A Nonlinear Modeling Framework for Autonomous Cruise Control

Connected vehicle systems (CVS) are considered in this paper where vehicles exchange information using wireless vehicle-to-vehicle (V2V) communication. The concept of connected cruise control (CCC) is established that allows control design at the level of individual vehicles while exploiting V2V connectivity. Due to its high level of modularity the proposed design can be applied to large heterogeneous traffic systems. The dynamics of a simple CVS is analysed in detail while taking into account nonlinearities in the vehicle dynamics as well as in the controller. Time delays that arise due to intermittencies and packet drops in the communication channels are also incorporated. The results are summarised using stability charts which allow one to select control gains to maintain stability and ensure disturbance attenuation when the delay is below a critical value. ARTICLE HISTORY

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“…whereK p ,K i ,K v ,K a are defined by (18) and we still consider the simplifications φ = 0, v w = 0 and J = 0 =⇒ m eff = m (cf. (17)).…”

Section: Appendix 1 Parameters Used In This Papermentioning

confidence: 99%

“…[18,22] For simplicity, we consider φ = 0, v w = 0 and J = 0 =⇒ m eff = m, while the other parameters are shown in Table A1 in Appendix 1.…”

Section: Vehicle Dynamics and Traffic Equilibriummentioning

confidence: 99%

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Connected cruise control: modelling, delay effects, and nonlinear behaviour

Orosz

2016

Vehicle System Dynamics

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225

119

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“…where v ∈ [vmin, vmax] is the velocity of the car, u ∈ [−3a, 2a] is the scaled input acceleration and ci for i = 1, 2 are proper constants to account for rolling resistance, air drag and headwind [16], which are chosen as c0 = 0.1, c1 = 0.00016, a = 0.5. The unit of velocity is in meters per second (m/s).…”

Section: Examplementioning

confidence: 99%

Abstraction, discretization, and robustness in temporal logic control of dynamical systems

Özay

2014

Proceedings of the 17th International Conference on Hybrid Systems: Computation and Control

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Abstraction-based, hierarchical approaches to control synthesis from temporal logic specifications for dynamical systems have gained increased popularity over the last decade. Yet various issues commonly encountered and extensively dealt with in control systems have not been adequately discussed in the context of temporal logic control of dynamical systems, such as inter-sample behaviors of a sampled-data system, effects of imperfect state measurements and unmodeled dynamics, and the use of time-discretized models to design controllers for continuous-time dynamical systems. We discuss these issues in this paper. The main motivation is to demonstrate the possibility of accounting for the mismatches between a continuous-time control system and its various types of abstract models used for control synthesis. We do this by incorporating additional robustness measures in the abstract models. Such robustness measures are gained at the price of either increased nondeterminism in the abstracted models or relaxed versions of the specification being realized. Under a unified notion of abstraction, we provide concrete means of incorporating these robustness measures and establish results that demonstrate their effectiveness in dealing with the above mentioned issues.

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“…see Refs. [30,31], where the effective mass m eff ¼ m þ I=R 2 contains the mass of the vehicle m, the moment of inertia I of the rotating elements, and the wheel radius R. Furthermore, g is the gravitational constant, / is the inclination angle, c is the rolling resistance coefficient, k is the air drag constant, v w is the speed of the headwind, g is the gear ratio (that includes the final drive ratio and the transmission efficiency), and T e is the engine torque. See Appendix A (Table 2) for parameter values used in this paper, which are for a ProStar truck, a class 8 HDV manufactured by Navistar, Lisle, IL [32].…”

Section: Optimizationmentioning

confidence: 99%

Fuel Consumption Optimization of Heavy-Duty Vehicles With Grade, Wind, and Traffic Information

Maurer

Orosz

2016

Journal of Computational and Nonlinear Dynamics

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In this paper, we establish a mathematical framework that allows us to optimize the speed profile and select the optimal gears for heavy-duty vehicles (HDVs) traveling on highways while varying parameters. The key idea is to solve the analogous boundary value problem (BVP) analytically for a simple scenario (linear damped system with quadratic elevation profile) and use this result to initialize a numerical continuation algorithm. Then, the numerical algorithm is used to investigate how the optimal solution changes with parameters. In particular, we gradually introduce nonlinearities (air resistance and engine saturation), implement different elevation profiles, and incorporate external perturbations (headwind and traffic). This approach enables real-time optimization in dynamic traffic conditions, therefore may be implemented on-board.

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A Nonlinear Modeling Framework for Autonomous Cruise Control

Cited by 19 publications

References 7 publications

Connected cruise control: modelling, delay effects, and nonlinear behaviour

Connected cruise control: modelling, delay effects, and nonlinear behaviour

Abstraction, discretization, and robustness in temporal logic control of dynamical systems

Fuel Consumption Optimization of Heavy-Duty Vehicles With Grade, Wind, and Traffic Information

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