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U.S. Department of Transportation U.S. Department of Transportation Icon United States Department of Transportation United States Department of Transportation

Public Roads - Summer 2020

Date:
Summer 2020
Issue No:
Vol. 84 No. 2
Publication Number:
FHWA-HRT-20-004
Table of Contents

Everybody Wins

by Craig Thor and Sarah Cigas

FHWA's Small Business Innovation Research Program is spurring market-ready innovations to address transportation challenges.

As part of its mission to enable and empower the strengthening of a world-class highway system that promotes safety, mobility, and economic growth, while enhancing the quality of life of all Americans, the Federal Highway Administration seeks out innovative solutions and technologies to address transportation challenges. However, FHWA often faces difficulties when trying to move potentially innovative solutions from laboratory testing and pilot studies to full market deployment. This challenge to deployment exists across all Federal agencies with large research programs.

 

FHWA's SBIR Program helps develop market-ready solutions from small businesses to address critical transportation issues.

 

In 1982, Congress passed the Small Business Innovation Development Act to encourage the initiative of the private sector and to use small businesses as effectively as possible in meeting Federal research and development objectives. The legislation, which has been reauthorized many times, created the Small Business Innovation Research (SBIR) program. SBIR requires Federal agencies with large research, development, and technology (RD&T) budgets to reserve a portion of those funds for awards to small business, encouraging domestic small businesses to engage in research and development addressing high-priority research areas.

The mission of the SBIR program is to support scientific excellence and technological innovation through the investment of Federal research funds in addressing the Nation's critical priorities to build a strong national economy. FHWA's SBIR program, which is part of the larger U.S. Department of Transportation program, favors research that has the potential for commercialization through products and applications sold to the private sector transportation industry, State departments of transportation, USDOT, or other Federal agencies.

 

 

SBIR at FHWA

The SBIR Program is structured in three phases. The objective of phase I is to establish the technical merit, feasibility, and commercial potential of the proposed RD&T efforts. After successful completion of a phase I contract, awardees are eligible to submit a proposal for phase II, which looks to further advance and commercialize the project technologies. Funding for phase II is based on the results achieved in phase I and the scientific and technical merit and commercial potential of the project as proposed for phase II. Furthermore, a phase IIB option is available for particularly promising phase II projects that need additional funding to meet their development or commercialization potential. Although rarely used by FHWA, a phase III contract, which does not include additional Federal funding, may also be awarded to pursue commercialization using objectives resulting from the phase I and II RD&T activities.

Given the specific focus on developing a commercially viable and market-ready product, not all RD&T activities or goals are a good fit under the SBIR program.

"However, in the cases where there is a relevant topic and promising approach from a small business, FHWA has found the SBIR program to be a great option for advancing technologies and making problem-solving innovations available to the end user," says Dr. Kelly Regal, Associate Administrator, FHWA Office of Research Development and Technology. "Of course, the small business benefits from the ability to pursue a good idea through Federal seed funding and, if successful, the sale of their innovative products and solutions. This creates a win-win-win opportunity for the Federal Government, the small business, and the traveling public."

FHWA invests in the SBIR program through a set-aside of extramural research funding, including funding provided by the Intelligent Transportation System Joint Program Office. FHWA typically funds two to four new SBIR phase I projects annually covering a range of strategic topics. The topics may be submitted by FHWA staff or the public. FHWA evaluates all topic proposals to identify those that will advance research that supports the USDOT strategic goals and that would be best addressed through a market-ready product. After phase I, which usually lasts about 6 months and offers up to $150,000 in funding, the small business may submit a proposal for a phase II project. A phase II project typically lasts 2 years and can receive up to $1 million in funding. An optional phase IIB may also be funded for another 2 years with up to $1 million in funding.

