Laura Boffi, University of Ferrara, Ferrara, Italy
Supervisor: Giuseppe Mincolelli
Title: "Cars with an Intent"
Abstract: In a near future autonomous cars will populate the urban environment. While they will actually consist of urban- scale robots immersed in a socio-technical context, so far autonomous cars have been almost exclusively looked at from the perspective of safety and functionality and they have not been designed towards being social “urban beings”. Cars with an Intent” is a design- research driven PhD project which envisions cars acting beyond their core objectives of functionality and safety, by embedding intentional behaviours to prompt positive and enriching car-to-human and human-to-human relationships.
Michael Gerber, CARRS-Q, QUT, Brisbane, Australia
Supervisor: Ronald Schroeter
Title: "Attention Management to Improve Fallback-Readiness in Conditional Automated Vehicles"
My research aims to explore automotive UI-concepts to support fallback-readiness in conditional automated vehicles. Such vehicles allow drivers to perform "non-driving related tasks" (NDRTs), as long as they remain ready to safely take over control of the vehicle when needed. However, one of the most challenging hurdles in this control transition is the likelihood of the driver’s lack of Situation Awareness (SA). Good SA is the basis of a safe transition. This research focuses on improving SA during NDRTs. My approach is to design AR-applications that utilise a fallback-driver’s attention in two ways. Self-initiated “voluntary attention" (VA) during the NDRT and interruption management to facilitate a task switch. Overall, the goal is a better management of the drivers’ attention towards the driving-related task during automated driving. An iterative SA adapted user-interface design method is proposed to develop design-considerations, implement proof of concepts, and evaluate the concepts in simulator
Kai Holländer, LMU Munich, Munich, Germany
Supervisor: Andreas Butz
Title: "Enhancing the Interaction Between Automated Vehicles & Vulnerable Road Users”
Researchers from industry and academia work on increasing the level of automation for everyday vehicles. This endeavour will eventually result in fully automated driving where no human controller is necessary, marking a groundbreaking change in the automotive sector. Vehicles interior, the way we think about individually owned cars and infrastructure might transform. As a side effect, the question arises if new explicit vehicle to pedestrian communication signals should be added to foster safety in the interaction between automated vehicles and vulnerable road users. At the moment, we see a lively debate in the automotive research domain regarding this open challenge. I believe that the interaction between those entities is a crucial aspect for the acceptance and success of automated driving. For my PhD thesis I want to contribute design guidelines on how to enhance safety for vulnerable road users when interacting with automated vehicles. Furthermore, I aim to propose novel concepts for pedestrian-vehicle interaction and suggestions on how to evaluate them.
Abhishek Mukhopadhyay, Indian Institute of Science, Bangalore, India
Supervisors: Imon Mukherjee and Pradipta Biswas
“Ride Quality Monitoring of Driver and Co-passengers in Autonomous Vehicle”
In autonomous vehicles, awareness of autopilot capacities and incapacities leads to distinct ‘co-driving’ practices. ‘Co-driving’ systems are designed to keep drivers engaged as well as interact with autopilots and other vehicles. Automatic detection of driver’s and co-passenger’s mental state and cognitive load can be used to take evasive action to prevent accident. Even though there are lot of options like facial expression, acoustic feature of voice, skin responses, and eye gaze movements are explored with varying range of success, detecting and reducing cognitive load of driver and co-passengers is challenging. This dissertation will contribute in developing an intelligent system which will estimate cognitive load of both driver and co-passengers considering outside situations and inside car environment. Accordingly, it will alert the driving system and enhance overall safety of autonomous vehicle and comfort level of drivers and passengers.
Holger Schmidt, Stuttgart Media University, Stuttgart, Germany
Supervisors: Albrecht Schmidt, Gottfried Zimmermann
Title: "Gaze Based Interactions in Future Automotive Applications Vehicles and ‘Readiness’ Test Design"
The ongoing development of self-driving vehicles seems to go well with the growing demand for the use of mobile devices throughout the day. However, for a long time to come, autonomous vehicles will still need manual intervention in unforeseen and potentially dangerous situations. Therefore, it is important for the drivers of autonomous vehicles to stay aware of the traffic situation around, and so to be quickly able to take over control of the vehicle. As core part of this dissertation we developed an adaptive prototype which represents media content on a simulated windshield display and uses gaze tracking as an additional
form of input device for the driver. Although we intentionally pull away the driver’s gaze from the driving situation, this seems to be less of a distraction than using hand-held mobile devices or dash-integrated display devices. We hypothesize that the time to regain control with our prototype is shorter than when using a hand-held mobile device or dash-integrated display device. We plan to evaluate this prototype in our stationary driving simulator.
Emily Shaw, University of Nottingham, Nottingham, United Kingdom
Supervisors: Gary Burnett, David Large
Title: "Ready, Set, Drive? Exploring Driver Skills and Training for Future Automated"
The introduction of vehicles with automation capability to the commercial market has and will fundamentally change the role of the driver. However, this role, as well as the skills required to effectively and safely carry out the driving task in future automated vehicles has yet to be mapped out. Many drivers do not have an accurate mental model of what automated systems can do. This drives behavioural adaptations that typically lead to well-known human performance reduction costs associated with automation. Using a combination of qualitative research methods and simulator studies, this research aims to explore the specific skills required to safely and effectively carry out all elements of the driving task for future vehicles. A key objective of this research is to ensure drivers of these vehicles are ready to take on the redesigned role of the driver and able to resume the driving task during dynamic operations.
Taufik Akbar Sitompul, School of Innovation, Design and Engineering, Mälardalen
University, Västerås, Sweden and CrossControl AB, Västerås, Sweden
Supervisor: Rikard Lindell
Title: "Using See-through Visualization in Industrial Vehicles”
This PhD project investigates the use of see-through visualization in three different industrial vehicles: excavators, mobile cranes, and forest harvesters. We
hypothesize that, by presenting critical information near operators’ line of sight, the risk of overlooked information while operating industrial vehicles can be reduced. The research involves (1) reviewing available see-through displays in order to envision what kind of visualization that could be possibly made, (2) indirect approaches for gaining sufficient knowledge on industrial vehicles’ operations, (3) developing mixed reality simulations to present see-through information for industrial vehicles’ operations, and (4) evaluating the effectiveness of such visualization by involving test users in controlled environments. The main expected contribution of this PhD project is the concepts of see-through visualization, which could be utilized to help operators of industrial vehicles to perform their work, while maintaining awareness of the machine and the surroundings.