CN212667349U - Intelligent driving vehicle active lane changing system considering intelligent vehicle group flow - Google Patents
Intelligent driving vehicle active lane changing system considering intelligent vehicle group flow Download PDFInfo
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- CN212667349U CN212667349U CN202020829145.3U CN202020829145U CN212667349U CN 212667349 U CN212667349 U CN 212667349U CN 202020829145 U CN202020829145 U CN 202020829145U CN 212667349 U CN212667349 U CN 212667349U
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Abstract
The utility model relates to an intelligent driving vehicle active lane changing system considering intelligent vehicle group flow, which 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; the lane change comprehensive decision method comprises the following steps: the motion information who acquires this vehicle and environment vehicle, road basic information, the motion gain of judgement lane changing, the vertical minimum safe distance that the calculation corresponds, judge whether the action of changing the lane causes great influence etc. to the traffic flow, the utility model discloses a communication between the intelligence car crowd fully acquires data, under different road conditions such as straight road and bend, considers the influence of road curvature to minimum safe distance model, and the comprehensive consideration is changed the action and is to the influence of target lane traffic flow, has established the system of changing the lane and has synthesized the decision-making model, provides feasible decision-making basis for intelligent internet connection car when changing the lane, finally obtains more comprehensively, more economical and more efficient comprehensive lane changing control method.
Description
Technical Field
The utility model relates to a consider intelligent vehicle of driving of intelligence car crowd flow and actively trade way system, in particular to a decision-making system is traded in initiative that is used for intelligence car crowd.
Background
With the rapid development of information communication technologies such as cloud computing, big data, internet of things and the like, nowadays, people step into the internet era of everything interconnection, and a new communication technology represented by 5G is merging with various industries, so that the development and the revolution of the society are continuously promoted. The automobile industry, as one of the traditional manufacturing industries, is also continuously transforming and upgrading towards the directions of intelligent manufacturing and internet plus.
An intelligent networked automobile (ICV) (intelligent Connected vehicle) is a combined product of an automobile intelligent technology and an internet technology, wherein the internet technology enables the intelligent automobile to break through the limitation of the sensing capability of a sensor carried by the automobile in multiple aspects such as environmental perception, behavior decision and the like, and the purpose of information interactive sharing of people, the automobile, roads, clouds and the like in the driving process of the automobile is achieved, so that the energy conservation, the safety, the high efficiency and the like of the automobile are greatly improved.
Lane changing is a driving behavior frequently occurring in traffic, and when the traffic flow is small, the reasonable lane changing behavior is beneficial to the vehicle to obtain higher running speed; when the traffic flow is large, the lane changing behavior may seriously affect the driving speed of the traffic flow, reduce the road traffic capacity, and the unreasonable lane changing behavior may even cause serious traffic accidents. Therefore, it is necessary to take into account the impact of lane change behavior on traffic flow when making lane change decisions.
Disclosure of Invention
The utility model aims to solve the technical problems, and designs an active lane change comprehensive decision-making model for considering the influence of lane change behavior on traffic flow on an intelligent vehicle group on the basis of a minimum safe distance model, thereby ensuring the reasonability and feasibility of lane change and avoiding the influence of unreasonable lane change behavior on road passing efficiency; and provides an intelligent driving vehicle active lane changing system considering the flow of the intelligent vehicle group.
The utility model provides a pair of consider intelligent driving vehicle of intelligent car crowd flow and initiatively trade system, a serial communication port, including camera, radar, wheel speed sensor, IMU subassembly, communication module, GNSS module, ECU module, HMI module and motion execution module. The camera, the radar, the wheel speed sensor, the IMU assembly, the communication module, the GNSS module, the HMI module and the motion execution module are all arranged on the vehicle body and are connected with the ECU module through a CAN bus on the vehicle to realize data transmission among the camera, the radar, the wheel speed sensor, the IMU assembly, the communication module, the GNSS module, the HMI module and the motion execution module; the cameras at least comprise 5 monocular cameras which are respectively arranged at the front side, the rear side, the middle part of the left side and the right side of the bicycle body and the middle part of the roof of the bicycle; the radar at least comprises 4 laser radars and 6 short-distance millimeter wave radars which are respectively positioned at the left front corner, the left rear corner, the right front corner and the right rear corner of the vehicle; the millimeter wave radar is respectively positioned at the front part, the middle part and the rear part of the left side and the right side of the vehicle body; the IMU component is used for measuring the angular speed, the acceleration, the yaw angle and the altitude of the vehicle; the GNSS module determines the absolute position of the vehicle by using an RTK-GNSS (real time kinematic GNSS) technology, and can reach centimeter-level positioning accuracy based on a carrier phase difference technology, wherein the absolute position comprises the current longitude and latitude and altitude of the vehicle; and the ECU module converts the obtained motion information into a control signal and controls a driving execution module, a braking execution module and a steering execution module in the motion execution module to execute corresponding operations.