As with all research endeavors, not all paths lead to new innovations. However, the SBIR program can provide a unique opportunity for success. It provides FHWA with a method of investing in specific innovations that can best address a strategic need. Additionally, SBIR gives creative and ambitious small businesses a chance to get a foot in the door and compete in a crowded marketplace. The small businesses also benefit from commercialization consultant services that are offered by the SBIR program, an area in which many small businesses may have very little experience. Finally, the intrinsic motivation of the small business is to produce a market-ready product that can be sold for a future profit. This blend of incentives, services, and opportunity is not typically available through more traditional FHWA RD&T funding approaches.

"Ultimately," says Dr. Regal, "The FHWA SBIR program has proven to be a worthwhile investment with unique advantages for the Government, the small business community, and the traveling public."

Artificial Intelligence in TMCs

A transportation management center (TMC) is the hub or nerve center of most freeway management systems. Traffic and transportation data are collected and processed, fused with other operational and control data, synthesized to produce information, and distributed to stakeholders such as the media, other agencies, and the traveling public.

The role of a TMC often goes beyond the roadway network and the particular responsible agency, functioning as the key technical and institutional hub to bring together the various jurisdictions, modal interests, and service providers to focus on the common goal of optimizing the performance of the entire surface transportation system. Because of a TMC's critical role in the successful operation of a freeway management system—and perhaps the broader surface transportation network—it is essential that the TMC be planned for, designed, commissioned, and maintained to enable operators and other practitioners to control and manage the functional elements of the freeway management system, and possibly beyond.

 

Advances in artificial intelligence and machine learning offer opportunities to address transportation challenges.

 

While TMCs are critical to the operation of the current driving environment, changes are on the horizon. The introduction of connected and automated vehicles as well as smart sensors will increase the amount of data that are available for TMCs to process. This data will be available on a larger scale and with greater speed than ever before—to the point where humans will not be able to keep up.

However, new advances in artificial intelligence (AI) may present a unique opportunity to address some of these challenges and enhance the efficiency of freeway operations. AI can be used to automate TMC operations and can "learn" to better optimize the flow of traffic. In the near term, this may provide substantial benefits as more connected and automated vehicles and new smart data sources enter the highway environment.

In February 1996, IBM's Deep Blue computer made history when it defeated the reigning world champion, Garry Kasparov, in a game of chess. While others were also working on similar technologies, this demonstrated to the world that computers would soon be able to solve complex and evolving problems at a level that surpassed human capabilities. More recently, Google's AlphaGo beat world-champion Lee Sedol at the game Go, further demonstrating the abilities that computers have to solve increasingly difficult problems and scenarios.

Successes like these inspired FHWA to consider what the possibilities may be for highway applications. Like playing a game of chess or Go, TMCs must respond to changes in the environment and decide what the next move is. Additionally, much like a chess grandmaster, the TMC must also look ahead to see what the possible down-field effects of those actions are and analyze a set of possibilities to find the optimal solution.

"The highway environment will make the first 'move,' " says FHWA research Dr. Peter Huang, "And it is the role of the TMC to decide what the counter-move will be and predict how the environment will respond with future moves."

For example, if there is a crash on a stretch of interstate, the TMC must decide if vehicles should be routed onto local streets. However, in order to avoid further complications on those roads, a TMC will need to consider whether to make other moves as well, such as adjusting signal timing or ramp metering. Each of these moves has its own corresponding outcomes and tradeoffs, all of which must be analyzed by the TMC. In a traditional TMC environment, digesting this amount of information in a short period of time can be difficult or impossible. However, as shown by systems such as Deep Blue or AlphaGo, computers—specifically AI and machine learning—present a unique opportunity to find the right move.

 

Traffic management centers like this one in California are the nerve centers of highway management.

 

 

Technology company Intelligent Automation, Inc. (IAI), working with the Delaware Department of Transportation (DelDOT), piloted the Artificial Intelligence Traffic Operations and Management System (AI-TOMS) on a 10-mile (16-kilometer) section of I–95 and surrounding arterials in northern Delaware. The system relies on real-time data from thousands of sensors on the highway and at intersections. Using the existing TMC operations systems, AI-TOMS analyzes the incoming data from vehicle detection radar systems, traffic loop detectors, and other smart infrastructure sensors to make operational recommendations to staff operating the center. Additionally, because AI-TOMS is a learning tool, it tracks the incoming data and resulting operational outcomes to continually enhance its understanding of how the myriad inputs may affect the eventual outcome. Over time, this enables the system to become smarter, resulting in better performance and enhanced safety within the corridor.

