Platoon Of Autonomous Vehicles Research Articles

Attack Detection and Estimation in Cooperative Vehicles Platoons: A Sliding Mode Observer Approach

Platoons of autonomous vehicles are currently being investigated by academic and industrial researchers as a way to increase road capacity and fuel efficiency. In order to fully reach such goals, a platoon must be endowed with cooperative capabilities, such as Cooperative Adaptive Cruise Control (CACC). This technique is based on the vehicles’ sensors and on wireless communication between them, in order to control their longitudinal dynamics. However, the use of wireless communication exposes individual vehicles to cyber-attacks that aim at disrupting the platoon. Detecting and estimating a class of such attacks is the challenge considered in this paper, where an adaptive sliding mode observer is designed for this purpose. Theoretical results on the observer stability and robustness and simulation results are provided.

Robust Approximate Constraint‐Following Control for Autonomous Vehicle Platoon Systems

AbstractWe consider an autonomous vehicle platoon system consisting of N+1 vehicles in the presence of modeling uncertainty. The uncertainty may be due to parameter variations, aerodynamics, external disturbances, etc., which is nonlinear and time‐varying. Subject to the collision avoidance consideration, the original state is one‐sided restricted. To resolve this restriction, we propose a state transformation to convert the bounded state into a globally unbounded state. Furthermore, motivated by the properties of artificial swarm systems, we incorporate the swarm system performance into the platoon system by treating it as a d'Alembert's constraint. By the Udwadia and Kalaba's approach, we obtain the analytic (closed‐form) expression of the constraint force. Based on this, a class of robust controls for each vehicle (except the leading vehicle) is proposed to drive the platoon system to follow the ideal swarm model. Four major system performances are accomplished: (i) compact vehicle formation, (ii) collision avoidance, (iii) stable platoon system formation, (iv) global behavior.

Provably Safe Cruise Control of Vehicular Platoons

We synthesize performance-aware safe cruise control policies for longitudinal motion of platoons of autonomous vehicles. Using set-invariance theories, we guarantee infinite-time collision avoidance in the presence of bounded additive disturbances, while ensuring that the length and the cruise speed of the platoon are bounded within specified ranges. We propose (i) a centralized control policy, and (ii) a distributed control policy, where each vehicle's control decision depends solely on its relative kinematics with respect to the platoon leader. Numerical examples are included.

Traffic Control Models Based on Cellular Automata for At-Grade Intersections in Autonomous Vehicle Environment

Autonomous vehicle is able to facilitate road safety and traffic efficiency and has become a promising trend of future development. With a focus on highways, existing literatures studied the feasibility of autonomous vehicle in continuous traffic flows and the controllability of cooperative driving. However, rare efforts have been made to investigate the traffic control strategies in autonomous vehicle environment on urban roads, especially in urban intersections. In autonomous vehicle environment, it is possible to achieve cooperative driving with V2V and V2I wireless communication. Without signal control, conflicted traffic flows could pass intersections through mutual cooperative, which is a remarkable improvement to existing traffic control methods. This paper established a cellular automata model with greedy algorithm for the traffic control of intersections in autonomous vehicle environment, with autonomous vehicle platoon as the optimization object. NetLogo multiagent simulation platform model was employed to simulate the proposed model. The simulation results are compared with the traffic control programs in conventional Synchro optimization. The findings suggest that, on the premises of ensuring traffic safety, the control strategy of the proposed model significantly reduces average delays and number of stops as well as increasing traffic capacity.

Optimal Distributed Control for Platooning via Sparse Coprime Factorizations

We introduce a novel distributed control architecture for heterogeneous platoons of linear time-invariant autonomous vehicles. Our approach is based on a generalization of the concept of leader–follower controllers for which we provide a Youla-like parameterization, while the sparsity constraints are imposed on the controller’s left coprime factors, outlining a new concept of structural constraints in distributed control. The proposed scheme is amenable to optimal controller design via norm based costs, it guarantees string stability and eliminates the accordion effect from the behavior of the platoon. We also introduce a synchronization mechanism for the exact compensation of the time delays induced by the wireless communications.

