… Driving in autonomous cars requires trust, especially in case of unexpected driving behavior
… This work evaluates mental models that experts and non-expert users have of autonomous …

… Tomizuka, “Probabilistic prediction of interactive driving behavior via hierarchical inverse
reinforcement learning,” in 2018 21st International Conference on Intelligent Transportation …

… real human driver behavior on … autonomous car of the future should be safe, efficient, and
courteous to others, perhaps even more so than represented in our current human-only driving …

… Peng [14] analyzed a new lattice model with the consideration of individual difference of
anticipation driving behavior based on car-following theory. Yu et al. [15] improved the optimal …

… autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles’
driving behaviors plays a crucial role in autonomous vehicles. Most traditional driving behavior …

… (dCACC—autonomous car does not communicate … behavior of two autonomous cars is
analyzed to propose the adjustment in Wiedemann’s model for autonomous driving behaviors, as …

… are quantified and the driving behavior benefit evaluation model … of driving behavior decision
making for autonomous driving … behavior is analyzed; In Section 4 and Section 5, a driving …

… ; the car drives autonomously on the highway in the 2030 scenario. Finally, we describe a
fully autonomous car … Our results indicate that UA and UX of highly autonomous cars is indeed …

… -driven cars. Behavior cloning in particular has been successfully used to learn simple
visuomotor policies end-to-end, but scaling to the full spectrum of driving behaviors remains an …

… Very few innovations can be expected to have as high an impact on future cars as the
capability to perceive the environment and to plan and conduct appropriate driving behavior. We …