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Federal Highway Administration > Publications > Public Roads > Vol. 76 · No. 3 > Managing Traffic Signals During Storms

November/December 2012
Vol. 76 · No. 3

Publication Number: FHWA-HRT-13-001

Managing Traffic Signals During Storms

by Ahmed Abdel-Rahim and C.Y. David Yang

Using weather data from the Clarus Initiative, researchers have developed a prototype system that could help reduce crashes at intersections. 

Clarus Initiative researchers have developed a prototype application for a secure, dependable, real-time, and weather-responsive control system for traffic signals. Idaho researchers are field testing the prototype using weather and road surface data from this signalized intersection in Moscow, ID.
Clarus Initiative researchers have developed a prototype application for a secure, dependable, real-time, and weather-responsive control system for traffic signals. Idaho researchers are field testing the prototype using weather and road surface data from this signalized intersection in Moscow, ID.

Adverse weather conditions such as rain, fog, and snow can reduce visibility and pavement friction, thereby impairing the ability of drivers to operate their vehicles safely. Lower visibility and reduced friction cause traffic to slow down, thereby limiting roadway capacity and significantly affecting both the safety and efficiency of arterial systems.

The effect of weather on traffic incidents and highway safety has been widely addressed in the literature. According to a study by the Western Transportation Institute, 17 percent of all traffic fatalities annually are attributed to weather-related factors. The same study also suggests that snow increases the risk of crashes that cause minimal injuries by approximately 120 percent, minor injuries by 80 percent, and major injuries and fatalities by 40 percent.

Other research examining the impact of weather on traffic signal operations along arterials shows that timing plans used under normal conditions become problematic in adverse weather. As reported by researchers at the University of Utah Traffic Lab in the paper “Modifying Signal Timing During Inclement Weather,” presented at the Transportation Research Board’s 2001 annual meeting, the reduction in average speeds and saturation flow rates, coupled with the increase in startup delays, make normal signal-timing parameters unsuitable during inclement weather.

Several studies have investigated the effect of inclement weather on signal timing. For example, a 2009 report by the Western Transportation Institute, Evaluation of the Utah DOT [Department of Transportation] Weather Operations/RWIS [Road Weather Information System] Program on Traffic Operations, shows that weather-responsive plans can improve both the safety and efficiency of traffic signal systems. Using microscopic simulation, the study revealed reductions of 7–23 percent in average delays and 4–9 percent in vehicle stops, and an increase of 3–12 percent in average speeds.

In 2004, the U.S. Department of Transportation (USDOT) launched the Clarus Initiative, a research effort focused on developing a database system for storing and quality-checking observations from fixed and mobile road weather sensors. The initiative is a joint endeavor of the department’s Intelligent Transportation Systems (ITS) Joint Program Office and the Federal Highway Administration’s (FHWA) Road Weather Management Program, part of the Office of Operations. Under the initiative, researchers at the University of Idaho are using Clarus to receive and analyze road weather information from different weather stations and adapt signal timing in response to changes in road surface conditions and visibility levels.

Weather Information in The Clarus Database

USDOT funded research to create Clarus (Latin for “clear”), which is a system for managing data on weather observations. The Clarus system’s functions include assimilation, quality checking, and dissemination of weather data. The goal of the initiative is to establish a partnership to create a nationwide weather-observing and forecasting system for surface transportation. The Clarus system operates using near real-time atmospheric and pavement observations from participating States’ environmental sensor stations (ESSs).