The intelligent vehicle group is a group of intelligent networked vehicles with the same or similar destinations; the communication module of the intelligent networked automobile realizes information interaction between automobiles and infrastructure by using an LTE-V2X technology, the working frequency range of the communication module is 5905 plus 5925MHz, the information interaction between automobiles and infrastructure uses the LTE-V-direct technology without transfer through a base station; the information interaction between the vehicle and the infrastructure uses an LTE-V-cell technology to realize large-bandwidth and large-coverage communication; the interactive information comprises authentication information, uploading information and issuing information; the authentication information is license plate number and other authentication information sent to the cloud server by the vehicle terminal after the device registration is completed, the uploading information comprises information including the current speed, position, driving direction, driving intention and the like of the vehicle reported by the vehicle at a certain frequency, and the issuing information comprises traffic events, roadside safety information and motion information of the environmental vehicle sent by the cloud server.
The HMI module comprises a user demand input module and a vehicle information feedback module, the user demand input module comprises an active input module and an intelligent sensing module, and the active input module inputs own demands to a vehicle by the way of touch sense, voice, body sense and the like of a driver; the intelligent sensing module senses information such as air conditions, user psychology and emotion changes in the vehicle in modes of olfaction sensing, biological sensing and the like, and intelligently senses the requirements of the user; the vehicle information feedback module informs the current running state and the running state of the vehicle in a future period of time to a user through the modes of vision, voice, touch and the like.
The ECU module comprises a self-vehicle basic information module, a high-precision electronic map module, a navigation module, a memory and a motion decision module, wherein the self-vehicle basic information module, the high-precision electronic map module, the navigation module and the motion decision module are respectively connected with the memory; the self-vehicle basic information module and the high-precision electronic map module are respectively connected with the navigation module; the navigation module is connected with the motion decision module; the basic information module of the self-vehicle comprises a static information module and a dynamic information module, and comprises information such as the absolute position, the relative position, the course, the speed, the acceleration and the like of the vehicle; the high-precision electronic map module comprises a basic map module, a regional map module and a real-time dynamic map module, and provides map information including a basic road network, buildings and the like and dynamic map information including traffic signals around a vehicle, environmental vehicles and the like; the navigation module comprises a global route drawing module and a local route drawing module, and is used for drawing the shortest route from the current position of the vehicle to the destination and drawing the route required to be followed at the current road section; the motion decision module comprises a motion decomposition module and a feedback regulation module; the memory is used for storing data.
The local route drawing module comprises a behavior decision module and a track drawing module, the behavior decision module comprises a motion gain judgment module, a safety judgment module and an environmental influence judgment module, whether the lane changing behavior can bring better motion effect for the self, whether the distance between the self and a front vehicle of an original lane, a front vehicle of a target lane and a rear vehicle of the target lane meets the requirement of minimum safe distance and whether the lane changing behavior has overlarge influence on the traffic flow of the target lane are judged respectively, and then a behavior decision of lane changing or lane keeping is made, and the track drawing module draws a motion track meeting the behavior requirement according to the decision made by the behavior decision module.
The motion decomposition module decomposes the motion trail drawn by the trail drawing module into the speed and the acceleration of the vehicle along the longitudinal direction and the lateral direction at each moment, transmits the speed and the acceleration to the motion execution module to complete corresponding motion operation, and the feedback adjustment module completes the self-adaptive adjustment of the motion state at the next moment according to the difference value between the current motion state and the expected motion state.
The utility model discloses a theory of operation, including following step:
step 1: the method comprises the steps that motion information of a vehicle is obtained through an IMU assembly and a wheel speed sensor, the motion information and relative position information of the vehicle in an adjacent lane are obtained through vehicle-vehicle communication, radar and the like, the vehicle-vehicle communication realizes information interaction between vehicles through a Periodic traffic mode, the motion information comprises the current speed and acceleration information of the vehicle and the vehicle in the adjacent lane, and the relative position information comprises the relative position relation of the vehicle in the adjacent lane and the vehicle in the longitudinal direction and the transverse direction;
step 2: judging whether the lane changing behavior can bring better running benefit for the vehicle, and the method specifically comprises the following steps;
(1) comparing the motion information of the vehicle and the adjacent lane vehicle according to the motion information acquired in the step 1, if the average speed and the acceleration of the adjacent lane vehicle are obviously higher than those of the vehicle, generating a lane change intention, otherwise, generating a lane keeping instruction by a behavior decision module 29, and repeating the step 1;
(2) temporarily setting the adjacent lane with higher running speed, higher acceleration and larger following distance as a target lane, wherein the following distance calculation formula is as follows:
drel＝vH·τ+L
wherein τ is the following distance, L is the length, and vHIs the average speed of the lane.
And step 3: if a lane change intention is generated in the step 2 and a target lane is determined, determining basic information of the current Road through communication between the vehicle and a Road Side Unit (RSU), completing calculation of a longitudinal minimum safety distance, and taking the calculation as a safety condition of lane change behavior; the longitudinal minimum safe distance comprises a longitudinal minimum safe distance between the vehicle and a vehicle in front of the target lane, a longitudinal minimum safe distance between the vehicle and a vehicle behind the target lane, and a longitudinal minimum safe distance between the vehicle and a vehicle in front of the original lane;
if the longitudinal distance between the self vehicle and any target in the front vehicle of the target lane, the rear vehicle of the target lane or the front vehicle of the original lane is less than the corresponding longitudinal minimum safety distance, the vehicle cannot change lanes, the behavior decision module 29 generates a lane keeping instruction, and the step 1 is repeated.
