Rhythm Engineering Blog

The Roomba Principle

By Jesse J. Manning, Vice President of Business Development

I’ve always been the kind of person who hates to do domestic chores – folding laundry, doing the dishes, and especially vacuuming the floor. Don’t ask me why. Maybe it’s because I believe there should be a better way of automating these time-consuming tasks while I work on better and more-interesting things. It’s not that I don’t know where the problems are. I can clearly see when the carpets are dirty or when the sink is full of dishes. I don’t have an issue gathering the data. I have an issue taking action to fix the problem – no time, no interest, and I’m just not that good at it.

Recently, we bought a Roomba at home. We’re quite a team, the Roomba and I. I’ve set it to vacuum the floors every other day at 1:00 pm, and if (through my powers of observation) I determine that the carpets need a little bit more attention, I take a few seconds to tweak the Roomba’s schedule or run it in a particular area. Together, we’ve managed to solve the problem of a dirty house. I collect data and adjust the Roomba to meet my needs, and the Roomba does the heavy lifting: the part I really don’t like to do.

Whether we know it or not, the Roomba Principle applies in so many areas of our everyday lives. In nearly every facet of life, tools have been developed to help us solve problems and free up our time to be more productive.

Given that basic reality, I’ve been somewhat surprised by a recent trend in the traffic industry that promotes investment in observation only. Over the last two years, tools that have been designed to automate data analysis and adjustment of traffic signal timing have been eclipsed by a demand for more and better data-collection systems. Don’t misunderstand: high-resolution data is an incredibly powerful ally in the traffic-signal optimization battle. With it, you can observe efficiencies and inefficiencies down to the smallest details and moments in time. Arrivals on red, arrivals on green, the delay of individual movements – all important data when it comes to better understanding how you can improve your signal timing. But data alone is a half-measure that does not provide the solution.

It’d be like observing my carpets with a microscope. If I collected data that showed 18 dirt particles per square inch within a two-and-a-half foot radius around the front door as compared to eight per square inch in front of the couch, I may know where I need to focus my cleaning efforts. But without my Roomba to follow up, I’m armed with a lot of really interesting yet useless data. My house guests would be less than impressed with reams of data about how dirty my floors are if I didn’t actually clean them.

Since becoming a part of the traffic industry, I’ve heard from hundreds of agencies about the lack of time, lack of staff and lack of resources when it comes to actually fixing signal timing challenges. Those challenges continue, and vendors in the traffic industry owe it to our agency partners to provide consulting, products, and services that matter and actually address their challenges. All the data in the world doesn’t make a corridor flow more efficiently. It won’t ease a frustrated motorist’s mind to know that you’ve got detail to the Nth degree on how poorly your signals are timed. An overabundance of information won’t reduce emissions or improve safety. Data in and of itself is a half-measure, and without the time / staff / resources to take action on the data, traffic industry vendors are doing a disservice to our agency partners by promoting the sizzle and forgetting the steak.

Data is important. We shouldn’t forget it. But we have an obligation to also provide you with the best tools in the industry to fix what the data shows is broken. Keep the solution in mind when deploying your next round of technology upgrades, because knowing your floors are dirty alone won’t solve the problem of cleaning them.

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Large Scale In|Sync Deployments: A View From the Field

By Sawyer Breslow, Sales Engineer

One of my most memorable In|Sync deployments was also the first large scale project I implemented. In October 2014, I flew into the small town of Farmington, NM, about an hour from Four Corners Monument. Our plane was not much bigger than a Volkswagen Beetle. This particular corridor had been selected as a candidate for an In|Sync adaptive system due to its connection to the downtown district, regular traffic influxes from shopping in the eastern section, and heavy weekend traffic generated from nearby Indian reservations.

From an adaptive turn-on standpoint, it went about as smooth as getting through airport security. With the corridor consisting of 11 intersections, me being a bit of a greenhorn and the client only having one technician, the process to free up controllers and turn them adaptive went slower than planned. On our first day of deployment, after about a quarter of the intersections were in adaptive, we broke for lunch at an old-school diner. I had bacon and eggs and we talked about fly fishing – a popular hobby along the San Juan River – and the technician’s interests in rideable miniature model trains.

We were about to get back to it when the skies opened up and it started to pour. This tends to cause a problem with traffic signal cabinets as they consist of mostly electronic components. Luckily the technician had a pop-up tent and we worked undercover for the rest of the deployment. When 4:00 p.m. rolled around, I expected the tech to check-out, mainly because he’d been working since 6:00 a.m. Knowing the importance of the project and being excited for the outcome, the tech opted to stay on until the job was done. So we worked until 8:30 p.m., way past what a normal deployment takes, to finalize the adaptive turn on.

Fast-forward to post deployment when the project is up and running and in support mode.The technician would occasionally call or send an email for support. He always ended each call or email with a show of appreciation for our guidance and for the impact In|Sync had in his community. He’s become a super-fan of In|Sync and witnessed first-hand the dramatic improvement in his corridor, to the point that citizens and city workers call-in to say how easy and stress-free their commutes are.

