used to achieve large bandwidth and large coverage communication.

[0091] The information exchanged by the communication module 5 includes authentication information, upload information and distribution information. The authentication information is the authentication information such as the license plate number sent by the vehicle terminal to the cloud server after completing the device registration. The upload information includes the information reported by the vehicle at a certain frequency, including the current speed, position, driving direction, driving intention, etc. of the vehicle. The distribution information includes traffic events, roadside safety information and movement information of the surrounding vehicles sent by the cloud server;

[0092] The GNSS module 6 uses RTK-GNSS (real time kinematic GNSS) technology to determine the absolute position of the vehicle. Based on carrier phase differential technology, centimeter-level positioning accuracy can be achieved. The absolute position includes the current latitude, longitude and altitude of the vehicle.

[0093] The HMI module 8 includes a user demand input module 27 and a vehicle information feedback module 28. The user demand input module 27 includes an active input module 39 and an intelligent perception module 40. The active input module 39 allows the driver to input his or her needs to the vehicle through touch, voice, body feeling and other means. The touch means include pressing a button, adjusting a knob, touching a screen and other means. The body feeling means include gesture input and other means. The intelligent perception module 40 includes the vehicle sensing the air condition in the vehicle, the user's psychology, emotional changes and other information through olfactory perception, biological perception and other means, and intelligently sensing the user's needs. The vehicle information feedback module allows the vehicle to inform the user of the current and future operating status of the vehicle through vision, voice, touch and other means.

[0094] The ECU module 7 converts the obtained motion information into a control signal to control the drive execution module 17, the brake execution module 18 and the steering execution module 19 in the motion execution module 9 to perform corresponding operations. The drive execution module 17 includes a drive ECU and a drive device, including an engine, a motor, a transmission, etc.; the brake execution module includes a brake ECU and an ABS system; the steering execution module includes a steering ECU and an EPS system;

[0095] The ECU module 7 includes a basic information module 12 of the vehicle, a high-precision electronic map module 13, a navigation module 14, a memory 15 and a motion decision module 16. The basic information module 12 of the vehicle, the high-precision electronic map module 13, the navigation module 14 and the motion decision module 16 are respectively connected to the memory 15; the basic information module 12 of the vehicle and the high-precision electronic map module 13 are respectively connected to the navigation module 14; the navigation module is connected to the motion decision module 16, and the memory 15 is used to store the corresponding data of the vehicle and the surrounding vehicles, and can also store the operation programs of each module and the corresponding operation results;

[0096] The vehicle basic information module 12 includes a static information module 20 and a dynamic information module 21. The static information module 20 includes absolute position information, relative position information and heading information. The absolute position information includes the latitude and longitude of the vehicle and the altitude information. The relative position information includes the position information of the vehicle relative to the surrounding environment. The heading information includes the current driving direction information of the vehicle. The dynamic information module 21 includes the speed and acceleration information of the vehicle.

[0097] The high-precision electronic map module 13 includes a basic map module 22, a regional map module 23 and a real-time dynamic map module 24. The basic map module 22 provides map information including basic road network information, building information, etc. The regional map module 23 provides road speed limit information, road lane lines, slope and curvature information, etc. of the area where the vehicle is currently located on the basis of the basic map module 22; the real-time dynamic map module 24 includes a traffic sign module 33, a mobile obstacle module 34 and a fixed obstacle module 35, which provide detailed traffic light information of the road section where the vehicle is currently located, the location and speed information of other vehicles and pedestrians, etc.;

[0098] The navigation module 14 includes a global route drawing module 25 and a local route drawing module 26. The global route drawing module 25 draws a route with the shortest time based on the current position, speed information and destination information of the vehicle and comprehensively considers the real-time traffic information obtained by the communication module. The local route drawing module 26 includes a behavior decision module 29 and a trajectory drawing module 30. The behavior decision module 29 includes a motion gain determination module 36, a safety determination module 37 and an environmental impact determination module 38. According to the actual traffic conditions of the current road, the safety and rationality of the lane changing behavior are determined, and the behavior decision of lane changing or lane keeping is made. The trajectory drawing module 30 draws a motion trajectory that meets the behavior requirements according to the decision made by the behavior decision module.

