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Adaptive Estimation-Based Safety-Critical Cruise Control of Vehicular Platoons

Vishrut Bohara, Siavash Farzan

TL;DR

This work tackles safe, stable adaptive cruise control in vehicle platoons under scenarios with and without vehicle-to-vehicle communication. It introduces an adaptive estimation framework paired with a safety-critical controller rooted in Lyapunov functions and Control Barrier Functions to handle estimation errors while preserving a minimum safe headway and string stability. The authors provide rigorous stability proofs, adaptive error dynamics to reduce conservativeness, and extensive validation in MATLAB and physics-based AirSim simulations, including ACC and CCC configurations. Results demonstrate robust string stability (gain around 0.57) and practical viability, achieving safe stopping distances and maintaining safety margins under noisy sensing and disturbances, thereby supporting real-world deployment in heterogeneous traffic.

Abstract

Optimal cruise control design can increase highway throughput and vehicle safety in traffic flow. In most heterogeneous platoons, the absence of vehicle-to-vehicle (V2V) communication poses challenges in maintaining system stability and ensuring a safe inter-vehicle distance. This paper presents an adaptive estimation-based control design for adaptive cruise control (ACC) that reliably estimates the states of the preceding vehicle while ensuring the autonomous vehicle operates within a safe region. Lyapunov functions and Control Barrier Functions (CBFs) are employed to design a safety-critical controller that guarantees safety despite potential estimation errors. The proposed unified control formulation addresses limitations in the existing cruise control solutions by simultaneously ensuring safety, stability, and optimal performance. The estimator-controller framework is implemented in scenarios with and without vehicle-to-vehicle communication, demonstrating successful performance in maintaining platoon safety and stability. Additionally, physics engine-based simulations reinforce both the practical viability of the proposed control framework in real-world situations and the controller's adeptness at maintaining safety amidst realistic operating conditions.

Adaptive Estimation-Based Safety-Critical Cruise Control of Vehicular Platoons

TL;DR

This work tackles safe, stable adaptive cruise control in vehicle platoons under scenarios with and without vehicle-to-vehicle communication. It introduces an adaptive estimation framework paired with a safety-critical controller rooted in Lyapunov functions and Control Barrier Functions to handle estimation errors while preserving a minimum safe headway and string stability. The authors provide rigorous stability proofs, adaptive error dynamics to reduce conservativeness, and extensive validation in MATLAB and physics-based AirSim simulations, including ACC and CCC configurations. Results demonstrate robust string stability (gain around 0.57) and practical viability, achieving safe stopping distances and maintaining safety margins under noisy sensing and disturbances, thereby supporting real-world deployment in heterogeneous traffic.

Abstract

Optimal cruise control design can increase highway throughput and vehicle safety in traffic flow. In most heterogeneous platoons, the absence of vehicle-to-vehicle (V2V) communication poses challenges in maintaining system stability and ensuring a safe inter-vehicle distance. This paper presents an adaptive estimation-based control design for adaptive cruise control (ACC) that reliably estimates the states of the preceding vehicle while ensuring the autonomous vehicle operates within a safe region. Lyapunov functions and Control Barrier Functions (CBFs) are employed to design a safety-critical controller that guarantees safety despite potential estimation errors. The proposed unified control formulation addresses limitations in the existing cruise control solutions by simultaneously ensuring safety, stability, and optimal performance. The estimator-controller framework is implemented in scenarios with and without vehicle-to-vehicle communication, demonstrating successful performance in maintaining platoon safety and stability. Additionally, physics engine-based simulations reinforce both the practical viability of the proposed control framework in real-world situations and the controller's adeptness at maintaining safety amidst realistic operating conditions.
Paper Structure (17 sections, 39 equations, 11 figures, 1 table)

This paper contains 17 sections, 39 equations, 11 figures, 1 table.

Table of Contents

  1. Introduction
  2. Problem Description
  3. Platoon Dynamics
  4. String Stability
  5. Estimator-based Safety Critical Controller
  6. Estimator Design
  7. Safety-Critical Controller Design
  8. Stability Analysis
  9. Adaptive Error Dynamics
  10. Results
  11. Acceleration -- Deceleration Scenarios
  12. String Stability Performance
  13. Connected Cruise Control
  14. Real-World Performance Evaluation
  15. Conclusions and Future Directions
  16. ...and 2 more sections

Figures (11)

  • Figure 1: Predecessor-successor configuration in Adaptive Cruise Control.
  • Figure 2: Block diagram of the proposed estimation-based control design illustrating various components in the framework. The components shown as dashed are only applicable in scenarios involving V2V communication.
  • Figure 3: Performance of the estimator and conservative behavior of the control law when leader vehicle accelerates.
  • Figure 4: Performance of the estimator and conservative behavior of the control law when leader vehicle decelerates.
  • Figure 5: Performance of the estimator and conservative behavior of the control law for constant leader vehicle jerk $u_j$.
  • ...and 6 more figures