Ultimately, the working relationship we have with Farmington is what we strive for with all our clients at Rhythm Engineering. When clients experience the benefits first-hand and witness the positive impact In|Sync has on their community, we feel we’ve not just met their expectations, but surpassed them.

To see a third party study on the E. Main St. Corridor in Farmington, NM, navigate to this link and select the independent study by AECOM (Farmington, NM). https://rhythmtraffic.com/resources/library/

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In|Sync Releases Alarm Notifications

Knowing when issues arise at your intersections is an important element in keeping traffic flowing at all times. Our goal in developing In|Sync’s first alarm notification system was to alert our partners of any issues going on at their intersections so they can be corrected quickly.

But we failed to realize two important facts – not all alarms are alike and too many alarms can result in alarm fatigue. Alarm fatigue is a sensory overload where a person is exposed to an excessive number of alarms. It can lead to longer response times, or in the case of the short story “The Boy Who Cried Wolf,” it can lead to ignored life-threatening events. The Cry Wolf syndrome was leading to our partners ignoring all alarms or turning off notifications altogether.

So we analyzed our current alarm notifications and removed ones that did not require corrective action. We also added new notifications that do require corrective action, such as a traffic light not responding. We then prioritized each alarm condition based on the impact the condition would have on the operation of In|Sync at the intersection.

Based on this priority, we designed an alarm recurrence frequency that was custom for each alarm type. For instance, selecting a recurring alarm for minor issues such as stuck ped detectors results in receiving a notification upon the detection of the stuck ped detector, twelve hours after the stuck ped detector was flagged and every 24 hours after until the ped issue is resolved. However, an intersection in flash alarm is a condition that needs immediate attention, so the recurrence level set on this alarm type is:

● Once the alarm is detected
● 15 min later
● 1 hour later
● 2 hours later
● 4 hours later
● 8 hours later
● 12 hours later
● 24 hours later, and ongoing at 24 hours until the alarm is resolved

We also recognized that there were users in the system that just wanted to be alerted of an alarm at the start of the condition and once the condition was resolved. For these type of users, we added the non-recurring alarm option.

Through eliminating unnecessary or confusing alarm notifications and defining a smarter recurring frequency notification system based on severity, In|Sync now ensures that our partners will receive the appropriate alerts at the right frequency.

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“We Ought to Run Government Like a Business!”

By Jesse J. Manning, Vice President of Business Development

How many times have you heard this refrain over the course of the last several decades of political campaigns? In a capitalist society that celebrates the ingenuity of entrepreneurial organizations, political candidates and voters alike have often wondered why we don’t replicate business strategies in our council chambers, our state legislatures and in the White House. It was a common talking point in 2016 when a businessman with no political background won the presidency.

Mostly dependent on your political beliefs, those results have been mixed. But as those of us who have either worked in government or worked with government know, government is not a business. For all the things we can learn from businesses, their processes are all about profit. And, as John Harvey wrote in Forbes in 2012, “not everything that is profitable is of social value and not everything of social value is profitable.”

But what are some of those “profit-driving” factors that could work well for government agencies, particularly in terms of providing new public goods and services? These common business drivers may help your own agency operate with a bit more efficiency:

1. Seek Targeted Customer Feedback

Businesses often survey their customers, either formally or informally. Governments do too; however, the citizen surveys that I’ve come across often attempt to be all-encompassing when it comes to issues. Specific government departments may receive better, more-helpful feedback by lowering the number of recipients and expected responses and targeting specific issues. For example, rather than asking “What’s the number one issue of concern in the City?” ask, “What’s the number one transportation-related issue in the City?”

Answers in general surveys may be overly broad, but a more-targeted survey can help identify specific issues that could be dealt with quickly and inexpensively. For example, if “traffic signal synchronization on Main Street” appears a few times in a targeted survey, traffic engineers have a specific, citizen-identified issue to look into and possibly fix. Such specificity rarely appears in broad surveys, and even if it does, it’s masked by more-generalized answers. Short, targeted surveys make it easier for citizens to respond, as well.

2. Set Timelines

Setting goals and sticking to them is a critical aspect of business success. While it’s hard to imagine governments setting quotas for daily activities or monthly results, project timelines are one area where government accountability could use a kick in the pants. Having sold to governments for over a decade, I’ve seen projects that drift aimlessly for months … and sometimes years … because there was no shared understanding of a project timeline.

When engaging in a project, particularly with multiple stakeholders, set firm timelines up front and hold each other accountable to them. Planning detailed timelines (rather than the simple, and rather meaningless, timelines in most RFPs) can help break up projects into bite-sized chunks that are much more manageable and aren’t as susceptible to delays.

