A city expressway vehicle fleet asymptotic stability control method and system based on distance-information adaptive criterion

Abstract

This invention discloses an asymptotic stability control method for urban expressway convoys based on a distance-information adaptive criterion. Belonging to the field of intelligent convoy control technology, the method includes: collecting the relative distance and speed between the vehicle and the preceding vehicle, as well as the motion state information of multiple preceding vehicles; monitoring the communication link in real time and calculating the signal quality factor of each preceding vehicle; constructing a dual adaptive coupled car-following model, which adjusts the vehicle's acceleration through both distance sensitivity coefficients and information sensitivity coefficients; deriving the asymptotic stability criterion for the convoy in equilibrium state based on the dual adaptive coupled car-following model and calculating stability indices in real time; and executing a hierarchical closed-loop control strategy based on the stability indices. This invention can simultaneously utilize distance-based sensitivity adjustment to ensure short-range safety and dynamically adjust the coordination weights according to signal quality, ensuring the asymptotic stability of the convoy in high-speed flow and complex communication environments.

Description

Technical Field

[0001] This invention relates to the field of intelligent vehicle fleet control technology, and more specifically to a method and system for asymptotic stability control of urban expressway vehicle fleets based on distance-information adaptive criteria. Background Technology

[0002] Currently, with the acceleration of urbanization, urban expressways and intercity highways have become the main arteries connecting major urban areas. Unlike ordinary urban roads, expressways are characterized by high speeds, large traffic volumes, and frequent merging and merging at entrances and exits. In these scenarios, traffic flow faces a dual challenge: First, the limitation of physical safety distance perception. Traditional car-following models usually assume that the sensitivity coefficient of the driver or controller is constant, ignoring the "risk field" effect where physical risk increases sharply when vehicles approach the minimum safe distance. During emergency braking or congested queuing, fixed-gain controllers often do not react sensitively enough, easily leading to rear-end collisions. Second, the uncertainty of information transmission. Although cooperative adaptive cruise control introduces vehicle-to-vehicle communication, existing models mostly assume perfect communication. In reality, in the complex electromagnetic environment of cities, the greater the distance, the higher the packet loss rate and the lower the signal-to-noise ratio. If the system blindly trusts low-quality remote data, it may introduce noise and cause convoy instability.

[0003] Therefore, how to provide a method and system for asymptotic stability control of urban expressway platoons based on distance-information adaptive criteria, which can simultaneously utilize distance-based sensitivity adjustment to ensure short-range safety and dynamically adjust the cooperative weights according to signal quality to ensure the asymptotic stability of the platoon in high-speed flow and complex communication environments, is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention provides a method and system for asymptotic stability control of urban expressway convoys based on distance-information adaptive criteria.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for asymptotic stability control of urban expressway convoys based on distance-information adaptive criterion includes the following steps: S1. Collect the relative distance and relative speed between this vehicle and the vehicle in front, as well as the motion status information of multiple vehicles in front, and monitor the communication link in real time to calculate the signal quality factor of each vehicle in front. S2. Construct a dual adaptive coupled car-following model, wherein the dual adaptive coupled car-following model adjusts the vehicle's acceleration through a distance sensitivity coefficient and an information sensitivity coefficient. S3. Based on the aforementioned dual adaptive coupled car-following model, derive the asymptotic stability criterion of the fleet under equilibrium state, and calculate the stability index in real time. S4. Execute a hierarchical closed-loop control strategy based on the stability index.

[0006] Furthermore, the signal quality factor is dynamically calculated from the real-time packet loss rate, signal-to-noise ratio, or delay time of the communication link, and is used to characterize the reliability of the forward vehicle's motion state information.

[0007] Furthermore, S2 constructs a dual adaptive coupled car-following model, which adjusts the vehicle's acceleration using both distance sensitivity coefficients and information sensitivity coefficients, expressed as:

[0008] in, for The instantaneous acceleration of the nth vehicle at time n; for The actual speed of the nth vehicle at time n; The baseline sensitivity coefficient; Minimum safe distance; for The headway between the nth car and the (n+1th car) at time n; for The moment ahead The car and the first one in front The relative speed between vehicles; The distance sensitivity coefficient is denoted as . ; Signal quality factor; For pre-targeting weights; This is the optimal velocity function.