[0099] The motion decision module 16 includes a motion decomposition module 31 and a feedback adjustment module 32. The motion decomposition module 31 decomposes the motion trajectory drawn by the trajectory drawing module into the longitudinal and lateral speeds and accelerations of the vehicle at each moment, and transmits them to the motion execution module 9 to complete the corresponding motion operation. The feedback adjustment module 32 completes the adjustment of the motion state at the next moment according to the difference between the current motion state and the expected motion state.

[0100] Combination Figure 7-15 As shown:

[0101] The present invention provides an active lane changing system for intelligent driving vehicles taking into account the flow of intelligent vehicle groups, comprising the following steps:

[0102] Step 1: Obtain the motion information of the vehicle through the wheel speed sensor 3 and the IMU component 4, and obtain the motion information and relative position information of the vehicle in the adjacent lane through vehicle-to-vehicle communication, radar 2, etc. The vehicle-to-vehicle communication realizes information exchange between vehicles through the periodic transmission mode. The motion information includes the current speed and acceleration information of the vehicle and the vehicle in the adjacent lane, and the relative position information includes the relative position relationship between the vehicle in the adjacent lane and the vehicle in the longitudinal and lateral directions;

[0103] Step 2: Determine whether the lane-changing behavior can bring better operating benefits to the vehicle, including:

[0104] (1) Based on the motion information obtained in step 1, the motion information of the ego vehicle is compared with that of the vehicles in the adjacent lane. If the average speed and acceleration of the vehicles in the adjacent lane are significantly higher than those of the ego vehicle, a lane change intention is generated. Otherwise, the behavior decision module 29 generates a lane keeping instruction and repeats step 1.

[0105] (2) The adjacent lane with a higher driving speed, acceleration, and greater following distance is temporarily designated as the target lane. The following distance is as follows: Figure 8 As shown, the calculation formula is:

[0106] d rel =v H ·τ+L

[0107] Where τ is the following distance, L is the vehicle length, v H is the average lane speed.

[0108] Step 3: If the lane-changing intention is generated in step 2 and the target lane is determined, the basic information of the current road is determined through communication between the vehicle and the roadside unit (RSU), and the calculation of the longitudinal minimum safety distance is completed, and this is used as the safety condition for the lane-changing behavior; the longitudinal minimum safety distance includes the longitudinal minimum safety distance between the vehicle and the vehicle in front of the target lane, the longitudinal minimum safety distance between the vehicle and the vehicle behind the target lane, and the longitudinal minimum safety distance between the vehicle and the vehicle in front of the original lane;

[0109] If the longitudinal distance between the vehicle and any of the vehicles in front of the target lane, behind the target lane, or in front of the original lane is less than the corresponding longitudinal minimum safety distance, the vehicle cannot change lanes, and the behavior decision module 29 generates a lane keeping instruction and repeats step 1.

[0110] Step 4: If the longitudinal distances between the ego vehicle and the vehicle in front of the target lane, the vehicle behind the target lane, and the vehicle in front of the original lane all meet the minimum safety distance condition in step 3, the calculation of the target lane traffic flow with or without lane changing behavior is completed, and it is further determined whether the minimum fluctuation of the traffic flow is met. If the traffic flow fluctuation caused by the lane changing is less than the set threshold condition value, it is considered that the decision condition for lane changing is met, and the behavior decision module 29 generates a lane changing instruction; otherwise, a lane keeping instruction is generated, and step 1 is repeated.

[0111] Step 5: If the traffic flow fluctuation calculated in step 4 meets the corresponding conditions, the lane change decision is considered feasible, the behavior decision module 29 issues a lane change instruction, and the trajectory drawing module 30 draws a reasonable lane change trajectory. At the same time, the ego vehicle transmits the lane change intention to other vehicles in the smart car group in the event-triggered traffic mode.

