The State of the Work Zone ITS Industry – 2018

We just enjoyed the 4th of July holiday. As we sat on the deck consuming bar-b-que and adult beverages we considered the state of the work zone ITS industry. We really have come a long way in the past year and that deserves recognition and a quick look back.

One of the most important and most overlooked recent changes is the blurring of the lines between the permanent ITS infrastructure world and the work zone ITS world. At last month’s ITS America show in Detroit, HERE demonstrated their new ability to incorporate live data feeds from work zones along with their partners including software provider GEWI and work zone ITS supplier iCone.

Waze is also incorporating real-time work zone data feeds in their traffic reporting. Both traffic data providers understand the importance of immediate and accurate work zone reporting and are working internally to make better use of our data.

This blurring is going the other direction as well, as Work Area Protection (formerly ASTI Transportation) now offers the option of including Iteris probe data in work zone travel and delay time calculations.

This blurring of the lines may be more important than we realize. Because it becomes less about us versus them for funding and more about an ITS system that works all of the time – especially in work zones. Work zones have always been an afterthought with ITS practitioners. But that is changing. They now understand that the single largest cause of nonrecurring congestion is work zones. And they are working to address that with their permanent systems.

In a recent article in Better Roads Magazine Frank Zucco of Wanco explained that work zone ITS is now much less expensive. Large, elaborate systems are still available and make sense for multi-year projects with major traffic impacts. But more and more simple systems are now being used for queue detection, trucks entering and dynamic merge applications. And, as Frank points out, those are now very dependable and inexpensive, making them a cost-effective solution for most projects.

Research now validates what we all knew intuitively. Queue detection, in particular, has shown major benefits according to the Texas Transportation Institute and AASHTO. We touched on this milestone two years ago in our post “The State of the Work Zone ITS Industry” published on 4/28/16.

And, lastly, work zone ITS helps facilitate the proliferation of automated and autonomous vehicles. Without real time reporting of work zones, AVs are left to navigate them on their own. And the AV world now understands that. We have become a part of the conversation. At the Automated Vehicle Symposium later this month in San Francisco sessions about work zones will be included for the third year in a row. See #33: “OEM/DOT Dialog on Dedicated Lanes, Work Zones and Shared Data” on July 11th. Autonomous vehicles are a big story that will only get bigger. Funding and research will flow to our industry as a result of these conversations.

As an industry, we aren’t yet to the point where our systems are used everywhere they could help. But we can finally see that light at the end of the tunnel.

FHWA’s National Dialogue on Highway Automation

Many thanks to Brian Watson of the American Traffic Safety Services Association for his recent email regarding the FHWA’s efforts to get road users involved in a discussion of the impacts and issues surrounding automated and autonomous vehicles. This is an important opportunity for those of us in work zone ITS to get involved. For that reason we have reprinted his email here:

I recently attended a webinar on the FHWA’s National Dialogue on Highway Automation. I have attached the link to the recorded session, and a background on the FHWA program below. Please note the five automation focus areas include many of the aspects of our industry. If you have any questions, or would like to get involved please let me know. The next meeting will take place in Detroit at ITS America in two weeks.

https://ops.fhwa.dot.gov/automationdialogue/index.htm

Background

Automated vehicles have the potential to significantly transform the nation’s roadways. They offer potential benefits in safety but also introduce uncertainty for the agencies responsible for the planning, design, construction, operation, and maintenance of the roadway infrastructure. The Federal Highway Administration (FHWA) is initiating a national conversation with partners and stakeholders to better understand the implications of highway automation to facilitate innovation and inform the Agency’s role in this area. This National Dialogue on Highway Automation represents a series of meetings held across the country to facilitate information sharing, identify key issues and prepare the infrastructure and the broader transportation community to safely and efficiently integrate automated vehicles into the road network. Input received during the National Dialogue will help inform national research, policy, and programs and will aid in the development of a national transportation community for automation.

This National Dialogue will engage an expanded set of stakeholders, beyond FHWA’s typical stakeholders, in order to ensure that this issue has broad input. These stakeholders will include but is not limited to original equipment manufacturers (OEMs), technology suppliers, transportation network companies (TNCs), associations, and public-sector partners.

The meetings will be held in different locations across the country, running from June 2018 through the end of 2018. These meetings will be conducted as 1 to 1.5 day events and generally include 100 to 150 participants. These meetings are meant to gather input and information from stakeholders and will include significant interactive components, such as breakout discussions and listening sessions.

