FHWA Request for Information Regarding Automated Driving Systems

This blog just posted a couple of days ago, but this topic can’t wait, so we are posting again today. On January 18th the Federal Register published a Request For Information from FHWA regarding automated driving systems (ADS). It asks DOT’s, manufacturers, trade associations, and other interested parties for their answers to questions in ten specific areas.  Download Docket FHWA-2017-0049. All comments must be received by March 5th, so please get started.

The work zone ITS world should be most interested in questions 4, 5, 9 and 10. You will also be interested in many of the other questions if you are involved in static signs, pavement marking or other permanent roadway safety infrastructure.

First, let’s commend the FHWA for asking these questions. It wasn’t long ago that we worried that automakers and regulating agencies did not know what they did not know. A great deal of time and effort has gone into building coalitions with these folks and it appears that is beginning to pay off.

So lets’ reward their curiosity with well written and timely responses. You can do so individually and/or through your industry associations such as the American Traffic Safety Services Association.

We will start the ball rolling now with these suggested responses to the four questions mentioned earlier. These are short in the interest of time, but should be fleshed out in any formal response.

Question 4: How should FHWA engage with industry and automation technology developers to understand potential infrastructure requirements?

Include work zone ITS providers and trade associations like ATSSA in the conversation. Many of us are already participating in AV events including the Automated Vehicles Symposium, the ITS World Congress, etc. Presentations at these events focused on work zones have lead to many productive conversations and several “ah-ha” moments for AV manufacturers. Please encourage more of this going forward.

Question 5: What is the role of digital infrastructure and data in enabling needed information exchange between ADS and roadside infrastructure?

Work zones will be the most common anomaly in digital maps unless we begin preparing now. Arrow boards, flagger stations, and other active work zones can be equipped to report their location and other pertinent information automatically and in real time. The same could be done for emergency responders and special events. Only by doing so can we hope to prevent crashes like the one reported January 23rd  ( Mercury News ). Safety is the driving force behind this initiative, but it will also reduce drive times, reduce air pollution, and improve the efficiency of our road networks.

Question 9: What variable information or data would ADS benefit from obtaining and how should that data be best obtained?

Work zones are the single most frequent cause of non-recurring congestion. Clearly real-time work zone data should be included. This data must include the precise location of the work zone, when and where lanes are closed and when they are opened up again, where flagging operations are taking place, and any other important features of the traffic control including lane splits, narrow lanes, crossovers, and full closures and detours. Finally delay times should also be included whenever available.

Question 10: What issues do road owners and operators need to consider in terms of infrastructure modifications and traffic operations as they encounter a mixed vehicle fleet during the transition period to a potentially fully automated fleet?

It is estimated that it will take at least 20 years to reach a point where the vast majority of vehicles are highly automated. Until then work zones will be just as dangerous for conventional vehicles as they are now. Don’t scrimp on traffic control devices, signage or pavement markings in the hopes that they won’t be needed.

As for those automated vehicles, most will not be capable of navigating autonomously though an active work zone. Plan to trigger the vehicles to hand over control to the driver well in advance of the work zone. Studies show drivers need a minimum of 8 to 10 seconds to regain situational awareness.

Work zones, incident response, and special events will test these systems more than anything else. Make them a big part of the conversation now to avoid problems in the not too distant future!

Caltrans QuickMap to Add Waze Data


Caltrans recently announced changes to their popular QuickMap travel app. The app is available online at http://quickmap.dot.ca.gov/ and from your app store for both Apple and Android. In QuickMap users choose what they want to see, and the area they are interested in seeing, and a custom map shows them exactly that and no more. Travel times and factors affecting travel times such as work zones, weather and other incidents are all displayed in near real time.

They have now added an option to see Waze data. This is significant to those of us interested in work zone ITS because Waze displays iCone sensor data as work zone locations. For example, Road-Tech currently has an iCone system on SR99 in Fresno and the work zone is displayed in QuickMap with an icon of a worker in a hard hat:

Eventually these icons when clicked on will display detailed travel speeds and other pertinent information. That data will help drivers avoid delays and better plan their routes. And in Waze, drivers can add their own information on work zones, crashes and other incidents.

QuickMap is testing the next mobile version in which users can input their own Waze markers directly from QuickMap. It will be one more way to get real-time work zone information to the people that need it most!

