Drivers Recognize the Importance of Connected Work Zones

We have been talking for the past couple of years about “connected work zones” – that is, the automatic and real-time method of putting our work zones on the digital map that everyone is quickly coming to depend upon when choosing a route.

We have argued that traffic control workers don’t need more to do when they are setting up or tearing down a work zone. So, to arrive at a point where we have timely and accurate reporting of work zones, it must happen automatically.

Several companies are now providing solutions. Those solutions vary in their complexity and technologies involved. But in their simplest form they each include a device attached to existing traffic control devices. One of those is normally the arrow board. The beauty of this approach is that when the arrow board is turned on, the system immediately tells the digital map that a work zone just popped up on that route at that precise location. And when it is turned off, it tells the map that the work zone is now gone. It happens every time a “smart” arrow board is used and those are becoming more and more common.

We all “get” this. But now the driving public is also recognizing the importance of these systems. An article by Tim Harlow in the January 27th Minneapolis Star-Tribune talks about a system supplied by Street Smart Rentals to Minnesota DOT in the Twin Cities.

He points out that the existing 511 system does a good job of informing the public about long-term projects, but that short-term and unplanned closures can cause just as much disruption yet are not included in their warnings to the public.

The system supplied by Mike Granger and Street Smart Rentals is changing that for the better. And with the arrival of autonomous vehicles, this will become even more important. In the article Brian Kary, MnDOT’s Director of Traffic Operations “said the technology is not active now, but it could be this summer or fall. MnDOT is evaluating costs before making it a permanent 511 feature. The agency also is setting up a timeline install the technology and figuring out how best to get information to other traffic information sources, such as Google, Waze and TomTom, since not everybody uses 511.”

We believe economies of scale will quickly and significantly reduce those costs. And the need for this information will bring down any barriers to those traffic information sources. We look forward to hearing more about this system and others like it the exciting year to come.

How Does the Traffic Message Channel Work?

We’ve talked in the past about the need to update the work zone information on digital maps in real time. But how does that process actually work? The answer is surprisingly simple while offering far more detail than you might expect. It is sent over FM radio and satellite channels using RDS-TMC protocols. RDS stands for “radio data system”. TMC stands for “traffic message channel”.

The information is sent in very small packages several times a second within a frequency used for digital identification of the station, song titles, etc. In this way, location codes and event codes are sent without interrupting the audio and updates any navigation devices in very near real time. That information can then be used in calculating the fastest route. It will also recalculate as incidents occur that cause significant delays.

In the United States the digitally coded traffic updates are distributed by Navteq over FM channels and by Sirius/XM satellite radio. iHeartMedia and TeleAtlas also provide commercial services in about 77 US metro areas.

Once received, the codes are automatically displayed in the driver’s preferred language making them more readily understandable and therefore more effective.

Each incident is digitally coded and sent as a TMC message. Each message consists of an event code, location code, expected incident duration, and other pertinent details. The message includes one or more phrases describing the problem. The first portion states the problem and the second portion gives clarification regarding the types of vehicles affected, recommended actions by the motorist, etc.

As you might expect, there are many work zone related messages. In fact, there are more than 150 work zone specific messages as well as many hundreds of messages just focused on queue length, travel delays, and lane closures. The work zone messages get fairly specific: mentioning pavement marking, resurfacing, bridge work, water main work, etc. They even mention temporary signals in one.

There are also many messages about incidents, weather, and special events.

The RDS-TMC system was developed before wide-spread use of GPS. So, they do not use a lat and long to identify the location. Instead location is described in relation to major intersections and points of interest.

As work zone reporting becomes more sophisticated, codes can still be added to provide additional detail such as the lanes that are closed, the length of the closure, expected delays, and more. Only a little more than half of the code capacity has been used so far. So there is plenty of room to grow. And that is important. Because autonomous vehicles will require far more detail. Discussions are already underway regarding what new details must be included and the formatting, etc. for them.

Is There an Ideal Sensor Location?

Are there “perfect” sensor locations? For example, when we deploy a queue warning system, are there sensor locations that will get us better data? Could that data inform us of slowing traffic sooner? Or could it be a better indication of traffic conditions than data from another location would be?

For end-of-queue warning systems we submit that the ideal sensor location is just upstream of where queuing is most likely to begin and, therefore where average speeds vary most.

There are locations like that throughout the work zone. Narrowing of lanes, lane shifts, temporary concrete barrier, bridge falsework and other construction activities affect drivers sense of safety. Anything that negatively affects that feeling of comfort will reduce the 85th percentile speed.

Short on-ramps with reduced merge distance have the same affect. However, if traffic always quickly accommodates those merges and returns to the previous 85th percentile speed, then that is not a perfect location. Only when the geometry in combination with traffic volume results in dynamic queuing does that become a good sensor location for queue warning systems.

