CarEs: An Emotional Model of a Car With the Stress Factor

Autonomous driving is a growing research field, that still has many challenges. The main challenges are related to decision‑making algorithms, human‑machine interaction, and acceptance of the technology. Also, the absence of human drivers in autonomous vehicles creates a gap between users and pedestrians interacting with the vehicle. This article aims to define vehicle awareness, which eases the collaboration with users to improve safety and have a more human‑like driving to increase technology acceptance. In addition, our approach can be extended to express vehicle social awareness towards pedestrians and road users. Our approach is based on affective computing. Affective computing is a tool to grant computers to genuinely become intelligent and interact better with humans. Moreover, one of its components is the generation of emotions, of which two of the most important elements are cognitive emotions and primary emotions. The article’s objective is to design the model of a primary emotion component, based on safety that can be personalized depending on the user’s driving style. This component is called the stress factor. The stress factor is correlated with the probability of an accident. The vehicle stress factors contain parameters that can be personalized as a function of a driving style. The stress factor is then attached to an existing cognitive emotion system (CarE) in the automotive domain which we called CarEs. The results of the system behavior showed promising results. The stress factor showed to be useful as a safety indicator. Also, the stress factor can be personalized with the vehicle operation state component. In conclusion, the new system known as CarEs generates vehicle awareness, by improving the vehicle’s collaboration with the driver. The collaboration has a positive impact on the vehicle’s safety and comfort, and people’s reliance on automated vehicles

Development of a Virtual Simulation Environment and a Digital Twin of an Autonomous Driving Truck for a Distribution Center

This paper presents the development of a Virtual Simulation Environment (VSE) and a Digital Twin (DT) of an autonomously driving truck for a distribution center. While autonomous driving on public roads still faces various technical and legal challenges, within a distribution center, which is a confined area, some of these restrictions do not apply. Therefore, distribution centers can be the first environment where the autonomous driving of trucks is possible. A distribution center is a closed environment with no, or minimal generic traffic, where the trucks have relatively low speeds, short stopping distance and layout precisely known. Dedicated sensors locate the trucks. This paper addresses the mentioned aspects of driving in the distribution centers describing the necessary steps taken for the design, implementation, and testing of a VSE for a distribution center, and a DT of an autonomously driving truck. The development of the VSE is based on the integration of a SysML modeling tool – IBM Rhapsody, MATLAB Simulink, and Unity Game Engine using a Model-Based System Engineering approach. The paper also presents the test and the validation of a driving scenario used in a distribution center, using the TruckLab setup of the Eindhoven University of Technology, The Netherlands. The VSE and the DT showed considerable potential as testing and validation tools for automotive engineers, making it possible to define driving test scenarios for different types of tractor and trailer combinations