And 4, step 4: if the longitudinal distances between the self vehicle and the front vehicle of the target lane, the rear vehicle of the target lane and the front vehicle of the original lane all meet the minimum safe distance condition in the step 3, finishing the calculation of the traffic flow of the lane changing behavior target lane, further judging whether the minimum fluctuation of the traffic flow is met, if the traffic flow fluctuation caused by lane changing is smaller than a set threshold value condition value, considering that the decision condition of lane changing is met, and generating a lane changing instruction by the behavior decision module 29; otherwise, generating a command of lane keeping and repeating the step 1.
And 5: if the traffic flow fluctuation calculated in the step 4 meets the corresponding condition, it is judged that the lane change decision is feasible, the behavior decision module 29 sends out an instruction for executing the lane change, the trajectory drawing module 30 draws a reasonable lane change trajectory, and meanwhile, the own vehicle transmits the lane change intention to other vehicles in the intelligent vehicle group in an eventtrieged traffic mode.
The utility model has the advantages that:
the utility model provides a consider intelligent driving vehicle of intelligent car crowd flow and initiatively trade system, the motion information of environment vehicle is acquireed to the mode through car communication in the intelligent car crowd, the analysis trades the influence of lane action to target lane traffic flow, the traffic flow influence model has been proposed, consider different road conditions simultaneously, respectively under the condition of straight road and bend, the comprehensive consideration road curvature is to the influence of minimum safe distance model, combine two kinds of models above-mentioned, the comprehensive decision-making model of trading has been established, for intelligent internet connection car provides feasible decision-making basis when producing the intention of trading, finally obtain more comprehensively, more reasonable lane-changing control method, the vehicle has been avoided simultaneously frequently, the emergence of unreasonable lane-changing action, the safety that the vehicle went has been guaranteed, the current efficiency of very big improvement road.
Drawings
FIG. 1 is a schematic view of the overall structure of the lane-changing system of the present invention;
FIG. 2 is a schematic view of the distribution of the cameras of the lane-changing system of the present invention;
FIG. 3 is a schematic diagram of the distribution of the lane-changing system radar of the present invention;
FIG. 4 is a schematic structural diagram of an HMI module in the lane changing system of the present invention;
FIG. 5 is a schematic structural diagram of a high-precision electronic map module in the lane-changing system of the present invention;
FIG. 6 is a schematic structural diagram of a behavior decision module in the lane changing system according to the present invention;
FIG. 7 is a logic diagram of the lane change integrated decision making method of the present invention;
FIG. 8 is a schematic view of a straight lane change scene of the present invention;
FIG. 9 is a view illustrating a lane change scene at a curve according to the present invention;
fig. 10 is a schematic view of the present invention when a collision occurs between a self-vehicle and an adjacent vehicle under a straight lane changing condition;
fig. 11 is a schematic view of the utility model when the self-vehicle collides with an adjacent vehicle under the condition of changing the lane at the curve;
FIG. 12 is a graph showing the relationship between the minimum safe distance between the self-car and the adjacent car and the time for changing the lane according to the present invention;
FIG. 13 is a graph showing the relationship between the minimum safe distance between the self-vehicle and the adjacent vehicle and the radius of the curve according to the present invention when the curve is changed;
FIG. 14 is a graph showing the relationship between the traffic flow and the acceleration of the lane-change vehicle when the lane change is performed or not;
FIG. 15 is a diagram showing the relationship between the traffic flow and the difference between the current speed and the expected speed of the lane-change vehicle when the lane-change is performed or not;
1. camera 2, radar 3, wheel speed sensor 4, IMU subassembly
5. Communication module 6, GNSS module 7, ECU module 8, HMI module
9. Motion execution module 10, laser radar 11, millimeter wave radar
12. The system comprises a self-vehicle basic information module 13, a high-precision electronic map module 14 and a navigation module