3. Allow in Outside Help

One of the most frustrating aspects of selling to government agencies is being treated with skepticism at best; often, we’re seen as an outright enemy. And I get it: salespeople can be icky, particularly if they don’t understand their products. If they’re pushy, it’s worse. But if you happen to find one who’s willing to educate — not just badmouth his competition or try to woo you with insider gossip and steak dinners — a salesperson can be an ally in actually getting things done.

Staff can save a lot of time if they simply include their vendors in presentations to decision-makers and  have an agreed-upon strategy ahead of time: focus on ROI, educate rather than sell and show a mutually-developed plan for getting the project completed. I’ve found that government staff often believe they need to operate in isolation when it comes to seeking approvals for those projects that may benefit the public. They don’t.


In many ways, government will never operate like a business. But if the goal is to replicate some of the more-efficient functions of a business, there is room for improvement. The three points above focus on streamlining decision-making processes, which seem to be a particular challenge for agencies regardless of location or size. However, if you include citizens in decision-making processes, set firm timelines for implementation of those decisions, and allow those seeking your business to do the heavy lifting, you’ll soon start hearing, “Now
that’s how a government ought to run!”

Rhythm Engineering“We Ought to Run Government Like a Business!”
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The Success of the Kansas City Streetcar

By Ryan Broomfield, Systems Architect

As a resident of downtown Kansas City, Missouri and a Systems Architect at Rhythm Engineering, I am filled with an enormous sense of pride and satisfaction to be making a difference nationally and also locally in my own community.

One of my favorite corridors we have developed technology for is the corridor that serves the Kansas City Streetcar. The Streetcar is a project that has exceeded every projection and has been an instrumental addition to the ongoing revitalization of Kansas City’s downtown. Original estimates of riders were highly ambitious and put daily ridership at 2,700. Incredibly, ridership has beat all expectations and averages over 5,000 per day resulting in numerous expansion initiatives and funding approval for additional cars.

Not only has the Streetcar been successful based on its own projections, it is one of the most successful streetcar projects in the country beating out similar projects with both free ridership and paid fares in cities across the U.S., including Atlanta, Washington D.C. and Seattle.

The system has become a national example to other cities of how a streetcar can be successful and for locals it is a strong source of KC pride. Additionally, the system has earned rave reviews from riders about being clean and well-lit, as well as being the transportation method of choice for downtown entertainment options.

Rhythm Engineering has contributed to this project by being the adaptive provider of choice for the traffic signals located along the Streetcar route. Balancing vehicle, pedestrian and streetcar demand in the heart of a major city’s urban grid is a challenging task for any adaptive system, and In|Sync delivers proven results.  

In|Sync accomplishes this feat by incorporating Transit Signal Priority (TSP) into its core algorithm. Many other TSP solutions take a naive approach and simply extend green intervals, create a forced early return to green, or, in some cases, abandon coordination and go into a transition state. In|Sync works with TSP differently in that we balance TSP demand as another type of important demand, rather than performing a deliberately responsive action.  It also doesn’t abandon coordination to accomplish this goal.

While this approach is less direct, it has resulted in significant improvements for the Streetcar’s travel time since it began public operation in May of 2016. A significant, measured reduction in travel time for the Streetcar was achieved over the baseline operation of In|Sync’s adaptive technology when measured with before/after studies. Here are some travel time studies that were performed on the Streetcar corridor with TSP enabled and without TSP enabled.

Personally, it has been a pleasure to ride the streetcar. I have used it for easy access to cherished Kansas City landmarks, such as Union Station and World War 1 Memorial, all the way down to the historic River Market, where fresh produce can be bought at the Farmers Market. Along the way, there are a variety of wonderful businesses, some old, some new, that benefit from the increased exposure of the streetcar. It’s absolutely worth spending a few days to discover some new favorite haunts, destination spots and storefronts.

Overall, we are all proud at Rhythm Engineering to have been a part of such a successful project and to have delivered on our mission of helping citizens get to their destinations faster and safer. We look forward to contributing to the future expansion and success of the Kansas City Streetcar.

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Autonomous Vehicle Technology – The Future of Traffic Engineering is Happening Now

By Dr. Reggie Chandra, PE

Traffic engineering in the future will be intimately connected to how the cars of the future operate.  We are less than a decade away from seeing this microchip technology, which will equip vehicles to monitor what is happening all around them and act accordingly.

How Did We Get Here?