[0112] Figure 8 and Fig. 9 The positions of the vehicles in the straight and curved lane changing situations are shown respectively. In order to conveniently represent the longitudinal and lateral distance relationship between the vehicles involved, the geodetic coordinate system is shown in the figure, with O as the origin, the X-axis pointing to the vehicle driving direction, and the Y-axis perpendicular to the X-axis pointing to the target lane. Therefore, the longitudinal acceleration, longitudinal velocity, longitudinal position and lateral position are respectively expressed as a i (t), v i (t), x i (t) and y i (t), where i∈{L d ,F d ,L 0 ,M}.

[0113] Combine the following Fig.10 , Fig.11 The calculation of the corresponding longitudinal minimum safety distance according to the current road conditions in step 3 is explained in detail, where M represents the vehicle, L d represents the front vehicle in the target lane, F d represents the vehicle behind the target lane, L 0 Represents the front car in the original lane:

[0114] When the current road is a straight road, Fig.10 This is a schematic diagram of a collision between the vehicle and the neighboring vehicle in a straight lane change situation;

[0115] (1) When the ego vehicle M and the front vehicle L in the target lane d When a collision occurs, the lateral displacement of the vehicle is:

[0116]

[0117] Where S is the initial lateral distance between the upper edge of the ego vehicle and the lower edge of the vehicle in front of the target lane, and W is the vehicle width (assuming that the vehicle length and width are the same in the embodiment). Considering all collision forms, the collision avoidance condition between the ego vehicle and the vehicle in front of the target lane is as follows:

[0118]

[0119] In the formula, x M (t) is the longitudinal displacement of the vehicle, is the longitudinal displacement of the vehicle in front of the target lane, L is the vehicle length, θ(t) is the yaw angle of the lane-changing vehicle, and satisfies the following formula:

[0120]

[0121] v lat (t) is the lateral speed of the vehicle, v M (t) is the longitudinal speed of the vehicle. The maximum θ(t), i.e. the maximum sin(θ(t)), occurs at t=t c +t adj The time is obtained. It is defined as the distance between the vehicle and the front vehicle in the target lane L d In [t c +t adj , t lat +t adj ] The distance that should be maintained during the time interval to avoid collision Ld =L+W×sin(θ(t c +t adj )), t lat is the time it takes for the vehicle to cut into the target lane from the original lane. The above formula is simplified to:

[0122]

[0123] Use S r (t) represents the distance between the ego vehicle M and the front vehicle L in the target lane d The longitudinal distance during the lane change process is obtained:

[0124]

[0125] In order to achieve the goal of the self-vehicle M and the front vehicle L in the target lane during the lane change process d The following equation must be satisfied to avoid any collision:

[0126]

[0127] In the formula S r (0) is the longitudinal distance from the front of the vehicle to the rear of the vehicle in front of the target lane at the initial moment, is the longitudinal position from the upper left corner of the front vehicle in the target lane to the origin of the coordinate system at the initial moment, xM (0) is the longitudinal position from the upper left corner of the vehicle to the origin of the coordinate system at the initial moment;

[0128] During the lane change process, the ego vehicle M does not collide with the front vehicle L in the target lane d Minimal safe distance (MSD) for any type of collision d ):

[0129]

[0130] Among them, a M (τ), are the accelerations of the vehicle and the vehicle in front of the target lane, respectively, v M (0) are the initial velocities of the vehicle and the vehicle in front of the target lane, L is the vehicle length, t c It indicates the time when the collision occurs during the process of cutting into the target lane after the lane-changing vehicle completes the adjustment of the longitudinal distance and longitudinal speed. It is generally half of the entire cutting process time, between 1.5s and 2.5s. adj It represents the time required for the vehicle to adjust the longitudinal distance and longitudinal speed before starting the lane change operation in order to successfully change lanes. This time is usually very small and can be ignored. c +t adj is the time when the collision occurs, T is the total lane change time;