15. Memory 16, motion decision module 17 and drive execution module
18. Brake execution module 19, steering execution module 20 and static information module
21. Dynamic information module 22, basic map module 23 and regional map module
24. Real-time dynamic map module 25 and global route drawing module
26. Local route drawing module 27 and user requirement input module
28. Vehicle information feedback module 29, behavior decision module 30 and track drawing module
31. Motion decomposition module 32, feedback regulation module 33 and traffic sign module
34. Moving obstacle module 35 and fixed obstacle module
36. Motion gain determination module 37 and security determination module
38. An environment influence judging module 39, an active input module 40 and an intelligent sensing module.
Detailed Description
In conjunction with FIGS. 1-6:
the utility model provides a pair of consider intelligent driving vehicle of intelligent car crowd flow and initiatively trade system, a serial communication port, including camera 1, radar 2, wheel speed sensor 3, IMU subassembly 4, communication module 5, GNSS module 6, ECU module 7, HMI module 8 and motion execution module 9. The camera 1, the radar 2, the wheel speed sensor 3, the IMU assembly 4, the communication module 5, the GNSS module 6, the HMI module 8 and the motion execution module 9 are all arranged on a vehicle body and are connected with the ECU module 7 through a CAN bus on the vehicle;
the camera 1 at least comprises 5 monocular cameras which are respectively arranged at the front side, the rear side, the middle part of the left side and the right side of the bicycle body and the middle part of the roof, and the monocular cameras use S-Cam 4 series cameras and are used for realizing the functions of object type identification, road indication information identification, light source type identification and the like;
the radar 2 at least comprises 4 laser radars 10 and 6 short-distance millimeter wave radars 11, wherein the laser radars 10 use Iris laser radars and are respectively positioned at the left front corner, the left rear corner, the right front corner and the right rear corner of the vehicle; the millimeter wave radar 11 uses a 77GHz short-distance millimeter wave radar SRR520 and is respectively positioned at the front part, the middle part and the rear part of the left side and the right side of the vehicle body;
the wheel speed sensor 3 uses a differential double-wire Hall sensor TLE4941-1C to complete the estimation of the current vehicle speed;
the IMU module 4 uses ADIS16448 ten-degree-of-freedom inertial sensors, including three-axis gyroscopes, three-axis accelerometers, three-axis magnetometers and barometers, for measuring angular velocity, acceleration, yaw angle and altitude of the vehicle; the gyroscope is used for measuring the angular velocity of the vehicle around three X, Y and Z axes of a vehicle coordinate system, the accelerometer is used for measuring the acceleration of the vehicle along the three X, Y and Z axes, the magnetometer is used for measuring the yaw angle of the vehicle relative to the three X, Y and Z axes, and the barometer is used for measuring the altitude of the vehicle;
the communication module 5 uses an LTE-V2X technology based on a cellular mobile communication system, the working frequency band of the communication module is 5905-5925MHz, a 9150C-V2X chip set is carried, the LTE-V-direct technology is used for realizing direct information interaction between vehicles when the vehicles communicate with each other, and the LTE-V-cell technology is used for realizing large-bandwidth and large-coverage communication when the vehicles communicate with each other under other conditions;
the information interacted by the communication module 5 comprises authentication information, uploading information and distribution information, the authentication information is license plate number and other authentication information sent to a cloud server by a vehicle terminal after equipment registration is completed, the uploading information comprises information including current speed, position, driving direction, driving intention and the like of a vehicle reported by the vehicle at a certain frequency, and the distribution information comprises traffic events, roadside safety information and motion information of environmental vehicles sent by the cloud server;
the GNSS module 6 determines the absolute position of the vehicle by using an RTK-GNSS (real time kinematic GNSS) technology, and the absolute position can reach centimeter-level positioning accuracy based on a carrier phase difference technology, wherein the absolute position comprises the current longitude and latitude and altitude of the vehicle;
the HMI module 8 comprises a user requirement input module 27 and a vehicle information feedback module 28, the user requirement input module 27 comprises an active input module 39 and an intelligent sensing module 40, the active input module 39 is used for inputting the requirement of a driver to a vehicle through the modes of touch, voice, body feeling and the like, the touch mode comprises the modes of pressing a key, adjusting a knob, touching a screen and the like, and the body feeling mode comprises the modes of gesture input and the like; the intelligent sensing module 40 senses information such as air conditions, psychology and emotion changes of the user in the vehicle in modes of olfaction sensing, biological sensing and the like, and intelligently senses the requirements of the user; the vehicle information feedback module informs the current and future running states of the vehicle to a user in the modes of vision, voice, touch and the like;
the ECU module 7 converts the obtained motion information into a control signal, controls a driving execution module 17, a braking execution module 18 and a steering execution module 19 in the motion execution module 9 to execute corresponding operations, wherein the driving execution module 17 comprises a driving ECU and a driving device, and comprises an engine, a motor, a transmission and the like; the brake execution module comprises a brake ECU and an ABS system; the steering execution module comprises a steering ECU and an EPS system;
the ECU module 7 comprises a vehicle basic information module 12, a high-precision electronic map module 13, a navigation module 14, a memory 15 and a motion decision module 16, wherein the vehicle basic information module 12, the high-precision electronic map module 13, the navigation module 14 and the motion decision module 16 are respectively connected with the memory 15; the vehicle basic information module 12 and the high-precision electronic map module 13 are respectively connected with the navigation module 14; the navigation module is connected with the motion decision module 16, and the memory 15 is used for storing corresponding data of the self vehicle and the environmental vehicle, and also storing operation programs and corresponding operation results of the modules;
the self-vehicle basic information module 12 comprises a static information module 20 and a dynamic information module 21, wherein the static information module 20 comprises absolute position information, relative position information and course information, the absolute position information comprises longitude and latitude and altitude information of a vehicle, the relative position information comprises position information of the vehicle relative to the surrounding environment, the course information comprises current driving direction information of the vehicle, and the dynamic information module 21 comprises speed and acceleration information of the vehicle;
the high-precision electronic map module 13 comprises a basic map module 22, a regional map module 23 and a real-time dynamic map module 24, wherein the basic map module 22 provides map information including basic road network information, building information and the like, and the regional map module 23 provides road speed limit information, road lane lines, gradient, curvature information and the like of the current region of the vehicle on the basis of the basic map module 22; the real-time dynamic map module 24 comprises a traffic sign module 33, a mobile barrier module 34 and a fixed barrier module 35, and provides detailed traffic light information of a current road section of a vehicle, and position and speed information of other vehicles and pedestrians;
the navigation module 14 comprises a global route drawing module 25 and a local route drawing module 26, the global route drawing module 25 draws a shortest route in use according to 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 comprises a behavior decision module 29 and a track drawing module 30, the behavior decision module 29 comprises a motion gain decision module 36, a safety decision module 37 and an environmental impact decision module 38, the safety and rationality of lane changing behavior are judged according to the actual traffic condition of the current road, a behavior decision for lane changing or lane keeping is made, and the track drawing module 30 draws a motion track meeting the behavior requirements according to the decision made by the behavior decision module;
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 time, and transmits the speeds and accelerations to the motion execution module 9 to complete corresponding motion operations, and the feedback adjustment module 32 completes the adjustment of the motion state at the next time according to the difference between the current motion state and the expected motion state.