Distributed receding horizon control for fuel-efficient and safe vehicle platooning

This paper investigates the problem of fuel-efficient and safe control of autonomous vehicle platoons. We present a two-part hierarchical control method that can guarantee platoon stability with minimal fuel consumption. The first part vehicle controller is derived in the context of receding horizon optimal control by constructing and solving an optimization problem of overall fuel consumption. The Second part platoon controller is a complementation of the first part, which is given on the basis of platoon stability analysis. The effectiveness of the presented platoon control method is demonstrated by both numerical simulations and experiments with laboratory-scale Arduino cars.

Constrained optimization and distributed computation based car following control of a connected and autonomous vehicle platoon

Motivated by the advancement in connected and autonomous vehicle technologies, this paper develops a novel car-following control scheme for a platoon of connected and autonomous vehicles on a straight highway. The platoon is modeled as an interconnected multi-agent dynamical system subject to physical and safety constraints, and it uses the global information structure such that each vehicle shares information with all the other vehicles. A constrained optimization based control scheme is proposed to ensure an entire platoon’s transient traffic smoothness and asymptotic dynamic performance. By exploiting the solution properties of the underlying optimization problem and using primal-dual formulation, this paper develops dual based distributed algorithms to compute optimal solutions with proven convergence. Furthermore, the asymptotic stability of the unconstrained linear closed-loop system is established. These stability analysis results provide a principle to select penalty weights in the underlying optimization problem to achieve the desired closed-loop performance for both the transient and the asymptotic dynamics. Extensive numerical simulations are conducted to validate the efficiency of the proposed algorithms.

Stability Margin Improvement of Vehicular Platoon Considering Undirected Topology and Asymmetric Control

The platooning of autonomous vehicles has the potential to significantly improve traffic capacity, enhance highway safety, and reduce fuel consumption. This paper studies the scalability limitations of large-scale vehicular platoons moving in rigid formation, and proposes two basic ways to improve stability margins, i.e., enlarging information topology and employing asymmetric control. A vehicular platoon is considered as a combination of four components: 1) node dynamics; 2) decentralized controller; 3) information flow topology; and 4) formation geometry. Tools, such as the algebraic graph theory and matrix factorization technique, are employed to model and analyze scalability limitations. The major findings include: 1) under linear identical decentralized controllers, the stability thresholds of control gains are explicitly established for platoons under undirected topologies. It is proved that the stability margins decay to zero as the platoon size increases unless there is a large number of following vehicles pinned to the leader and 2) the stability margins of vehicular platoons under bidirectional topologies using asymmetric controllers are always bounded away from zero and independent of the platoon size. Simulations with a platoon of passenger cars are used to demonstrate the findings.

Multiple-Model Switching Control of Vehicle Longitudinal Dynamics for Platoon-Level Automation

Platooning of autonomous vehicles has the potential to significantly benefit road traffic. This paper presents a new robust acceleration tracking control of vehicle longitudinal dynamics toward platoon-level automation. Based on a multiple-model switching structure, this design divides the large uncertainties of vehicle dynamics into small uncertainties and, accordingly, develops multiple robust controllers for the multiple-model set. The switching control system automatically selects the most appropriate candidate controller into the loop, according to the errors between current vehicle dynamics and multiple models. This technique offers more consistent and approximately linear node dynamics for upper level platoon control, even under relatively large vehicle uncertainties. Simulation comparison with a sliding model controller and a fixed H-infinity controller is conducted for a passenger car to demonstrate the enhanced robustness of the switching control method. The experimental test for the same car is performed for further validation.

