Yuxiao Chen

Enhanced eco-driving system based on V2X communication

The concept of Eco-driving is proposed to reduce the fuel consumption of vehicles while maintaining dynamic performance. MPC controller has been introduced to achieve comprehensive goals including safety, fuel consumption and comfort of driving. Yet the information of the surrounded vehicles and road conditions have not been fully utilized. An enhanced algorithm taking the driving style of preceding vehicle, host vehicle drivers and road information into account is proposed in this paper. It is tested by the results of simulation that the controller becomes more flexible and can reduce the fuel consumption of the controlled vehicle in different working conditions with the help of the enhanced algorithm.

Preliminary results on correct-by-construction control software synthesis for adaptive cruise control

A plethora of driver convenience and safety automation systems are being introduced into production vehicles, such as electronic stability control, adaptive cruise control, lane keeping, and obstacle avoidance. Assuring the seamless and safe integration of each new automation function with existing control functions is a major challenge for vehicle manufacturers. This challenge is compounded by having different suppliers providing software modules for different control functionalities. In this paper, we report on our preliminary steps to address this problem through a fresh perspective combining formal methods, control theory, and correct-by-construction software synthesis. In particular, we begin the process of synthesizing the control software module for adaptive cruise control from formal specifications given in Linear Temporal Logic. In the longer run, we will endow each interacting software module with an assume-guarantee specification stating under which environment assumptions the module is guaranteed to meet its specifications. These assume-guarantee specifications will then be used to formally prove correctness of the cyber-physical system obtained when the integrated modules interact with the physical dynamics.

Correct-by-Construction Adaptive Cruise Control: Two Approaches

Motivated by the challenge of developing control software provably meeting specifications for real-world problems, this paper applies formal methods to adaptive cruise control (ACC). Starting from a linear temporal logic specification for ACC, obtained by interpreting relevant ACC standards, we discuss in this paper two different control software synthesis methods. Each method produces a controller that is correct-by-construction, meaning that trajectories of the closed-loop systems provably meet the specification. Both methods rely on fixed-point computations of certain set-valued mappings. However, one of the methods performs these computations on the continuous state space whereas the other method operates on a finite-state abstraction. While controller synthesis is based on a low-dimensional model, each controller is tested on CarSim, an industry-standard vehicle simulator. Our results demonstrate several advantages over classical control design techniques. First, a formal approach to control design removes potential ambiguity in textual specifications by translating them into precise mathematical requirements. Second, because the resulting closed-loop system is known a priori to satisfy the specification, testing can then focus on the validity of the models used in control design and whether the specification captures the intended requirements. Finally, the set from where the specification (e.g., safety) can be enforced is explicitly computed and thus conditions for passing control to an emergency controller are clearly defined.

Obstacle Avoidance for Low-Speed Autonomous Vehicles With Barrier Function

This paper presents an obstacle avoidance algorithm for low speed autonomous vehicles (AV), with guaranteed safety. A supervisory control algorithm is constructed based on a barrier function method, which works in a plug-and-play fashion with any lower level navigation algorithm. When the risk of collision is low, the barrier function is not active; when the risk is high, based on the distance to an “avoidable set,” the barrier function controller will intervene, using a mixed integer program to ensure safety with minimal control effort. This method is applied to solve the navigation and pedestrian avoidance problem of a low speed AV. Its performance is compared with two benchmark algorithms: a potential field method and the Hamilton–Jacobi method.

Fast Trajectory Planning and Robust Trajectory Tracking for Pedestrian Avoidance

This paper presents an integrated design method for pedestrian avoidance by considering the interaction between trajectory planning and trajectory tracking. This method aims to reduce the need for control calibration by properly considering plant uncertainties and tire force limits at the design stage. Two phases of pedestrian avoidance—trajectory planning and trajectory tracking—are designed in an integrated manner. The available tire force is distributed to the feedforward part, which is used to generate the nominal trajectory in trajectory planning phase, and to the feedback part, which is used for trajectory tracking. The trajectory planning problem is solved not by searching through a continuous spectrum of steering/braking actions, but by examining a limited set of “motion primitives,” or motion templates that can be adopted in sequence to avoid the pedestrian. An emergency rapid random tree (RRT) methodology is proposed to quickly identify a feasible solution. Subsequently, in order to guarantee accuracy and provide safety margin in trajectory tracking with presence of model uncertainties and exogenous disturbance, a simplified LQR-based funnel algorithm is proposed. Simulation results provide insight into how pedestrian collisions can be avoided under given initial vehicle and pedestrian states.

Validating Noncooperative Control Designs Through a Lyapunov Approach

A decentralized verification procedure is proposed to verify stability and performance for systems with multiple controllers designed by noncooperative agents. The key concept is to use Lyapunov functions as measure of the influence of each controller on the system. Sum of squares programming is used to verify Lyapunov derivative conditions, thus providing a sufficient condition for the specification. Dual decomposition is then used to decentralize the algorithm with the guarantee that decentralized verification is equivalent to centralized verification. The verification procedure is extended to decentralized control synthesis. To reduce the conservatism caused by improper choice of Lyapunov candidate, a perturbation algorithm is proposed to modify the Lyapunov candidate such that it better suits the purpose of verification.

Correct by construction design of autonomous vehicles through a barrier function method

This paper presents a supervisory control structure to ensure safety of low speed autonomous vehicles. The method can provably ensure safety for an autonomous robotic vehicle to navigate in an urban/indoor environment with multiple moving objects. A polar algorithm is developed to construct a polytopic avoidable set, which is then used to construct barrier functions. Then the mixed integer programming (MIP) is used to solve for the control action ensuring safety. The method was tested in simulations with multiple random walking and non-hostile objects. The results show that the proposed method can effectively navigate the autonomous vehicle with guaranteed safety.

Decentralized chassis control with guaranteed performance: A lyapunov approach

This paper presents a Lyapunov-based method for verification and synthesis of decentralized chassis control systems. The method provides performance guarantees without exposing the control algorithms of each agent. We use a Lyapunov derivative condition to guarantee stability and set invariance of the closed-loop system. Agents are asked to exchange polynomials that represent the influence of the control actions on the system dynamics, while the control algorithms are kept secret. Dual decomposition is used to ensure that the solution converges and is equivalent to that of a centralized solution.