[0131] (2) To avoid the collision between the ego vehicle M and the vehicle F behind in the target lane d In case of any kind of collision, the following formula must be satisfied for conservative reasons:

[0132]

[0133] Use S r (t) represents the distance between the ego vehicle M and the vehicle F behind in the target lane d The longitudinal distance during the lane change process is obtained:

[0134]

[0135] In order to achieve the goal of the self-vehicle M and the target lane rear vehicle F during the lane change process d The following equation must be satisfied to avoid any collision:

[0136]

[0137] In the formula S r (0) is the longitudinal distance from the front of the vehicle behind to the rear of the vehicle in the target lane at the initial moment, is the longitudinal position from the upper left corner of the rear vehicle in the target lane to the origin of the coordinate system at the initial moment, xM (0) is the longitudinal position from the upper left corner of the vehicle to the origin of the coordinate system at the initial moment;

[0138] During the lane change process, the ego vehicle M does not collide with the vehicle F behind it in the target lane d The minimum MSD(M,F) for any type of collision to occur d ):

[0139]

[0140] Among them, a M (τ), are the accelerations of the ego vehicle and the vehicle behind the target lane, v M (0) are the initial velocities of the ego vehicle and the vehicle behind in the target lane, respectively;

[0141] (3) To avoid the collision between the vehicle M and the vehicle L in front of the original lane 0 For any kind of collision to occur, the following formula must be satisfied:

[0142]

[0143] Define the vehicle and the vehicle in front of the original lane L 0 In [0,t c +t adj ] The distance that should be maintained during the time interval to avoid collision L0 =L+W×sin(θ(t c +t adj )),Use S r (t) represents the distance between the vehicle M and the vehicle L in the original lane. 0 The longitudinal distance during the lane change process is obtained:

[0144]

[0145] In order to achieve the same lane change as the front vehicle L in the original lane, 0 The following equation must be satisfied to avoid any collision:

[0146]

[0147] In the formula S r (0) is the longitudinal distance from the front of the vehicle to the rear of the vehicle in front of the original lane at the initial moment, is the longitudinal position from the upper left corner of the front vehicle in the original lane to the origin of the coordinate system at the initial moment, x M (0) is the longitudinal position from the upper left corner of the vehicle to the origin of the coordinate system at the initial moment;

[0148] During the lane change process, vehicle M does not make contact with the vehicle ahead L in the original lane 0 The minimum MSD(M,L) for any type of collision to occur0 ):

[0149]

[0150] Among them, a M (τ), are the accelerations of the vehicle and the vehicle in front of the original lane, v M (0) are the initial velocities of the vehicle and the front vehicle in the original lane respectively;

[0151] When the current road is a curve, Fig.11 This is a schematic diagram of a collision between the vehicle and the neighboring vehicle in a lane change situation on a curve.

[0152] (1) In order to ensure that the ego vehicle M does not collide with the front vehicle L in the target lane during the lane change process d Any kind of collision must meet the following conditions:

[0153]

[0154] Where S r (t) represents the distance between the ego vehicle M and the front vehicle L in the target lane d Longitudinal distance during lane change, Where R is the radius of curvature of the outer lane and H is the lane width.

[0155] According to the law of cosines, the initial moment of lane change is the time between the vehicle M and the vehicle L in the target lane. d Minimum safety distance MSD(M,L d )for:

[0156]

[0157] Among them, l 2 (0) is the vehicle L in the target lane at the initial moment d The arc length from the inner lane to the ego vehicle M is calculated to ensure that there is no collision between the ego vehicle and the vehicle in front of the target lane during the lane change process. φ is l 2 (0) corresponds to the central angle of the circle,

[0158] (2) In order to achieve the goal of the self-vehicle M and the target lane rear vehicle F in the lane change process d No collision of any kind occurs, the following equation must be satisfied:

[0159]

