Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic. (arXiv:1911.06818v1 [eess.SY])

This paper studies the energy and traffic impact of a proposed Cooperative and Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the anticipative mode, more immediately beneficial when automated vehicle fleet penetration is low, and 2. the connected mode, beneficial in coordinated platooning scenarios and high…

Model Hierarchy for the Shape Optimization of a Microchannel Cooling System. (arXiv:1911.06819v1 [math.OC])

We model a microchannel cooling system and consider the optimization of its shape by means of shape calculus. A three-dimensional model covering all relevant physical effects and three reduced models are introduced. The latter are derived via a homogenization of the geometry in 3D and a transformation of the three-dimensional models to two dimensions. A…

Backward propagation of chaos. (arXiv:1911.06835v1 [math.PR])

This paper develops a theory of propagation of chaos for a system of weakly interacting particles whose terminal configuration is fixed as opposed to the initial configuration as customary. Such systems are modeled by backward stochastic differential equations. Under standard assumptions on the coefficients of the equations, we prove propagation of chaos results and quantitative…

Robust Model Predictive Control via System Level Synthesis. (arXiv:1911.06842v1 [math.OC])

In this paper, we consider the robust model predictive control (MPC) problem of a linear time-variant (LTV) system with both norm-bounded disturbances and model uncertainty. In robust MPC, a series of constrained optimal control problems (OCPs) are solved. Solving these robust OCPs is challenging since disturbances can cause deviation from the predicted states and model…

An Optimal Transport approach for the Schr\”odinger bridge problem and convergence of Sinkhorn algorithm. (arXiv:1911.06850v1 [math.PR])

This paper exploit the equivalence between the Schr\”odinger Bridge problem and the entropy penalized optimal transport in order to find a different approach to the duality, in the spirit of optimal transport. This approach results in a priori estimates which are consistent in the limit when the regularization parameter goes to zero. In particular, we…

Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic. (arXiv:1911.06818v1 [eess.SY])

This paper studies the energy and traffic impact of a proposed Cooperative and Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the anticipative mode, more immediately beneficial when automated vehicle fleet penetration is low, and 2. the connected mode, beneficial in coordinated platooning scenarios and high…

Model Hierarchy for the Shape Optimization of a Microchannel Cooling System. (arXiv:1911.06819v1 [math.OC])

We model a microchannel cooling system and consider the optimization of its shape by means of shape calculus. A three-dimensional model covering all relevant physical effects and three reduced models are introduced. The latter are derived via a homogenization of the geometry in 3D and a transformation of the three-dimensional models to two dimensions. A…

Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning. (arXiv:1911.06832v1 [cs.LG])

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturing…

Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. (arXiv:1911.06833v1 [cs.LG])

Model-free reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG) often require additional exploration strategies, especially if the actor is of deterministic nature. This work evaluates the use of model-based trajectory optimization methods used for exploration in Deep Deterministic Policy Gradient when trained on a latent image embedding. In addition, an extension of DDPG…