Traffic Congestion: Intelligent Routing & Its Effects on Fuel Efficiency & Total Congestion Costs

Kofi Adofo Raymond Govus Andrew Jairam Michelle Udeli

EXECUTIVE SUMMARY

The average American has been shifting towards an increasingly vehicle-dependent lifestyle over the past quarter of a century due to changes in generational demographic and housing preferences. Current patterns in metropolitan growth have favored edge areas over city centers. Furthermore, most new growth is characterized as single-use land development, such as business parks, housing suburbs, or strip malls. This stratification of land uses necessitates additional driving and eliminates the ability to group vehicle trips. Additionally, the number of cars in the country has continued to dramatically outpace the construction of new highways or public transportation options. The combinations of these two factors result in ever increasing congestion rates and vehicle residence time among commuters. This translates to significant levels of unnecessary emissions which could be something targeted early in campaign to reduce national C02 levels. Furthermore, looking beyond emissions, the time and money wasted in congestion alone should necessitate a solution to the problem.

The solutions which we proposed to the congestion problem are stratified by the time scale which they operate on. Short term solutions involve making the current system more efficient and distributing the traffic load among the available mass transit options. Long term solutions will require a different approach to the manner which we regulate growth and transportation. Incentives to decrease the proximity between housing and employment in metropolitan areas should be pursued as well as a large scale re-investment in mass public transit. For both solutions, a reinvestment in the national transportation infrastructure is required along with informed and targeted policy changes.

BACKGROUND

Traditionally, urban Americans both resided and worked within city centers. At the start of the last century, people lived relatively close to one another and thus their costs of transporting both themselves and their goods were relatively low. The primary method of transport was by foot with low need for vehicles within city quarters. Living and working at high densities allowed companies and factories to transport goods via shipping and the rail system. As time progressed, inhabitants of urban centers began moving further away to suburban locations. There were several causes of this urban sprawl, some of which were the increase population and household income, decreasing costs in transport, a strong economy and disjointed municipal governments. Around the late 1950s, the typical American city still had a large density where most people worked, however a majority of these workers resided in suburban areas and commuted to work using vehicles. As time progressed, the cost of transport continued to fall and thus allowed people to live further from their place of work. This phenomenon is known as urban sprawl. The high density walking city that existed last century had been transformed into a medium density driving city of today (Glaeser et al. 2001).

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A survey of the location of jobs in the 100 largest U.S. metropolitan areas, taken in 2001, found that across the largest 100 metropolitan areas, on average, only 22% of people work within three miles of the city center (Glaeser et al. 2001). That survey also recorded that over 35% of people work more than ten miles from the city centers. This increase in the population of workers traveling to and from city centers creates a demand for more travel space. This results in a large number of vehicles on the road, exceeding the road’s capacity and causing traffic congestion. Traffic congestion increases transit times as a consequence of increased idling during peak travel hours.

Figure 1 - Congestion Growth Tend from 1982 to 2007. Source: 2009 Urban Mobility Report

With the steady increase in the world’s population, the negative effects that congestion has on the climate system will increase. According to the 2009 Urban Mobility Report generated by Texas A&M University, the annual time delay per peak traveler increased from about 14 hours in the year 1982 to about 36 hours in the year 2007. Figure 1 shows the change in congestion growth for various population area sizes from the year 1982 to 2007. Congestion growth has shown a positive trend for all population area sizes. From this figure, it is apparent that the total hours of delay per peak traveler increases as the population area size increases.

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Figure 2- Wasted Fuel per Traveler from 1982 to 2007 for Small to Large Cities, Source: 2009 Urban Mobility Report

As congestion time increases for commuters, fuel consumed or “wasted fuel” becomes very important factor. Figure 2 shows the total amount of fuel wasted while idling for peak drivers in 2007. For the year 2007, the total amount of wasted fuel (in gallons) per peak traveler for all city sizes was approximately 24. That average increased from an average of about 7 gallons in the year 1982. With these averages, the total congestion costs were calculated and analyzed by Texas A&M University. Figure 3 shows the results of the calculation of total congestion cost per peak traveler.