The Kurzweil Curve reveals the power of technology will keep growing exponentially, according to Ray Kurzweil. His prediction is that by 2050, you will be able to buy a device with the computational capacity of all mankind for the price of a nice refrigerator today.1 Kurzweil continues that within the past 60 years, life in the industrialized world has changed almost beyond recognition except for living memories from the first half of the 20th Century. This pattern will culminate in unimaginable technological progress in the 21st Century, leading to a singularity.1

Singularity is defined as an era in which our intelligence will become increasingly non-biological and trillions of times more powerful than it is today — the dawning of a new civilization that will enable us to transcend our biological limitations and amplify our creativity.2

Already examples exist of this foresight in the car of the future technology. The Wall Street Journal reports that self-driving cars, or the autonomous vehicle, are on the horizon. Widespread embrace of self-driving vehicles could eliminate 90% of all auto accidents in the U.S., prevent up to $190 billion in damages and health-costs annually and save thousands of lives, according to a new report by consulting firm McKinsey & Co, as reported by WSJ. The report, compiled after interviews with dozens of industry officials, also predicts mass adoption of auto-piloted vehicles beginning in about 15 years and initial implementations early next decade.3

According to Reuters, fully autonomous vehicles could make up nearly 10% of global vehicle sales, or about 12 million cars a year, by 2035. The Boston Consulting Group added manufacturers and suppliers are rapidly rolling out new hardware designed to speed adaptation of self-driving systems. Carmakers Mercedes-Benz®, Audi® and BMW® demonstrated vehicles with various autonomous capabilities to show attendees at this year’s Consumer Electronics Show in Las Vegas. Daimler’s chief executive, Dieter Zetsche, and Audi’s chief technology officer, Ulrich Hackenberg, said they expect various autonomous systems to be rolled out in stages over the next five to 10 years.4

Emerging Technologies

Before vehicles begin to drive people around, there are other technologies that are already on the market to help make motorists’ lives easier.

  1. The Waze app:“Helps motorists navigate traffic better. Drivers enter their destination and the app displays several route options, enabling drivers to avoid accidents, traffic jams and roads affected by weather. It will also update the driver on changes in traffic.”6
  2. Traffic Light Assist: “Promises to help motorists make every green light. Using both live and predictive data beamed into the vehicle’s navigation unit via onboard Wi-Fi, local data sources provide information about traffic light patterns. The in-car system uses that data and the motion of the car to predict exactly how long it will be until the green light turns red.  Audi® has been testing this system in Europe as well as in Las Vegas, NV.”7
  3. Mobileye: “Reduces the risks of traffic accidents, thus saving lives. The EyeQ® chip (now in its 3rd generation) performs detailed interpretations of the visual field in order to anticipate possible collisions with other licensed vehicles, pedestrians, animals, debris and other obstacles. The product also detects roadway lanes, road boundaries, and barriers, as well as reads traffic signs and traffic lights. This technology is currently being tested with several carmakers.”8
  4. Cruise System: “Available for installation on your 2012 or newer Audi A4 or S4, although there is a wait list now. The technology, called RP-1, uses a combination of sensors, radar, and cameras to drive the vehicle. Using advanced computer vision and obstacle detection, the RP-1 keeps the car in its lane and a safe distance from vehicles in front of it.”9

The future looks like it is moving toward self-driving vehicle technology through advanced microchip technology. But how does it work?

Autonomous Vehicle Technology

The Google driverless car, now called Waymo, uses an array of detection technologies, including sonar devices, stereo cameras, lasers, and radar, according to an article in Extreme Tech. The light detection ranging (LIDAR) system is at the heart of object detection, according to Google engineers. It’s highly accurate up to a range of 100 meters, and although there is several detection technologies on the car that work at greater distances, they do not have the kind of accuracy that LIDAR can provide. The article states the LIDAR system can rotate 360-degrees and take up to 1.3 million readings per second, making it the most versatile sensor on the car. Mounting it on top of the car ensures its view isn’t obstructed.10

Several carmakers have incorporated various technologies into a functioning autonomous vehicle. In an article titled “The Six Things I Learned From Riding in a Google Self-Driving Car” published in The Oatmeal, the author declares that human beings are terrible drivers with a plentitude of human errors; therefore self-driving cars can eliminate these errors. The Google car is programmed to act like “nervous student driver,” so it takes things slow and deliberate. The writer also notes that the technology, while still a work in progress, is wanted/needed “like…yesterday.”11

Volvo® has announced plans to test 100 self-driving vehicles on city streets by 2017. The development team outlined the “one-of-a-kind” pilot scheme that will see “ordinary people” in self-driving cars in an uncontrolled urban environment.12

Has this technology been tried out in a real world setting? Yes. The University of Michigan has designed a Safety Pilot Model Deployment, which is a scaled-down version of a future in which all vehicles will be connected. The model deployment experiment will discover how well connected vehicle safety technologies and systems work in a real-life environment with real drivers and vehicles. It will test performance, usability, and collect data to better understand the safety benefit of a larger scale deployment.13

According to an article in The MIT Technology Review, some of the results from the University of Michigan study are in. “After studying communication records for those vehicles, National Highway Traffic Safety Administration (NHTSA) researchers concluded that the technology could prevent more than half a million accidents and more than a thousand fatalities in the United States every year. The technology stands to revolutionize the way we drive,” says John Maddox, a program director at the University of Michigan’s Transportation Research Institute.14

Shortly after the Ann Arbor trial ended, the U.S. Department of Transportation announced that it would start drafting rules that could eventually mandate the use of car-to-car communication in new cars, according to the article in The Review. “More than five million crashes occur on U.S. roads alone every year, and more than 30,000 of those are fatal. The prospect of preventing many such accidents will provide significant impetus for networking technology.”14

What’s Next?