[0160] S r (t) represents the distance between the ego vehicle M and the vehicle F behind in the target lane dAccording to the cosine theorem formula, the longitudinal distance between the self-vehicle M and the target lane rear vehicle F at the initial moment of the lane change is d Minimum safety distance MSD(M,F d )for:

[0161]

[0162] Where R is the radius of curvature of the outer lane, H is the lane width, l 2 (0) is the vehicle F behind the target lane at the initial moment d The arc length from the inner lane to the ego vehicle M is calculated to ensure that there is no collision between the ego vehicle and the vehicle behind in the target lane during the lane change process. φ is l 2 (0) The corresponding central angle of the circle;

[0163] (3) In order to achieve the goal of the self-vehicle M and the front vehicle L in the original lane during the lane change process 0 No collision of any kind occurs, the following equation must be satisfied:

[0164]

[0165] S r (t) represents the distance between the vehicle M and the vehicle L in the original lane. 0 The longitudinal distance during the lane change process is, according to the geometric relationship, the initial moment of the lane change between the vehicle M and the vehicle L in the original lane. 0 Minimum safety distance MSD(M,L 0 )for:

[0166]

[0167] Among them l 1 (0) is the initial moment of the self-vehicle M and the front vehicle L in the original lane 0 The distance along the outer lane is to ensure that the vehicle does not collide with the vehicle in front of it during the lane change process.

[0168] The traffic flow of the lane with or without the lane change target lane described in step 4 is respectively:

[0169] (1) When there is no lane-changing behavior, the traffic volume in the target lane is:

[0170]

[0171] In the formula, v H is the average speed of the target lane, T is the total duration of the statistical period, t 2 is the time interval between two adjacent vehicles,

[0172] (2) When there is lane changing, the entire statistical period is divided into the first half of the lane changing, the second half of the lane changing, and the period without lane changing. The traffic volume of the target lane is:

[0173]

[0174] The first part of the formula is the traffic flow in the first half of the lane change period, the second part is the traffic flow in the second half of the lane change period, and the third part is the traffic flow in the period without lane change. L is the current speed of the vehicle, a is the acceleration of the vehicle, t 1 ,t 2 are the duration of the first half and the second half of the lane change, T 1 is the total time required to complete the lane change, T 1 =t acc +t lat , where the time required for the vehicle to accelerate to the target speed is t lat The time required for the vehicle to change lanes.

[0175] The minimum fluctuation of vehicle flow in step 4 is:

[0176] J c =β (δ-1) ·(nn c )

[0177] Wherein, β is the traffic flow fluctuation influence coefficient, which is a positive number less than 1. In this embodiment, the value is 0.95. When you want to reduce the lane changing frequency, you can increase this value appropriately. δ is the number of times the lane changing intention is generated but the lane changing operation is not performed in step 2. When the lane changing intention is generated multiple times but the lane changing behavior is not successfully performed, the lane changing motivation is stronger, and the influence of traffic flow fluctuation gradually decreases.

[0178] Fig.12 It shows the relationship between the minimum safe distance between the vehicle and the neighboring vehicle and the lane changing time under the straight lane changing condition. In this embodiment, the vehicle length L = 5m. It can be concluded that for the minimum safe distance between the vehicle and the front vehicle in the target lane and the vehicle and the rear vehicle in the target lane, when the acceleration difference is positive, the value increases with the increase of the lane changing time, and the larger the longitudinal acceleration difference, the more significant the increase of the minimum safe distance. When the longitudinal acceleration difference is negative, the minimum safe distance decreases with the increase of the lane changing time, and the larger the longitudinal acceleration difference, the more significant the decrease of the minimum safe distance, and even negative values ​​appear in a certain area. As for the minimum safe distance between the vehicle and the front vehicle in the original lane, the value is always positive and increases with the increase of the lane changing time. The larger the longitudinal acceleration difference, the more significant the increase of the minimum safe distance. To a certain extent, a positive longitudinal speed difference will lead to a larger minimum safe distance.