Different Control Algorithms for a Platoon of Autonomous Vehicles

This paper presents a concept of platoon movement of autonomous vehicles (smart cars). These vehicles have Adaptive or Advanced cruise control (ACC) system also called Intelligent cruise control (ICC) or Adaptive Intelligent cruise control (AICC) system. The vehicles are suitable to follow other vehicles on desired distance and to be organized in platoons. To perform a research on the control and stability of an AGV (Automated Guided Vehicles) string, we have developed a car-following model. To do this, first a single vehicle is modeled and since all cars in the platoon have the same dynamics, the single vehicle model is copied ten times to form model of platoon (string) with ten vehicles. To control this string, we have applied equal PID controllers to all vehicles, except the leading vehicle. These controllers try to keep the headway distance as constant as possible and the velocity error between subsequent vehicles - small. For control of vehicle with nonlinear dynamics combi­nation of feedforward control and feedback control approach is used. Feedforward control is based on the inverse model of nominal dynamics of the vehicle, and feedback PID control is designed based on the linearized model of the vehicle. For simulation and analysis of vehicle and platoon of vehicles – we have developed Matlab/Simulink models. Simulation results, discussions and conclusions are given at the end of the paper.

Nonlinear dynamics of autonomous vehicles with limits on acceleration

The stability of autonomous vehicle platoons with limits on acceleration and deceleration is determined. If the leading-vehicle acceleration remains within the limits, all vehicles in the platoon remain within the limits when the relative-velocity feedback coefficient is equal to the headway time constant [k=1/h]. Furthermore, if the sensitivity α>1/h, no collisions occur. String stability for small perturbations is assumed and the initial condition is taken as the equilibrium state. Other values of k and α that give stability with no collisions are found from simulations. For vehicles with non-negligible mechanical response, simulations indicate that the acceleration-feedback-control gain might have to be dynamically adjusted to obtain optimal performance as the response time changes with engine speed. Stability is demonstrated for some perturbations that cause initial acceleration or deceleration greater than the limits, yet do not cause collisions.

Resilience in Large Scale Distributed Systems

Distributed systems are comprised of multiple subsystems that interact in two distinct ways: (1) physical interactions and (2) cyber interactions; i.e. sensors, actuators and computers controlling these subsystems, and the network over which they communicate. A broad class of cyber-physical systems (CPS) are described by such interactions, such as the smart grid, platoons of autonomous vehicles and the sensorimotor system. This paper will survey recent progress in developing a coherent mathematical framework that describes the rich CPS “design space” of fundamental limits and tradeoffs between efficiency, robustness, adaptation, verification and scalability. Whereas most research treats at most one of these issues, we attempt a holistic approach in examining these metrics. In particular, we will argue that a control architecture that emphasizes scalability leads to improvements in robustness, adaptation, and verification, all the while having only minor effects on efficiency – i.e. through the choice of a new architecture, we believe that we are able to bring a system closer to the true fundamental hard limits of this complex design space.

Multilevel Reconfiguration Strategy for the System of Systems Engineering: Application to Platoon of Vehicles

In the present work, a generic method for multilevel modeling and reconfiguration of the System of Systems Engineering (SoSE) is proposed based on the bond graph modeling approach. The proposed formulation is applied to the road traffic dynamic for a platoon of Intelligent Autonomous Vehicles (IAVs). A bond graph model-based reconfiguration strategy is proposed for the multilevel model of the road traffic dynamic combining three levels namely submicroscopic, microscopic and macroscopic. This multilevel model is simulated for two scenarios of normal and faulty situations in a platoon of four IAVs.

Cooperative Intersection Negotiation for Multiple Autonomous Platoons

This paper presents a strategy for autonomously resolving intersection contention between platoons of autonomous vehicles. Each member of a platoon is represented by a dynamic model and a path tracking controller as well as a vehicle gap controller. These models and controllers are incorporated in simulation environments. Multiple vehicles in convoys simultaneously arriving at an intersection are simulated to ensure an optimized intersection negotiation taking into account a raft of widely varying requirements that exist in a public transport environments. A set of concepts such as initiative, infrastructure adaptation, and priority propagation are introduced and used to promote globally and locally optimal crossing patterns, avoiding vehicle stoppage in most circumstances. Results from a multiple convoy dynamic model simulation validate the strategy presented.