[0009] Furthermore, the expression for the asymptotic stability criterion is:

[0010] in, The current equilibrium front-end spacing; This is the derivative of the optimal velocity function at the equilibrium spacing; This is the comprehensive information sensitivity coefficient.

[0011] Furthermore, implementing a hierarchical closed-loop control strategy based on the stability index includes: Level 1 adjustment: If multi-vehicle communication is available, increase the number of cooperating vehicles or increase the aiming weight to increase the comprehensive information sensitivity coefficient of the asymptotic stability criterion; Secondary intervention: If primary adjustment is ineffective or communication is unavailable, the criterion is re-established by increasing the reference sensitivity coefficient or increasing the distance between the vehicles. Level 3 warning: If the above adjustments are ineffective or the parameters reach physical limits, a driver takeover warning will be triggered, and a deceleration signal will be sent to vehicles behind.

[0012] Furthermore, in the first-level adjustment, the method to increase the number of cooperative vehicles is to obtain motion status information of vehicles further away through vehicle-to-vehicle communication requests, thereby expanding the communication sensing range.

[0013] Furthermore, in the secondary intervention, the way to increase the baseline sensitivity coefficient is to switch the vehicle control mode to sport mode or control logic with higher response sensitivity.

[0014] Furthermore, in the secondary intervention, the method of increasing the distance between the vehicles is: to maintain a greater safe distance between the vehicle and the vehicle in front through active braking control.

[0015] Furthermore, the three-level warning includes: triggering a tactile or auditory alarm signal to prompt the driver to take over, and sending an emergency deceleration warning message to the following vehicle via a communication terminal.

[0016] An asymptotic stability control system for urban expressway convoys based on a distance-information adaptive criterion includes: Data acquisition module: Collects the relative distance and relative speed between this vehicle and the vehicle in front, as well as the motion status information of multiple vehicles in front, and monitors the communication link in real time to calculate the signal quality factor of each vehicle in front; Model building module: Constructs a dual adaptive coupled car-following model, which adjusts the vehicle's acceleration through both distance sensitivity coefficient and information sensitivity coefficient; Stability criterion module: Based on the aforementioned dual adaptive coupled car-following model, the asymptotic stability criterion of the fleet under equilibrium state is derived, and the stability index is calculated in real time; Hierarchical control module: Executes a hierarchical closed-loop control strategy based on the stability index.

[0017] As can be seen from the above technical solution, compared with the prior art, the present invention provides a method and system for asymptotic stability control of urban expressway convoys based on distance-information adaptive criteria. It can simultaneously utilize distance-based sensitivity adjustment to ensure short-range safety and dynamically adjust the cooperative weights according to signal quality to ensure the asymptotic stability of the convoy in high-speed flow and complex communication environments. The specific beneficial effects are as follows: 1. Mechanistic security: Introducing a distance sensitivity coefficient This gives the model a naturally "infinite" response gain when approaching the minimum safe distance. Mathematically, this guarantees that vehicles will never rear-end each other under extreme congestion or emergency braking conditions, solving the problem of traditional linear models being insensitive at close range.

[0018] 2. Robustness to environmental adaptation: By introducing a quality factor It can automatically adjust its coordination strategy based on communication quality in scenarios such as urban canyons and tunnels. When the communication signal between multiple vehicles is poor, it actively adjusts parameters, degenerating into a highly sensitive single-vehicle following mode; when the signal is good, it automatically utilizes information from multiple vehicles to improve efficiency.

[0019] 3. Smooth control switching: Based on the derived stability criterion, a hierarchical control logic of "stability-adjustment-intervention-early warning" is constructed to avoid abrupt changes in control strategy and improve ride comfort. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0021] Figure 1 This invention provides a schematic flowchart of an asymptotic stability control method for urban expressway vehicle fleets based on a distance-information adaptive criterion. Figure 2 A schematic diagram of the decision-making and hierarchical control process provided by the present invention; Figure 3 This is a schematic diagram of the system flow provided by the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1: See Figure 1 Embodiment 1 of the present invention discloses an asymptotic stability control method for urban expressway convoys based on a distance-information adaptive criterion, comprising the following steps: S1. Collect the relative distance and relative speed between this vehicle and the vehicle in front, as well as the motion status information of multiple vehicles in front, and monitor the communication link in real time to calculate the signal quality factor of each vehicle in front. S2. Construct a dual adaptive coupled car-following model, wherein the dual adaptive coupled car-following model adjusts the vehicle's acceleration through a distance sensitivity coefficient and an information sensitivity coefficient. S3. Based on the aforementioned dual adaptive coupled car-following model, derive the asymptotic stability criterion of the fleet under equilibrium state, and calculate the stability index in real time. S4. Execute a hierarchical closed-loop control strategy based on the stability index.