Figure. The figure consists of boxes and icons connected by lines and arrows. The figure shows the flow of information as data from a road weather information system are transmitted from various collection sites (represented by dots) throughout a State (in this case, Idaho, as suggested by a State outline behind the dots) to a road weather information system (RWIS) server (represented by an icon connected to the dots by lines) overseen by the State department of transportation. From there, the data pass through the Clarus system, which includes collector services, quality checking, and a Web portal. The Clarus system is represented by three icons enclosed in a box and connected by a line to the State department of transportation RWIS server. Next, the data are funneled (represented by a vertical line from the Clarus system) to a local area network (represented by a horizontal line beneath the Clarus system). The local area network consists of individual traffic controllers and processing units (represented by boxes and lines connected to the local area network). The processing units transmit information through microwave or Bluetooth communications (represented by a bubble connected to the local area network’s traffic controllers and processing units by two-way arrows) to and from road users (represented by a box connected to the bubble by two-way arrows), including vehicles, pedestrians, emergency medical services, and heavy vehicles.
Shown here is the information flow for integrating Clarus data into the operation of a traffic signal system. From collection sites in Idaho, data are transmitted to the State DOT’s road weather information system (RWIS) server. From there, the data pass through the Clarus system, which includes collector services, quality checking, and a Web portal. Next, the data are funneled to a local area network consisting of individual traffic controllers and processing units. The processing units transmit information through microwave or Bluetooth® communications to and from road users, including vehicles, pedestrians, emergency medical services (EMS), and heavy vehicles (HVs).

The States provide observations of various types to the Clarus database in order to report with the highest possible degree of reliability the weather conditions, visibility level, and roadway surface conditions at or near their ESS locations. For example, the States use a combination of observation types such as “essSurfaceStatus,” which reports the status of the roadway surface (dry, wet, or snow and ice), and “essSurfaceTemperature,” which reports the temperature of the roadway surface, to determine the road surface conditions at their ESS locations. Similarly, States use observation type “essVisibility” to provide an estimate of visibility levels (measured by distances that motorists are able to see). Observation type “PrecipType” and “essPrecipRate” provide data relevant to the precipitation type and rate, respectively, which are important in traffic signal operation. These observation types are sufficient to determine conditions that are relevant to the operation of traffic signal systems.

Designing the Clarus Prototype

Researchers at the University of Idaho working on the Clarus project employed state-of-the art secure software and systems engineering to generate a “survivable” prototype of a weather-responsive control system for a signalized intersection. Survivability is defined as the capability of a system to fulfill its mission in a timely manner, despite component failures caused by malfunction, intrusions, attacks, sabotage, or natural disasters.

Weather Condition Observation Types at
Road Weather Information System Sites

Weather Element

Observation Type

Temperature essAirTemperature
essSurfaceTemperature
Surface essSurfaceStatus
Precipitation essPrecipRate
PrecipType
essPrecipYesNo
Visibility essVisibility

The Clarus software design ensures accurate execution of two tasks. In the first task, the software uses a network connection between the Clarus database and traffic controllers at signalized intersections to obtain near real-time data on atmospheric conditions, weather, visibility, and road surface conditions. In the second task, the software adapts signal timing at the intersections in response to inclement weather.

The system design requires minimal hardware for full implementation, as it operates using current traffic controllers at the ESS locations and existing cabinet standards and technologies. “Incorporating the link to the Clarus system is a milestone in the development of traffic control systems, making them sensitive to current weather and road conditions,” says Paul Pisano, team leader for the Road Weather and Work Zone Management program in FHWA’s Office of Operations.

This figure shows the software architecture for the weather-responsive traffic signal control system. The figure consists of two large boxes, one above the other. The top box includes five smaller boxes connected to one another by arrows. The first of the smaller boxes, located in the top left of the box, is labeled "Clarus Data Conversion Interface" and is connected to two boxes, one to the right labeled "Network Interface" and one below it labeled "Clarus Data Management." The latter box is connected to its right to a box labeled "Algorithm Engine," which in turn connects to the final small box, labeled "Traffic Controller." The "Traffic Controller" box connects upward to the "Network Interface" box, closing the loop of the five smaller boxes inside the one large, top box. Below the top large box is the other large box, labeled "Operation Monitoring and Contingency Management System." The two large boxes are connected by two-way arrows.
Shown here is an overview of the software architecture and its interface with Clarus. The dark blue blocks indicate the hardware interfaces.

