Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles

By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles’ deployment, and provide employment. It is becoming clear that fully driverless vehicles will not be able to handle “edge” cases in the near future, suggesting that new methods are needed to monitor remotely driverless vehicles’ safe deployment. While the remote operations concept is not new, a super-human driver is needed to handle sudden, critical events. We envision that the remote operators do not directly drive the vehicles, but provide input on high level tasks such as path-planning, object detection and classification. This can be achieved via input from multiple individuals, coordinated around a task at a moment’s notice. Assuming a 10% penetration rate of driverless vehicles, we show that one remote driver can replace 14,840 human drivers. A comprehensive nationwide interoperability standard and procedure should be established for the remote monitoring and operation of driverless vehicles. The resulting system has potential to be an order of magnitude safer than today’s ground transportation system. We articulate a research and policy roadmap to launch this nationwide system. Additionally, this hybrid human–AI system introduces a new job category, likely a source of employment nationwide.

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Response to Reviewer's Comments
Reviewer #1: "Very interesting paper and very good job. A nationwide remote monitoring system for driverless vehicles are proposed, which could increase safety dramatically, speed these vehicles' deployment, and provide employment. The remote operators do not directly drive the vehicles, but provide input on high level tasks such as path-planning, object detection and classification. No more comments." → Thank you, we appreciate your kind feedback and interest in our work! Reviewer #2: "This is an interesting paper, it is well written and easy to follow. I have the following comments:" (1) "on Page 8, the authors assumed arrival rate is constant. This assumption, in my opinion, is kind of over simple. If we look at the distribution of crashes (assuming that number of crashes and remote drivers needed are proportional), it is not evenly distributed by hour, day (week day vs weekend), as well as other conditions (roadway type, weather, etc.). Taking the fallen tree as an example, significant more remote drivers may be needed under adverse weathers. I encourage the authors discuss it in the paper." → Thank you for raising this point. The study we have conducted here is a peak hour analysis that addresses the highest demand seen daily, thus treating the arrival rate as constant. Of course, it is very well-known that traffic intensities vary across time, so the issue is worth addressing. We have now added an additional subsection to Materials and Methods section that reviews how to extend these staffing calculations to time-varying settings. Some of our authors are researchers in this area, so we are able to make use of their expertise. Moreover, this also demonstrates that our peak hour analysis is justified, as the calculations are quite similar. In fact, these calculations reduce to the previous expressions when one considers the maximum rate across time. It is worth noting that this approach is akin to how we have calculated the time-varying staffing levels in Fig  2. Thank you for this suggestion, we believe this discussion has strengthened the paper.
(2) "Lines 103 to 107 on Page 4, can you further clarify how you come up with the number of 6.25 m disengagements? " → We have now added clarification on how this figure is reached, which is through aggregating the nationwide miles driven by each hour of the day and then converting from miles to disengagements through the product of the peak hour miles and the disengagement rate, which is 11,000 miles per disengagement.
(3) "Minor: first line on Page 10. "Inter-arrival and service distributions" should be "Interarrival and service time distributions?" missing "time"? " → Thank you for catching this, we have now clarified that this distribution refers to the service time specifically.
(4) "One question not related to the work in this paper, but I am curious. How about if the remote driver makes mistakes and "causes" a crash? Should he/she take responsibility? " → This is a great question, and we are very eager to see how it is eventually settled in practice. There are not many precedents we can draw upon, but perhaps air traffic control is again our best analogy. In this case, it seems that both the individual controllers and their employers can be held liable for mistakes. In such settings, it seems that the existence or absence of negligence is established on whether a well-trained expert would have been able to avoid the end result or if indeed it was an egregious error. While there are many differences between these settings, we would expect something similar to hold for autonomous vehicles. Employers may then offer to somewhat shield their remote operator employees from individual liability as a way of recruiting the best talent to the position. Of course, this response is again mostly speculative, as there is not yet a legal precedent for it. Nevertheless, it is fascinating to consider!