Fork in the road: In-vehicle navigation systems and older drivers

Emmerson, C; Guo, Aw; Blythe, PT; Namdeo, Anil; Edwards, Stuart

doi:10.1016/j.trf.2013.09.013

Cited by 38 publications

(30 citation statements)

References 29 publications

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“…Several studies have assessed older drivers’ use and perceptions of NA systems under actual and simulated driving conditions. Collectively these studies showed that older drivers: used NA systems frequently; reported only minimal distraction, but more than reported by younger drivers; traveled to places they would not have gone to without the system; more frequently travelled during times and on roadways that they would normally avoid; reported increased feelings of safety, confidence, attentiveness, and relaxation when using NA systems; tended to still bring paper maps along in case the NA system failed; took longer and had more difficulty learning to use NA systems; were more likely to have learned how to use the system from a friend or family member; had more difficulty than younger drivers reading the displays; more frequently used the system with a “co-navigator” passenger than reported by younger drivers; some reported feeling that the NA system was more like a human co-navigator than a technological device; reported higher preferences for verbal turn-by-turn instructions; and would not buy a system targeted to “old” people (Dingus et al 1997; Kessler et al 2012; Eby & Kostyniuk 1998; Eby & Kostyniuk 1999; Eby & Molnar 1999; Chan & Rose 2002; Emmerson et al 2013; Novotný & Bouchner 2011; Oxley et al 1995; Vrkljan & Polgar 2007; Zhang et al 2012)…”

Section: Resultsmentioning

confidence: 99%

Use, perceptions, and benefits of automotive technologies among aging drivers

et al. 2016

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Advanced in-vehicle technologies have been proposed as a potential way to keep older adults driving for as long as they can safely do so, by taking into account the common declines in functional abilities experienced by older adults. The purpose of this report was to synthesize the knowledge about older drivers and advanced in-vehicle technologies, focusing on three areas: use (how older drivers use these technologies), perception (what they think about the technologies), and outcomes (the safety and/or comfort benefits of the technologies). Twelve technologies were selected for review and grouped into three categories: crash avoidance systems (lane departure warning, curve speed warning, forward collision warning, blind spot warning, parking assistance); in-vehicle information systems (navigation assistance, intelligent speed adaptation); and other systems (adaptive cruise control, automatic crash notification, night vision enhancement, adaptive headlight, voice activated control). A comprehensive and systematic search was conducted for each technology to collect related publications. 271 articles were included into the final review. Research findings for each of the 12 technologies are synthesized in relation to how older adults use and think about the technologies as well as potential benefits. These results are presented separately for each technology. Can advanced in-vehicle technologies help extend the period over which an older adult can drive safely? This report answers this question with an optimistic “yes.” Some of the technologies reviewed in this report have been shown to help older drivers avoid crashes, improve the ease and comfort of driving, and travel to places and at times that they might normally avoid.

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Section: Resultsmentioning

confidence: 99%

Use, perceptions, and benefits of automotive technologies among aging drivers

et al. 2016

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“…For example, accessibility requirements for such individuals include (e.g., [11]): using touchscreen devices with voice interaction and ensuring displayed information is as simple to understand and uncluttered as possible. Key functionality examples include visual and auditory collision warnings, night vision enhancement and health and stress monitoring (e.g., [12], [13]). HMI adaptability refers to the ability to personalize features (e.g., text and image size/types) settings (e.g., option to display more or less information and have more or less steps to complete an action, and modes of interaction (see [1]).…”

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confidence: 99%

Exploring the Usability of a Connected Autonomous Vehicle Human Machine Interface Designed for Older Adults