Automation Focus Areas

  1. Planning and Policy: This focus area will explore relevant issues for the planning and policy community, such as travel demand changes from automation, land use implications, infrastructure funding, right of way use, transportation systems management and operations, automation legislation/policy and other topics.
  2. Digital Infrastructure and Data: This focus area will center on the data requirements and needs of automated vehicles (e.g., digital work zone maps, road closures, etc.). It will explore the possibility of developing new partnerships and collaboration between public agencies and industry for data sharing and safety.
  3. Freight: This focus area will deal with truck platooning applications and automated truck freight delivery issues. It will cover possible implications on traffic patterns and operations, as well as potential infrastructure considerations.
  4. Operations: This focus area will survey the range of operations challenges from highway automation and initiate a discussion on what further research is necessary to address them. These challenges may include incident management and system inefficiency which may have implications on traffic patterns and roadway capacity.
  5. Multimodal Safety and Infrastructure Design: This focus area will cover infrastructure requirements, standardization, and consistency for automation. It will highlight topics where automation technology developers and public agencies need collaboration to plan for locations where existing roadway infrastructure, road conditions, design features and environments could lead to potential safety hazards.

Autonomous Navigation Challenges, Part 2

In our last post we looked at the current state of the art in autonomous vehicle navigation. Another way in which the problem of navigation in unmapped or incorrectly mapped areas will be overcome is through artificial intelligence. We looked at the potential of this technology in our 4/10/17 post entitled, “Machine Learning and Work Zones”. Michael Reser published an article May 8th in Electronic Design entitled, “How AI Will Help Pave the Way to Autonomous Driving”.

Mr. Reser’s main point is that given the unfathomable quantity of data that must be digested and acted upon by autonomous vehicles (AVs) the technology will progress much faster and more accurately through machine learning. “Translating it all into a real-world challenge for AI-backed autonomous-driving systems, the expected outcome of such massive data processing is nothing short of getting the right answer in the shortest possible time to determine a proper action to avoid a traffic incident.”

“To put it differently, (a) large set of data in combination with realistic scenarios and nonlinear parameter sets enables systems and applications to fail safely and learn faster.”

He goes on to list the many challenges that must also be addressed including how to tie images from multiple sensors with varying resolution quality into one accurate picture. Another was how to validate and tie different data sources together in time. They must have a consistent way of labeling those sources in time.

Mr. Reser goes on to say they are not there yet, but he sees the process as inevitable.

“For true enablement of Level 4 and Level 5 automated driving, the system should be functional in all weather and driving conditions, which is obviously a given requirement. Still, it’s a much bigger challenge than sometimes mentioned and admitted”.

Like most AV challenges, this one has serious implications for work zones. It will be interesting to watch as this process unfolds.

One View of the Current State of the Art in Autonomous Navigation

Much has been written about autonomous vehicles and their methods of navigation. But most of that writing is little more than science fiction. The systems described are usually just concepts that engineers are working toward. What is the current state of the art?

Dyllan Furness posted May 9th about emerging technology in Digital Trends magazine His article, titled “Get lost: MIT’s self-driving car takes on unmarked roads” examined the current capabilities of autonomous vehicles. He found that current AVs are only able to drive on well-mapped city streets. This deficiency would affect autonomous vehicles ability to navigate a work zone as well. As he wrote in his opening lines, “If you find yourself on a country road in a self-driving car, chances are you’re both pretty lost. Today’s most advanced autonomous driving systems rely on maps that have been carefully detailed and characterized in advanced. That means the millions of miles of unpaved roads in the United States are effectively off-limits for autonomous vehicles.”

MIT is working to change that by developing a method of navigating using simple GPS, Google map data and a variety of sensors. ““We were realizing how limited today’s self-driving cars are in terms of where they can actually drive,” Teddy Ort, an MIT CSAIL graduate student who worked on the project, told Digital Trends. “Companies like Google only test in big cities where they’ve labeled the exact positions of things like lanes and stop signs. These same cars wouldn’t have success on roads that are unpaved, unlit, or unreliably marked. This is a problem.””

Certainly, work zones fall into this problem area. And MIT’s new system could address our issues, as well. In particular, by using Google map data this system would also pick up near real-time work zone data like we described in our 9/25/17 post. Then the sensors could identify traffic control devices and follow them safely through the work zone.

It is good to see that at least one organization understands the limits of current technology and is looking for a better, safer way for autonomous vehicles to find their way through rural roads and work zones.

Work Zone Traffic Control “Down-Under”

We just returned from a wonderful trip to Australia where we spoke to the Traffic Management Association of Australia (TMAA) about work zone ITS. Their members were all excited and focused on finding safer, more efficient ways to manage their work zones.

The program was packed full of interesting speakers and a variety of timely topics. They also gave us all just the right amount of time to discuss those topics between sessions. It was very well run.

The attendees seemed to enjoy talking to Americans and all asked what we thought of the meeting. My first answer was always the same: traffic control companies in both countries share the exact same set of problems:

1) Speeding in work zones.

2) End-of-queue crashes.

3) Hiring, training and retaining good employees.

4) A perception by the driving public that we are there to make their lives miserable.

5) Insufficient funding for maintenance and construction.

6) Changing standards and levels of enforcement from one state to the next.

7) Varying commitment and funding levels from one state to the next.

