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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
This magazine is an archived publication and may contain dated technical, contact, and link information.
|Publication Number: Date: January/February 2004|
Issue No: Vol. 67 No. 4
Date: January/February 2004
Take a look at the latest automotive innovations and intersection technologies for improving driver performance.
|Intersections like the one shown offer logical settings for deploying intelligent vehicle technologies.|
Cited in more than 90 percent of police crash reports, driver error remains the leading cause of crashes on America's roads. To help improve driver performance and safety, the U.S. Department of Transportation (USDOT) and the Intelligent Transportation Systems (ITS) Joint Program Office at the Federal Highway Administration (FHWA) established the national Intelligent Vehicle Initiative (IVI). A significant new direction for USDOT safety programs, the IVI focuses on preventing crashes by helping drivers avoid hazardous mistakes.
Other partners in the project include the Federal Motor Carrier Safety Administration, the National Highway Traffic Safety Administration, the Federal Transit Administration, the American Trucking Associations, ITS America, the motor vehicle industry, seven universities, and 10 State and local transportation agencies. A departure from the past, the initiative looks at "preventing" crashes, rather than "reducing the severity" of crash-related injuries to people and property.
"The mission of the IVI is to reduce the number and severity of crashes through the application of advanced driver assistance systems," explains Ray Resendes, IVI program manager at FHWA. "Through the IVI program, the Federal government, and FHWA along with its partner agencies, is helping the transportation industry produce better safety systems more quickly."
During the summer, a 3-day national IVI meeting and vehicle demonstration was held at FHWA's Turner-Fairbank Highway Research Center. Several State departments of transportation (DOTs), local transportation agencies, and members of the private sector displayed intelligent vehicle technologies developed under the IVI. The technologies included an avoidance system for intersection collisions, a bus equipped with an innovative frontal collision warning system, cars with adaptive cruise control and lanedeparture warning systems, and a tractor-trailer truck featuring onboard trucker safety advisory and automatic crash notification systems. Products in testing are expected to appear soon in passenger cars, including rear-end collision-avoidance systems and roadway-departure warning systems. Eight IVI operational tests also are underway.
An outgrowth of the IVI initiative, FHWA's new intelligent intersection testing facility at the Turner-Fairbank Highway Research Center in McLean, VA, opened during the national IVI meeting and demonstration in the summer. The intersection-the first of its kind in the United States-will be used to develop and evaluate vehicle-based and vehicle-roadway cooperative systems that can save lives by helping drivers avoid intersection crashes.
|This illuminated display (the no-left-turn sign) warns drivers that it is unsafe to make a left turn at the intersection.|
In 2002, more than 9,400 people were killed and 1.4 million injured in crashes at intersections. To prevent intersection crashes, drivers need warning systems that alert them to the potential for a collision or tell them when it is safe or unsafe to pass through an intersection.
At FHWA's intersection testing facility, researchers from the California Partners for Advanced Transit and Highways (PATH) program, the Intelligent Transportation Systems Institute at the University of Minnesota, and Virginia Polytechnic Institute and State University's (Virginia Tech) Transportation Institute demonstrated new technologies that provide drivers with these warnings.
Researchers from the California PATH program-a collaboration by the University of California and the California DOT-designed their system to prevent drivers from being broadsided by vehicles on cross streets or making left turns when oncoming vehicles are approaching. The system uses a combination of millimeter wave and laser radar sensors, plus in-pavement loops to detect other vehicles. A wireless communication system that operates in the 5.9 gigahertz band, and is dedicated to highway communications, transmits information from the sensors to a computer located at the roadside.
Using a timing algorithm, the roadside computer monitors the speeds of the approaching vehicles and determines when a left turn would not be safe. During the demonstration, as one vehicle approached an intersection in preparation to make a left turn, a large road sign reading "No Left Turn" flashed to warn the driver in the left-turning vehicle of an approaching vehicle that could not be seen. The message on the sign seemingly grew 50 percent in size as it flashed. The researchers found that this type of sign is especially visible to drivers when placed just above eye level on the opposite corner of the intersection. In specially equipped vehicles, the computer also can trigger an invehicle display to warn drivers of the intersection hazard.
|This electronic stop sign between the traffic signals illuminates during the red light phase.|
the California researchers decided to focus on human-centered technologies rather than on changes to the roadway infrastructure. "We understand that traffic engineers have worked assiduously to develop and implement a host of important tools in making intersections safer, such as channelization, protected left turns, warning signals, and timing plans," says Jim Misener, the leader of the Transportation Safety Research Program at California PATH. "However, a significant number of intersection crashes still occur because the driver is decidedly human and capable of making perception and judgment errors."