Google Maps are Wrong!

At any given time, perhaps 5% of Google Maps data is wrong. And the reason is simple. Construction traffic control requires contractors to close lanes, redirect traffic into oncoming lanes, or close roads altogether until the work has been completed. Those closures are reported to state and local agencies. And those reports are picked up by Google and other traffic data aggregators. But they are often wrong or out of date.

In most states, contractors are required to request permission to close a lane. That request must be made well in advance of the date on which they wish to close the lane, 7 to 10 days on average. By the time that day comes long, construction delays, weather, and other issues often postpone the work and the lane closure does not take place.

Contractors also often make several requests so they will have a multi-day window in which they can perform the work. The days they don’t work are called ghost closures. Some states have moved to eliminate ghost closures by requiring contractors to call the local traffic management center when the lane is taken and again when it is opened back up. This certainly helps, but it does not eliminate the problem altogether.

To make matters worse, many closures are never reported at all. Utility companies are notorious for closing lanes without permission. They reason that they are only there for a short time and so won’t affect traffic all that much. But as traffic becomes more dependent on accurate travel time and route information, any disruption causes problems, and may even be dangerous.

Incident response closes lanes; school crossing guards stop traffic; special events close roads and reroute traffic; flooding, fires and other environmental events also result in route closures and restrictions.

This is an important point of discussion in the automated/autonomous vehicle world, too. If autonomous vehicles depend on historic GPS data to plan and drive a route, they will run into unexpected construction. So they must decide how they will adapt to changes in geometry, in the number and location of lanes, and much more. And delays resulting from these closed lanes and detours should be measured and included in any travel time algorithms.

It is worth noting that the folks in the traffic data companies know of the problem but they can’t solve it on their own. Industry is beginning to fill this need. Arrow boards and flagger stop/slow paddles are being reinvented to become “smart devices”. They report in automatically when work begins and ends. And they also report their precise location. As the work moves, that is reported as well, so map data for work zones can now be reported in real time.

Much work remains to be done. But the solution to this problem is clear. The closures must be reported in real time from the field. And that includes any changes in geometry when lanes are temporarily shifted in one direction or another. Highway construction, incident response and special events all experience unexpected changes on a daily and often hourly basis. Maps must reflect those changes if our system is to be as safe and efficient as possible.

Improving the Effectiveness of Smart Work Zone Technologies, Part 2

illinoisstudyIn our last post we discussed a brilliant new paper published in November by the Illinois Center for Transportation Studies. Today let’s look at their conclusions regarding work zone travel time systems. The writers point out that, “Two critical components for the success of a smart work zone deployment are the quality of the traffic data collected by sensor networks and the algorithms used for data processing.” We examined sensor types last time. Today we look at algorithms

They conclude that, “The travel time estimation is consistently poor for all algorithms and sensor networks investigated in this study. The main reason is that the instantaneous travel time calculation is a poor estimator of the true travel time in a dynamic traffic environment. In addition, the use of Bluetooth sensors can only provide the travel time of vehicles that just exited the work zone. Consequently, the travel time estimation even using Bluetooth sensors is not likely to improve the accuracy of the travel time estimates when the traffic conditions are quickly changing.”

This makes perfect sense. In a work zone you are more likely to see frequent and dynamic queuing. And that is the kryptonite for every algorithm superman. It’s too bad, because we would all like to see accurate travel time estimates, especially for work zones with significant impacts. But, ironically, it is those impacts that make estimation so difficult.

They also discussed the potential use of more advanced algorithms. This is a subject for which I have only a very limited understanding. So I am not able to examine the relative advantages and disadvantages of popular methods. But for work zones, they really aren’t practical anyway. Unless it is a very long term project, one lasting several years, the work required ahead of time to test and adjust the algorithms is expensive and still won’t make much of a difference in the travel time accuracy.

As an industry, we have worked for years to make our systems faster and easier to set up. This, to my mind, would be moving backwards. Instead, let’s work to make our travel time estimates more useful to travelers. Perhaps it makes more sense to talk about delay times. Drivers seem to expect predicted travel times to match their experience perfectly. But when it comes to delay times, they are more likely to be relieved when the delay they encounter is slightly less than predicted.