Figure 3 - Total Annual Cost of Congestion per Peak Traveler, Source: 2009 Urban Mobility Report

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Total Congestion Cost = Cost of Wasted Fuel + Average Cost of Time

To calculate the total cost of wasted fuel, the national average cost of fuel was multiplied by the total amount of fuel wasted per peak traveler. The average cost of time was estimated by Texas A&M University to be about $15.47/peak traveler, which was multiplied by the total delay per peak traveler. The sum of the two previous calculations yielded the total congestion cost per peak traveler from 1982 to 2007. For the year 2007, the total congestion cost per peak traveler was approximately $757 per year. For the entire U.S., the travel delay, in billions of hours, increased from 14 in 1982 to about 36 in 2007. The total wasted fuel for the nation per peak traveler increased from about 9 gallons in 1982 to about 24 gallons in 2007.

The travel time index was introduced in the 2009 Urban Mobility Report to be an approximate measure of the additional time added to a route due to congestion. The travel time index is essentially the ratio of travel time in the peak time period to the travel time at free-flow (no congestion) conditions. An example of how this quantity is used goes as follows: A driver obtains directions from a popular navigation website. This navigation website estimates the driver’s arrival time based on local speed limits. If the travel time index (TTI) for the driver’s city is 1.35, and the estimated time of arrival is 20 minutes, the driver would reach their destination in approximately 27 minutes. That is to say that the estimated arrival time is multiplied by the TTI and the predicted travel time, with the inclusion of traffic congestion can be calculated. Figure 4 shows a plot of the daily fluctuations in TTI (blue line).

Figure 4 - Daily Fluctuations in Time Travel Index (TTI), Source: 2009 Urban Mobility Report

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As the amount of congestion increases during peak times (6-9am, 3-7pm), the total TTI also increases. Since congestion causes and increase of time travel, the planning time index (PTI) can calculate determine how what time drivers should leave in order to arrive at their destination in ample time. The buffer index (BI) is just the difference between TTI and PTI.

Figure 5 takes into account all of the previous terms, and compares a general plot of congestion, traffic volume, fuel cost and transit ridership.

Figure 5 - Fluctuations of National Traffic Volume, Congestion, Transit Ridership and Fuel cost from 2005 to 2008. As the national average price of fuel increased, so did the total amount of transit ridership. The total volume of traffic as well as the total TTI decreased at this same time. The TTI dropped so low during the summer of 2008 that it fell below the TTI value for May 2008.

Traffic congestion is an increasing problem throughout the entire world. In addition to being time-consuming, congestion has an impact on air quality and thus the climate system. Traffic congestion is becoming an even bigger problem with the steady increase of the world’s population. Transportation sources accounted for approximately 29% of the total U.S. greenhouse gas (GHG) emissions. Some of these GHG’s include Carbon dioxide, Methane and Nitrous oxide. Vehicles also emit toxins such as Hydrofluorocarbons (cooling systems) and black carbon.

A gallon of regular grade gasoline contains about 8.8kg of CO2 or about 19.4 lbs. of CO2. On average, Methane, Nitrous oxide and Hydrofluorocarbons emissions represent roughly 5-6% of total GHG emissions from the transportation sector. Carbon dioxide emissions, however, account for about 94-95% of GHG emissions from the transportation sector. In the year 2008 the total amount of GHG emissions was about 1184.5 Tg CO2 Eq. Of that figure, 1111.2 Tg CO2 Eq. was

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from Carbon dioxide, 1.4 Tg CO2 Eq. was from Methane, 21.2 Tg CO2 Eq. was emitted from Nitrous oxide and 50.7 Tg. CO2 Eq. was emitted from Hydrofluorocarbons.

With these figures predicted to amplify in the future due to an increasing population, it is imperative that some solutions be developed in order to alleviate this growing problem. This paper proposes both long term and short-term solutions to decrease the total emissions produced from congestion. The main focus will be on short-term solutions and their effectiveness. While long-term solutions are very important, the short-term solutions listed in the paper, take about less than 10 years to implement, thus significantly decreasing the total emissions from traffic congestion into the atmosphere.

SHORT-TERM SOLUTIONS

There are several relatively inexpensive solutions to CO2 emissions that can be implemented across the nation in the short term; most of them involving rerouting of certain vehicles on the road. This can be done with incentives and technology by the name of Intelligent Transport Systems (ITS). For highways, the use of ITS for rerouting traffic, dividing the lanes into express and local, and for electronic toll systems would greatly reduce the amount of congestion and emissions due to idling on the freeways. For local roads, short term solutions would be to implement toll-ways and express lanes on certain roads that have the most congestion; just like on the highways. Similar to that, congestion tax could eventually be a needed implementation to dissuade drivers from using heavily congested areas at certain times. The elimination of usual idle-inducing infrastructure such as intersections permitting direct left turns could also help reduce congestion on roadways. Short term solutions, primarily involving the use of Intelligent Transport Systems, help current road infrastructure greatly improve the environment by reducing emissions at a relatively low cost. These solutions are considered low cost because they do not require the building of new highways, or in some cases, new road or lanes. In the rare occasion that a new road or set of lanes is required, the passageway will simply act as on or off ramp to already existing infrastructure.