Improving Rural Intersections
Although crashes at rural intersections occur less frequently than those at intersections in urban or suburban areas, rural crashes tend to be more severe due to high speeds. In addition, many rural intersections involve major roads with higher speeds and volumes crossing more minor roadways with lower speeds and volumes. This geometry leads to frequent collisions caused by drivers on the minor roads selecting unsafe gaps in the traffic stream on the major roads as they attempt to cross or turn into the intersections.
To mitigate this problem, researchers at the University of Minnesota demonstrated the use of an Intersection Decision Support (IDS) system during the IVI meeting. Minnesota's system helps drivers identify unsafe gaps in high-speed traffic at two-way, unsignalized intersections in rural areas. The IDS system, which consists of an array of ground-mounted radars interconnected through wireless technologies, collects and sends data on the speed and location of approaching vehicles to a central processing unit, which calculates and identifies unsafe gaps in the approaching traffic. When the system detects an unsafe gap, it triggers an illuminated roadside sign to warn the waiting traffic that it is dangerous to enter the intersection.
"The decision to use a sign that comes on only when it is unsafe for the stopped driver to cross an intersection, rather than a traditional traffic signal, was based on the fact that the traditional signal can stop traffic unnecessarily on the high-speed leg of the intersection," says Max Donath, director of the Intelligent Transportation Systems Institute at the University of Minnesota. "Large trucks often travel on these rural, high-speed roads and when they are forced to stop at a traffic signal, it can take them a long time to get going again, which can impede traffic flow through the intersection."
Researchers from Virginia Tech demonstrated infrastructure-only and infrastructure- cooperative approaches to preventing the most common type of intersection crashes. "Virginia Tech is focusing on 'straight crossing path' crashes, which account for approximately 30 percent of all intersection crashes and occur when a driver continues into an intersection against a red light and collides with a crossing vehicle," explains Vicki Neale, leader of the Safety and Human Factors Engineering Group at Virginia Tech. "We are working on technologies to warn drivers before they violate a signal or stop sign so they can come to a safe stop prior to entering an intersection."
Virginia Tech's infrastructure-only approach uses an IDS (infrastructureto- vehicle communication) system to alert drivers of an imminent traffic signal violation. Using a signal controller to provide information about signal phase and timing, sensors detect a vehicle's location and speed, and the IDS system determines whether a vehicle will cross into an intersection during the red light phase of a traffic signal. If the system predicts a violation, an electronic stop sign hanging between the traffic signal heads illuminates as a warning to the violating driver approaching the intersection. Virginia Tech's infrastructure-cooperative system contains the following components: a roadside traffic signal controller that provides information about signal phase and timing, an infrastructure-to-vehicle communications system, an in-vehicle global positioning system (GPS) receiver and associated roadway map representation, and an in-vehicle computer and driver-vehicle interface. With the information provided by these components, the system recognizes that the driver is not going to stop for the red light, then emits an audible tone and displays a stop sign icon on the dashboard to alert the driver to a hazardous situation.
Although these three projects are still in development, they are making progress toward full-scale deployment. In California, the researchers' next step will be to conduct field operational tests with drivers at real intersections. Researchers in Minnesota also will be testing at actual intersections, in addition to developing a driver simulator to determine how motorists will react to the system and convening a national panel of experts to help with deployment. At Virginia Tech, the researchers believe that the infrastructure-only system will be deployable in the near future. They anticipate that the roadside cooperative system portion could be in place by the time auto manufacturers complete development and begin installation of the in-vehicle technologies that they are working on currently.
|Three San Mateo County Transit District buses like this one are equipped with frontal collision warning systems.|
Preventing Transit Crashes
Frontal collision crashes account for nearly 30 percent of all transit vehicle-related crashes and often lead to property damage, service interruptions, injuries, and increased traffic congestion. At the IVI demonstration, participants had the opportunity to ride a bus equipped with a prototype warning system designed to prevent frontal collisions. Developed by researchers and officials from the San Mateo County (California) Transit District (SamTrans), the California PATH program, Gillig Corporation (a transit bus manufacturer in California), and several local transit agencies, the system provides drivers with an alert if it detects a collision hazard in front of the vehicle or that a crash may occur.
