The automobile is considered essential for transportation in most Western countries. Numerous studies indicate that driving ability declines as people age, especially after 80, leading to increased crash rates and poorer performance on driving tests. For many older adults, driving is a key enabler for maintaining an active, engaged, and independent lifestyle, allowing the freedom to get out for work, social activities, shopping, physical exercise, and many other activities. The challenge of ensuring drivers continue to have the required skills for safe driving across the lifespan is important and requires balancing a crash risk with the well-being of older drivers.

In an article published in IEEE Instrumentation & Measurement Magazine, researchers propose a new role for advanced driver assistance systems (ADAS) technologies in extending driver capabilities into older age. These ADAS technologies can take on two roles: first, acting as assistive devices enhancing safety and convenience for drivers in day-to-day situations, and second, as measurement systems to assess age-related declines in driving skills. There is potential for new information from these sensor systems to build knowledge about driving safety and provide supportive feedback to the driver to extend their safe driving careers.

ADAS/SAV as System for Safer Driving

While fully autonomous vehicles may be the solution, eventually, the technology is yet to be available on a large scale. For the foreseeable future, the researchers note that there will be combinations of vehicles on the road, some with and some without autonomous features. With the assumed driving model where the human driver is responsible for supervising and responding to the SAV functions, having systems to determine if the driver is attentive and alert is needed in the first example of driver assessment by the SAV system. This ensures the human driver can perform a takeover when required.

Many other ADAS functions provided within the vehicle have the potential to support the older driver, and these include functions such as proximity detection, lane departure warnings, blind spot detectors, backup systems, and others. These technologies support drivers of all ages, but a key challenge is that their use by older drivers is limited by their complexity, ease of use, and clarity of function, especially if there is limited training on how to use them and car-to-car differences in these alert systems for the same function.

ADAS sensor and alert functions that can support older drivers. A: Lane tracking, B: Forward proximity, C: Backward proximity, D: Blind spot detection.

 

This alternative model for SAV/human driver interaction assumes that when the human driver is operating the vehicle, the systems within the vehicle that are part of telematic, ADAS or SAV driving functions act in the background to support and assess their driving. Using in-car sensors as part of an ongoing assessment system has been proposed. Some works explored the communication of the knowledge produced from these systems through feedback mechanisms and coaching systems.

Ethical Considerations of Driving Risk Knowledge

Risk information may aid older drivers in better understanding how new ADAS features will assist them so that they respond to them when they provide help. The concept of using driving data to assess and understand driving ability is quickly followed by the questions of who, when, and how this information is relayed to anyone, including the driver. For the older driver, the knowledge and assessment of their driving is personal data, and they should have control over how and to whom this information is shared. 

Sharing the knowledge with a family member, such as a spouse or an adult child, could be acceptable. The more extensive scope of data sharing also must consider whether information is shared beyond the family, such as with the driver's health care providers, insurers, and regulatory authorities in conjunction with licensing.

Communications and processing model for driver risk assessment through vehicle-based OBDII, ADAS, and SAV sensor systems.

 

Driving data is highly identifiable as it typically contains GPS vehicle location, including where a car spends most nights and the owner's residential address. Entities with data can assess driving risks and behaviors for individual cars without the knowledge or permission of the actual drivers. These considerations immediately open questions around the ethical use of identifiable driving data, ownership of a given person's driving data, and ensuring that the actual driving knowledge derived from the data collected from the car is shared and summarized appropriately and in a timely way. 

According to the researchers, developing algorithms and methods to model risk is a new field of research, and this work will need to ensure that the algorithms and methods do not introduce bias across age, gender, socio-economic, or urban/rural status. By ensuring that the development datasets fully represent all drivers, the algorithms can be developed without inadvertently adding bias to their risk identification. 

Future Directions

The innovative technologies associated with ADAS and SAV systems are not just about driving the vehicle. They also have the potential to support safe driving by older adults when the older adult is driving. For ADAS and SAV to serve the needs of older drivers, solutions are required for day-to-day assistance so that their skills stay on par with other drivers and systems provide ongoing assessment of driver risk. 

As technology advances, new research is crucial to understand the methods and algorithms for these assessments. Protocols must include designs for communicating the information to the people who need the knowledge. Efforts to use vehicle sensor data to address older driver safety should consider the ethical and moral frameworks for how data will be used and communicated. Technology is at a crossroads where the advances in sensors to support ADAS and SAV can be reused to provide knowledge to the many stakeholders in older driver safety.

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