Several rerouting technologies can be used on the highways. Students from the University of California- Berkeley came up with ten technology related solutions to mitigate congestion and CO2 waste (Daganzo). The main function of these technologies is to eliminate FIFO lanes, or “First In, First Out” lanes. FIFO lanes are lanes that, much like the “first come, first serve” ideal used while standing in line, cater to motorists who enter the highway first. This creates what some researchers call a “1 pipe flow” that forces drivers across all lanes to drive relatively at the same speeds; this could be disadvantageous at congested off ramps the cause the high volume of cars to spill back onto the highway, creating a bottle-neck effect and reducing speed across all lanes (3). According to The US Department of Transportation Federal Highway Administration, (FHWA) this “bottlenecking” accounts for 40% of traffic congestion (FWHA 7).

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One of UC Berkeley’s suggestions is to expand the usage of variable messaging systems (VMS) that tells drivers which lanes to use depending on their destinations. VMS’s should be placed at least ¼ miles from the next exit and ban last minute lane changes so motorists cannot “cut in” at the last moment (Daganzo 5). This will be enforced by traffic fines.

Another proposed way to use the VMS is to ensure that High Occupancy Vehicle (HOV) lanes are being used to its highest efficiency. During peak hours, HOV lanes will only be accessible for carpools; Off peak, the lanes will be open. Speed sensors in the VMS’ will determine whether to open the HOV lanes or not during out times (Daganzo 7).

The next three suggestions from UC Berkeley deal with metering the on and off ramps. In many cases, on and off ramps can accommodate two lanes; one for each highway queue (Daganzo figure 4). Depending on traffic conditions, the sensors can open and close certain lanes for certain destinations; advising drivers to change lanes if they are blocking the way for those going to other destinations. Also, the metered ramps will divert traffic if the ramps are too full. In certain cases, traffic could be diverted to the next exit close by if the next exit is convenient and available. This could be done voluntarily or involuntarily by simply closing lanes heading towards a bottlenecked location, and diverting traffic elsewhere.

The seventh solution by UC Berkeley is setting up “Dynamic Speed Limits.” Lanes will have designated, and sometimes temporary speed limits depending on traffic conditions in order to optimize flow. By lowering or raising speed limits, certain traffic can get to a certain location at a certain time in order to avoid other traffic from other areas (Daganzo 13).

The next two solutions involve rationing free access, and more efforts to divert traffic, which will be discussed later. The final solution proposed solution by UC Berkeley is dynamic use of the shoulder lanes. Shoulder lanes can be used to move around bottlenecks if they occur, but they are only effective if used with caution and at low speeds (Daganzo 17). Technology will be used to alert traffic and permit the use of shoulder lanes.

There are other short term solutions for highway congestion that have already been put into operation across the country. High Occupancy Vehicle (HOV) and High Occupancy Toll (HOT)

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lanes are already present in cities such as San Diego, Houston, Miami, and Denver (Mtc). HOV lanes are lanes that are available exclusively for vehicles with 2 (or sometimes 3) or more occupants present. This is meant to encourage carpooling and reduce congestion by reducing the amount of cars on the highway at given times; specifically during rush hour. In High Occupancy Tolls, a single occupant with a prepaid account can pay to use a High Occupancy Vehicle lane. Because of this, HOT lanes have become controversial and have been pejoratively named “Lexus Lanes,” implying that these lanes are meant to solely help motorists of higher socioeconomic class. This has been disproven by a study from California Polytechnic State University, San Luis Obispo, who determined that only about 25% of travelers in the San Francisco Bay Area that have taken advantage of the lanes have been of the higher income bracket (MTC). The studies have shown that HOT lanes are actually popular among lower to middle income families, and that usage of these lane are more closely tied to current traffic conditions and priority of getting to one’s destination on time (MTC). “[HOT Lanes] really are a form of ‘congestion insurance’ for any traveler willing to pay the toll - whether it is a businessperson late for a meeting or a parent racing to pick up a child at day care (Mtc).” According to the Metropolitan Transportation Commission implementing these lanes and their network takes about 5 to 10 years to fully build and develop (Mtc).