For the prototype, the Clarus researchers used microprocessor traffic controller communications based on the National Transportation Communications for ITS Protocol (NTCIP), verifying that the necessary read and write capabilities were available from the microprocessor to any NTCIP-compliant traffic controller. An off-the-shelf microprocessor and connecting cable were sufficient. The prototype functions for any field traffic control application where the overall process can be distilled to predictable tasks.

Field Testing the Clarus Prototype

In May 2012, the Idaho Transporta-tion Department (ITD) began field-testing a prototype of the weather-responsive traffic signal system developed as part of the Clarus project. The University of Idaho and ITD will continue testing the prototype through August 2013. The goal of the project is to develop and implement a real-time, weather-responsive traffic signal control system for the State of Idaho with the intent to improve the efficiency and safety of traffic signal operations during inclement weather. The ITD project is an example of how researchers can use Clarus data to inform traffic signal operation.

“Winter driving conditions decrease safety for the traveling public,” says Brent Jennings, ITD’s highway safety manager. “ITD continues to look for innovative ways to increase highway safety that align with our journey toward zero deaths on all roadways in Idaho. The department’s Office of Highway Safety is excited about the recently implemented research project with the University of Idaho that integrates the Clarus weather data system into traffic signal operations. This project will assist in adapting automated signal timing during times of inclement weather, which has the potential to reduce deaths and serious injuries.” 

The system will receive and use weather information from Clarus and Idaho’s road weather information stations to adapt signal timing in response to inclement weather. Researchers will install the weather-responsive system at one or more intersections during November 2012 and January 2013 and monitor the performance of the system and associated traffic controllers throughout the test period. Then they will use the data to evaluate the system’s performance.

The computer monitors, processing unit, and controller interface device shown here are some of the equipment set up at a University of Idaho laboratory to run a hardware-in-the-loop microscopic simulation model.
The computer monitors, processing unit, and controller interface device shown here are some of the equipment set up at a University of Idaho laboratory to run a hardware-in-the-loop microscopic simulation model.

Weather is a significant impediment to highway operations,” says Mark Kehrli, director of the FHWA Office of Transportation Operations. “Rather than throwing up our hands and saying, ‘You can’t change the weather,’ ITD is showing that there are real-world solutions to these types of impacts that can be implemented today.”

Benefits of Weather-Responsive Systems

The University of Idaho researchers evaluated and tested the survivable weather-responsive traffic signal system developed for this project by conducting a benefits analysis. The researchers used a hardware-in-the-loop microscopic simulation model to assess the operational and safety benefits. The model includes a workstation running the VISSIM microscopic simulation model for the network, a traffic controller, and a controller interface device to facilitate the exchange of data between the simulation model and the traffic controller. An external processing unit runs the software application and the weather-responsive control algorithm and is connected to both the Clarus system and the traffic controller. The researchers evaluated the traffic safety benefits through surrogate measures, such as the number and type of conflicts due to weather effects.

The results show that average intersection delays and average number of stops increased significantly during both snow and ice conditions. This pattern is consistent in the three levels of traffic volumes (low, moderate, and high) examined in the simulation study. The study revealed that, under snow and ice conditions, weather-responsive signals reduced intersection delays by an average of 8.2 percent and decreased the number of stops by an average of 9.5 percent. The reduction in delays and stops was higher for moderate and high traffic volumes.