Just like ATSSA, the TMAA brings contractors, manufacturers, academia and government agencies together to discuss these problems and identify solutions. The TMAA does an especially good job of this. We look forward to learning more from them in the years to come!

Data Latency and Work Zone ITS

We met recently with a large local agency to discuss the idea of connected work zones and the concept of reporting work zones in real time to the digital maps we all use to get from Point A to Point B. She was excited about the idea but had concerns about delays that are sometimes experienced between the time when an incident occurs and the time when it is reported to you by your navigation app.

According to Waze, 65 million drivers regularly use their navigation service to get home as quickly and efficiently as possible. Drivers want to know about problems along their routes before they reach them and in time to take another faster route if it makes sense to do so. Richard Russell, a former sales engineer with Google, said five years ago that, “we actually want negative latency, and will perceive anything less as latency.”

That was about the time that Google purchased Waze. Waze works because users report problems in real time thus helping to reduce latency. HERE has found another way to reduce latency. They look at in-vehicle sensors such as hard braking sensors to identify and locate traffic issues the moment they begin. HERE also plans to begin including user reports to get as close to real-time reporting as possible.

Today, work zones are the single largest cause of non-recurring congestion. So, if we could report work zones in real time (see Work Zone Reporting to Autonomous Vehicles – posted 9/25/18) it will make these services even more valuable. Imagine arrow boards equipped with a device to report location and display status every time it is turned on or off!

Yet how will these services process an unimaginable amount of data including location, date & time, type of incident, and some form of verification and get it to the user without at least some delay? That is a problem only Waze or HERE can answer. We can tell you they are working on it.

In the meantime, some small amount of latency (a few seconds to as much as a minute) is going to exist. But the service is still valuable. In today’s worst-case scenario Driver A leaves home and asks for the fastest route to work. The app recommends the best one based on conditions at that time. Perhaps moments earlier an arrow board was turned on when a contractor closed a lane along that route for maintenance work. A short time later the app reports that roadwork and reroutes Driver A along a now preferable route. The app still saves him time, just not quite as much time as it might have with instant knowledge of all work zones.

Zero latency is the goal. But let’s not allow the perfect to be the enemy of good.

USDOT Roundtable on Data for Automated Vehicle Safety

On December 7th of 2017 the USDOT convened an interesting group of stakeholders to discuss automated vehicle data needs. The goal was simply to better understand what will be needed, so we can all work in that same direction. Attendees included automakers, regulators, local agencies, privacy advocates, data aggregators including Waze and HERE, universities, and industry.

They have published a short document detailing their findings. Download “roundtable-data-automated-vehicle-safety-report[3585]” here.

A set of four principles was discussed and supported by the group. Those included

  • Promote best practices for data security and privacy.
  • Act as a facilitator to promote voluntary data exchanges.
  • Start out small to find what works and then build on that.
  • Coordinate across modes to save time and money.

Number 2 is perhaps the most problematic. Vehicle and component manufacturers are still playing their cards very close to their vests. They will continue to protect whatever competitive advantage they feel they have. They don’t mind sharing what everyone else is sharing but don’t want to go beyond that point for obvious reasons. So, what will be shared will start with basics such as crash data, AV hours driven, etc. and will grow from there.

The good news, for our purposes here, is the discussion of high priority use cases. #1 on the list is “Monitoring Planned and Unplanned Work Zones”. The data they felt was of the highest value included, “Work zone locations, planned duration of project, updates, planned lane closures, changes in signing, directions, or parking.”

Other encouraging use cases include #2 “Providing Real-Time Road Conditions”. There they discuss the need for data on detours and missing or deficient signs and pavement markings.

Under testing discussions, there was an emphasis on safety-critical scenarios which would have to include work zones. Clearly manufacturers must test not just in ideal conditions, but in all conditions including bad weather, poorly delineated work zones, and in and around major and minor incidents.

They coined the term “Edge Cases” which refer to a “problem or situation that occurs only at the extreme operating parameter.” Certainly, most testing today will continue at or below 35 MPH on a sunny day and under controlled conditions. But once we are all satisfied that AVs can drive safety in ideal conditions, it will be time for the worst-case scenarios. Again, work zones will surely be a part of that.

The last use case of interest was improving roadway inventories. The group felt high-value data for this effort included,””edge-to-edge”, high-definition map elements (e.g., signs and signals, curbs, pavement markings, tolls, express lanes, bridge heights and weight capacities, highway dividers, overpasses, pedestrian areas, bicycle lanes, taxi drop-off zones, (and) quality metrics.”

Under “proposed federal roles” they talk about the USDOT acting as a facilitator of sharing and discussions between the various stakeholders. It’s good to know work zones are now a part of that discussion. Thank you to USDOT for helping make that happen. Our greatest fear just a few short years ago was that the automotive industry would get too far down the road with their development to accommodate special circumstances including work zones, special events and incident response. It’s great to see that won’t be the case.