Search

CN-122009173-A - Motor vehicle tracking method based on road interaction

CN122009173ACN 122009173 ACN122009173 ACN 122009173ACN-122009173-A

Abstract

The invention discloses a motor vehicle tracking method based on road interaction, which comprises the steps of establishing a vehicle motion model frame through interaction logic between a vehicle and other vehicles and lane lines in the transverse direction and the lane direction, establishing a lane direction acceleration model through the distance and speed relation between the vehicle and other vehicles in the same lane, establishing a target transverse lane change resistance model through the distance, speed and other relation between adjacent lanes and vehicles in front and back of the lane, establishing a transverse lane resistance model through the relative distance between the vehicle and the lane lines, establishing a measurement model through radar scattering point characteristics, and realizing target tracking through a filtering algorithm. The technical problems of insufficient robustness and accuracy of the existing motor vehicle target tracking algorithm are solved.

Inventors

  • Han Xuehan
  • BAI JIAN
  • HAN CHANG
  • ZHANG XIAOYANG
  • LIU XIAOLU

Assignees

  • 北京遥感设备研究所

Dates

Publication Date
20260512
Application Date
20251216

Claims (10)

  1. 1.A method of tracking a motor vehicle based on road interactions, the method comprising: Establishing a vehicle motion model frame through the interaction logic of the vehicle to be tested and other vehicles and the interaction logic of the vehicle to be tested and the lane lines; the vehicle motion model of the vehicle to be tested is obtained by filling the vehicle motion model frame with an acceleration model in the lane direction, a target course lane change resistance model and a transverse lane resistance model, wherein the acceleration model in the lane direction is determined by the distance and speed relation between the vehicle to be tested and other vehicles in the same lane, the target course lane change resistance model is determined by the distance and speed relation between the other vehicles in adjacent lanes, and the transverse lane resistance model is determined by the relative distance between the vehicle to be tested and a lane line; establishing a measurement model by radar scattering point characteristics, wherein the measurement model is used for reflecting the real-time radial distance, azimuth angle and radial speed of the vehicle to be measured; substituting the data in the measurement model into the vehicle motion model, and realizing tracking of the vehicle to be tested through a filtering algorithm.
  2. 2. The method for tracking motor vehicles based on road interaction according to claim 1, wherein the step of establishing a vehicle motion model frame through interaction logic of the vehicle to be tested and other vehicles and interaction logic of the vehicle to be tested and lane lines comprises the following steps: the vehicle motion model frame satisfies: Where v k is zero-mean Gaussian noise, For additional acceleration terms caused by inter-vehicle motion state coupling, and lane lines, Γ k is the process noise distribution matrix, For the motion state of the ith vehicle at time k, F k is a state transition matrix, The i-th vehicle k+1 moment motion state.
  3. 3. A method of tracking a motor vehicle based on road interaction as claimed in claim 2, wherein the process noise distribution matrix satisfies: Wherein T is a sampling interval, and the additional acceleration term satisfies: Wherein, the The extra acceleration in the x direction is determined by the front vehicle on the same lane; The extra acceleration in the y direction is determined by vehicles adjacent to the adjacent lane and the current lane; Is divided into two parts: Wherein, the The lane changing resistance generated for the vehicle attempting to change the lane is determined by the vehicles adjacent to the adjacent lane and the current lane under the condition that lane changing is not met; Additional lateral acceleration for this type of driving the vehicle toward the center balance point of each lane.
  4. 4. A method of tracking a motor vehicle based on road interaction as claimed in claim 3, wherein the acceleration model of the lane direction is determined by the distance and speed relationship of the vehicle under test to other vehicles on the same lane, comprising: extra acceleration in x direction Whether there are vehicles in the front distance l e is classified into two cases: when there is no vehicle in front, the vehicle is in a free running state in the x direction, When a vehicle is in front, the vehicle runs in the x direction and is mainly influenced by a front vehicle, and modeling is performed by adopting a vehicle following model, and variables are introduced Representing that the front vehicle of the ith vehicle at the moment k is the jth vehicle, and obtaining according to a following vehicle model: Wherein c, beta, gamma are undetermined parameters, and tau is reaction time.
  5. 5. A method of tracking a motor vehicle based on road interaction as defined in claim 4, wherein said target heading lane-change resistance model is determined by distance and speed relationships of other vehicles in adjacent lanes, comprising: Introducing g=1 indicates that the vehicle changes lane to the left and g= -1 indicates that the vehicle changes lane to the right, Represents the transverse velocity of the ith vehicle at time k when When the lane change resistance to the lane change attempting vehicle under the lane change condition is not satisfied The method meets the following conditions: Wherein, the For the excitation acceleration of the ith vehicle at the moment k, deltaa th is an excitation threshold, l 1 ,l 2 is the distance between the ith vehicle and a new rear vehicle and the distance between the ith vehicle and a front vehicle during lane change, l th1 ,l th2 is a safety distance threshold, f (·) is a resistance function, and the requirements on the transverse speed of the ith vehicle are met Opposite in direction and the numerical value is equal to L th1 -l 1 and l th2 -l 2 are positively correlated.
  6. 6. A method of tracking motor vehicles based on road interactions as claimed in claim 5, wherein the lane change of the vehicle to be tested is required to meet safety and excitation criteria: For a vehicle following the current lane of the ith vehicle at time k, The method is characterized in that the method comprises the following vehicle is a lane-changing rear target lane of an ith vehicle at the k moment, and when the vehicle meets the following conditions: l 1 ≥l th1 ,l 2 ≥l th2 and then the lane change is performed, wherein, For the acceleration of the ith vehicle in the x-axis direction before and after lane change, b safe is the safe acceleration, p is the polite coefficient, and the influence degree of other vehicles on lane change is determined.
  7. 7. A method of tracking a motor vehicle based on road interaction as claimed in claim 6, wherein the transverse lane resistance model is determined by the relative distance of the vehicle under test from the lane lines, comprising: Additional lateral acceleration driving a vehicle to a central point of balance of each lane The method comprises the following steps: Wherein j= - ≡l, -1, L, fact, The coordinate values of the ith vehicle in the y-axis direction at the k moment are respectively, Is a slope, satisfy Is the lane center offset, satisfies
  8. 8. A method of tracking motor vehicles based on road interactions as claimed in claim 7, wherein the ith vehicle has the following metrology model: Wherein, the The j-th measurement acquired for the k-time radar, The method is characterized in that the radial distance, the azimuth angle and the radial speed measured at the j-th moment of k are respectively measured, w k is zero-mean Gaussian measurement noise, covariance of the zero-mean Gaussian measurement noise is R k , and h (g) is a nonlinear observation function and is defined as follows: based on the motion model and the measurement model, the EKF algorithm is utilized for filtering.
  9. 9. A motor vehicle tracking system based on road interaction, characterized in that the system comprises a control device and a radar detection device, the control device controlling the radar detection device to perform the method according to claim 1.
  10. 10. An electronic device, characterized in that it is mounted on a radar detection device, said device comprising a processor and a memory electrically connected to said processor, said memory being adapted to store a computer program, said processor being adapted to invoke said computer program to perform the method according to claim 1.