This journey began with the rapid growth in microchip technology and the how it will initially impact traffic engineering. Starting with driver-assistance technology currently on the market, to vehicle technology advancements, and finally a real-world scenario that brings of all these functions together, a world with self-driving cars is not that far away. However, as this microchip technology continues to advance, traffic signal technology lags far behind. What can be done to catch the industry up? That is exactly what Rhythm Engineering is working on.

 


 

About the Author

Dr. Reggie Chandra, PE, PTOE spent a large portion of his career as a public traffic engineer focused on optimizing and synchronizing signals. He grew frustrated with the tools available for him to perform his job. Dr. Chandra knew the traffic signal technology had fallen decades behind, creating crowded and unsafe roadways, smog, and wasted time and fuel. He also knew traffic engineers alone didn’t have all the answers.

In 2005, Dr. Chandra set out to find a solution. In February of 2008, his team flipped the switch on an artificially intelligent, digital, adaptive traffic signal system that could optimize signals to automatically adapt to traffic in real time.

Since its launch, In|Sync has become the most widely adopted adaptive traffic control systems in the United States. More U.S. traffic agencies select In|Sync than any other adaptive traffic control system, making it the fastest growing such system in U.S. history. As of January 2015, In|Sync is the solution of choice for more than 1500 intersections in 29 states. Independent studies prove that In|Sync reduces stops by up to 90%, cuts fuel consumption and emissions up to 30%, and even reduces accidents by up to 30%. Dr. Chandra currently serves as the Founder, President and CEO of Rhythm Engineering, LLC. The company has ranked twice on the Inc. 500 list of the fastest growing private companies in the U.S.

Born and raised in India, Dr. Chandra came to the United States with his wife Jenny at the age of 27 to pursue the American dream. He earned a bachelor’s degree in civil engineering, a master’s degree in traffic engineering (Univ. of Florida) and a Ph.D. in organizational leadership (Regent University).

In 2012, Dr. Chandra released his first book, Shades of Green: Why Traffic Signals Frustrate You and What You Can Do to Fix Them. This book explains how traffic signals work and how we can fix the problem of unsynchronized traffic signals.

Dr. Chandra enjoys international travel with his friends and family, and finding ways to give back to society such as making dreams come true for adults facing life-threatening illness via The Dream Foundation, and also supports the Community Services League.

Citations

  1. Kurzweil, Ray (2001, March, 7) The Law of Accelerating Returns http://www.kurzweilai.net/the-law-of-accelerating-returns
  2. Kurzweil, Ray (2006) Viking Press, New York, NY – http://www.kurzweilai.net/the-law-of-accelerating-returns
  3. Ramsey, Mike (2015) published in The Wall Street Journal, Self Driving Cars Could Cut Down on Accidents, Study Says http://www.wsj.com/articles/self-driving-cars-could-cut-down-on-accidents-study-says-1425567905?KEYWORDS=self-driving+cars
  4. Reuters, (2015) published in Fortune, 12 million driverless cars to be on the road by 2035, study says http://fortune.com/2015/01/08/12-million-driverless-cars-to-be-on-the-road-by-2035-study-says/
  5. https://www.waze.com
  6. http://www.autoblog.com/2014/01/09/audi-traffic-light-assist-ces-2014/
  7. http://www.mobileye.com/
  8. http://www.getcruise.com
  9. Whitwam, Ryan (2014) published in Extreme Tech, How Google’s self-driving cars detect and avoid obstacles http://www.extremetech.com/extreme/189486-how-googles-self-driving-cars-detect-and-avoid-obstacles
  10. Inman, Matthew, (2015) published in The Oatmeal, 6 things I learned from driving in a Google Self-driving Car http://theoatmeal.com/blog/google_self_driving_car
  11. Bryant, Ross (2015) published in dezeen magazine, Volvo announced “one–of-a-kind” public tests for self-driving cars http://www.dezeen.com/2015/02/24/volvo-public-testing-self-driving-cars-2017-gothenburg/
  12. http://safetypilot.umtri.umich.edu
  13. Knight, Will (2015) published in Technology Review, Car-to-Car Communication: A simple wireless technology promises to make driving much safer. http://www.technologyreview.com/featuredstory/534981/car-to-car-communication/
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In|Sync’s Dynamic Period Explained

By Lisa Honeyman, Technical Writer

In|Sync 1.6 introduced many improvements that expanded features that were already established in In|Sync 1.4. Dynamic period is one of those features that has been an integral part of In|Sync’s method for proactively serving demand during changing traffic patterns. With In|Sync 1.6, we’ve incorporated feedback regarding In|Sync 1.4’s dynamic period and built an improved solution that responds to changing traffic conditions in a more effective manner.

