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Combating Congestion Utilizing Adaptive Traffic Signal Systems

Gregory Blazina

University of St Francis

MBAD 656 – Transportation Management & Economics

Donald Maier PH.D.

August 10, 2007

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Abstract

Traffic congestion is an inescapable problem in large and growing metropolitan areas across the country. With 88% of America’s daily commuters using private vehicles, eliminating traffic congestion is practically impossible. The challenge then becomes finding the best methods to manage congestion as to minimize its impact on commuters, the environment, and the economy. The field of transportation engineering continues to grow and expand with an increasing use of advanced technologies to reduce congestion within our nation’s roadways. One set of technologies, which has evolved over the past 30 years and shows excellent potential for improving traffic conditions in urban areas is advanced traffic signal systems. These systems are the focus of this paper.

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Congestion has traditionally been labeled as a problem to be solved. Between 1980 and 1999, vehicle miles of travel on U.S. roadways grew by 76 percent, while lane miles increased by only 3 percent. Average daily vehicle volumes in urban areas rose by 43 percent between 1985 and 1999, from 10.331 million to 14.757 million (Wachs, 2002, para.1). In a study of 68 urban areas, published by the Texas Transportation Institute in 2001, it was reported that the percentage of daily travel taking place during congested periods increased from 32 percent in 1982 to 45 percent in 1999. The typical motorist faced seven hours per day of congested roadways verses 5 hours in 1982. Congestion, and innovative solutions to manage it, is not a new phenomenon. In ancient Rome, the Caesars noticed that the movement of goods carts on narrow city streets so congested them that they became impassable and unsafe for pedestrians. They issued an edict requiring vehicles delivering goods to make deliveries at night, but this was soon overturned as citizens complained that their sleep was interrupted by the sounds of vehicles and animals. In England, Charles II issued a famous edict in 1660 to ban standing carriages, wagons, and horses from the streets of Westminster and London because they were excessive and were creating a public nuisance. He ordered that they be required to wait for their passengers off the main thoroughfares to enable the traffic on the boulevards to flow more freely (Wachs 2002 A Long History Section para 1-2). Industrialization brought urbanization and by the late 19th century, cities were incredibly crowded places. Congestion was defined by the high density of dwelling units, the high occupancy of residential housing, the proximity of living areas to work areas, environmental hazards of factories and transportation systems based on animal power. TRAFFIC SIGNAL SYSTEMS 4
The innovation proposed at that time was improved public transportation, first on the surface powered by horses and later elevated or underground, powered by cables, steam and eventually electricity. At the first national Conference on Planning and the Problems of Congestion nearly 100 years ago, speakers urged lower densities and the deliberate suburbanization of the population. As more of the population moved from the centers of large cities and relied on public transportation, the perception of congestion changed from crowded neighborhoods to crowded streetcars on tracks so filled with trolley cars that movement was extremely slow. Further innovations in elevated and underground transit routes along with the development of signaling systems to control complex flows in the transit networks help to provide some congestion relief. The invention of the automobile provides the means to increase the capacity for movement and meant that cities could continue to grow and spread. The rapid reduction, in just a few decades, of the cost of ownership of a vehicle in relationship to workers wages meant that a growing number of people had the ability to become mobile. The most rapid growth rates in automobile ownership and issuance of driver’s licenses occurred between 1910 and the Great Depression and city streets became clogged with autos. Roads were widened and straightened and intersections were increasing managed by signs and mechanical signs that were eventually replaced by electric signals coordinated to accommodate higher traffic volumes.