[0179] Fig.13 The relationship between the difference in the minimum safe distance between the vehicle and the neighboring vehicle and the curve radius under the conditions of changing lanes on a curve and a straight road is shown. In this embodiment, the lane width H = 3.75m, and the total lane change time is taken as 3s. It can be concluded that when the curve radius is smaller, the difference in the minimum safe distance is more significant. As the radius gradually increases, the difference becomes smaller and smaller, indicating that when the curve radius is small, the minimum safe distance model for lane change on a straight road cannot be simply applied, otherwise it may be possible to successfully change lanes on a straight road but fail to change lanes on a curve.

[0180] Fig.14 It shows the relationship between the traffic volume and the acceleration of the lane-changing vehicle with or without lane-changing, where T = 120s, τ = 1.5s, L = 5m, v H =25m / s,v L =19m / s. As can be seen from the figure, with the increase of lane-changing acceleration, the impact of lane-changing behavior on traffic flow gradually decreases. When the acceleration is too large, the increase in acceleration has no obvious impact on traffic flow. Therefore, in order to ensure the riding comfort of passengers, it is not advisable to use excessive acceleration.

[0181] Fig.15 It represents the relationship between the traffic flow and the difference between the current speed and the expected speed of the lane-changing vehicle with or without lane-changing, where v H =28m / s,a=3m / s 2 When the acceleration is kept constant, the greater the difference between the current speed and the expected speed, the longer the acceleration time required by the vehicle, which prolongs the duration of the lane change. As can be seen from the figure, the greater the difference between the current speed and the expected speed, the greater the impact of lane change on the traffic flow in the target lane, so such lane change behavior should be reduced.

Claims

1. An active lane changing method for intelligent driving vehicles considering the flow of intelligent vehicle groups, Features: The following steps are involved: Step 1: Obtain the motion information of the ego vehicle and the vehicles in the adjacent lanes, and the relative position information of the ego vehicle and the vehicles in the adjacent lanes. The motion information includes the current speed and acceleration information of the ego vehicle and the vehicles in the adjacent lanes, and the relative position information includes the relative position relationship between the vehicles in the adjacent lanes and the ego vehicle in the longitudinal and lateral directions. Step 2: Based on the corresponding information obtained in step 1, determine whether the lane change behavior can bring better operating benefits to the vehicle and determine the target lane: Compare the motion information of the ego vehicle with that of the vehicles in the adjacent lane. If the average speed and acceleration of the vehicles in the adjacent lane are significantly higher than that of the ego vehicle, then the intention to change lanes is generated. Otherwise, the lane keeping is continued. The process of determining the target lane is as follows: The adjacent lane with a higher driving speed, acceleration and greater following distance is temporarily set as the target lane. The following distance calculation formula is: d rel =v H ·τ+L Where τ is the following distance, L is the vehicle length, and v H is the average lane speed; Step 3: If the lane-changing intention is generated in step 2 and the target lane is determined, the basic information of the current road is determined through communication between the vehicle and the road side unit (RSU), and the calculation of the longitudinal minimum safety distance is completed, and this is used as the safety condition for the lane-changing behavior; the longitudinal minimum safety distance includes the longitudinal minimum safety distance between the vehicle and the vehicle in front of the target lane, the longitudinal minimum safety distance between the vehicle and the vehicle behind the target lane, and the longitudinal minimum safety distance between the vehicle and the vehicle in front of the original lane; If the longitudinal distance between the vehicle and any of the vehicles in front of the target lane, behind the target lane, or in front of the original lane is less than the corresponding minimum longitudinal safety distance, the vehicle cannot change lanes, stays in the current lane, and repeats step 1; Step 4: If the longitudinal distances between the ego vehicle and the vehicle in front of the target lane, the vehicle behind the target lane, and the vehicle in front of the original lane all meet the minimum safety distance condition in step 3, the calculation of the traffic flow in the target lane with or without lane change is completed, and further judgment is made as to whether the minimum fluctuation of the traffic flow is met. If the traffic flow fluctuation caused by lane change is less than the set threshold condition value, it is considered that the decision condition for lane change is met, otherwise the vehicle maintains the current lane and step 1 is repeated; Step 5: If the traffic flow fluctuation calculated in step 4 meets the corresponding conditions, the lane change decision is considered feasible, a reasonable lane change trajectory is drawn and the vehicle is controlled to follow the trajectory. At the same time, the ego vehicle transmits the lane change intention to other vehicles in the intelligent vehicle group in an event-triggered transmission mode; The traffic flow of the target lane with or without lane change described in step 4 is specifically: (1) When there is no lane-changing behavior, the traffic volume in the target lane is: ， In the formula, v H is the average speed of the target lane, T is the total duration of the statistical period, t 2 is the time interval between two adjacent vehicles, , (2) When there is a lane change, the traffic flow in the target lane is: ， In the formula, v L is the current speed of the vehicle, a is the acceleration of the vehicle, t 1 ,t 2 are the duration of the first half and the second half of the lane change, T 1 The total time required to complete the lane change; The traffic flow fluctuation described in step 4 is specifically: J c =β (δ-1) ·(nn c ) Where β is the traffic flow fluctuation influence coefficient, which is a positive number less than 1, and δ is the number of times the lane change intention is generated but the lane change operation is not performed in step 2. When the lane change intention is generated multiple times but the lane change behavior is not successfully executed, the lane change motivation is stronger and the influence of traffic flow fluctuation gradually decreases.