Express lanes are popular and effective ways to route traffic and reduce congestion. In several cities like Detroit, Miami and Washington D.C, express lanes are used to separate local traffic from regional traffic. The express lanes, which may be combined with HOV and HOT lanes, generally do not have as many on and off ramps. On and off ramps are limited in order to prohibit short distance traveling on the lanes. This may also help travelers avoid certain exits that usually cause bottlenecking and FIFO lanes. The lanes are also separated from the local lanes by barriers to prohibit local lane drivers from crossing over into express lanes. These barriers make it easier for express lanes to merge with other rerouting infrastructure such as HOT and HOV lanes. Because of its merging with HOT and HOV, as well as its convenience, express lanes may charge toll for usage.

Another solution is the use of electronic toll-collection systems used on highways that charge toll fees to a driver’s prepaid account. This electronic toll collecting system has already become prevalent all over the Northeastern United States with a system called E-ZPass. There are similar transponder programs in other states like California (FasTrak), Kansas(K-Tag), and Florida (SunPass). Similar programs in Illinois and Virginia have since been integrated with E- ZPass by sharing technology under the E-ZPass network, E-ZPass Interangency Group (E- ZPass). According to the Research and Innovative Technology Administration (RITA), the E- ZPass system alone reduced toll plaza delay by approximately 85 percent, reducing the delay by 2,091,000 annual vehicle hours. The case study of E-ZPass was conducted on one of its first implementation highways; the New Jersey Turnpike, which is one of the main highways servicing the New York Metropolitan Area. Passenger car delay was reduced by 1.8 million hours per year, and truck delay was reduced by 291,000 hours per year (Rita). For E-ZPass users,

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delay was reduced by 1,344,000 hours per year. As a result, volatile emissions resulting from traffic congestion have been reduced by 0.35 tons and nitrogen oxide emissions (NOx) has been reduced by 0.56 tons per workday, with 58% of the NOx reduction coming from heavy duty trucks (Rita).

The proven effectiveness and popularity of E-ZPass and comparable programs suggests that it could be effective nationwide. Small to medium sized cities are growing very rapidly, and traffic congestion in the cities is growing as a result. Much like the building of interstates to connect all areas of the continental US, a national electronic toll collection system, presumably under the E- ZPass IAG network, would connect every populous region in the entire continental US by eliminating inconveniences of highway travel. With the aforementioned express lanes and/or HOT lanes, electronic tolls can be set to make these conveniences a premium. For highways that already have tolls, the E-ZPass prices could remain the same as regular tolls. One good example of this would be the Philadelphia portion of Interstate-95. Philadelphia, a large city that already has E-ZPass, can split the I-95 where there are more than three lanes in one direction. Already a project that has started on toll highways in the area, even though there is no discount on the tolls, the convenience and time saved has been enough to encourage more travelers to purchase E- ZPass. Conversely, in smaller cities that are rapidly becoming unsustainable due to large growth and expansion while having little to no toll-ways, such as Atlanta and its Interstate 75, charging a premium for E-Z Pass in express lanes while leaving the local lanes free of charge can prove to be a more plausible and likeable approach. By doing it this way, those who drive locally and have become accustomed to not paying may choose to take the slightly slower and more congested local lanes (even though significantly faster and less congested than before because of a portion of traffic being diverted to express lanes), as opposed to paying for the fastest route, the E-ZPass express lanes. This will most likely be even more effective in even smaller cities where those who are not in a rush can take the slower local lanes, while those with stricter deadlines may pay a premium for a more direct and faster flowing route. This can be combined with one or two lanes that are also designated for buses, HOV and HOT lanes.

While the aforementioned highway infrastructure reform techniques can certainly prove to be effective strategies to reduce traffic emissions by congestion, there are some ways to reform local roads to boast similar results. Like highways, many roads can be tolled as well. These are called “variably priced” roads or lanes (FWHA 11). These roads have been proposed as a response to the growing rate of congestion in small and medium sized cites (FWHA6). According to the Federal Highway Administration (FWHA), the average traveler “pays” an annual “congestion tax” of between $850 and $1600 of lost time and fuel sitting in rush hour traffic in America’s ten most congested areas (FWHA 6). This is equivalent to about 8 workdays per year lost by each person by sitting in traffic. In all of the U.S, the average time lost per person is about 36 hours per year, and combined with 63 hours per person lost annually in the more congested areas, congestion causes about 4.2 billion hours of delay every year (Time). By variable pricing major arteries that go into a city, traffic could be greatly reduced. VMS devices

