Abstract
Many safety and implementation issues plague the broad deployment of autonomous vehicles. A viable path to address these issues may include borrowing technology and policy design from the air traffic control (ATC) space. Air traffic is currently operating in a mixed human-automation environment made possible through restrictions. Future plans for air traffic systems include full automation, but the inclusion of proactive risk mitigation will be necessary to manage system and human errors to prevent catastrophic incidents. Autonomous vehicles will likely operate in a mixed environment upon initial implementation, but the same type of forward-facing risk assessment, mitigation, and restrictions will be necessary to provide a safe transportation environment. This paper evaluates the adaptation of “critical pairs” from aviation to autonomous vehicles as a proactive risk mitigation tool. The implementation of critical pairs evaluates each vehicle in relation to the others, and, based on feasible errors, determines speed and position adjustments to avoid a collision in the event of such errors. This type of proactive risk assessment would help prevent collisions or other dangerous events by giving the vehicles enough space and time to preemptively react to otherwise unexpected errors. This information can be used to determine if, how, and when errors may occur that would endanger other vehicles and may be a human monitored function in the face of full autonomous driving. This paper also addresses the type of infrastructure and regulation changes, such as dedicated autonomous vehicle roadways, pedestrian infrastructure, and specialized transition areas, that would be needed to support transition into a transportation system that includes autonomous vehicles, and would eventually support a fully autonomous environment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Landry, S.J.: Intensity control: a concept for automated separation assurance safety and function allocation in NextGen. In: AIAA ATIO Conference, Indianapolis, Indiana, USA (2012)
Parasuraman, R., Riley, V.: Humans and automation: use, misuse, disuse, abuse. Hum. Factors J. Hum. Factors Ergon. Soc. 39(2), 230–253 (1997)
Prevot, T., Homola, J., Mercer, J.: Human-in-the-loop evaluation of ground-based automated separation assurance for NextGen. In: Congress of International Council of the Aeronautical Sciences Anchorage, Anchorage, AK (2008)
Surakitbanharn, C.A.: Analyzing critical pair identification as a human-controlled function in air traffic control. In: Industrial Engineering, Purdue University (2017)
Cummings, M., Guerlain, S.: Developing operator capacity estimates for supervisory control of autonomous vehicles. Hum. Factors Ergon. Soc. 49(1), 1–15 (2007)
Fagnant, D.J., Kockelman, K.: Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transp. Res. Part A: Policy Pract. 77, 167–181 (2015)
Carsten, O., et al.: Control task substitution in semiautomated driving: does it matter what aspects are automated? Hum. Factors 54(5), 747–761 (2012)
Radlmayr, J., et al.: How traffic situations and non-driving related tasks affect the take-over quality in highly automated driving. In: Human Factors and Ergonomics Society, Chicago, Illinois (2014)
Gold, C., et al.: “Take over!” How long does it take to get the driver back into the loop? In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Los Angeles, CA. SAGE Publications Sage (2013)
Merat, N., et al.: Transition to manual: driver behaviour when resuming control from a highly automated vehicle. Transp. Res. Part F: Traffic Psychol. Behav. 27, 274–282 (2014)
Metzger, U., Parasuraman, R.: Automation in future air traffic management: effects of decision aid reliability on controller performance and mental workload. Hum. Factors J. Hum. Factors Ergon. Soc. 47(1), 35–49 (2005)
Bonnefon, J.-F., Shariff, A., Rahwan, I.: Autonomous vehicles need experimental ethics: are we ready for utilitarian cars? arXiv preprint arXiv:1510.03346 (2015)
Hubaux, J.-P., Capkun, S., Luo, J.: The security and privacy of smart vehicles. IEEE Secur. Priv. 2(3), 49–55 (2004)
Goodall, N.J.: Machine ethics and automated vehicles. In: Road Vehicle Automation, pp. 93–102. Springer (2014)
Greenblatt, J.B., Shaheen, S.: Automated vehicles, on-demand mobility, and environmental impacts. Curr. Sustainable Renewable Energy Rep. 2(3), 74–81 (2015)
Surakitbanharn, C., Surakitbanharn, C.A., Landry, S.J.: A comparison of an intensity control measure versus dynamic density to capture complexity within a sector. In: 15th AIAA Aviation Technology, Integration, and Operations Conference (2015)
Surakitbanharn, C.A.: Evaluating intensity as a controller function for NextGen scenarios with increased capacity (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Surakitbanharn, C.A. (2018). Designing a Proactive Risk Mitigation Environment for Integrated Autonomous Vehicle and Human Infrastructure. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-73888-8_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73887-1
Online ISBN: 978-3-319-73888-8
eBook Packages: EngineeringEngineering (R0)