The power source is our greatest limiting factor today.  Batteries, solar systems, etc. take up space. They must be located where we can reach them easily for maintenance. For this reason, many sensors are located on message signs and arrow boards where they can draw power from them and even share communications devices.

Arrow boards are placed at the taper. Queuing begins there, of course. But we will only catch speed variance due to conflicts at that merge point. We won’t see if that variance continues upstream.

Message signs are placed in advance of the work to warn of slowing downstream. We should always place one sensor at a point that queuing would reach as a result of a worst-case scenario. And a message sign location may be able to serve both purposes. But we normally want the sensors located where queuing begins and we want the message signs located upstream to warn of that slowing – not located together. If sensors and message signs share the same locations they are likely either too close to the work zone or too far from the source of the queuing to warn traffic before they reach the problem area.

We generally space sensors out every half mile to a mile apart with the understanding that we will learn about any queuing quickly. And that is a good approach. After all, we can’t predict all causes of queuing. But couldn’t we adjust those locations a little one way or the other to catch these obvious causes of slowing a little earlier?

It would be helpful to see research into sensor location. But in the meantime, let’s evaluate our work zones and adjust our sensor locations to monitor the more obvious sources of slowing. Our systems will perform better and improve work zone safety even more than they do today.

Final Report on Every Day Counts 3

USDOT has published their final report on the activities included in Every Day Counts 3. That included the promotion of work zone ITS. We talked about their efforts in past posts (10/27/14 and 12/14/16 ) and applauded both their efforts and the results, but now we can look at the final numbers. Read the report HERE.

When they began in January 2015 there were 7 states that had already made the use of technology to reduce work zone traffic impacts a mainstream practice. 8 more states were in the assessment stage at that time. Bu December of 2016 – just two short years later – 11 included work zone ITS as a mainstream practice and 13 more had moved to the assessment stage – a 37% increase!

More important, those efforts are already bearing fruit. Wisconsin’s initial tests indicate a significant reduction in end-of-queue crashes. They are now working with a university partner to develop a queue warning system decision support tool to help project designers know when to include a system in their jobs.

Illinois DOT has awarded on-call contracts to provide work zone ITS system in three of its districts. They, too have studied the effectiveness of these systems. Once they finalize their research they plan to incorporate that in their future system deployments.

Massachusetts DOT “uses smarter work zone technology applications in all construction work zones that meet a specific impact level and a preset scoring criteria threshold.”

And New Jersey DOT developed scoring criteria for designers to use when determining whether work zone ITS should be included in a project. Work zone ITS was also added to its preliminary engineering checklist as a tool for mitigation of work zone impacts.

Thanks again to FHWA for their foresight and hard work on this. It was just the push states needed to get started in work zone ITS and is sure to save a great many lives in the years to come!

 

A New Approach to Geolocation

In our last post we discussed an interesting discussion on automated vehicles and work zones that took place as part of ATSSA’s Midyear meetings. Another automated vehicle presentation was made during ATSSA’s Sign Committee meeting. Mr. Jamie Retterath of Vergence Automation (https://vergenceautomation.com/ ) began by discussing the relative advantages and disadvantages of different kinds of sensors. He pointed out that no single device works best in all conditions. He suggested a combination of sensors and software is the best way to “see” in all conditions. The car’s software would then choose the sensor image with the most contrast and clarity.

But the most interesting part of his presentation was a way of positioning vehicles anywhere they travel and in any weather conditions. GPS is not accurate enough to guide vehicles by itself. And the geometry of the road changes frequently due to construction, variations in pavement markings, etc.

He called them fiducial signs, meaning points of reference. Even with a foot of snow, these signs would tell vehicles exactly where they were in relation to the road. A series of small signs, perhaps as small as 12” square, would be posted on both sides of the road similar to what’s shown in the photo above.

These signs would be posted in the digital map. Sensors would see the signs and triangulate their position from them. Anytime the road geometry was changed the next vehicles that drove that stretch would recognize the change and would send that data in to change the digital map. It is a simple and relatively inexpensive way to speed the adoption of autonomous vehicles.

We asked about work zones. Mr. Retterath said the first autonomous car to come across a closed lane would see the obstruction and drive around it.  Like other changes it encounters, the vehicle would report the closed lane and it would update the digital map in near real time. The same could be done for lane shifts, crossovers, or other geometric changes.

These signs would improve location accuracy and could help speed the adoption of autonomous vehicles, thus saving many lives. Its just a concept at this point, but it represents yet another clever way of moving Towards Zero Deaths.