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will direct proper traffic into these areas and direct the rest of traffic to other streets where travel is free. Variably priced roadways can provide access onto bridges, main roads, quick access onto highways, and/or quick access in and out of the heart of cities. This is very much like the HOV and HOT lanes on the highway, which are in fact variably priced roadways as well (FWHA 11). Because of the similarities to HOV and HOT lanes that are accompanied by VMSs to ensure their efficiency, variably priced roadways can prove to become popular methods of allocating traffic and redistributing traffic onto more roadways throughout the cities. This is based on the same premise of “paying for convenience,” which was proven to help those of all socioeconomic classes with HOV and HOT lanes (MTC).

This could also be paired with the expansion of programs like E-ZPass. Paying for convenience could become even more convenient if all payments could be consolidated to one place. An E- ZPass credit-card-like system could be very beneficial in reducing time and difficulty in paying for driving expenses that cause congestion and wasted fuel due to their inconvenience. For example, a driver could use E-ZPass to get onto the express lanes leading down to the city, then use his account to get off the highway onto a variably priced off ramp leading straight into the city; where this variably priced ramp (which is now a road) leads the driver straight to an office building where variably priced parking is reserved in optimal locations for E-ZPass users. This could potentially shave off 10-20 minutes or possibly more on a daily commute without costing much more than the average driver who pays for tolls with cash, then uses more change to pay a parking meter for a space downtown, which will not be reserved and always available. Furthermore, all these payments could be paid for at the end of the month with a credit card online or with a monthly bill; the same way E-ZPass currently charges its customers (E-ZPass). The effectiveness of this program could help E-ZPass expand even more and be used at other places notorious for local road congestion and limited parking; like airports and sports arenas. A one-stop payment for all the driving expenses could greatly improve the way people drive and provide incentives for driving efficiently. In addition to convenience, further incentives could be allowing the E-ZPass member to pay for gas with the card, and providing seasonal bonuses or coupons for driving off peak hours, or consuming less gas than before.

Much like tolling certain thru-ways in a city, certain zones in a city can be tolled in its entirety with a congestion tax. This tax has already been in effect overseas in the United Kingdom, where the City of London is completely zoned off by congestion tax. This tax, as controversial as it is, has greatly reduced the amount of traffic in the city. A quote from reporter James Monaghan of City Mayors, “Despite of the prophets of doom and even some of its supporters back in 2003 [when congestion tax was implemented], the centre of the UK capital has achieved and maintained its figure of 30 per cent fewer traffic delays inside the charging zone compared with the period before charging was introduced.” (Monaghan) A report in BBC News even went on to claim that congestion tax has even gone on to boost health by 183 years of life for every 100,000 residents by reducing CO2 emissions (BBC). Congestion tax has also proven to be

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beneficial to public transit use. In the “Virtuous Cycle,” developed by the NHWTA, the congestion tax, along with the previously mentioned variably priced roads, raises the amount of transit ridership, while reducing congestion and travel time, making public transportation more reliable, and making service more frequent and at lower rates (FWHA 10).

A congestion tax has been proposed in San Francisco, America’s second most congested city as of 2008. It proposes to charge $3 for every motorist’s entrance or exit from the city (Ganga). Although it is currently a very unpopular proposal with San Francisco residents, if the comparable congestion tax in London (with comparable initial unpopularity) can be a positive reference, then over time, the congestion tax may prove to be more beneficial than detrimental; especially considering the “tax” one pays by lost time a fuel (FWHA 6).

Finally, the third solution for reducing emissions on the roadways is to establish a “No Left Turn” policy. As the name suggests, direct left turns at intersections can be eliminated. VMS as well as GPS systems can be used to assist this policy by providing routes that help drivers avoid idling at traffic lights when attempting to turn left. Though not prevalent in city planning, this policy so far has been popular amongst the business sector with companies like UPS and Office Depot adopting this theory. UPS alone has reported a savings of 28.5 million miles, 3 million gallons, and 31,000 metric tons CO2 a year since starting the program (New York Times). The town of Fort Kent, Maine has adopted the “No Left Turn” policy due to their growing congestion problems. The SAD 27 board of directors in Fort Kent issued a voluntary call for drivers to eliminate left turn usage in order to improve travel efficiency around school time and other peak driving hours that cause congestion. This has also been done to improve safety for the children traveling to school. Just from the voluntary call for implementation, members on the board of directors claim success of the program. We’re combining safety and student transportation,” he said. “From what I’ve looked at I’ve seen a better flow of traffic on Pleasant Street [A street that is notorious for congestion in Fort Kent] , especially at the elementary school.”(Bayley)

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Another example of the “No Left Turn” policy is the Median U-turn crossover, also known as the “Michigan Left” due to its popular usage in the State of Michigan.(Bessert) It replaces left turns at intersections with a U-turn farther upstream in a queue, followed by a short drive downstream in the opposite lane in order to then make a right turn. This method has proven to actually be an effective way to reduce time, congestion, and therefore emissions due to idling (Bessert).

