# A VR Truck Docking Simulator Platform for Developing Personalized Driver Assistance
### Content and Goals of the VISTA Project  
While performing the docking manoeuvre at the distribution centre, the driver has to operate a truck with one or even two attached trailers (truck combination) towards the loading bay. Handling the manoeuvre properly is a challenge: the driver has constrained visibility from the cabin and the manoeuvre area is limited in space. Additionally, the manoeuvre must be performed in a place that has a dynamic nature (e.g., other trucks manoeuvring, people walking, etc.), meaning that accidents can happen, resulting in significant costs due to collision damage. For that reason, the Intelligent Truck Applications in Logistics (INTRALOG) project developed and investigated the effect of an automated docking system [8]. Path tracking and path planning algorithms have been developed for logistic vehicle combinations with one or two articulations, for both forward and rearward docking manoeuvres.  
Although some of the main problems of this driving scenario could be attenuated with the usage of sensors on the trailing vehicles and the usage of an automated docking system, it would also imply that all the trucks need the same technology integrated, resulting in significant costs. Moreover, trailers and trucks are often owned by different companies, which complicates the possibility for trailer instrumentation. Furthermore, logistic companies also have challenges in attracting skilled drivers, so they have a desire to provide support to less-trained drivers. This induces a desire for docking support functionality, suiting drivers with varying skills and experience. Based on these observations, a novel approach is currently being explored in the project VISTA (Vision Supported Truck docking Assistant). The VISTA project aims to develop a framework integrating a camera-based localization system to track in real-time the position of truck and trailer(s) during the docking process at a distribution centre. Based on this localization system, the optimal docking path from the current position to the final unloading station is calculated and provided in the form of audiovisual assistive instructions (e.g., steering recommendation) either displayed as an appropriately coloured light array located above the windshield or on an HMI module displayed on a tablet placed on top of the cockpit in the truck cabin.  
The target of the present research is to develop the VISTA-Sim, a platform that uses a VR-simulator as an environment to investigate driver performance, train drivers and develop and evaluate different forms of context-sensitive and personalized driver assistance feedback systems. The driving scenario in which this platform is studied refers to the docking of a truck combination towards the loading bay in a distribution centre. VISTA-Sim has two main goals. First, the simulator will serve as a tool that allows the validation of an HMI and different feedback components (such as lights or audiovisual hints, e.g., indication arrows or verbalized steering recommendations) designed for the VISTA project. This offers a driver-centred design approach that allows making decisions in an early stage of the project. The second goal is to use this platform as a tool to record data that can be used by machine-learning algorithms to learn about novice- and expert behaviours, allowing the implementation of a driver model. These insights can be used to estimate individual driving behaviour or to detect differences from expert driver performance, in order to provide context- and user-adequate feedback.  
In summary, this paper proposes a novel and holistic approach to develop and evaluate personalized driver assistance using VR technology.