From the Concept of Being “the Boss” to the Idea of Being “a Team”: The Adaptive Co-Pilot as the Enabler for a New Cooperative Framework

The “classical” SAE LoA for automated driving can present several drawbacks, and the SAE-L2 and SAE-L3, in particular, can lead to the so-called “irony of automation”, where the driver is substituted by the artificial system, but is still regarded as a “supervisor” or as a “fallback mechanism”. To overcome this problem, while taking advantage of the latest technology, we regard both human and machine as members of a unique team that share the driving task. Depending on the available resources (in terms of driver’s status, system state, and environment conditions) and considering that they are very dynamic, an adaptive assignment of authority for each member of the team is needed. This is achieved by designing a technology enabler, constituted by the intelligent and adaptive co-pilot. It comprises (1) a lateral shared controller based on NMPC, which applies the authority, (2) an arbitration module based on FIS, which calculates the authority, and (3) a visual HMI, as an enabler of trust in automation decisions and actions. The benefits of such a system are shown in this paper through a comparison of the shared control driving mode, with manual driving (as a baseline) and lane-keeping and lane-centering (as two commercial ADAS). Tests are performed in a use case where support for a distracted driver is given. Quantitative and qualitative results confirm the hypothesis that shared control offers the best balance between performance, safety, and comfort during the driving task.This research was supported by the ECSEL Joint-Undertaking,which funded the PRYSTINE project under the Grant 783190

A Review of Shared Control for Automated Vehicles: Theory and Applications

The last decade has shown an increasing interest on advanced driver assistance systems (ADAS) based on shared control, where automation is continuously supporting the driver at the control level with an adaptive authority. A first look at the literature offers two main research directions: 1) an ongoing effort to advance the theoretical comprehension of shared control, and 2) a diversity of automotive system applications with an increasing number of works in recent years. Yet, a global synthesis on these efforts is not available. To this end, this article covers the complete field of shared control in automated vehicles with an emphasis on these aspects: 1) concept, 2) categories, 3) algorithms, and 4) status of technology. Articles from the literature are classified in theory- and application-oriented contributions. From these, a clear distinction is found between coupled and uncoupled shared control. Also, model-based and model-free algorithms from these two categories are evaluated separately with a focus on systems using the steering wheel as the control interface. Model-based controllers tested by at least one real driver are tabulated to evaluate the performance of such systems. Results show that the inclusion of a driver model helps to reduce the conflicts at the steering. Also, variables such as driver state, driver effort, and safety indicators have a high impact on the calculation of the authority. Concerning the evaluation, driver-in-the-loop simulators are the most common platforms, with few works performed in real vehicles. Implementation in experimental vehicles is expected in the upcoming years.This work was supported in part by the ECSEL Joint Undertaking, which funded the PRYSTINE project under Grant 783190, and in part by the AUTOLIB project (ELKARTEK 2019 ref. KK-2019/00035; Gobierno Vasco Dpto. Desarrollo económico e infraestructuras)

Safe and seamless transfer of control authority - exploring haptic shared control during handovers

This research aimed at investigating the impact of lateral assistance systems on drivers' performance and behaviour during transitions from Highly Automated Driving (HAD). The thesis focused on non-critical transitions and analysed the differences between system and user-initiated transitions. Hence, two experiments were developed and conducted in driving simulators to address questions relating to how handover procedures, which provide varying levels of lateral assistance, affect drivers' performance and behaviour at different stages of the transition. In particular, it was investigated which type of assistance yields better results depending on who initiated the transition of control. Drivers were induced to be Out-Of-The-Loop (OOTL) during periods of HAD and then exposed to both system and user-initiated transitions. Results showed that after user-initiated transitions, drivers were generally more engaged with the steering task and the provided assistance was not helpful and, in some cases, caused steering conflicts and a comfort drop. On the contrary, after system-initiated transitions, drivers were not engaged with the steering control and were more prone to gaze wandering. Strong lateral assistance proved to be most beneficial within the first 5 seconds of the transition, when drivers were not committed to the steering control. The provision of assistance at an operational level, namely when drivers had to keep the lane centre, was not enough to ensure good performance at a tactical level. Drivers were able to cope with tactical tasks, presented as lane changes, only after around 10 seconds from the start of the transitions in both user and system initiated cases (Chapter 3 and Chapter 4). The introduction of non-continuous lateral assistance, used to trigger steering conflicts and, in turn, a faster steering engagement, did not yield particular benefits during user-initiated transitions but it might have triggered a faster re-engagement process in system-initiated ones (Chapter 5). The results suggest that assisting drivers after user-initiated transitions is not advisable as the assistance might induce steering conflicts. On the contrary, it is extremely beneficial to assist drivers during system-initiated transitions because of their low engagement with the driving task. The thesis concludes with a general overview of the conducted studies and a discussion on future studies to take this research forward