TRAFFIC SIGNAL SYSTEMS 5 Traffic Signal Controls
Traffic signal control is system for synchronizing the timing of any number of traffic signals with the goal of reducing stops and overall vehicle delay and maximizing throughput. These systems vary in complexity from simple systems that use historical data to set fixed timing plans, to adaptive signal control, which optimizes timing plans for the network of signals according to real-time traffic conditions. As the population continues to grow, the demand on the existing transportation infrastructure will become increasingly hard to meet. Building enough road capacity to handle all drivers who want to travel in peak hours at the same time without delays is impractical and prohibitively expensive. State Route 895 in Virginia, called the Pocahontas Parkway, is an 8.8 mile parkway built for a cost of 381 million dollars or a little over 43.2 million dollars per mile (Morton 2007 para.5). In many instances adding road capacity is a good idea but no large region can afford to build enough to completely eliminate peak hour congestion, so intelligent systems such as advanced traffic signal control will be critical for operating our current roadway systems at maximum capacity. Adaptive Control Strategies Adaptive control strategies are currently the most advanced and complex control systems available. They are similar to traffic responsive signals in that they receive real-time data through detectors, but instead of matching conditions to an existing timing plan, the system uses an online computer to create an optimal timing plan. No library of timing plans is needed, which works well for areas experiencing high growth rates where libraries of timing plans would need frequent updating. An ACS system uses real-time TRAFFIC SIGNAL SYSTEMS 6 data from detectors to perform constant optimizations on the signal timing plan for a network. This means that signals can adapt to non-recurring congestion, incidents, events, or traffic demand growth over time without needing to be rest. Projects in the U.S. have found that installing adaptive computer control has resulted in about a 20 percent travel time reduction when compared to interconnected pre-timed signals using old timing plans (Meyer 1997 p. 8-9). In addition to significantly reducing travel time, traffic signals control improvements also reduce stops, fuel consumption, and emissions. In a street network with poorly times traffic signals, the fuel consumption by vehicles stopping and idling accounts for approximately 40% of network wide vehicle fuel consumption. The Texas Light Synchronization Grant Program II, achieved reduced fuel consumption 13.5% (20.8 million gallons / year), delay 29.6% (22 million hours / year) and stops 11.5% (729 million stops / year). The total savings to the public was $252 million and more significantly the study indicated that an average of 19 gallons of fuel was saved for every dollar that was spent on the ACS project (Fambro et. al. 1995). Los Angeles, with its large population and their dependence on the automobile, experiences extremely heavy congestion on its arterials. The situation is compounded by activity centers such as the Coliseum and the airport which create large and less predictable traffic surges. In an effort to reduce and improve congestion management, the city created Automated Traffic Surveillance and Control, one of the most advanced traffic management systems which include centralized adaptive traffic signal control. The system was initially used around the Coliseum for the 1984 Olympic Games. The system

TRAFFIC SIGNAL SYSTEMS 7 included surveillance via loop detectors and closed circuit television, signal optimization software, and real-time remote signals (Dahlgren 1996). This ACS has had tremendous success in reducing system wide congestion as well as in clearing event traffic. Since the system was implemented Coliseum traffic clears within an hour after a big concert compares with over two hours previously. In addition, the system has reduced stops by 35%, intersection delay by 20%, travel time by 13%, fuel consumption by 12.5% and air emissions by 10%. The benefit / cost ratio was found to be 9.8: 1, and they system paid for itself in less than one year (Rowe 1990). In 1991, residential population and economic development skyrocketed in Oakland County, Michigan. Unfortunately along with the benefits of this growth came significant traffic congestion. The cost solving the congestion problem by expanding roads and highways was estimated at 1 billion dollars. Instead, Oakland County looked for a more innovative approach and the result was the implementation of the Faster and Safer Travel through Traffic Routing and Advanced Control system (Fast-Trac). This system combined advanced traffic management with advanced traveler information with an adaptive control strategy at the core. Oakland County chose to use only surveillance cameras instead combining them with loop detectors for several reasons. Video cameras can be installed on any surface and in any weather conditions, a very important factor in the Michigan climate. Also one video camera can monitor several lanes of traffic while a conventional loop detector can only monitor one. This system has shown remarkable success on several fronts. There was an 89% drop in the number of accidents at the most dangerous intersections, a 100% decrease in TRAFFIC SIGNAL SYSTEMS 8 the number of serious injuries at those same intersections, and over 40 hours a year saved from the average commute time (Gravet undated). Results showed that this system eased traffic flow and reduced the need for police to manually direct traffic during concerts and other major events. Overall the program is credited for a 19% increase in rush hour travel speed and significant decrease in accidents by reducing the number of stops by one third. It also reduced carbon dioxide emissions by 12 percent. Adaptive Control Strategies Cost No solution to managing congestion is without a price. The most common challenge to the implementation of an Adaptive Control System is initial financial cost. Luckily, as the successes in California, Michigan, and Texas have proven, the benefits from a well designed system far outweigh the initial costs. The central hardware for a typical ACS system will range between $30,000 and $50,000. The cost of the software will depend on the sophistication of the system and range from $70,000 to $200,000. Local controllers $4,000 to $10,000 a piece and detectors $5,000 to $10,000 a piece need to be installed at each intersection. ASC, when compared to standard traffic control devices can reduce operations and maintenance costs, since the cost of maintenance for these systems in much lower than the cost of retiming (Gartner 1995). The US Department of Transportation and Federal Highway Administration’s deployment tracking database shows that few areas re-time their signals every year. In fact it is estimated that nearly 75% of all signals in the United States need to be