Optimality and oscillations near the edge of stability in the dynamics of autonomous vehicle platoons

A model that includes the mechanical response of a vehicle to a demanded change in acceleration is analyzed to determine the string stability of a platoon of autonomous vehicles. The response is characterized by a first-order time constant τ and an explicit delay td. The minimum value of the acceleration feedback control gain is found from calculations of the velocity of vehicles following a lead vehicle that decelerates sharply from high speed to low speed. Larger values of ξ (in the stable range) give larger values of deceleration for vehicles in the platoon. Optimal operation is attained close to the minimum value of ξ for stability. Small oscillations are found after the main peak in deceleration for ξ in the stable region but near the transition to instability. A theory for predicting the frequency and amplitude of the oscillations is presented.

Distributed Predictive Control for a Class of Hybrid Systems with Event-Based Communication

This paper proposes a strategy for distributed model predictive control (DMPC) with event-based communication for piecewise affine (PWA) systems coupled via a common cost function and, possibly non-convex, constraints. In order to achieve cooperation between subsystems, each subsystem optimizes over its own inputs and the inputs of directly interconnected systems. In the proposed scheme, all subsystems optimize in parallel in each time step, and the subsystems only communicate information to interconnected subsystems if a triggering condition is met. Under some assumptions on a terminal control law, recursive feasibility and stability of the scheme are established. Simulation results for a platoon of autonomous vehicles are used to illustrate the approach.

Optimisation of high-speed crash avoidance in autonomous vehicles

In the context of a future scenario of autonomous vehicle platooning, this paper considers the optimisation of a vehicle’s standard brake, acceleration and steering control inputs, for collision avoidance. We consider the case where escape into the neighbouring lane is feasible. An iterative simulation-based method is used, which allows vehicle parameters to be optimised simultaneously; this also allows us to find the best vehicle handling balance for such a manoeuvre and to quantify the cost of suboptimal design. The paper also considers the relative advantages of speed reduction in conjunction with rapid lane change. The goal here is to quantify the best possible vehicle escape manoeuvre and the relative cost of alternative strategies. The paper does not provide an immediately practicable controller, but simple open-loop approximation of the optimal controls suggests a route towards future real-time solution.

Robust Distributed Predictive Control of Communicating and Constrained Systems

AbstractThis paper proposes a strategy for distributed model predictive control for linear time invariant systems coupled via a common cost function and constraints. Each subsystem solves a local robust model predictive control (RMPC) problem which considers uncertain predictions received from other subsystems. In the chosen communication scheme, subsystems exchange information about optimized local trajectories and time-varying disturbances sets obtained from the local RMPC. The latter optimizes over feedback policies based on a cost function motivated by min-max approaches and can be implemented as a single tractable quadratic program. Under some assumptions, the proposed scheme remains feasible even in the presence of delays and packet loss. Simulation results for a platoon of autonomous vehicles in a leader-follower scenario illustrate the approach.

Kinematic Control of Platoons of Autonomous Vehicles

In this paper, an approach to control the motion of a platoon of autonomous vehicles is presented. The proposed technique is based on the definition of suitable task functions that are handled in the framework of singularity-robust task-priority inverse kinematics. The algorithm is implemented by a two-stage control architecture such that intervehicle communication is not required. The effectiveness of the approach is investigated by means of numerical simulation case studies

Redundant Manipulator Techniques for Partially Decentralized Path Planning and Control of a Platoon of Autonomous Vehicles

An approach to real-time trajectory generation for platoons of autonomous vehicles is developed from well-known control techniques for redundant robotic manipulators. The partially decentralized structure of this approach permits each vehicle to independently compute its trajectory in real-time using only locally generated information and low-bandwidth feedback generated by a system exogenous to the platoon. Our work is motivated by applications for which communications bandwidth is severely limited, such for platoons of autonomous underwater vehicles. The communication requirements for our trajectory generation approach are independent of the number of vehicles in the platoon, enabling platoons composed of a large number of vehicles to be coordinated despite limited communication bandwidth.