As shown in connection with fig. 7-15:
the utility model discloses a theory of operation, including following step:
step 1: the method comprises the steps that motion information of a vehicle is obtained through a wheel speed sensor 3 and an IMU assembly 4, the motion information and relative position information of the vehicle in an adjacent lane are obtained through vehicle-vehicle communication, a radar 2 and the like, information interaction between vehicles is achieved through a Periodic transmission mode of the vehicle-vehicle communication, the motion information comprises the current speed and acceleration information of the vehicle and the vehicle in the adjacent lane, and the relative position information comprises the relative position relation of the vehicle and the vehicle in the adjacent lane in the longitudinal direction and the transverse direction;
step 2: judging whether the lane changing behavior can bring better running benefit for the vehicle, and the method specifically comprises the following steps;
(1) comparing the motion information of the vehicle and the adjacent lane vehicle according to the motion information acquired in the step 1, if the average speed and the acceleration of the adjacent lane vehicle are obviously higher than those of the vehicle, generating a lane change intention, otherwise, generating a lane keeping instruction by a behavior decision module 29, and repeating the step 1;
(2) temporarily setting the adjacent lane with higher driving speed, higher acceleration and larger following distance as a target lane, wherein the following distance is shown as a figure 8, and the calculation formula is as follows:
drel＝vH·τ+L
wherein τ is the following distance, L is the length, and vHIs the average speed of the lane.
And step 3: if a lane change intention is generated in the step 2 and a target lane is determined, determining basic information of the current Road through communication between the vehicle and a Road Side Unit (RSU), completing calculation of a longitudinal minimum safety distance, and taking the calculation as a safety condition of lane change behavior; the longitudinal minimum safe distance comprises a longitudinal minimum safe distance between the vehicle and a vehicle in front of the target lane, a longitudinal minimum safe distance between the vehicle and a vehicle behind the target lane, and a longitudinal minimum safe distance between the vehicle and a vehicle in front of the original lane;
if the longitudinal distance between the self vehicle and any target in the front vehicle of the target lane, the rear vehicle of the target lane or the front vehicle of the original lane is less than the corresponding longitudinal minimum safety distance, the vehicle cannot change lanes, the behavior decision module 29 generates a lane keeping instruction, and the step 1 is repeated.
And 4, step 4: if the longitudinal distances between the self vehicle and the front vehicle of the target lane, the rear vehicle of the target lane and the front vehicle of the original lane all meet the minimum safe distance condition in the step 3, finishing the calculation of the traffic flow of the lane changing behavior target lane, further judging whether the minimum fluctuation of the traffic flow is met, if the traffic flow fluctuation caused by lane changing is smaller than a set threshold value condition value, considering that the decision condition of lane changing is met, and generating a lane changing instruction by the behavior decision module 29; otherwise, generating a command of lane keeping and repeating the step 1.
And 5: if the traffic flow fluctuation calculated in the step 4 meets the corresponding condition, it is judged that the lane change decision is feasible, the behavior decision module 29 sends out an instruction for executing the lane change, the trajectory drawing module 30 draws a reasonable lane change trajectory, and meanwhile, the own vehicle transmits the lane change intention to other vehicles in the intelligent vehicle group in an eventtrieged traffic mode.