Bar chart. This bar chart shows the percent reduction in traffic delays and number of stops as a result of implementing the weather-responsive system during snow and ice conditions. The vertical axis is labeled "Percent Reduction" and ranges from 0 to 14 percent in increments of 2 percent. The horizontal axis is labeled "Traffic Volume Level," and three sets of bars represent traffic volume levels—low, moderate, and high. At low volumes, the reduction in average delay was about 5 percent, and reduction in number of stops was about 6 percent. At moderate volumes, the reduction in average delay was about 8 percent, and reduction in number of stops was about 9 percent. At high volumes, the reduction in average delay was about 11 percent, and reduction in number of stops was about 13 percent.
Reductions in Delays and Stops During Snow and Ice Conditions

 

Bar chart. This bar chart shows the percent reduction in rear-end, crossing, and lane-change conflicts as a result of implementing the weather-responsive system during snow and ice conditions. The vertical axis is labeled "Percent Reduction" and ranges from 0 to 70 percent in increments of 10 percent. The horizontal axis is labeled "Traffic Volume Level," and three sets of three bars represent low, moderate, and high levels. At low volumes, the reduction in rear-end collisions was about 18 percent, reduction in crossing collisions was about 12 percent, and reduction in lane-change collisions was about 4 percent. At moderate volumes, the reduction in rear-end collisions was about 32 percent, reduction in crossing collisions was about 22 percent, and reduction in lane-change collisions was about 9 percent. At high volumes, the reduction in rear-end collisions was about 64 percent, reduction in crossing collisions was about 44 percent, and reduction in lane-change collisions was about 18 percent.
Reductions in Traffic Conflicts During Snow and Ice Conditions

The results of the simulation study reaffirm the potential safety benefits of weather-responsive traffic signal systems. In addition to fewer delays and stops, potential benefits include reductions in crash numbers, expressed as percent reductions in total, rear-end, and crossing conflicts. The potential benefits in crash reduction also were higher as traffic volumes increased. Rear-end crashes were the conflict type most eliminated by the system, with a potential average reduction of approximately 32 percent for moderate volume levels and 64 percent for high volume levels.

Although these results are based on microscopic simulation modeling and surrogate safety measures, they provide an indication of the crash reduction potential of weather-responsive traffic signal systems.

Future Activities

Detecting a traffic control system’s departure from normal behavior due to faults or malicious acts has challenged the security and survivability research community for years. Many researchers believe too little progress has been made to counter malicious acts, such as intrusions, attacks, or sabotage.

“The approach described here is a powerful step in the right direction toward increasing the reliability of the transportation system and the safety of the travelers,” says FHWA’s Pisano.

The focuses of future research include three areas. One is field-testing the system at signalized intersections under a variety of weather conditions. Another is expanding control modifications to include other traffic control parameters, such as vehicle passage time, minimum green, and offsets (one of the signal control parameters that defines the time lapse between the start of green in two intersections). The third area is increasing the power of the system to maintain reliable, secure, and survivable traffic signal service.

State departments of transportation have invested millions of dollars in environmental sensor stations, primarily for winter maintenance purposes,” Pisano says. “This project shows how these agencies can maximize the benefits of these investments, improving highway safety and mobility under a wide range of weather events.”


Ahmed Abdel-Rahim is an associate professor in the Department of Civil Engineering at the University of Idaho. He is an affiliate faculty with the Center for Traffic Operations and Control at the university’s National Institute for Advanced Transportation Technology. Abdel-Rahim’s research interests include traffic operation and control technology, security and survivability of transportation networks, hardware-in-the-loop simulation modeling, and highway design and traffic safety. Abdel-Rahim received his B.Sc. and M.Sc. degrees in civil engineering from Assiut University, Egypt. He received his Ph.D. in civil engineering from Michigan State University.

C. Y. David Yang is currently the team leader for the Human Factors Team in FHWA’s Office of Safety Research and Development (R&D) in McLean, VA. He joined FHWA in 2008, and work described in this article was carried out when Yang was with FHWA’s Office of Operations R&D. He attended Purdue University, where he received his B.S., M.S., and Ph.D. degrees in civil engineering. His doctoral dissertation used principles of human information processing and human factors to develop design recommendations for advanced traveler information systems.

For more information, contact David Yang at 202–493–3284 or david.yang@dot.gov.

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