Connected Vehicle Infrastructure University Transportation Center

Connected Motorcycle Crash Warning Interfaces

Final Report

Abstract

Crash warning systems have been deployed in the high-end vehicle market segment for some time and are trickling down to additional motor vehicle industry segments each year. The motorcycle segment, however, has no deployed crash warning system to date. With the active development of next generation crash warning systems based on connected vehicle technologies, this study explored possible interface designs for motorcycle crash warning systems and evaluated their rider acceptance and effectiveness in a connected vehicle context. Four prototype warning interface displays covering three warning mode alternatives (auditory, visual, and haptic) were designed and developed for motorcycles. They were tested on-road with three connected vehicle safety applications – intersection movement assist, forward collision warning, and lane departure warning – which were selected according to the most impactful crash types identified for motorcycles. It showed that a combination of warning modalities was preferred to a single display by 87.2% of participants and combined auditory and haptic displays showed considerable promise for implementation. Auditory display is easily implemented given the adoption rate of in-helmet auditory systems. Its weakness of presenting directional information in this study may be remedied by using simple speech or with the help of haptic design, which performed well at providing such information and was also found to be attractive to riders. The findings revealed both opportunities and challenges of visual displays for motorcycle crash warning systems. More importantly, differences among riders of three major motorcycle types (cruiser, sport, and touring) in terms of riders’ acceptance of a crash warning interface were revealed. Based on the results, recommendations were provided for an appropriate crash warning interface design for motorcycles and riders in a connected vehicle environment.

Highlights

  • CVT-based motorcycle CWS, through its prototype crash warning interface (CWI) and applications, delivered positive impact on participants and was considered beneficial.
  • Combined auditory and haptic displays show considerable promise for implementation.
  • Auditory display using in-helmet headset system was successful in presenting warnings. The presentation of directional information turned out to be a weak point, using speech in addition to various channels may be a good solution.
  • Riders could easily distinguish between the haptic warnings and handlebar vibration. As with visual displays, the haptic design performed well at presenting directional information.
  • Visor-mounted LED light strips were level with eyes which make them hard to be ignored. However, naïve users may look at them when triggered. Moving the strips further apart, deep into the peripheral vision or up to the edge of the visor might discourage riders from looking directly at them and getting distracted.
  • Mirror-mounted LED light strips were good for situations like lane changes when mirrors are more likely to be checked.
  • Environment could influence the performance of CWI, so it would make sense to develop a smarter CWI by adjusting alerts based on environmental measure, such as self-adjusted brightness of visual alerts based on lighting conditions.
  • CWS applications overall received slightly lower scores from sport riders than cruiser and touring riders, who might put more emphasis on riding comfort and safety. Cruiser and touring riders preferred the in-helmet headset over other displays, while sport riders showed no preference.
  • Style and better integration of motorcycle CWSs would help improve their acceptance. Incorporating additional capabilities into protective gear and helmets will likely promote adoption by riders.
  • Findings would not only benefit CVT based motorcycle CWS design, but also traditional CWS design for motorcycles.

Publications

Song, M., McLaughlin, S., & Doerzaph, Z. (2017). An on-road evaluation of connected motorcycle crash warning interface with different motorcycle types. Transportation Research Part C: Emerging Technologies.

Song, M., McLaughlin, S., & Doerzaph, Z. (2016). On-Road Evaluation of Connected Motorcycle Crash Warning Interface. In Transportation Research Board 95th Annual Meeting (No. 16-0776).

Song, M., McLaughlin, S., Doerzaph, Z. Evaluation of Connected Motorcycle Crash Warning Interfaces. Published within the proceedings of the Transportation Research Board 2015 Annual Meeting (Emerging Professionals & Emerging Technologies podium session sponsored by TRB Young Member Council: Evaluation of Connected Motorcycle Crash Warning Interfaces). January 12, 2015.

Presentations

Song, Miao (2016). Crash Warning Systems for Connected Vehicles: Motorcycle Applications. Presented at the Motorcycle Research and Technology Workshop, Fifth International Symposium on Naturalistic Driving Research, August 30-September 1, 2016, Blacksburg, VA

Song, M., McLaughlin, S., Doerzaph, Z. Evaluation of Connected Motorcycle Crash Warning Interfaces. Presented at the Transportation Research Board 2015 Annual Meeting (Emerging Professionals & Emerging Technologies podium session sponsored by TRB Young Member Council: Evaluation of Connected Motorcycle Crash Warning Interfaces). January 12, 2015.

Sponsor Organization

Research and Innovative Technology Administration
University Transportation Centers Program
Department of Transportation
1200 New Jersey Avenue, SE
Washington, DC 20590
USA

UTC Grant Manager

Harwood, Leslie
Phone: 540-231-9530
Email: lharwood@vtti.vt.edu

Performing Organization

Virginia Polytechnic Institute and State University, Blacksburg
Virginia Tech Transportation Institute
3500 Transportation Research Plaza
Blacksburg, Virginia 24061
USA

Research Investigators

Doerzaph, Zac
McLaughlin, Shane

More Information

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