In|Sync uses dynamic periods to determine when, how and how much a period can change, ensuring that In|Sync can constantly adjust to shifting traffic patterns. It requires that two conditions exist:

  • All intersections have the same period
  • All intersections in a configuration belong in a coordination group

Once these conditions are met, you can enable the dynamic period feature, define limits on how much a period can change and specify a reference intersection where global offsets can be applied. In|Sync then determines whether a change in period is necessary, the type of change and the amount of change by using a three-step approach.

Step 1 – Each intersection evaluates miscellaneous time left in the previous two periods

In|Sync Processors at each intersection evaluate how much miscellaneous time occurred in the previous two periods at the intersection. Miscellaneous time is excess time remaining at the end of the period after all demand for all phases has been served at least once.

  • If an intersection reports that the previous two periods did not have any available time, the intersection initially votes to increase the period.
  • If the previous two periods reported more than 20 seconds of available miscellaneous time, the intersection initially votes to decrease the period.
  • Otherwise, the intersection initially votes to keep the existing period.

 Step 2 – Each intersection compares Maximum Average Vehicle Density against the previous time period

The In|Sync Processor at each intersection then goes further and does the following analysis based on the maximum average vehicle density over the previous time period (dynamic period occupancy):

  • If the initial vote is to increase period length and:
    • Dynamic Period Occupancy is 5% or less, the vote is changed to decrease the period.
    • Dynamic Period Occupancy is greater than 5% and less than 20%, the vote is changed to keep the existing period.
    • Otherwise, the vote remains to increase the period.
  • If the initial vote is to keep the existing period length and:
    • Dynamic Period Occupancy is less than 20%, the vote is changed to decrease the period.
    • Dynamic Period Occupancy is between 20 – 50%, the vote remains to keep the existing period.
    • Otherwise, the vote is changed to increase the period.
  • If the initial vote is to decrease the period length, the vote is to decrease the period.

Step 3 – Collect votes from intersections and determine period change

When dynamic period is enabled, In|Sync designates one intersection within the tunnel to be the decision maker regarding dynamic period changes. This intersection’s In|Sync Processor receives the votes from each intersection and ultimately makes two decisions: the type of period change and how much it should change. This evaluation happens:

  • Once every 60 seconds
  • Only if all processors are online
  • Only if there is not a period change already proposed
  • After two full periods have elapsed since a period change

 Determine period change type

The decision-making intersection changes the dynamic period based on the following criteria:

  • If all processors vote to decrease, then the outcome is to DECREASE
  • If some processors vote to decrease and some processors remain the same, then the outcome is to REMAIN THE SAME
  • If any processor votes to increase, then the outcome is to INCREASE

 Determine period change value

Only the decision-making intersection determines the new period value. This value is based upon the following criteria:

  • If the vote is increase and there has never been a dynamic period change, increase the period by ¼ from the current period.
  • If the vote is increase and the previous dynamic period change was an increase, increase the period by ½ from the current period.
  • If the vote is increase and the previous dynamic period was a decrease, increase the period length by ¼ from the current period.
  • If the vote is decrease and there has never been a dynamic period change, decrease the period by ¼ from the current period.
  • If the vote is decrease and the previous dynamic period change was a decrease, decrease the period by ½ from the current period.
  • If the vote is decrease and the previous dynamic period change was an increase, decrease the period by ¼ from the current period.

After determining the type of period change and how much it should change, the deciding intersection processor sends the new period length to each intersection in the tunnel, which is applied to the next period. This process is continual, meaning that when dynamic period is enabled, In|Sync applies this analysis every period, continually adapting the length of the period to best accommodate current traffic demand.

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Adaptive Detection Cameras: Is it a Smart Traffic Management Choice for Your City?

By Thomas Officer, Technical Coordinator

The Operations Department at Rhythm Engineering has often been asked why we use cameras instead of induction loops in order to recognize vehicle presence for our adaptive traffic control systems, In|Sync. Today I’ll answer that questions.

Learn more about In|Sync’s detection camera options

Many cities use induction loops to provide information on traffic flow in order to adjust traffic signals and improve vehicle movement across corridors. Traffic professionals can all agree that the induction loop system is affective — loops provide valuable information to traffic engineers and professionals at intersections around the world — however, loops aren’t always the best answer.

With many systems, loops provide a limited amount of information because they can only detect vehicles that are directly above them. Often times motorcycles or bicycles who are at the intersection go unnoticed — a problem that is frequently addressed in the traffic industry. And while there are always advancements in the traffic industry that have improved loops over time, another problem comes up: money.

Inductive loops have a very high cost of installation because the loops need to be installed within the roadway — a process that can cost a lot. But it’s more than just money; a large construction project can take up time and disrupt normal traffic for motorists — meaning a community has to deal with the changes and frustrations that come with updating the intersection.