2. According to claim 1, a method for active lane changing of an intelligent driving vehicle taking into account the flow of intelligent vehicle groups, Features: In step 3, the corresponding longitudinal minimum safety distance is calculated according to the current road conditions as follows: When the current road is a straight road, the minimum longitudinal safety distance includes: (1) The ego vehicle M and the front vehicle L in the target lane d The minimum longitudinal safety distance is: ， Among them, a M (τ), are the accelerations of the vehicle and the vehicle in front of the target lane, respectively, v M (0) are the initial velocities of the vehicle and the vehicle in front of the target lane, L is the vehicle length, t c It indicates the time when the lane-changing vehicle collides with the target lane after completing the adjustment of the longitudinal distance and longitudinal speed, t adj Indicates the time required for the vehicle to adjust the longitudinal distance and longitudinal speed before starting the lane change operation in order to successfully perform the lane change operation, t c +t adj is the time when the collision occurs, T is the total lane change time; (2) The ego vehicle M and the vehicle F behind in the target lane d The minimum longitudinal safety distance is: ， Among them, a M (τ), are the accelerations of the ego vehicle and the vehicle behind the target lane, v M (0) are the initial velocities of the ego vehicle and the vehicle behind in the target lane, respectively; (3) Vehicle M and vehicle L in the original lane 0 The minimum longitudinal safety distance is: ， Among them, a M (τ), are the accelerations of the vehicle and the vehicle in front of the original lane, v M (0) are the initial velocities of the vehicle and the front vehicle in the original lane respectively; When the current road is a curve, the minimum longitudinal safety distance includes: (1) The ego vehicle M and the front vehicle L in the target lane d The minimum longitudinal safety distance is: ， Where R is the radius of curvature of the outer lane, H is the lane width, l 2 (0) is the vehicle L in the target lane at the initial moment d The arc length along the inner lane to the vehicle M, for l 2 (0) The corresponding central angle of the circle; (2) The ego vehicle M and the vehicle F behind in the target lane d The minimum longitudinal safety distance is: ， (3) Vehicle M and vehicle L in the original lane 0 The minimum longitudinal safety distance is: ， Among them l 1 (0) is the initial moment of the self-vehicle M and the front vehicle L in the original lane 0 Distance along the outside lane.