To develop the system, the researchers began by collecting data on transit crashes to identify the magnitude and consequences of frontal collisions and to understand the conditions that lead to frontal collisions. Data-acquisition systems also were installed on buses in the SamTrans fleet to collect information on the movement of surrounding vehicles and stationary obstacles. In addition, researchers studied the needs of the bus drivers who will operate the system, including an evaluation of how to present warnings to drivers, and the types of audible or visual alerts that would be most effective.
Using the collected information, the researchers identified a set of scenarios that could result in frontal collisions and developed a warning system based on those scenarios. Currently, three buses operated by SamTrans are equipped with prototype collision warning systems, which include frontal obstacle and corner detection sensors that search for hazards in front of the bus and monitor for "cut-in" vehicles that change lanes too closely to the bus.
|The computer that controls the frontal collision warning system on this SamTrans bus is housed inside the vehicle.|
If the sensors detect potential hazards, the system sends a warning consisting of a series of illuminated light-emitting diodes (LED) positioned inside the bus near the driver. The LEDs increase in brightness as the bus moves closer to the hazard and turn off as the hazard is avoided. Audible tones were not used as warning signals because the researchers determined that passengers might find the tones to be annoying and potentially alarming. However, the researchers currently are evaluating the viability of some audible warnings to determine whether there are any that could be used to warn the driver, while not alarming passengers.
The California researchers are working to integrate the frontal collision warning system with a side collision system under development in a partnership with Pennsylvania. The research includes collaboration with manufacturers and suppliers of transit buses to increase deployment and commercialization of the warning systems.
|Light-emitting diode panels on either side of the front windshield warn the bus driver of collision hazards.|
Not just for transit vehicles, collision warning and avoidance systems also can improve the safety of passenger vehicles. The National Highway Traffic Safety Administration is working with an automobile manufacturer to develop and test an Automotive Collision Avoidance System (ACAS). At the IVI meeting, a vehicle equipped with ACAS was on hand for participants to view.
Consisting of a rear-end collision warning system and an adaptive cruise control system, ACAS provides drivers with visual and audible warnings when it detects an imminent crash with the rear of another vehicle. The adaptive cruise control system also helps drivers maintain a set speed when there is no impeding traffic and reduce their speed when slower moving traffic is detected.
Although researchers and auto manufacturers previously have tested adaptive cruise control and rear-end collision warning systems, ACAS is the first to combine the two into a single integrated system. In addition, previous rear-end collision warning and adaptive cruise control systems were limited in their ability to detect vehicles. Many of the previous systems detected vehicles by transmitting microwaves from the front of a host vehicle and measuring the time it takes for the microwaves to return after striking a vehicle in their path. Other systems used lasers to detect the reflection of traffic ahead of the host vehicle and measure the distance to the traffic.
Studies have shown, however, that microwave- and laser-based systems sometimes have difficulty identifying which vehicles on a roadway are in the path of the host vehicle. The systems can be particularly inaccurate during lane changes or as road segments change from straight to curved or curved to straight.
Due to these inaccuracies, the ACAS researchers have focused on improving how the system recognizes curves in the roadway. Traditional sensors detect curves by measuring the yaw rate. In addition to yaw-rate sensors, ACAS uses three other detection methods. First, the vehicles are equipped with a GPS that can locate the vehicle's position on a digital map of the roadway. Based on the geometry of the roadway on the digital map, the GPS can predict the curvature of the road ahead of the host vehicle. Second, ACAS uses video cameras installed on the windshield to view the scene in front of the vehicle. A special vision system installed with the cameras then can find the lane markings on the video and use them to estimate the forward road geometry. Finally, ACAS uses radar to detect and analyze the tracks of other vehicles using a patented technique called scene-mapping.
Based on information from these four methods, ACAS can predict the curvature of the upcoming roadway more accurately, locate the closest vehicle in the path of the host vehicle, provide warnings to the driver about potential hazards via a drivervehicle interface, and control the speed of the host vehicle through the brake and throttle when the driver uses the adaptive cruise control. The driver-vehicle interface includes warning icons about speed and potential collision hazards. As the potential for a collision increases, the warning icon becomes larger and more noticeable. The final icon flashes and is accompanied by an audible warning.