 

Automated Vehicle Roundtable Held at ATSSA Midyear Meetings

The American Traffic Safety Services Association (ATSSA) recently concluded their annual Midyear meetings in Williamsburg, Virginia. Their Innovation Council met on August 23rd. But before the meeting began officially, they held a joint round-table discussion with members of the Automotive Safety Council. The ASC represents manufacturers of automotive safety system components including cameras, LIDAR, radar and other sensors.

The ASC led off by presenting a sort of Automotive Sensors 101 class that explained the different technologies, what they do well, and what they don’t do so well. This was a big help to ATSSA members who must design traffic control devices that these sensors will be able to “see” and react to in the very near future.

Cameras used for lane tracking look out about 500 feet on highways with a viewing angle of 40 to as much as 100 degrees. The viewing distance decreases on city streets while the viewing angle increases. As camera technology improves, they plan to hold the lane keeping range to 150m as there is little benefit to extending it. Instead they will widen the field of view to better detect pedestrians, balls rolling into the street, etc.

Cameras currently see black & white (gray scale) and red. White lane markings are much easier for cameras to see than yellow because white has far better contrast.

The ASC maintained (as we do) that digital maps must be updated in real time. Long term work zones are easy enough to include in digital maps. Short term work zones are more of a problem. And chip seals are the worst as they are short term AND include no pavement markings – just chip seal markers.

As we move from level 3 to 4 and 5 automotive system hardware won’t change much. It will probably decrease in price, but that’s all. Rather the system functionality and human-machine language will be the key differentiators. The algorithms used by the vehicle to decide what is important, what is not, and how the vehicle should react will constantly evolve and improve.

The ASC shared their market forecast for growth in the next few years. In 2020 the first level 5 vehicles will be sold. Level 2 (driver assist) vehicles will total about 13 million vehicles. By 2030 more than 90 million vehicles will have at least level 2 automation and level 5 will total nearly 3 million vehicles. But that means less than 5% of all vehicles on the road in 2030 will be level 5.

There are still very different approaches to level 3 automation. At level 3, vehicles will automatically center in their lanes, follow a route and stop when required. But unexpected conditions, such as work zones, causes the vehicle to return control to the driver. Some manufacturers see level 3 as a step toward levels 4 and 5. But others, especially Google, feel level 3 is dangerous and so will not produce cars requiring human control at any time. Level 3 peaks in 2025 at 2 million vehicles then drops as level 4 and 5 vehicles become more popular and available.

The ASC group told us control will be ceded in work zones. But how that will happen is not clear. Still, they agreed with us on the need for sufficient time for the driver to acclimate before having to make important decisions.

Once the ASC concluded their presentation, Scott McCanna of David Evans & Associates made a presentation from our industry perspective and asked several thought-provoking questions about work zones along the way.

When channelizing devices including cones, drums and delineators are used to redefine a lane, will device spacing become important for automated vehicles? Will we need to maintain some minimal spacing to hold CAVs attention? And what happens when one or two cones are knocked down? Will the automated vehicle become disoriented? Or revert to the old lane markings?

It was further suggested than CAV logic should see drums and cones as a higher priority when choosing a direction of travel than existing pavement markings. Drums, cones, etc. should indicate a change…perhaps one that automatically triggers driver control in the case of Level 3 CAVs.

The time went by very quickly and everyone agreed it was a great first step in building better understanding between our two industries. Future meetings are already planned to build on this and plan for our future.

 

FHWA Work Zone Data Initiative

We in the work zone traffic control world and specifically the work zone ITS world have long wrestled with how best to gather and evaluate work zone data. This has been a topic of discussion at conferences, peer-to-peer exchanges, and in DOTs nationwide. These systems are now providing a great deal of data and the FHWA feels it is time we settled on a standard approach to that data. In response, they have launched the Work Zone Data Initiative (WZDI).

The stated goals of the initiative are:

“To develop a recommended practice for managing work zone data.” And to “create a consistent language for communicating information on work zone activity across jurisdictional and organizational boundaries.”

They are working to develop a specification for work zone data that supports DOT efforts throughout the project and also allows some sort of standardized evaluation and comparison once that project is complete. They want the data to become more useful for project planning, for real-time traffic operations, and for post project analytics.

This is something our industry must be involved in. Please let us know if you are. But if you are not, please contact Todd Peterson, FHWA Work Zone Management Team Transportation Specialist to express your interest. His email address is Todd.Peterson@dot.gov .

 

USDOT has also announced a competition on Advancing Innovative Ways to Analyze Crash Data. They point out that most crash data (as well as work zone data) is siloed and made available only on an annual basis. By opening those sources of data up, DOT hopes to take advantage of new tools such as machine learning (see 4/10/17 post) to gain insights on ways we can reduce roadway fatalities.

This effort is not work zone specific, but could result in improvements that our past state and project specific analysis was unable to find.