[0024] Specifically, in urban expressway and intercity highway scenarios, this module uses multi-source sensors for data fusion: Distance adjustment mechanism: The relative distance to the vehicle in front is collected at high frequency using onboard millimeter-wave radar and lidar. Relative velocity is used to construct distance sensitivity.

[0025] Signal conditioning mechanism: Obtain the signal from the vehicle ahead via the onboard communication terminal. to The module monitors the movement status of multiple vehicles. Simultaneously, it monitors the communication link quality in real time and calculates the signal quality factor for each preceding vehicle. (Characterizing the quality of the signal), used to characterize the reliability of the data source.

[0026] Specifically, this invention innovatively proposes a dynamic model coupling distance regulation and signal regulation. Based on the traditional car-following model, this model introduces distance-based sensitivity regulation (physical layer) and signal quality-based sensitivity regulation (information layer). The model formula is as follows: (1) in, for The instantaneous acceleration of the nth vehicle at time n; for The actual speed of the nth vehicle at time n; The baseline sensitivity coefficient; Minimum safe distance; for The headway between the nth car and the (n+1th car) at time n; for The moment ahead The car and the first one in front The relative speed between vehicles; The distance sensitivity coefficient is denoted as . ; Signal quality factor; For pre-targeting weights; This is the optimal velocity function.

[0027] Assume the convoy is in a uniform flow equilibrium state, with an equilibrium spacing of... The equilibrium speed is At this time, we have: (2) (3) Apply small perturbation , making the position .

[0028] At the equilibrium point For nonlinear terms Perform a Taylor expansion. Due to equilibrium... Its partial derivatives simplify to:

[0029] Define the effective sensitivity coefficient. : (4) make The linearized perturbation equation is then: (5) Performing a Laplace transform on equation (5), let... for The transformation formula, using : (6) Define the transfer function ,but Substituting into equation (6), canceling out... And by rearranging, we obtain the characteristic equation: (7) Vehicle instability typically occurs during long-wave disturbances (low-frequency) phases, causing... Perform a second-order Taylor expansion on the transfer function: (8) Approximation using binomial expansion Substitute it into equation (7) to perform coefficient matching.

[0030] Compare First-order coefficients: Examine the summation term on the right side of the equation .

[0031] because (A first-order minor quantity), this term is related to the external... After multiplication, it becomes The term (a second-order minor). Therefore, in In the first-order coefficient matching, the summation term contributes 0.

[0032] The equation becomes: (9) Solving for: (10) Compare Second-order term coefficients: Left side The coefficient is 1.

[0033] The contribution of the summation term on the right is .

[0034] make Then the equation is: (11) Will Substitute into equation (8) and solve. : (12) (13) (14) Derivation of stability criterion: Based on the long-wave asymptotic stability condition Substitute : (15) Simplify the inequality (assuming) , eliminating the denominator): (16) Will and Substituting back into equation (16), and based on the frequency domain transfer function analysis method, the asymptotic stability critical criterion of the above model is derived. The values ​​on both sides of the inequality are calculated in real time to generate stability indices. The core criterion is: (17) in, The current equilibrium front-end spacing; The derivative of the optimal speed function at the equilibrium spacing represents the sensitivity of traffic flow to changes in spacing. Generally, the larger the vehicle spacing, the smoother the traffic flow. The smaller; The comprehensive information sensitivity coefficient represents the total contribution of multi-vehicle cooperation after considering communication quality. The physical meaning of this criterion is that the "distance coefficient" (left side) must be greater than twice the "residual disturbance strength" (right side), where the residual disturbance strength is the initial disturbance minus the disturbance mitigated by the multi-vehicle communication information system. When communication quality is good ( When the value is large, the value on the right decreases, and stability is easily satisfied; when congestion reduces the spacing... When the distance is reduced, the value of the distance coefficient on the left increases, automatically providing stability support.