LONG-TERM SOLUTIONS

As described earlier, a large driving force behind increasing congestion rates is the shift in American housing preference from urban to suburban. This decentralization of the American lifestyle means that for most living outside of the city limits, a personal vehicle is no longer a luxury rather a necessity to facilitate the suburban lifestyle. Any long term solutions to reduce congestion need to address the suburban dilemma in two manners; first by attempting to curtail rampant suburban growth through planned ‘smart growth’ while fostering redevelopment of urban areas, and secondly by looking to accommodate those living in the suburbs by providing viable options of public transportation to commuters.

The first long term solution to congestion focuses on a distinction in management strategies. The traditional solution to congestion problems was to simply build more roads. This plan however, is proving ineffectual as it appears demand always outpaces supply. An increasingly popular saying of “You can’t pave your way out of congestion” epitomizes the notion. The next popular option was demand management strategies, such as ridesharing programs. This solution however, also appears to fall short of addressing the problem. If demand management and supply augmentation couldn’t offer the solution to the increasing congestion rates, at least in their current formulation, then what would? A proposed solution that is gaining popularity focuses on land use planning, which could be thought of as long-term demand management. Reid Ewing concisely summarizes “As the stock in the other ideas—demand management and supply enhancement—has gone down, the stock of land use planning has gone up (2004). The

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term Smart Growth, has come to generalize this proactive land use planning, and is gaining in popularity. Generally speaking, our transportation needs are predominantly determined by the fixed locations we commute to. Therefore, transportation is inextricably linked to land use and, therefore, to programs such as smart growth.

The term Smart Growth does not have a set definition; however, some principles of smart growth have been proposed and offer a clear idea of the concept. Smart growth emphasizes the interaction between land use planning and transportation management. Some key ideas behind smart growth are outlined below.

Smart growth involves both:

Orderly Dispersion Recognition that growth will continue to occur but the goal must be to guide the development and the Accompanying transportation system improvements to optimize the use of the current transportation system and new system investments.

Functional Mobility To maintain a level of mobility so that the community still works—freight can move, employers still want to locate in the community, and residents still want to live there.

Some principals of Smart Growth are:

• Create a range of housing opportunities and choices. • Create walkable neighborhoods. • Encourage community and stakeholder collaboration. • Foster distinctive, attractive places with a strong sense of place. • Make development decisions predictable, fair, and cost-effective. • Mix land uses. • Preserve open space, farmland, natural beauty, and critical environmental areas. • Provide a variety of transportation choices. • Strengthen development and direct it toward existing communities.

Smart growth looks to address the congestion problem at its root source: sprawl. The current growth pattern for many American cities is large, single land use developments. Examples of this are strip malls, business parks, and suburb developments. These single land use developments force users to make separate trips to shop, work, and return home. Smart growth works to mix land uses in compact design patterns so that options aside from driving are much more appealing. A strong focus on smart growth in new land developments will help to ensure that the unnecessary driving created by urban sprawl is curbed.

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Another long term solution to congestion is to address the source of the increasing urban sprawl in America. American metropolitan areas have distinctly lower population densities than their global counter parts (Voith 1999). This low population density, as described above, contributes to congestion as people are living further and further away from their jobs. Richard Voith, a economic advisor in the research department of the Philadelphia Federal reserve bank, summarizes:

“Most observers of U.S. metropolitan development, with its low density and increasing concentration of low-income households in the center, assume that this pattern is simply a result of American preferences for open space, of the abundant supply of land, and of changes in transportation and communications technology. This pattern, however, may reflect not only people’s tastes and technological change but also the relative costs of housing and land, which, in part, reflect the tax advantages of owner-occupied housing. While mortgage interest and property taxes have long been deductible from federal income taxes, the value of these deductions for high-income households increased significantly in most of the second half of the century as marginal tax rates for these households increased (Voith 1999).”