Fig. 8 and 9 show the position of each vehicle in the case of a straight lane change and a curved lane change, respectively. For convenience of representation of the longitudinal and lateral distance relationships between the vehicles involved, a geodetic coordinate system is shown in the figure, with O as the origin, the X-axis pointing in the direction of travel of the vehicle, and the Y-axis perpendicular to the X-axis pointing in the target lane. Thus, the longitudinal acceleration, the longitudinal velocity, the longitudinal position and the lateral position are respectively denoted as ai(t)，vi(t)，xi(t) and yi(t) where i ∈ { L ∈ [ ]d,Fd,L0,M}。
The following describes in detail the calculation of the corresponding longitudinal minimum safe distance according to the current road condition in step 3 with reference to fig. 10 and 11, where M represents the own vehicle and L represents the own vehicledRepresenting the front vehicle of the target lane, FdRepresenting the rear vehicle of the target lane, L0Representing the front vehicle of the original lane:
when the current road is a straight road, fig. 10 is a schematic diagram of a collision between a self-vehicle and an adjacent vehicle under the condition of changing the straight road;
(1) when the vehicle M and the front vehicle L of the target lanedWhen collision happens, the transverse displacement of the self vehicle is as follows:
where S is an initial lateral distance between an upper edge of the host vehicle and a lower edge of the vehicle ahead of the target lane, W is a vehicle width (assuming that the length of the vehicle involved in the embodiment is the same as the vehicle width), and considering all collision types, the collision avoidance condition between the host vehicle and the vehicle ahead of the target lane is as follows:
in the formula, xM(t) is the longitudinal displacement of the vehicle,
the longitudinal displacement of the front vehicle of the target lane, L is the vehicle length, and theta (t) is the yaw angle of the lane changing vehicle, and the following formula is satisfied:
vlat(t) lateral speed of the vehicle, vM(t) is the longitudinal vehicle speed of the vehicle, and the maximum θ (t), i.e., the maximum sin (θ (t)) is t when t is equal to tc+tadjThe time is obtained. Defined as the vehicle and the front vehicle L of the target lanedAt [ t ]c+tadj，tlat+tadj]Interval of time is the distance to be kept to avoid collision
tlatFor the time of the process of cutting into the target lane from the original lane, the above formula is simplified as follows:
with Sr(t) represents the host vehicle M and the target lane preceding vehicle LdThe longitudinal distance in the lane changing process is obtained：
In order to achieve the aim that the self vehicle M and the front vehicle L of the target lane are in the lane changing processdThe absence of any form of collision needs to satisfy the following equation:
in the formula
Sr(0) The longitudinal distance from the vehicle head to the vehicle tail in front of the target lane at the initial moment,
the longitudinal position from the upper left corner of the front vehicle of the target lane to the origin of coordinates at the initial moment, xM(0) The longitudinal position from the upper left corner of the vehicle to the origin of coordinates at the initial moment;
front vehicle L without a target lane in the lane changing process of the self vehicle MdMinimum Safe Distance (minimum Safe Distance) MSD (M, L) at which any type of collision occursd)：
Wherein, aM(τ)、
Acceleration, v, of the vehicle, respectively, in front of the target laneM(0)、
The initial speeds of the vehicle and the front vehicle of the target lane, L is the length of the vehicle, tcIndicating the completion of longitudinal distance and longitudinal direction of the lane-changing self-vehicleAfter the speed is adjusted, the time for collision in the process of cutting into the target lane is generally half of the time of the whole cutting-in process and is between 1.5s and 2.5s, and tadjRepresenting the time required for the longitudinal distance and longitudinal speed adjustment of the own vehicle before the lane change operation is started in order to successfully perform the lane change, which is generally small and negligible, tc+tadjT is total lane change time when collision occurs;
(2) to avoid the following vehicle F from the vehicle M and the target lanedAny type of collision occurs, and for conservative reasons, the following equation is satisfied:
with Sr(t) shows the host vehicle M and the rear vehicle F of the target lanedThe longitudinal distance in the lane changing process is obtained as follows:
in order to achieve the aim that the self vehicle M and the target lane rear vehicle F in the lane changing processdThe absence of any form of collision needs to satisfy the following equation:
in the formula
Sr(0) The longitudinal distance from the vehicle head to the vehicle tail behind the target lane at the initial moment,
the longitudinal position from the upper left corner of the rear vehicle of the target lane to the origin of coordinates at the initial moment, xM(0) The longitudinal position from the upper left corner of the vehicle to the origin of coordinates at the initial moment;
rear vehicle F not in contact with target lane in lane changing process of self vehicle MdMinimum value of MSD (M, F) at which any form of collision occursd)：
Wherein, aM(τ)、
Acceleration, v, of the vehicle behind the host vehicle and the target lane, respectivelyM(0)、
Respectively the initial speeds of the self vehicle and the rear vehicle of the target lane;
(3) to avoid the self-vehicle M and the front vehicle L on the original lane0Any type of collision occurs, and the following equation is satisfied:
defining the vehicle and the front vehicle L of the original lane0At [0, tc+tadj]Interval of time is the distance to be kept to avoid collision
With Sr(t) represents the own vehicle M and the preceding vehicle L on the original lane0The longitudinal distance in the lane changing process is obtained as follows:
in order to achieve the aim that the self-vehicle M and the front vehicle L of the original lane are in the lane changing process0The absence of any form of collision needs to satisfy the following equation:
in the formula
Sr(0) The longitudinal distance from the head of the bicycle to the tail of the bicycle in front of the original lane at the initial moment,
the longitudinal position from the upper left corner of the front vehicle of the original lane to the origin of coordinates at the initial moment, xM(0) The longitudinal position from the upper left corner of the vehicle to the origin of coordinates at the initial moment;
the self vehicle M does not contact the front vehicle L of the original lane in the lane changing process0Minimum value of any collision MSD (M, L)0)：
Wherein, aM(τ)、
Acceleration, v, of the vehicle, respectively, in front of the original laneM(0)、
Respectively the initial speeds of the self-vehicle and the front vehicle of the original lane;
when the current road is a curve, fig. 11 is a schematic diagram of a collision between a vehicle and an adjacent vehicle in a curve lane change situation.
(1) In order to achieve the purpose that the self vehicle M does not contact the front vehicle L of the target lane in the lane changing processdThe occurrence of any type of collision is satisfied:
in the formula Sr(t) represents the host vehicle M and the target lane preceding vehicle LdThe longitudinal distance in the course of lane change,
wherein R is the curvature radius of the outer lane and H is the lane width.