[0035] Specifically, when congestion leads to near When the distance coefficient increases, the stability is enhanced; when the communication quality is good, the information coefficient increases. As the threshold increases, the term on the right (perturbation threshold) decreases, and stability is also enhanced. That is, when this inequality is not satisfied, priority is given to increasing the number of cooperating vehicles through multi-vehicle communication. Or target weight (Level 1 adjustment); if ineffective, actively increase the baseline sensitivity coefficient. (Secondary intervention).

[0036] For details, see Figure 2 According to stability index Based on the criterion status, the following hierarchical closed-loop control is executed: (1) Steady state (satisfying stability indicators): a) Strategy: Maintain efficient following mode.

[0037] b) Operation: Utilize a smooth control algorithm to output throttle / brake commands, optimizing fuel economy while ensuring safety.

[0038] (2) Critical / unstable state (does not meet stability index): Entering a multi-level intervention process: 1) Level 1 adjustment: a) Triggering condition: Multi-vehicle communication is available.

[0039] b) Operation: Obtain vehicle information from a more distant location via multi-vehicle communication requests (addition) ), or increase the weight of attention given to vehicles in the distance (increase) By utilizing the "electronic pre-aiming" effect, the subtrahend term on the right side of the inequality is increased, thus restoring stability.

[0040] 2) Secondary intervention: a) Triggering condition: Multi-vehicle communication is unavailable, but the sensitivity coefficient is adjustable.

[0041] b) Operation: Actively increase the baseline coefficient (Switch to Sport mode) to directly increase the "distance coefficient" on the left side of the inequality; or slightly increase the current distance by braking. To reduce the derivative of the optimal velocity (That is, reducing the "residual disturbance intensity" on the right side of the inequality), since within this velocity range The attenuation effect with increasing spacing plays a dominant role, making the stability criterion easier to establish.

[0042] 3) Level 3 Early Warning: a) Triggering conditions: All of the above methods are ineffective or the physical limit is reached.

[0043] b) Operation: Trigger a tactile / auditory alarm to prompt the driver to take immediate control and send a deceleration warning to vehicles behind to prevent chain-reaction rear-end collisions.

[0044] Specifically, the system first calculates the values ​​on both sides of the stability criterion inequality in real time. If the criterion holds, the fleet is determined to be in a stable state and the current efficient following mode is maintained. If the criterion does not hold, the fleet is determined to be in a critical or unstable state and a tiered intervention process is immediately initiated. First, the availability of multi-vehicle communication is checked. If available, a first-level adjustment strategy is executed, using communication requests to obtain motion status information of more distant vehicles to increase the number of cooperating vehicles. Or increase the targeting weight for distant vehicles. This increases the comprehensive information sensitivity coefficient on the right side of the criterion inequality to restore fleet stability; if multi-vehicle communication is unavailable or the first-level adjustment is ineffective, a second-level intervention strategy is implemented to proactively increase the baseline sensitivity coefficient. This can be achieved by directly increasing the distance sensitivity coefficient on the left side of the criterion inequality, or by increasing the current headway through braking control. To reduce the derivative of the optimal velocity function This reduces the remaining disturbance intensity, allowing the criterion to be re-established. If the criterion is still not satisfied after the above adjustments or the parameter adjustment reaches the physical limit, a three-level warning strategy is implemented. This immediately triggers a tactile or auditory alarm to prompt the driver to take over the vehicle, and simultaneously sends an emergency deceleration warning signal to the vehicles behind via the communication terminal to prevent chain-reaction rear-end collisions.

[0045] On the other hand, see Figure 3 An asymptotic stability control system for urban expressway convoys based on distance-information adaptive criterion, comprising: Data acquisition module: Collects the relative distance and relative speed between this vehicle and the vehicle in front, as well as the motion status information of multiple vehicles in front, and monitors the communication link in real time to calculate the signal quality factor of each vehicle in front; Model building module: Constructs a dual adaptive coupled car-following model, which adjusts the vehicle's acceleration through both distance sensitivity coefficient and information sensitivity coefficient; Stability criterion module: Based on the aforementioned dual adaptive coupled car-following model, the asymptotic stability criterion of the fleet under equilibrium state is derived, and the stability index is calculated in real time; Hierarchical control module: Executes a hierarchical closed-loop control strategy based on the stability index.