The Intersection Dilemma Zone

A second collaborative SBIR effort between IAI and DelDOT also relies on AI, but addresses a challenge at intersections. Drivers often face a predicament when a stoplight suddenly turns yellow, requiring either an abrupt stop or a rapid acceleration through the intersection. This is known as the dilemma zone. In this situation, a vehicle may not have adequate breaking distance to safely stop nor sufficient time to safely proceed through the intersection before the light turns red. The dilemma zone has been a common cause of rear-end and side-impact crashes at high-speed intersections.

To address this issue, existing technologies use two approaches: controlling traffic light phases and providing warnings to drivers to prepare to stop. In the first approach, green light phases are extended until sensors determine that no cars are in the dilemma zone. To accomplish this, systems define the dilemma zone as a fixed area on the pavement and assume that any vehicle located in that area at the onset of a yellow light will be faced with the dilemma zone predicament. However, this fails to account for the variation of each vehicle's size, speed, and ability to decelerate. The second approach provides warning signals to drivers, but these signals typically lack direct coordination with the signal controllers.

To provide a more individualized and effective signal control and warning system, IAI developed a technology focused on increasing dilemma zone safety using ITS technology. This system accurately identifies vehicles in the dilemma zone based on the time it would take each vehicle to stop once a yellow light appears. Using sensors, the system identifies each vehicle's size, speed, and location to estimate the time needed to reach the intersection. When the two-part system determines that a vehicle will be trapped in the dilemma zone at the onset of a yellow light, it first uses advanced signal control protocols to adjust light phases and prevent dilemma zone situations. If vehicles remain in the dilemma zone, the system can alert drivers using an infrastructure warning system, comprised of roadside flashers that are activated based on commands from the detection controller.

Looking toward the future, IAI has also developed an onboard warning system, which uses information from the detection control computer to calculate an individual vehicle's stopping distance and current speed and displays a warning video on a mobile device such as a tablet or smartphone. The warnings notify individual drivers to begin decelerating so there is ample time to stop safely before the intersection. In the future, these systems can be integrated into the vehicle-to-infrastructure communication environment that is being developed by the Federal Government in coordination with State DOTs, private industry, and international partners. Both the infrastructure and onboard warning systems are already integrated into IAI's technology and are ready to be deployed in existing and future market opportunities.

IAI's system has provided promising developments to support FHWA's connected vehicle initiative. FHWA has completed indoor lab testing, outdoor parking lot testing, and testing at the FHWA Turner-Fairbank Highway Research Center. In addition, FHWA conducted human factors studies to confirm the effect of warning systems on driver behavior and safety. Furthermore, because it is an AI-based system like the AI-TOMS, it learns over time and will continue to optimize its performance.

Because of the success of both projects with IAI, DelDOT received a $5 million grant through FHWA's Advanced Transportation and Congestion Management Technologies Deployment Program, to which DelDOT is adding $5 million of its own funding for a total investment of $10 million.

"Using these funds, DelDOT plans to deploy these AI technologies, as well as other promising solutions, across the State in an effort to create a truly innovative, next-generation approach to traffic management that uses smart sensors and AI to provide the most efficient and safe operations of our highway network," says Dr. Huang.

Installing Mini-Roundabouts Using Recycled Plastic

Mini-roundabouts, as implied by the name, serve as small-scale versions of the modern roundabout traffic control system that directs vehicles circularly through an intersection. Mini-roundabouts retain the same operating principles to reduce congestion and improve safety, but their small size enables jurisdictions to install them within the footprint of an existing intersection. This eliminates the need to widen roads or relocate utilities. To compensate for their small size, the central islands and splitters are made traversable for trucks and large vehicles that are unable to complete the limited-radius turns.