According to the cosine law, the self-vehicle M and the front vehicle L of the target lane at the initial time of lane change of the curvedMinimum safety distance MSD (M, L)d) Comprises the following steps:
wherein l2(0) Front vehicle L of target lane at initial momentdThe arc length distance from the inner lane to the self-vehicle M ensures that the self-vehicle does not collide with the front vehicle of the target lane in any mode in the lane changing process,
phi is l2(0) The corresponding central angle of the circle is the angle,
(2) in order to achieve the aim that the self vehicle M and the target lane rear vehicle F in the lane changing processdWithout any kind of collision, the following equation needs to be satisfied:
Sr(t) shows the host vehicle M and the rear vehicle F of the target lanedThe longitudinal distance in the lane changing process is determined by the formula of the cosine law, and the self vehicle M and the target lane rear vehicle F at the initial time of lane changing of the curvedMinimum safety distance MSD (M, F)d) Comprises the following steps:
wherein R is the curvature radius of the outer lane, and H is the lane widthDegree of2(0) Rear vehicle F as initial target lanedThe arc length distance from the inner lane to the self-vehicle M ensures that the self-vehicle does not collide with the rear vehicle of the target lane in any form in the lane changing process,
phi is l2(0) The corresponding central angle;
(3) in order to achieve the aim that the self-vehicle M and the front vehicle L of the original lane are in the lane changing process0Without any kind of collision, the following equation needs to be satisfied:
Sr(t) represents the own vehicle M and the preceding vehicle L on the original lane0The longitudinal distance in the lane changing process is the self-vehicle M and the front vehicle L of the original lane at the initial time of the lane changing of the curve according to the geometric relation0Minimum safety distance MSD (M, L)0) Comprises the following steps:
wherein l1(0) For the initial moment, the self-vehicle M and the front vehicle L of the original lane0Along the distance of the outer lane, in order to ensure that the self-vehicle does not collide with the front vehicle of the original lane in any form in the lane changing process,
and 4, the traffic flow of the lane change target lane is respectively as follows:
(1) when the lane changing behavior does not exist, the traffic flow of the target lane is as follows:
in the formula, vHIs the average speed of the target lane, and T is the statistical time periodTotal time of t2Is the interval time distance between two adjacent vehicles,
(2) when lane changing behaviors exist, the whole statistical time interval is divided into a first lane changing half section, a second lane changing half section and a non-lane changing time interval, and the traffic flow of a target lane is as follows:
in the formula, the first part is the traffic flow in the first half of the lane changing period, the second part is the traffic flow in the second half of the lane changing period, and the third part is the traffic flow in the non-lane changing period, vLIs the current speed of the vehicle, a is the acceleration of the vehicle, t1、t2Respectively the duration of the first half section and the second half section of the lane change,
T1total time required to complete the lane change, T1＝tacc+tlatWherein the time required for the vehicle to accelerate to the target vehicle speed
tlatThe time required for changing lanes for the self vehicle.
The minimum fluctuation of the vehicle flow in the step 4 is as follows:
Jc＝β(δ-1)·(n-nc)
where β is a coefficient of influence of fluctuation in the traffic flow, a positive number smaller than 1, and in the present embodiment, 0.95 is selected, and this value is appropriately increased when it is desired to reduce the frequency of lane change, and δ is the number of times that the lane change is not performed but the intention of lane change is generated in step 2. When the lane change intention is generated for many times and the lane change behavior is not smoothly executed, the lane change motivation is stronger, and the influence effect of the fluctuation of the traffic flow is gradually reduced.
Fig. 12 shows a relationship between the minimum safe distance between the own vehicle and the adjacent vehicle and the lane change time under the straight lane change condition, and in this embodiment, the vehicle length L is 5 m. It can be concluded that, for the minimum safe distances between the vehicle and the vehicle ahead of the target lane and between the vehicle and the vehicle behind the target lane, when the acceleration difference is positive, the value increases with the increase of the lane change time, and the greater the longitudinal acceleration difference, the more significantly the minimum safe distance increases. And when the longitudinal acceleration difference is a negative value, the minimum safety distance is reduced along with the increase of the lane changing time, and the larger the longitudinal acceleration difference is, the more remarkable the reduction of the minimum safety distance is, and even a negative value appears in a certain area. The minimum safe distance between the self vehicle and the vehicle in front of the original lane is always a positive value, and increases along with the increase of lane changing time, the larger the longitudinal acceleration difference is, the more remarkable the minimum safe distance is increased, and to a certain extent, the larger the minimum safe distance is caused by the positive longitudinal speed difference.
Fig. 13 shows the relationship between the minimum safe distance difference between the own vehicle and the adjacent vehicle and the radius of the curve under the conditions of curve and straight lane change, in this embodiment, the lane width H is 3.75m, and the total lane change time is 3 s. It can be found that the minimum safe distance difference is more obvious when the radius of the curve is smaller, and the difference is smaller and smaller along with the gradual increase of the radius, which indicates that when the radius of the curve is smaller, the straight lane changing minimum safe distance model cannot be simply applied, otherwise, the situation that the straight lane can be successfully changed and the curve changing fails may occur.
Fig. 14 shows the relationship between the flow rate and the acceleration of the lane change vehicle with/without lane change, where T is 120s, τ is 1.5s, L is 5m, and v isH＝25m/s，vL19 m/s. As can be seen from the figure, the influence of the lane change behavior on the traffic flow rate gradually decreases as the lane change acceleration increases, and when the acceleration is too large, the influence of the increase in acceleration on the traffic flow rate is not significant, so that it is not preferable to use too large acceleration in order to ensure the riding comfort of the passengers.
