LAUSR

In recent years, Connected and Automated Vehicles (CAVs) have become a major focus of research and development efforts in the automotive industry. CAVs are expected to significantly impact the transportation, energy and land use and the broader economy and society. CAVs have also re-invigorated the field of vehicle dynamics and control, and inspired many contemporary directions for research. The cross disciplinary focus in which the treatment of vehicle dynamics and control is integrated with developments in perception, artificial intelligence based decision making, motion planning, energy management, wireless communications, cybersecurity, etc. has added much excitement to the field, and attracted many researchers from other domains. CAVs have also promoted a paradigm shift with real interest emerging in the use of advanced (by automotive industry standards) methods, such as model predictive control and reinforcement learning, in production. Consequently, a Theme Issue which is focused on the ongoing research on CAVs is both relevant and timely to the Vehicle Systems Dynamics journal. The papers in this Theme Issue come from several leading research groups in automotive control worldwide; the papers correspond to a subset of invited talks given at 3rd IAVSD Workshop on Dynamics of Road Vehicles held on 28–30 April 2019 in Ann Arbor, Michigan, USA. A brief description of the contributions follows. The paper by T. Ersal, I. Kolmanovsky, N. Masoud, N. Ozay, J. Scruggs, R. Vasudevan and G. Orosz titled ‘Connected and Automated Road Vehicles: State of the Art and Future Challenges’ provides a general overview of the field. Recent approaches to modelling the dynamics and model based control design for automated vehicles are summarised, and new methods for safety verification of these controllers are highlighted. The advantages of vehicle automation and connectivity in powertrain control and optimisation are quantified and the positive impacts of CAVs on traffic dynamics are emphasised. Finally, the longterm societal effects of CAV deployments are discussed and future opportunities in the field are pointed out. The paper by K. Berntorp, R. Quirynen, T. Uno and S. Di Cairano titled ‘Trajectory Tracking for Autonomous Vehicles on Varying Road Surfaces’ describes the development and implementation of an adaptive nonlinear model predictive controller for vehicle dynamics. The tire stiffness is estimated under normal driving conditions (when slip is small) and this estimate is used to inform the entire tire force curve based on the model library. The latter is used for model predictive control during driving at tire-road adhesion limits. Feasibility of real time implementation is demonstrated, and preliminary experimental results are included. The paper by R. Hult, M. Zanon, S. Gros, H. Wymersch and P. Falcone titled ‘Optimization-based Coordination of Connected, Automated Vehicles at Intersections’ proposes a two stage procedure for controlling traffic flow through intersections. In the