In a recent round of controlled testing, 12 drivers took turns driving the ACAS prototype vehicle two times around a 93.4-kilometer (58-mile) route accompanied by a researcher. The goal of the test was to gather feedback on the quality of the images on the in-vehicle display, the feel of the adaptive cruise control, and the accuracy of the rear-end collision warning system. Based on the results, the ACAS researchers began a smallscale field operational test in March 2003 where drivers are given test vehicles for approximately 4 weeks to use as their personal vehicles. Researchers anticipate that the test results from all the drivers will be complete in February 2004, with final results available later in 2004.
Trucks with a Brain
In addition to buses and passenger cars, several tractor-trailer trucks were on display at the IVI meeting. MackTM Trucks and McKenzie Tank Lines, Inc.-primary members of the Mack Trucks IVI partnership, whose membership also includes AssistWare Technology, Inc., XATA Corporation, Vehicle Enhancement Systems, Inc. and Richard Bishop Consulting- demonstrated the use of several new technologies.
The two companies have developed a trucker advisory system (TAS) that will provide drivers unfamiliar with an area with an advance alert about upcoming hazardous roadway features such as extra-tight ramps or work zones. In cooperation with several State DOTs, the two companies identified more than 500 "trucker advisory zones" in 10 States, determined the latitude and longitude of the zones, and created a database of the areas.
Trucks participating in the test are equipped with an onboard computer, the database, and GPS. Using this equipment, TAS identifies whether drivers are in close proximity to any of the hazardous driving areas and shows an alert message on an invehicle display that indicates the type and location of the hazard based on crash history for the location.
"These days, truck drivers are traveling fewer set routes and increasingly are traveling in unfamiliar territory to pick up freight," says Jim Kennedy, director of maintenance for McKenzie. "TAS familiarizes drivers with these unknown areas and decreases the risk of crashes in locations known for rollover hazards, steep grades, or other dangers."
|The onboard computers shown here operate trucker advisory and automatic collision notification systems.|
Because TAS employs computer technology that many truck fleets already are using, Kennedy considers TAS to be highly deployable in the near future. When testing is complete, if it shows that the technology increases safety, the key to widespread deployment will be ensuring that each truck has enough memory space on its onboard computers to hold the TAS database.
In addition to TAS, the researchers are testing an automatic collision notification (ACN) system. Each truck in the test is equipped with front, rear, and tilt sensors that are activated when the truck suddenly accelerates or decelerates and then abruptly stops. If the system is activated, an e-mail about the incident and the truck's location is sent via wireless technologies to the company's Central Network Center in Tallahassee, FL. Using the information in the e-mail, personnel at the center can notify local authorities about the incident, the commodities being transported, and any dangers associated with a release of the commodities.
"The ACN system is most beneficial for trucks carrying hazardous materials, which, if released, could be harmful to the environment and surrounding populations," says Kennedy. The system enables authorities to take faster control of spills and alert communities sooner about the potential danger posed by the materials or the need to evacuate. In addition, because authorities can start to clean up spills more quickly, ACN will help protect animals, plants, and wildlife more effectively. After hearing about incidents, authorities also can alert roadway authorities about potential traffic delays and ensure that motorists have sufficient warning to avoid traffic caused by an incident.
The partnership currently is operating a fleet of trucks equipped with TAS, ACN, and other intelligent safety systems. The partnership is collecting data on the operation of these systems, along with information about other hazardous areas to add to the TAS database. The researchers also are studying the value of the alerts currently sent through the ACN program. The partnership anticipates that it will complete the data analysis and issue a final report by 2005. By then, the partnership will have collected 19 months of test data on 36 trucks, equaling more than 11.3 million kilometers (7 million miles) of information.
A Safer Future
The idea of preventing vehicle crashes is not new. The technologies that the researchers demonstrated at the IVI meeting are innovative because they focus on a new side of crash prevention-the human side. These intelligent technologies will help improve driver performance-and therefore, increase safety on the roads.
"Systems to save lives are available today," says FHWA's Resendes. "However, the IVI partnership is helping to ensure that better systems will be commercially available tomorrow and into the future."
Keri A. Funderburg is a contract writer for FHWA and a contributing editor with PUBLIC ROADS.
For more information about the IVI partnership or intelligent transportation technologies, visit http://www.its.dot.gov/ivbss/index.htm or contact Ray Resendes at 202-366-2182 or email@example.com.