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Experiences of Advanced Driver Assistance Systems Amongst Older Drivers Experiences of Advanced Driver Assistance Systems amongst Older Drivers An evidence review for the Department for Transport Contributors: Helen Burridge, Sarah Edwards, Amy Guo, Caroline Luxton-White, Molly Mayer, Sal Mohammed, Daniel Phillips, Emma Sayers, Ian Shergold, Arnaud Vaganay (editor) Date: 6 February 2020 PreparedThis report for:has beenDepartment produced for by Transport NatCen Social Research under contract with the Department for Transport. Any views expressed in it are not necessarily those of the Department for Transport. At NatCen Social Research we believe that social research has the power to make life better. By really understanding the complexity of people’s lives and what they think about the issues that affect them, we give the public a powerful and influential role in shaping decisions and services that can make a difference to everyone. And as an independent, not for profit organisation we’re able to put all our time and energy into delivering social research that works for society. NatCen Social Research 35 Northampton Square London EC1V 0AX T 020 7250 1866 www.natcen.ac.uk A Company Limited by Guarantee Registered in England No.4392418. A Charity registered in England and Wales (1091768) and Scotland (SC038454) This project was carried out in compliance with ISO20252 Contributors Based on the CRediT taxonomy.1 Role Contributor Conceptualization Daniel Phillips, Arnaud Vaganay Data curation Caroline Luxton-White, Molly Mayer, Emma Sayers, Arnaud Vaganay Analysis Helen Burridge, Sarah Edwards, Caroline Luxton-White, Molly Mayer, Sal Mohammed, Emma Sayers Funding acquisition Daniel Phillips Investigation Caroline Luxton-White, Molly Mayer, Emma Sayers Methodology Arnaud Vaganay, Daniel Phillips Project administration Daniel Phillips, Arnaud Vaganay, Molly Mayer Resources Not applicable Software Not applicable Supervision Arnaud Vaganay Validation Amy Guo, Ian Shergold, Arnaud Vaganay Visualization Helen Burridge, Molly Mayer Writing-original draft Sarah Edwards, Molly Mayer, Arnaud Vaganay Writing-review & editing Helen Burridge, Molly Mayer, Ian Shergold, Arnaud Vaganay Acknowledgements: The authors would like to thank Catherine Davie, Claudia Senese, and Helena Titheridge, members of the Department for Transport advisory group for providing guidance on the requirements and scope of this project. Contact author: Arnaud Vaganay, [email protected] 1 CRediT is a taxonomy, developed by Casrai (Consortia Advancing Standards in Research Administration Information), that includes 14 roles used to present the contributors to scholarly output. It aims to more accurately represent the range of contributions researchers make to a report. https://casrai.org/credit/ NatCen Social Research | Experiences of Advanced Driver Assistance Systems i amongst Older Drivers Contents 1 Introduction ................................................................. 8 1.1 Background ............................................................................................. 8 1.2 Why this evidence review is needed ....................................................... 8 1.3 Research questions ................................................................................ 9 1.4 Study objectives and potential implications ............................................. 9 2 Methodology .............................................................. 10 2.1 Overview ............................................................................................... 10 2.2 The methodological process ................................................................. 10 3 Results ...................................................................... 13 3.1 Overview of the included studies .......................................................... 13 4 Findings ..................................................................... 16 4.1 Awareness of ADAS ............................................................................. 16 4.2 Ownership of ADAS .............................................................................. 17 4.3 Experience with ADAS .......................................................................... 18 4.4 Learning to use ADAS .......................................................................... 19 4.5 Frequency of use of ADAS and changes in driving behaviour .............. 20 4.6 Perceptions and opinions of ADAS ....................................................... 21 5 Discussion and conclusion ........................................ 32 5.1 Emerging themes .................................................................................. 32 5.2 Limitations ............................................................................................. 34 5.3 Conclusion ........................................................................................... 35 6 References ................................................................ 36 6.1 Background literature ............................................................................ 36 6.2 Included studies .................................................................................... 37 Tables Table 3:1 Age threshold and country used in each study ...................................... 14 Table 4:1 Awareness of ADAS by age in England ................................................ 17 Table 4:2 Use of ADAS by age in England* ........................................................... 19 Table 4:3 Perceived utility of different types of ADAS ............................................ 27 Figures Figure 3:1 Study methods of included studies ........................................................ 13 NatCen Social Research | Experiences of Advanced Driver Assistance Systems 1 amongst Older Drivers Glossary Advanced Driver Assistance Systems (ADAS) can be classified as automatic systems, warning systems, information systems, and hands-free devices. The following glossary provides a list and definition of all ADAS covered in this review, grouped by type of system. Automatic systems Technologies that automatically respond to driving conditions with little or no input required from the driver. Technology Definition Alternative name Adaptive Automatically change the direction of the Adaptive light headlights light beam when steering left or right on control curved roads. Adaptive Cruise Automatically adjusts the vehicle speed to Intelligent speed Control (ACC) maintain a constant gap between the adaption systems; vehicle and the vehicle ahead. automatic cruise control Automatic Automatically manoeuvres vehicle into a Parking assist; parking parking space to perform parallel, self-parking perpendicular, or angle parking. Typically system; semi- requires some driver input. automated parking assist Automatic Automatically activates when rain is windscreen detected. wipers Autonomous Monitors traffic conditions in the vehicle’s Automatic braking; Emergency path and provides a visual or auditory automatic braking system warning. Automatically brakes if no action is emergency taken by the driver. braking; emergency braking ECall Dials emergency services (either 999 or Automotive 112) after a collision or accident emergency response system; Emergency response system Lane Keep Detects when the vehicle is moving out of a Automatic lane Assist lane and provides a visual, auditory or maintain; lane vibration warnings. If no action is taken by assist; LKA the driver, steps are automatically taken to ensure the vehicle stays in its lane. Intersection Monitors oncoming traffic at a road junction Intersection crossing assist or across the opposite driving lane. If the navigation; right gap is too small to permit a turn, activates a turn assist visual or auditory warning and prevents the vehicle from moving. Traffic jam A form of ACC that estimates the distance Traffic jam assist of the vehicle from other vehicles and assistant maintains distance by accelerating or 2 NatCen Social Research | Experiences of Advanced Driver Assistance Systems amongst Older Drivers decelerating whilst the vehicle is in a traffic jam. Warning systems Technologies that provide warnings to drivers about driving conditions in the form of visual or auditory signals or vibrations. Technology Definition Alternative name Blind spot Detects vehicles in the driver’s blind spot Blind spot monitor; detection and provides a visual, auditory or vibration blind spot warning; warning. side view assist lane change assist Cross Traffic Detects traffic behind the vehicle and Detection provides a visual or auditory warning. System Fatigue alerts Detects driver drowsiness and fatigue and provides a visual or auditory warning. Forward Detects slower moving or stationary objects Collision collision in the path of the vehicle and provides avoidance warning auditory warnings to prevent or reduce the systems severity of collision. Lane Departure Detects when the vehicle is moving out of a Warning (LDW) lane and provides a visual, auditory or haptic warning. Parking sensor Detects and alerts drivers when there is a Backing aids; danger of collision with a pedestrian, animal reverse assist or other object when the vehicle is reversing. Pedestrian Detects and alerts drivers when there is a detection danger of collision with a pedestrian, animal sensors or other object whilst moving forward. Information systems Technologies that provide information to drivers regarding the vehicle and driving conditions. Technology Definition Alternative name In-vehicle Connects driver with a person who can
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