 

Vehicles approaching an intersection when the light turns yellow may be faced with the dilemma of braking abruptly or accelerating through the intersection.

 

While the benefits of roundabouts are well-known, including increased safety and efficiency, the installation can require the closure of an intersection and the use of permanent materials. Working through the FHWA SBIR program, engineering company ZKxKZ, Inc. identified and developed a design that addresses these issues by providing low-cost, easily-installed mini-roundabouts made from recycled plastic. Whereas conventional methods involve cutting the pavement and filling it with reinforced concrete, this new technology can be installed directly onto existing pavement that is in good condition.

ZKxKZ is using a polyethylene-based composite to take a completely different approach to mini-roundabouts—and potentially other infrastructure installations as well. The material, which is used for railroad ties and is known to be both strong and durable, offers the opportunity to design and precut pieces for assembly at the installation site. Using computer-aided design, ZKxKZ engineers take measurements from geometrical design for an installation site and translate it in a modular mini-roundabout design, which is made up of hundreds of parts that fit together like a jigsaw puzzle.

Using this approach, pre-cut boards can be delivered onsite, ready to be installed. To complete the installation, the pre-cut plastic boards are lined up on the pavement according to the plan's geometric design. The installer then drills through each piece's precut holes and into the pavement, fills the holes with cement, and secures the boards using anchors. This process simplifies the labor and, importantly, does not require the complete closure of the intersection, therefore minimizing the impact on the traveling public.

ZKxKZ's recycled mini-roundabout system has undergone testing to confirm its practicality and functionality at five locations: three installations in Sundre, Canada; one in Jackson, GA; and most recently, in Annandale, VA. The system has shown success in solving critical operational and safety problems. The success of these installations and the future potential for other infrastructure-related improvements, such as channeling curbs and bike lane dividers, led FHWA to invest further into the development of the system through a phase IIB award. Additionally, the United States Air Force identified a number of potential uses to address its priorities as well and is also contributing significant resources through the SBIR program to further realize the potential of this innovation.

 

A mini-roundabout made of recycled plastics in an intersection in Annandale, VA. The modular designs can be installed with minimal damage to the roadway and without closing the intersection to traffic.

 

Already, this low-cost and easily installed system has demonstrated its ability to address certain traffic and safety issues prevalent on roads. Mini-roundabouts are typically installed to improve safety and traffic flow by forcing vehicles to reduce their speed as they approach the intersection and by doubling the capacity relative to all-way stop control to alleviate congestion. ZKxKZ's system provides a convenient method for demonstrating the effects of mini-roundabouts at particular intersections because it is easy to install and remove. If the jurisdiction decides the system is not effective at its location, it can be removed and the road can be easily returned to its original form.

"The simple installation techniques and adaptable design characteristics have made this construction technique an effective solution with potential to address a variety of traffic issues," says Dr. Wei Zhang, a highway research engineer with FHWA's Office of Safety Research and Development.

Driving Success

Again and again, the SBIR program has produced effective innovations to answer transportation challenges. The program's focus on market-driven solutions helps to achieve successful adoption because all of the innovations are addressing a real need for which a market exists. This creates an environment in which FHWA can advance its strategic goals, a small business with a great idea can find success in a crowded market, and the public benefits from safer, efficient, and more durable infrastructure.


Craig P. Thor, Ph.D. is the senior research and technology legislative and budget analyst in the FHWA Office of Corporate Research, Technology, and Innovation Management. He also serves as the SBIR program manager. He holds a Ph.D. in biomedical engineering from Virginia Tech.

Sarah Cigas graduated from the University of Southern California in 2020 with a B.S. in civil engineering. She served as a Summer Transportation Internship Program for Diverse Groups intern with FHWA in 2018. Following graduation, she plans to pursue a master's degree in structural engineering.

For more information, contact Craig Thor at craig.thor@dot.gov or visit www.volpe.dot.gov/work-with-us/small-business-innovation-research.