These are just some of the reasons are why traffic professions should consider a shift in detection technology, and it is also why Rhythm Engineering decided to develop other options of adaptive traffic management in the first place. While inductive loops get the job done, cameras could do it better.

In|Sync is Rhythm’s Adaptive Traffic Control System that utilizes the In|Sync Processor with detection cameras in order to respond to actual vehicle demand at the intersection. With high-quality cameras, our algorithm can best detect vehicle presence at any intersection and respond to actual demand at the intersection in real time. (Learn more about In|Sync here).

One major advantage of adaptive cameras over induction loops is that it does not require a civil engineering firm or an outside company to install, unlike with in-road loops. With In|Sync, your city technicians can easily install the cameras in a quick and efficient manner, wire them up to the intersection cabinet and allow the Rhythm Engineering Operations team to configure the cameras. (Learn more about installation and In|Sync deployment here).

Once installed, In|Sync will immediately start responding to real-time traffic flow. The detection system will begin adapting signals in a more efficient and safer manner by recognizing the actual vehicle presence in real time.

Rhythm’s In|Sync cameras are a more intelligent way to decrease congestion while increasing the efficiency of traffic flow. While inductive loops work, the cost of installation and the possibility of missing vehicles are risks that your intersection might not want to take. As you know, we as motorist want to get to point A & B faster, with all green signals and with less traffic jams — all without the hassle of construction. In|Sync makes that happen.

Not only can In|Sync cameras be used to control traffic lights by way of detecting vehicles, but it will also recognize bicycles and motorcycle riders at the intersection stop bar. This technology transmits information over IP addresses to your controller, which allows more effective and advanced traffic control of signal lights.

By using In|Sync in your detection library, you are increasing the amount of information you gather about traffic flow at any particular intersection. In comparison to inductive loops, you can cut installation costs in a major way by allowing your own technicians to install In|Sync. And down the line, Rhythm always provides the support needed to insure that your cameras will work at a superior performance level, that your traffic safety and speeds will increase, and that your citizen complaints with go down.

Rhythm EngineeringAdaptive Detection Cameras: Is it a Smart Traffic Management Choice for Your City?
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In|Sync Transit Signal Priority Functionality

Transit Signal Priority (TSP) is one of the most cost-effective approaches to enhancing the effectiveness and efficiency of transit operations. However, while many TSP implementations have minimal impact on non-transit vehicle travel times, there are cases where TSP deployments have created additional delay for non-transit vehicles. In|Sync’s goal is to actively handle TSP requests to both improve transit travel time efficiency and minimize impact to normal traffic operations. It does this through the use of several priority strategies.

In|Sync supports continuous TSP signals captured through recognized I/O devices. It

does not support TSP devices that produce a pulsating or intermittent signal — but pulsating signals can be converted to a continuous signal within the Priority software.

With In|Sync, traffic professionals can change TSP priority at an intersection based on the goals for the configuration, all because In|Sync treats TSP as another form of demand. It doesn’t cause traditional “transition” scenarios that some TSP solutions generate, and all coordination, early release settings, geometry restrictions, etc. are adhered to while TSP is active.

In addition, In|Sync employs a real-time, active priority strategy in only responding to actual TSP calls from an intersection in order to serve that transit vehicle. It does not support a passive strategy in which signals are adjusted based on pre-defined transit schedules.

TSP at a Local Intersection Level

In|Sync handles TSP on a local intersection level, and not at a global level. This means that if a TSP call is received at one intersection, it doesn’t affect the time along a tunnel across intersections. In|Sync’s behavior is determined by how TSP is configured within In|Sync. When TSP is activated, In|Sync performs a combination of the following behaviors:

  1. Prioritize the currently active TSP phase.

In|Sync serves the phase in which the TSP signal call is received. It does this by prioritizing the sequence or by determining where extra time exists in the period and allowing extra servicing of the phase receiving the TSP call. This feature allows In|Sync to flexibly choose to prioritize the TSP phases with the goal of minimizing impact to other movements.

  1. Extend the currently active TSP phase.

If time in the period and configuration allows for additional service of the TSP phase without impacting other phases, In|Sync automatically extends the currently active TSP phase. This feature allows In|Sync to “hold” the TSP phase longer than originally intended to allow the transit vehicle to get through the intersection.

  1. Create demand on a phase when TSP is active but no vehicle queue exists.

In|Sync brings up the empty movement when no vehicles exist in anticipation of the arrival of the transit vehicle.

  1. Eliminate extensions on non-TSP phases during TSP actuation.

In|Sync schedules time to service other phases at the intersection but does not hold additional time for late arrivals or higher-than-anticipated demand. This promotes an “early return” to green for the TSP phase. In|Sync then determines which phase demands service and serves that phase.

  1. Gap out non-TSP phases during TSP actuation.

In|Sync terminates any active non-TSP phases at the intersection, allowing the system to then determine which phase requires service. This method heavily promotes an “early return” to green for the TSP phase.