Human-machine collaboration for automated driving using an intelligent two-phase haptic interface

Prior to realizing fully autonomous driving, human intervention is periodically required to guarantee vehicle safety. This poses a new challenge in human–machine interaction, particularly during the control authority transition from automated functionality to a human driver. Herein, this challenge is addressed by proposing an intelligent haptic interface based on a newly developed two‐phase human–machine interaction model. The intelligent haptic torque is applied to the steering wheel and switches its functionality between predictive guidance and haptic assistance according to the varying state and control ability of human drivers. This helps drivers gradually resume manual control during takeover. The developed approach is validated by conducting vehicle experiments with 26 participants. The results suggest that the proposed method effectively enhances the driving state recovery and control performance of human drivers during takeover compared with an existing approach. Thus, this new method further improves the safety and smoothness of human–machine interaction in automated vehicles

Examining Preference For Autonomous Vehicle (Av) Among Qatari Residents

Because of growing body of researches that predict the autonomous vehicles to be the future mode of transport. It is important to investigate the preference of Autonomous vehicles among Qatari citizens for fast developing country such as Qatar. Stated Preference survey is distributed to 315 individuals living across Qatar. Based on the participants characteristics, the drivers are exposed to different scenarios and asked to choose one of the presented four modes of transport (Normal car, Private own autonomous vehicles, Shared autonomous vehicles, Public transport).The characteristics of each respondent have an impact on the preferences and attitude toward autonomous vehicles AVs and this was quantified through multinomial logit model. Currently, the key observations were as following: ? There is substantial hesitation toward adoption of AVs in Qatar, with 52% of choice decision that supports normal cars. ? Comfortable scale is an important factor in Qatar because good comfortable scale will increase the utility to use such mode of transport. ? Public transport is considered the least preferred mode of transport in Qatar especially if the individual owns a private car. In other word, people in Qatar give less utility value for SAV and public transport. Educating the young generation about the benefits of using AVs and public transport will enhance their background regarding the advanced modes of transport and encourage them to use conventional car alternatives in the future

Human-Machine Cooperative Decision Making

Diese Dissertation beschäftigt sich mit der gemeinsamen Entscheidungsfindung in der Mensch-Maschine-Kooperation und liefert neue Erkenntnisse, welche von der theoretischen Modellierung bis zu experimentellen Untersuchungen reichen. Zunächst wird eine methodische Klassifikation bestehender Forschung zur Mensch-Maschine-Kooperation vorgenommen und der Forschungsfokus dieser Dissertation mithilfe eines vorgestellten Taxonomiemodells der Mensch-Maschine-Kooperation, dem Butterfly-Modell, abgegrenzt. Darauffolgend stellt die Dissertation zwei mathematische Verhaltensmodelle der gemeinsamen Entscheidungsfindung von Mensch und Maschine vor: das Adaptive Verhandlungsmodell und den n-stufigen War of Attrition. Beide modellieren den Einigungsprozess zweier emanzipierter Kooperationspartner und unterscheiden sich hinsichtlich ihrer Ursprünge, welche in der Verhandlungs- beziehungsweise Spieltheorie liegen. Zusätzlich wird eine Studie vorgestellt, die die Eignung der vorgeschlagenen mathematischen Modelle zur Beschreibung des menschlichen Nachgebeverhaltens in kooperativen Entscheidungsfindungs-Prozessen nachweist. Darauf aufbauend werden zwei modellbasierte Automationsdesigns bereitgestellt, welche die Entwicklung von Maschinen ermöglichen, die an einem Einigungsprozess mit einem Menschen teilnehmen können. Zuletzt werden zwei experimentelle Untersuchungen der vorgeschlagenen Automationsdesigns im Kontext von teleoperierten mobilen Robotern in Such- und Rettungsszenarien und anhand einer Anwendung in einem hochautomatisierten Fahrzeug präsentiert. Die experimentellen Ergebnisse liefern empirische Evidenz für die Überlegenheit der vorgestellten modellbasierten Automationsdesigns gegenüber den bisherigen Ansätzen in den Aspekten der objektiven kooperativen Performanz, des menschlichen Vertrauens in die Interaktion mit der Maschine und der Nutzerzufriedenheit. So zeigt diese Dissertation, dass Menschen eine emanzipierte Interaktion mit Bezug auf die Entscheidungsfindung bevorzugen, und leistet einen wertvollen Beitrag zur vollumfänglichen Betrachtung und Verwirklichung von Mensch-Maschine-Kooperationen