**11. Conclusions**

The proposed design/automation approach reflects an ethically aligned and principled approach to a multi-dimensional design problem. Human benefit, well-being and respect for human rights and identity are important goals for new assisted driving technologies. Such systems must also be verifiably safe and secure. In this way, the solution needs to carefully balance goals around safety and human benefit. As indicated in this research, well-being and human benefit goals and associated KPI are defined to ensure that these concepts are properly considered in the design process, and to ensure that well-being and human benefit is a tangible outcome of new assisted driving solutions.

Arguably, existing high automation approaches do not support positive ageing. Crucially, 'technology progress' in closely intertwined with concepts of progress from a societal values perspective. New assisted driving solutions provide an opportunity to change/improve the lived experience of older adults, particularly in relation to autonomy and social participation. Enabling driver persistence is an issue for all of society and not just older adults.

The application of new car-based sensors underpinned by machine learning techniques, and innovative multimodal HMI communication methods can support driver persistence, driver enablement and successful ageing. The proposed adaptive automation/co-pilot concept is predicated on an analysis of the literature and relevant ageing data (i.e. TILDA data). The co-pilot concept and associated innovative multimodal HMI will be further elaborated using human factors/stakeholder evaluation methods (for example, participatory co-design and evaluation in a test simulator).

It is anticipated that this new car-based technology will deliver (1) safe driving (2) driving persistence and (3) an enhanced driver experience. (4) Health monitoring is built into (1), (2) and (3). In this way, health monitoring is not a goal of new driving assistance systems. Rather, it is an enabler of driver assistance systems and promotes safe driving, driving persistence and an enhanced driver experience.

### **Acknowledgements**

The authors would like to thank the Science Foundation Ireland (SFI) who cosponsored this research.

**41**

**Figure 2.** *Personae (James).*

**B. Personae**

*Research phases and status.*

**Table 5.**

See **Figure 2** and **3.**

2 Advancement of

3 Specification of

scenarios

4 Specification of high-

approach

5 Co-design of evaluation of HMI concept

profiles, personae and

theoretical principles underpinning advancement of new driving concept

level multimodal HMI

*Ethical Issues in the New Digital Era: The Case of Assisting Driving*

**Phase Description Details Status**

driver challenges, self-regulation of driving, driver

Health conditions that impact on older adult driving Assisted driving concepts and issues pertaining to

The detection/interpretation of driver states (i.e. physical, cognitive and emotional states) using a combination of sensor-based technology and

Innovative multimodal communication approaches

Segmentation of driver profiles in relation to driver

Advancement of personae and scenarios

approach (adaptive automation)

Specification of scenarios

machine learning research

6 Simulator evaluation Detailed evaluation in simulator To do

concept

Advancement of technology role, purpose and

Iterative refinement of scenarios and multimodal

Iterative integration of scenarios with sensor and

Preliminary co-design/evaluation with stakeholder panel (desktop simulation of high-level concept

Specification of preliminary UI concept

Complete

Complete

Complete

Complete

Ongoing

1 Literature review Driver task, older adult driver segmentation, older

cessation

Successful ageing

ethics and user acceptability

machine learning techniques

and driving solutions

persistence and ability

*DOI: http://dx.doi.org/10.5772/intechopen.88371*

### **Conflict of interest**

The authors declare no conflict of interest.

### **Appendices and Nomenclature**

### **A. Research phases and status**

See **Table 5.**


*Ethical Issues in the New Digital Era: The Case of Assisting Driving DOI: http://dx.doi.org/10.5772/intechopen.88371*

### **Table 5.** *Research phases and status.*

*Security and Privacy From a Legal, Ethical, and Technical Perspective*

outcome of new assisted driving solutions.

for all of society and not just older adults.

**Acknowledgements**

sponsored this research.

**Conflict of interest**

See **Table 5.**

The authors declare no conflict of interest.

**Appendices and Nomenclature**

**A. Research phases and status**

**11. Conclusions**

in using a driving simulator. A health event cannot be induced as part of a driving simulation exercise. However, we can evaluate the overall concept, driver responses and the usability of specific driver input/output communication mechanisms.

The proposed design/automation approach reflects an ethically aligned and principled approach to a multi-dimensional design problem. Human benefit, well-being and respect for human rights and identity are important goals for new assisted driving technologies. Such systems must also be verifiably safe and secure. In this way, the solution needs to carefully balance goals around safety and human benefit. As indicated in this research, well-being and human benefit goals and associated KPI are defined to ensure that these concepts are properly considered in the design process, and to ensure that well-being and human benefit is a tangible

Arguably, existing high automation approaches do not support positive ageing. Crucially, 'technology progress' in closely intertwined with concepts of progress from a societal values perspective. New assisted driving solutions provide an opportunity to change/improve the lived experience of older adults, particularly in relation to autonomy and social participation. Enabling driver persistence is an issue

The application of new car-based sensors underpinned by machine learning techniques, and innovative multimodal HMI communication methods can support driver persistence, driver enablement and successful ageing. The proposed adaptive automation/co-pilot concept is predicated on an analysis of the literature and relevant ageing data (i.e. TILDA data). The co-pilot concept and associated innovative multimodal HMI will be further elaborated using human factors/stakeholder evaluation methods

It is anticipated that this new car-based technology will deliver (1) safe driving (2) driving persistence and (3) an enhanced driver experience. (4) Health monitoring is built into (1), (2) and (3). In this way, health monitoring is not a goal of new driving assistance systems. Rather, it is an enabler of driver assistance systems and promotes safe driving, driving persistence and an enhanced driver experience.

The authors would like to thank the Science Foundation Ireland (SFI) who co-

(for example, participatory co-design and evaluation in a test simulator).

**40**