FIG. 15 is a graph showing the relationship between the flow rate of vehicles with/without lane change and the difference between the current vehicle speed and the desired vehicle speed of the lane change vehicle, where vH＝28m/s,a＝3m/s2. Current vehicle speed and expectation with acceleration held constantThe larger the vehicle speed difference is, the longer the acceleration time required by the vehicle is, and the lane changing duration is prolonged. As can be seen from the figure, the larger the difference between the current vehicle speed and the desired vehicle speed, the greater the influence of lane change on the traffic flow of the target lane, and therefore such lane change behavior should be reduced.
Claims (5)
1. An intelligent driving vehicle active lane changing system considering intelligent vehicle group flow is characterized by comprising a camera, a radar, a wheel speed sensor, an IMU assembly, a communication module, a GNSS module, an ECU module, an HMI module and a motion execution module; the camera, the radar, the wheel speed sensor, the IMU assembly, the communication module, the GNSS module, the HMI module and the motion execution module are all arranged on the vehicle body and are connected with the ECU module through a CAN bus on the vehicle to realize data transmission among the camera, the radar, the wheel speed sensor, the IMU assembly, the communication module, the GNSS module, the HMI module and the motion execution module; the cameras at least comprise 5 monocular cameras which are respectively arranged at the front side, the rear side, the middle part of the left side and the right side of the bicycle body and the middle part of the roof of the bicycle; the radar at least comprises 4 laser radars and 6 short-distance millimeter wave radars which are respectively positioned at the left front corner, the left rear corner, the right front corner and the right rear corner of the vehicle; the millimeter wave radar is respectively positioned at the front part, the middle part and the rear part of the left side and the right side of the vehicle body; the IMU component is used for measuring the angular speed, the acceleration, the yaw angle and the altitude of the vehicle; the communication module is used for realizing mutual information transmission between the vehicle and the surrounding environment; the GNSS module is used for providing the current longitude and latitude and the altitude of the vehicle; the ECU module converts the obtained motion information into a control signal, and controls a driving execution module, a braking execution module and a steering execution module in the motion execution module to execute corresponding operations; the HMI module includes a user demand input module and a vehicle information feedback module.
2. The intelligent driven vehicle active lane changing system considering the intelligent vehicle group flow according to claim 1, wherein the intelligent vehicle group is a group of intelligent networked vehicles with the same or similar destinations; the communication module of the intelligent networked automobile realizes information interaction between automobiles and infrastructure by using an LTE-V2X technology, and the information interaction between the automobiles and the infrastructure uses the LTE-V-direct technology; the information interaction between the vehicle and the infrastructure uses an LTE-V-cell technology; the information comprises authentication information, uploading information and issuing information.
3. The intelligent driving vehicle active lane changing system considering the intelligent vehicle group flow according to claim 1, wherein the ECU module comprises a vehicle basic information module, a high-precision electronic map module, a navigation module, a memory and a motion decision module, and the vehicle basic information module, the high-precision electronic map module, the navigation module and the motion decision module are respectively connected with the memory; the self-vehicle basic information module and the high-precision electronic map module are respectively connected with the navigation module; the navigation module is connected with the motion decision module; the basic information module of the self-vehicle comprises a static information module and a dynamic information module; the high-precision electronic map module comprises a basic map module, a regional map module and a real-time dynamic map module; the navigation module comprises a global route drawing module and a local route drawing module; the motion decision module comprises a motion decomposition module and a feedback regulation module.
4. The intelligent driving vehicle active lane changing system considering the flow of the intelligent vehicle group according to claim 3 is characterized in that the local route drawing module comprises a behavior decision module and a track drawing module, the behavior decision module comprises a motion gain judgment module, a safety judgment module and an environmental influence judgment module, the safety and the reasonability of lane changing behaviors are judged according to the current road passing condition, a behavior decision of lane changing or lane keeping is made, and the track drawing module draws a motion track meeting the behavior requirements according to the decision made by the behavior decision module.
5. The intelligent driving vehicle active lane changing system considering the flow of the intelligent vehicle group as claimed in claim 3, wherein 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, transmits the speeds and accelerations to the motion execution module to complete corresponding motion operations, and 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.
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| CN113291324A (en) * | 2021-06-25 | 2021-08-24 | 的卢技术有限公司 | Intelligent automobile personalized lane change decision-making method, system and medium |
| CN113375689A (en) * | 2021-08-16 | 2021-09-10 | 腾讯科技（深圳）有限公司 | Navigation method, navigation device, terminal and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113291324A (en) * | 2021-06-25 | 2021-08-24 | 的卢技术有限公司 | Intelligent automobile personalized lane change decision-making method, system and medium |
| CN113291324B (en) * | 2021-06-25 | 2022-05-10 | 的卢技术有限公司 | Intelligent automobile personalized lane change decision-making method, system and medium |
| CN113375689A (en) * | 2021-08-16 | 2021-09-10 | 腾讯科技（深圳）有限公司 | Navigation method, navigation device, terminal and storage medium |
| CN113375689B (en) * | 2021-08-16 | 2021-11-05 | 腾讯科技（深圳）有限公司 | Navigation method, navigation device, terminal and storage medium |
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