In|Sync gives priority to the TSP movement as part of its normal green time allocation. It does not step out of its plan to serve a TSP movement and then struggle to get back in step with other intersections; instead, it stays coordinated throughout the TSP call and service. In normal operating conditions, the In|Sync algorithm chooses which phase pair to serve based on how many vehicles are waiting and how long they have been waiting, where more vehicles and longer wait times equals higher priority. When configuring TSP inputs within In|Sync, you assign the same type of priority of service to each type of TSP signal. In|Sync has four different TSP levels: Off, Low, Medium and High.

OFF:

No special treatment

LOW:

When a TSP signal is received, the phase receiving the TSP signal is extended if it is currently being served and time exists in the configuration. This serves the TSP phase sooner and allocates more time to the phase.

MEDIUM:

When a TSP signal is received, the phase receiving the TSP signal is extended if currently being served and time exists in the configuration. It also stops any other phase from extending beyond its scheduled time during a TSP call. This causes the system to serve other movements faster, cutting them off at their scheduled time, even if additional vehicles are present for that movement.

HIGH:

When a TSP signal is received, the phase receiving the TSP signal is extended if currently being served and time exists in the configuration. It also cuts the scheduled time for other non-TSP phases to the minimum green. This priority stops service on other phases before all demand for that movement is served.

Now that you know how In|Sync’s TSP functionality works, learn more about In|Sync’s additional operating features by visiting the website here. Want to know how In|Sync has changed traffic for other communities around North America? View case studies here.

Rhythm EngineeringIn|Sync Transit Signal Priority Functionality
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What SB 743 Meant for the Traffic Industry

By Justin P. Schlaefli, PE TE PTOE 

On September 27, 2013, the way we look at transportation in California changed. On that date, Governor Jerry Brown signed SB 743 into law, sending shockwaves through the transportation industry — which will be felt for years to come.

SB 743 involves a major change to the CEQA Guidelines requiring the use of Vehicle Miles Traveled (VMT) metrics rather than level of service based metrics for measuring vehicle impacts on transportation facilities. The intent of this change is to reduce reliance on the automobile by encouraging development in “Transit Priority Areas” as well as remove disincentives to infill development and reduce greenhouse gas emissions. While indeed serving critical goals, this change has secondary effects which influence the viability of many roadway improvement projects as well as impacting infrastructure funding mechanisms that California has relied on for decades.

While the Governor’s Office of Planning and Research (OPR) has been engaged in drafting and re-drafting CEQA Guidelines for the past several years, the transportation industry is still catching up. Current versions of the draft guidelines include the following key points:

  • Development within one-half mile of an existing major transit stops may be presumed to have a less than significant transportation impact. This mean development of this type may not be required to fund transportation infrastructure improvements.
  • Transit, bike and pedestrian projects may be presumed to have a less than significant transportation impact making them easier to construct.
  • Induced travel effects of major roadway capacity expansion projects are required to be analyzed meaning that road extensions and widenings may no longer be an infrastructure “improvement” but may have an “impact” under CEQA. This could impact the funding and viability of many infrastructure projects.
  • Safety impacts of road widening projects may be considered significant

As a result of many of these changes, funding and planning for transportation and infrastructure projects must be revised to comply with the new rules and priorities. The transportation industry is already headed in this direction, but important questions remain. Fundamentally, the challenge of the future transportation professional will be how to do more with less. It is unfortunate that the characteristics that often occur in the highest congestion locations also occur in areas which are most impacted by the changes of SB 743.

For example, major transit lines often occur in areas with significant density and congestion. Additionally, infill development typically occurs in areas which are already built-out and often experience congestion. A large part of the funding for local transportation projects has historically come from impact fees driven by the rules of CEQA. With those rules changing, large projects in congested areas could avoid paying these fees or avoid constructing roadway infrastructure. Alternatively, proposed roadway infrastructure could be considered to cause a CEQA impact and therefore be rendered infeasible or have a significantly increased cost.

This leads to the conclusion that we must increase the effectiveness of the existing road system. This must be done in a way that is sensitive to all roadway users. This must also be done in a way that avoids costly projects which lack funding or which induce VMT or cause safety concerns for other modes of transportation.

We must do more with less.

A solution which enhances safety, considers the needs of all roadway users, is cost effective and which avoids major induced VMT is ideal. This means that the transportation professional must be willing to go beyond the “traditional” road improvement projects of the past several decades and must add more tools in the tool box. The successful transportation professional of the future will recognize that creative solutions and funding options will keep residents and stakeholders happy. The shelf life of our existing playbook is about to expire … time for a new set of plays!

 

About the author:

Justin P. Schlaefli, PE TE PTOE is President of Urban Systems Associates, Inc. based in Southern California. He has over 16 years of experience in the transportation industry working for both public and private clients. Questions about SB 743 or transportation solutions which might be the most effective under likely future guidelines, please contact Justin@urbansystems.net

Rhythm EngineeringWhat SB 743 Meant for the Traffic Industry
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