Voith argues that US tax treatment affects household choices regarding where to live and how much land to consume. The deductibility of mortgage payments and property taxes from federal income taxes adds extra incentives for consumers to seek housing options outside of city limits where home ownership is more common. Estimates suggest that for U.S. metropolitan areas, the direct impact has lowered density about 15 percent (Voith 1999).

While Voith agrees that a variety of factors have contributed to the decrease in population densities in American metropolitan areas, the federal tax laws should not be one of them. Changing these regulations, along with urban redevelopment programs, is the first step to addressing the long term sources of congestion.

The next long term solution to congestion is an expansion of public transportation options paired with the intelligent transportations systems highlighted earlier. The topic of public transportation deserves more elaboration than this paper allocates. Instead, I will briefly review some statistics in favor of an expansion of mass transportation.

The Maryland Department of Transportation estimates that:

• A full rail car removes 200 cars from the road. • A full bus removes 60 cars. • A full van removes 12 cars. (Maryland Transit 1999)

According to an FTA study of six urban corridors served by high-capacity rail transit:

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• Public transportation passengers saved 17,400 hours daily over auto travel in the corridors. • Remaining road users in the corridors saved 22,000 hours of delay per day due to the absence of vehicles from public transportation users. • Travelers on surrounding roads in the corridors saved an additional 20,700 hours daily as spillover congestion was reduced. • These reductions represent a savings of $225 million annually in the six corridors analyzed.

(Transit Benefits 2000)

The FTA values the aggregate benefits from transit-related congestion relief at $19.4 billion annually. (Status Nation’s Highway 2000) Another study indicates that every dollar of public funds invested in public transportation returns up to $6 in economic benefits in urban regions. (Public Transportation 1999). These statistics offer insight into the cost efficiency of public transportation and its effect on congestion. Looking to the future, the solution to congestion will need to rely on public transportation to relieve the already overused highway system.

One final complication involved in long term solutions to the congestion problem is the role that the price of carbon will play. As we continue to recognize the ever increasing cost of emitting C02, it is obvious that price adjustments are a necessity. The regulation of carbon will dramatically affect the cost-benefit analyses associated with all decisions in the transportation field. This uncertainty leaves those planning for long term solutions to the various transportation problems in a difficult position.

A clear policy on carbon pricing would be advantageous towards the reduction of congestion in a variety of ways, most importantly by addressing consumer. When fuel accurately reflects its costs, the choice to live farther away from work becomes more costly. An unnecessary trip to distant shopping centers also becomes less appealing. The principles of smart growth become much more important and appealing. Furthermore, mass transportation will become even more cost efficient and those areas with transit options will be even more valued.

Long term solutions to congestion will involve multiple approaches to the problem. These solutions can be divided into changing our growth patterns, our transportation options, and our transportation valuation. No singular long term solution to congestion will be completely effective; instead an informed approach involving all three will yield the best result.

ANALYSIS OF SHORT-TERM SOLUTIONS

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Of the short term solutions taken into consideration, three have been calculated in terms of gallons of gas saved per year, CO2 emission and other gas emissions produced per gallon. The reduction of the FIFO system, the use of nationwide E-Z Pass, and No Left Turn act have been chosen as the major short term solutions. Due to past research for these short term solutions the estimated gallons of gasoline saved per year in 2008 are given. To further break down the amount of gallons of gasoline saved per year and to conceptualize the amount of CO2 emissions per gallon, a formula of 8.8 kg of CO2 per 1 gallon of gasoline is given. This formula yields numbers of 4,048,000,000kg CO2 saved for the reduction of the FIFO system, 10,560,000kg CO2 saved for the nationwide E-Z Pass, and 26,400,000kg CO2 saved for implementing the No Left Turn act. The emissions of CO2 makes up 95% of total emissions caused by gasoline, the other 5% involving N2O, CH4, and HFC are also calculated. Although the reduction of the FIFO system yields the highest number, the concept of bottlenecking is taken into account when observing the amount of gallons of gasoline saved per year. This concept of bottlenecking is later taken into account when calculating a raw estimation for the best short term solution for reducing congestion.