3. An active lane-changing system for an intelligent driving vehicle considering the flow of an intelligent vehicle group, which executes the active lane-changing method for an intelligent driving vehicle considering the flow of an intelligent vehicle group as claimed in claim 1 or 2, It is characterized in that It includes a camera, a radar, a wheel speed sensor, an IMU component, a communication module, a GNSS module, an ECU module, an HMI module and a motion execution module; the camera, radar, wheel speed sensor, IMU component, communication module, GNSS module, HMI module and motion execution module are all arranged on the vehicle body, and are connected to the ECU module through the CAN bus on the vehicle to realize data transmission between each other; the camera includes at least 5 monocular cameras, which are respectively arranged at the front side, rear side, left side and right middle part of the vehicle body and the middle part of the roof; the radar includes at least 4 laser radars and 6 short-range millimeter wave radars, and the laser radars are respectively located at the left front, left rear, right front and right rear corners of the vehicle; the millimeter wave radars are respectively located at the front, middle and rear parts of the left and right sides of the vehicle body; the IMU component is used to measure the angular velocity, acceleration, yaw angle and altitude of the vehicle; the GNSS module is used to provide the current latitude and longitude and altitude of the vehicle; the ECU module converts the obtained motion information into a control signal to control the driving execution module, the braking execution module and the steering execution module in the motion execution module to perform corresponding operations.

4. The active lane changing system for intelligent driving vehicles considering the flow of intelligent vehicle groups according to claim 3, It is characterized in that The smart car group is a group of smart connected cars with the same or similar destinations; the communication module of the smart connected car uses LTE-V2X technology to realize information interaction between cars and between cars and infrastructure, and the information interaction between cars uses LTE-V-direct technology; the information interaction between cars and infrastructure uses LTE-V-cell technology; the interaction information includes authentication information, upload information and download information.

5. According to claim 3, an active lane changing system for intelligent driving vehicles taking into account the flow of intelligent vehicle groups, It is characterized in that The HMI module includes a user demand input module and a vehicle information feedback module. The user demand input module includes an active input module and an intelligent perception module. The active input module allows the driver to input his or her needs to the vehicle through touch, voice, and body sensation; the intelligent perception module allows the vehicle to perceive the air conditions in the vehicle, the user's psychological and emotional changes through olfactory perception and biological perception, and intelligently perceive the user's needs; the vehicle information feedback module allows the vehicle to inform the user of the current and future operating status of the vehicle through vision, voice, and touch.

6. The active lane changing system for intelligent driving vehicles considering the flow of intelligent vehicle groups according to claim 3, It is characterized in that The ECU module includes a basic vehicle information module, a high-precision electronic map module, a navigation module, a memory and a motion decision module. The basic vehicle information module, the high-precision electronic map module, the navigation module and the motion decision module are respectively connected to the memory; the basic vehicle information module and the high-precision electronic map module are respectively connected to the navigation module; the navigation module is connected to the motion decision module; the basic vehicle information module includes a static information module and a dynamic information module; the high-precision electronic map module includes a basic map module, a regional map module and a real-time dynamic map module; the navigation module includes a global route drawing module and a local route drawing module; the motion decision module includes a motion decomposition module and a feedback adjustment module.

7. The active lane changing system for intelligent driving vehicles considering the flow of intelligent vehicle groups according to claim 6, It is characterized in that The local route drawing module includes a behavior decision module and a trajectory drawing module. The behavior decision module includes a motion gain determination module, a safety determination module and an environmental impact determination module. The behavior decision module determines the safety and rationality of lane changing behavior according to the current road traffic conditions and makes a behavior decision of lane changing or lane keeping. The trajectory drawing module draws a motion trajectory that meets the behavior requirements according to the decision made by the behavior decision module.

8. The active lane changing system for intelligent driving vehicles considering the flow of intelligent vehicle groups according to claim 7, It is characterized in that The motion decision module includes a motion decomposition module and a feedback adjustment module. The motion decomposition module decomposes the motion trajectory drawn by the trajectory drawing module into the longitudinal and lateral speeds and accelerations of the vehicle at each moment, and transmits them to the motion execution module to complete the corresponding motion operation. The feedback adjustment module completes the adjustment of the motion state at the next moment according to the difference between the current motion state and the expected motion state.

Images