TRAFFIC SIGNAL SYSTEMS 9 re-timed and most metropolitan areas do not have the resources to perform this function (Hicks, Carter. 2000). However as mentioned earlier, with ACS there is no need to reset signals, because the system continually generates new timing plans. This is especially beneficial to areas of high growth, where even the best fixed timing plans quickly become out of date. As with any major improvement project it is crucial to use pilot studies and other evaluation tools in selecting a system that will work well for a particular area. Some systems may not improve congestion in a certain area at all. A limited ACS was installed in Anaheim California and produced little improvement and even increased delays in some cases. According to the US Department of Transportation who sponsored an evaluation of the system, detector placement may have been the cause of the sub optimal performance (Hicks, Carter 2000). The loop detectors in Anaheim were located closer than usual to the intersection and did not give the ACS completely accurate information on current traffic conditions. Therefore the ACS computer could not create an optimal timing plan. The results of the system installed in Anaheim should not be taken a failure on the part of the adaptive control strategy itself, but rather as a caution to potential ACS implementers, stressing the importance of field tests and preliminary research. Discussion Adaptive Control Strategies offer the most cost effective, environmentally friendly, and politically safe solution to managing congestion in our over crowded cities. There are more than 330,000 traffic signals in the United States and it is estimated that over 75% of these could be improved by the addition of ACS. Poor traffic signal timing TRAFFIC SIGNAL SYSTEMS 10 accounts for 5-10% of all traffic delays or totaling 295.8 million vehicle hours of delay on major roadways alone. Optimizing these signals can produce a benefit cost ratio of up to 40:1. Congestion pricing and peak hour tolls have long been proposed by transportation economists but the majority of American reject this solution because it is viewed a just another tax forcing them to pay for something that they have already paid for through gasoline taxes. Many also view this as favoring the wealthier and subsidized drivers and being an added burden to the majority of the working class. The addition and widening of existing roads and highways as mentioned earlier is costly and especially difficult in already land strapped areas. Widening all major commuting roads would involve demolishing thousands of buildings, cutting down trees, displacing thousands of residents and turning major metropolitan areas into giant concrete slabs. Improving the current transit system is another alternative but in 2000 in the United States only 4.7% of all commuters traveled by public transportation, the major reason being most transit commuting is concentrated in a few large densely settled regions with extensive fixed rail systems (Downs 2004). Many transit systems are already experiencing funding issues and unless the government can find a way to pay for improvements that will guarantee an increase in utilization the viability of this alternative is questionable. Adaptive Control Strategies have proven themselves to be an effective solution to managing traffic congestion. The technology is available for the implementation of signal systems that can accommodate not only recurring traffic congestion but also systems that can adequately adjust signal timing for non recurring traffic congestion caused by random fluctuations in traffic patterns or due to incidents. Peak hour traffic congestion in all large TRAFFIC SIGNAL SYSTEMS 11 and growing metropolitan regions is inevitable but through the use of ACS the rate at which it intensifies can be managed successfully.

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References
Dahlgren, Joy, et al., (1996) Lessons from Case Studies of Advanced Transportation and Information Systems, California PATH.
Downs, Anthony (2004), Traffic: Why It’s Getting Worse and What Government Can Do. Policy Brief #128. Retrieved July 5, 2007 from The Brookings Institution Web site: http://brook.edu/printme.wbs?page=comm./policybriefs/pb128.htm Fambro, Daniel, et. al., (1995) Benefits of the Texas Traffic Light Synchronization (TLS) Grant Program II, Texas Transportation Institute
Gartner, Nathan H., Stamatindius, Chronis, and Tarnoff, Philip, J., (1995) Development of Advanced Traffic Signal Control Strategies for Intelligent Transportation Systems: Multilevel Design, Transportation Research Record 1494.
Gravat, Jack, (undated) FAST-TRAC - Success In Any Lane, Retrieved July 15, 2007 from Federal Highway Administration Web Site: http://www.itsdocs.fhwa.dot.gov/%5CJPODOCS%5CPRESSREL/$801!.PDF
Hicks, Brandy and Carter, Mark, (2002) What Have We Learned About Intelligent Transportation Systems?-- Arterial Management, US Department of Transportation/Federal Highway Administration. Retrieved July 15, 2007 from Federal Highway Administration Web site: http://ops.fhwa.dot.gov/arterial_mgmt/index.htm TRAFFIC SIGNAL SYSTEMS 13

References
Meyer, Michael, (1997) A Toolbox for Alleviating Traffic Congestion and Enhancing Mobility, Institute of Transportation Engineers 8-9
Morton, Roger, (May 2007) Combating Congestion: Who Pays the Bill. Retrieved June 28, 2007 from High Beam Research Web site: http://www.highbeam.com/doc/1G1-164487112.html
Rowe, Edwin, (1990) The Los Angeles Automated Traffic Surveillance and Control (ATSAC) System, Los Angeles Department of Transportation
Wachs, Martin (October 2002), Fighting Traffic Congestion with Information Technology. Retrieved July 15, 2007 from http://www.rff.org/rff/News/coverage/2002/October/Fighting-Traffic-Congestion-with-Information-Technology.cfm

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