Description

Motor vehicle tracking method based on road interaction Technical Field The invention relates to the technical field of maneuvering target tracking, in particular to a maneuvering vehicle tracking method based on road interaction. Background With the transition of modern war modes to informatization and intellectualization, higher requirements are put on the real-time performance, the accuracy and the robustness of motor vehicle target tracking. Since 1960 r.e. kalman proposed a kalman filter algorithm, kalman filter has been widely used in the field of target tracking as a highly efficient and reliable estimator. Conventional motion models, however, present challenges in handling motor vehicle targets in complex roadway environments. Because from a motion model point of view, the vehicle is not following a simple, single motion pattern when traveling on a road. The running of the vehicle is commonly influenced by road conditions (such as curves, slopes, intersections and the like), traffic rules (such as speed limit, signal lamps and traffic rules); in addition, there are complex interactions between vehicles, such as following behavior between traveling vehicles, lane changing interactions between vehicles in different lanes, etc. Therefore, chandler, songD, kestingA et al have studied the vehicle following and lane changing models and proposed a series of vehicle motion models such as GHR, but the existing models have significant drawbacks. Firstly, the influence of the existing lane changing model on the front and rear vehicles of the target lane is not comprehensive enough, lane changing resistance caused by the front and rear vehicles of the target lane cannot be fully quantized, so that lane changing decision and behavior of the vehicle are difficult to accurately predict, secondly, in the aspect of vehicle driving characteristic modeling, the traditional model ignores the behavior rule of a driver under the visual guidance of lane lines, namely the driver usually tends to drive in the middle of the lane and does not drive in a long-time line, the key characteristic directly influences the transverse movement track and lane changing process of the vehicle, but the existing research does not bring the transverse movement track and lane changing process into a lane changing model construction system, so that deviation exists between the model and the actual vehicle movement characteristic, and the adaptability and prediction accuracy of a target tracking algorithm on complex behavior of the vehicle are greatly weakened. In summary, the existing target tracking technology is difficult to meet the requirement of efficiently and accurately tracking the motor vehicle target in a complex road environment, and the innovation of the invention provides a powerful tool for solving the problem of motor vehicle tracking in a complex scene. When the following model and the lane changing model are considered at the same time, the novel motor vehicle target tracking algorithm based on road interaction is constructed by innovatively improving the target lane vehicle interaction resistance and the driver lane driving characteristic in the lane changing model. Disclosure of Invention The motor vehicle target tracking algorithm based on road interaction provided by the invention is an innovative improvement on the traditional following and lane changing model. On the basis of the synergy of the following model and the lane changing model, the lane changing model is improved based on the MOBIL model, lane changing resistance brought by vehicles in front of and behind a target lane is fully considered, a quantitative model is built, a lane changing decision process of the vehicle is accurately depicted, meanwhile, the behavior characteristics of a driver, which tend to run in the middle of the lane under the influence of lane lines, are innovatively integrated, and the prediction of the transverse movement track of the vehicle is optimized. Through multi-dimensional modeling and algorithm fusion, efficient and accurate tracking of motor vehicle targets in complex road environments is achieved. In order to achieve the above purpose, the technical scheme of the invention is as follows: a method of tracking a motor vehicle based on road interaction, comprising the steps of: Step one, a motion model of a vehicle target is established, namely, assuming that N k tracks are shared at the moment k, the direction x is a lane direction, the direction y is a transverse direction perpendicular to the lane, and the motion state of the ith vehicle at the moment k is defined as Satisfy the following requirementsWherein, the The coordinate values of the ith vehicle in the x, y axis direction at the k moment,The velocity of the ith vehicle in the x and y axis direction at the k moment is v k, the F k is a state transition matrix, and the Γ k is a process noise distribution matrix.The influence of all interaction relations between roads on