Morgan

Voinescu

Alford

et al. 2018

Advances in Intelligent Systems and Computing

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Users of Level 4-5 connected autonomous vehicles (CAVs) should not need to intervene with the dynamic driving task or monitor the driving environment, as the system will handle all driving functions. CAV humanmachine interface (HMI) dashboards for such CAVs should therefore offer features to support user situation awareness (SA) and provide additional functionality that would not be practical within non-autonomous vehicles. Though, the exact features and functions, as well as their usability, might differ depending on factors such as user needs and context of use. The current paper presents findings from a simulator trial conducted to test the usability of a prototype CAV HMI designed for older adults and/or individuals with sensory and/or physical impairments: populations that will benefit enormously from the mobility afforded by CAVs. The HMI was developed to suit needs and requirements of this demographic based upon an extensive review of HMI and HCI principles focused on accessibility, usability and functionality [1,2], as well as studies with target users. Thirty-one 50-88 year-olds (M 67.52, three 50-59) participated in the study. They experienced four seven-minute simulated journeys, involving inner and outer urban settings with mixed speed-limits and were encouraged to explore the HMI during journeys and interact with features, including a real-time map display, vehicle status, emergency stop, and arrival time. Measures were taken pre-, during-and post-journeys. Key was the System Usability Scale [3] and measures of SA, task load, and trust in computers and automation. As predicted, SA decreased with journey experience and although cognitive load did not, there were consistent negative correlations. System usability was also related to trust in technology but not trust in automation or attitudes towards computers. Overall, the findings are important for those designing, developing and testing CAV HMIs for older adults and individuals with sensory and/or physical impairments. IntroductionWe are moving at a rapid pace towards fully autonomous vehicles that handle all driving related functions without the need for user intervention. Level 5 fully connected autonomous vehicles (CAVs) are defined by SAE International [4] as systems that can handle 'the full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver', whereas Level 4 highly automated vehicles are similar but only have such system capabilities for some driving modes and may require human intervention for some non-driving related actions. Both levels assume that the user is not an active driver and can therefore have eyes and mind off the road. This means they will not require driving input devices such as a steering wheel and pedals. Instead, user interaction with Level 4 and 5 CAVs will be through human-machine interface (HMI) dashboards providing vehicle-related (e.g., speed, time/distance to destination, local area information)...

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“…One clear benefit of using a navigation system is that it can allow for decreased exposure to traffic by providing a shorter/faster route (Antin et al, 2009;Feenstra, Hogema, & Vonk, 2008). On the other hand, the fact that navigating has become so easy may also encourage some drivers to go to places that they would not otherwise have visited, thus increasing exposure (Emmerson, Guo, Blythe, Namdeo, & Edwards, 2013). Furthermore, having alternative routes may lead drivers off motorways onto access roads, which reduces safety (SWOV, 2010).…”

Section: Following Route Guidance Instructionsmentioning

confidence: 99%

The use of navigation systems in naturalistic driving

Knapper

Nes

Christoph

et al. 2016

Traffic Injury Prevention

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Objective: In this study we assessed the use of portable navigation systems in everyday driving by applying in-vehicle naturalistic driving.Method: Experienced users of navigation systems, seven female and fourteen male, were provided with a specially equipped vehicle for approximately one month. Their trips were recorded using four cameras, GPS data and other sensor data. The drivers' navigation-system use data were coded from the video recordings, which showed how often and for how long the system was activated and how often and for how long a driver operated the system. Results: The system was activated for 23% of trips, predominantly on longer and unique trips.Analyses of the percentage of time for which the speed limit was exceeded showed no evidence of differences between trips for which the navigation system was used or not used. On trips for which the navigation system was activated, participants spent about 5% of trip time interacting with the device. About 40% of interacting behaviour took place in the first 10% of the trip time, and about 35% took place while the car was standing still or moving at a very low speed, i.e. 0-10 km/h. Conclusion: These results shed light on how and when drivers use navigation systems. They suggest that although drivers regulate their use of such systems to some extent, they often perform risky tasks while driving.

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Fork in the road: In-vehicle navigation systems and older drivers

Cited by 38 publications

References 29 publications

Use, perceptions, and benefits of automotive technologies among aging drivers

Use, perceptions, and benefits of automotive technologies among aging drivers

Exploring the Usability of a Connected Autonomous Vehicle Human Machine Interface Designed for Older Adults

The use of navigation systems in naturalistic driving

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