[0046] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0047] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for asymptotic stability control of urban expressway convoys based on distance-information adaptive criterion, characterized in that, Includes the following steps: S1. Collect the relative distance and relative speed between this vehicle and the vehicle in front, as well as the motion status information of multiple vehicles in front, and monitor the communication link in real time to calculate the signal quality factor of each vehicle in front. S2. Construct a dual adaptive coupled car-following model, wherein the dual adaptive coupled car-following model adjusts the vehicle's acceleration through a distance sensitivity coefficient and an information sensitivity coefficient. S3. Based on the aforementioned dual adaptive coupled car-following model, derive the asymptotic stability criterion of the fleet under equilibrium state, and calculate the stability index in real time. S4. Execute a hierarchical closed-loop control strategy based on the stability index.

2. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 1, characterized in that, The signal quality factor is dynamically calculated from the real-time packet loss rate, signal-to-noise ratio, or delay time of the communication link, and is used to characterize the reliability of the forward vehicle's motion status information.

3. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 1, characterized in that, A dual adaptive coupled car-following model is constructed, in which the vehicle's acceleration is jointly adjusted by distance sensitivity coefficient and information sensitivity coefficient, and the expression is: in, for The instantaneous acceleration of the nth vehicle at time n; for The actual speed of the nth vehicle at time n; The baseline sensitivity coefficient; Minimum safe distance; for The headway between the nth car and the (n+1th car) at time n; for The moment ahead The car and the first one in front The relative speed between vehicles; The distance sensitivity coefficient is denoted as . ; Signal quality factor; For pre-targeting weights; This is the optimal velocity function.

4. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 3, characterized in that, The expression for the asymptotic stability criterion is: in, The current equilibrium front-end spacing; This is the derivative of the optimal velocity function at the equilibrium spacing; This is the comprehensive information sensitivity coefficient.

5. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 1, characterized in that, Executing a hierarchical closed-loop control strategy based on the stability index includes: Level 1 adjustment: If multi-vehicle communication is available, increase the number of cooperating vehicles or increase the aiming weight to increase the comprehensive information sensitivity coefficient of the asymptotic stability criterion; Secondary intervention: If primary adjustment is ineffective or communication is unavailable, the criterion is re-established by increasing the reference sensitivity coefficient or increasing the distance between the vehicles. Level 3 warning: If the above adjustments are ineffective or the parameters reach physical limits, a driver takeover warning will be triggered, and a deceleration signal will be sent to vehicles behind.

6. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 5, characterized in that, In the first-level adjustment, the number of cooperative vehicles is increased by obtaining motion status information of vehicles further away through vehicle-to-vehicle communication requests, thereby expanding the communication sensing range.

7. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 5, characterized in that, In the secondary intervention, the way to increase the baseline sensitivity coefficient is to switch the vehicle control mode to sport mode or control logic with higher response sensitivity.

8. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 5, characterized in that, In the secondary intervention, the way to increase the distance between the vehicles is by using active braking control to maintain a greater safe distance between the vehicle and the vehicle in front.

9. The asymptotic stability control method for urban expressway convoys based on distance-information adaptive criterion according to claim 5, characterized in that, The three-level warning system includes: triggering tactile or auditory alarm signals to prompt the driver to take over, and sending emergency deceleration warning information to following vehicles via a communication terminal.

10. An asymptotic stability control system for urban expressway convoys based on distance-information adaptive criterion, characterized in that, include: Data acquisition module: Collects the relative distance and relative speed between this vehicle and the vehicle in front, as well as the motion status information of multiple vehicles in front, and monitors the communication link in real time to calculate the signal quality factor of each vehicle in front; Model building module: Constructs a dual adaptive coupled car-following model, which adjusts the vehicle's acceleration through both distance sensitivity coefficient and information sensitivity coefficient; Stability criterion module: Based on the aforementioned dual adaptive coupled car-following model, the asymptotic stability criterion of the fleet under equilibrium state is derived, and the stability index is calculated in real time; Hierarchical control module: Executes a hierarchical closed-loop control strategy based on the stability index.

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