CO produced per Gallons of Gasoline 2 N2O, CH4, and HFCs Saved per Year gallon produced per gallon FIFO (United States) 460,000,000 gal 4,048,000,000 kg 202,400,000 kg EZ Pass (NY Metro Area) 1,200,000 gal 10,560,000 kg 528,000 kg Left Turn (UPS alone) 3,000,000 gal 26,400,000 kg 1,320,000 kg

Furthermore, an investigation is made to observe whether or not population played a major role in the selection of a short term solution. Atlanta, Georgia is taken into account for a large city and Nashville, Tennessee is taken for a medium city. These two cites, although heavily congested, differed by population and amount of peak travelers. A population of over 3 million people qualifies as a “large city” and a population of less than 1 million qualifies as a “medium city.” The publishing of these calculations are very rare, because research concerning the matter is considered proprietary in many cases. When calculating estimations there are some assumptions that are taken into consideration; the number of passengers occupying a vehicle is 1.25, the average fuel economy per vehicle is 20.3 mpg, and the numbers estimated only reflect those of passenger and light weight vehicles, not heavy trucks.

Once a number is given for the population of peak travelers per city, it is put into a formula to yield estimation for “Annual Fuel Listed.” That equation is given as:

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Annual Fuel Listed = (Travel Time) x (Average Peak Period System) ÷ (Average Fuel Economy) x (250 Working Days Per Year)

Knowing the total fuel listed gave enough information for calculating the amount of fuel listed for the implementation of the FIFO system, and the Total fuel saved utilizing the E-Z pass process. For the city of Atlanta, Georgia the Net Total of fuel listed after an implementation of the reduction of FIFO is an estimated 74,912,000 gallons of gasoline. That is a 20% decrease in the amount of fuel listed in Atlanta, Georgia in 2008. For the city of Nashville, Tennessee the Net Total of fuel listed after an implementation of the reduction of FIFO is an estimated 10,064,800 gallons of gasoline, that’s a 19% decrease in the amount of fuel isted in Nashville, Tennessee in 2008.

Net Total Fuel per Fuel Total fuel Populatio peak isted fuel saved Total Total Fuel n of peak traveler after isted with Populatio fuel isted isted by travelers s reducing after E-Z n (1000's) (gallons) FIFO (1000's) (gallons FIFO by reducing Pass ) 50% FIFO by (gallons 50% )

93,640,00 37,456,00 18,728,00 74,912,00 4,440 2,371 40 761,904 0 0 0 0

Estimated Fuel Listed for Very Large City Atlanta, Georgia

Net Total Fuel isted Population Fuel per fuel isted Total Total fuel Fuel after of peak peak after Population isted isted by reducing travelers travelers reducing (1000's) (gallons) FIFO FIFO by (1000's) (gallons) FIFO by 50% 50%

995 547 23 12,581,000 5,032,400 2,516,200 10,064,800

Estimated Fuel Listed for Medium City Nashville, Tennessee

In order to see the true outcome of the best short term solution, the Annual Cost Due to Congestion has been calculated. Knowing these numbers for our given short term solutions should give a glimpse on whether or not a change should be made to the given cites congestion problem. The formula for Annual Cost Due to Congestion is given as:

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Annual Cost Due to Congestion = (Annual Passenger Vehicle Delay Cost + Annual Passenger Fuel Cost) + Annual Commercial Cost

The outcome for the city of Atlanta, Georgia is given for a Normal case, a FIFO case, and an E-Z Pass case. For the outcome of the Normal case where no action would be taken place, Atlanta

showed a Congestion cost of $2,367,061,250 and a CO2 emission of 824,032,000 kg. For the outcome of the FIFO case Atlanta showed a Congestion cost of $2,312,375,490 and a CO2 emission of 659,225,600 kg. For the outcome of the E-Z Pass case Atlanta showed a Congestion

cost of $2,364,836,490 and a CO2 emission of 817,327,244.8 kg. The outcomes for the city of Nashville, Tennessee are given for a Normal case, a FIFO case, and an E-Z Pass case as well. For the outcome of the Normal case where no action would be taken place, Nashville showed a

Congestion cost of $350,217,430 and a CO2 emission of 3,081,913,384 kg. For the outcome of the FIFO case Nashville showed a Congestion cost of $351,394,530 and a CO2 emission of 3,092,271,864 kg. For the outcome of the E-Z Pass case Nashville showed a Congestion cost of

$355,733,139 and a CO2 emission of 3,130,451,624 kg. The numbers reflect that population has a definite effect on the short term solutions in the reduction of congestion. In a Very Large city such as Atlanta, Georgia, one that is heavily populated and congested, the use of a reduced FIFO system would greatly save money and reduce the cost of congestion. However, in Nashville, Tennessee keeping a normal case will still save the city money as it pertains to the cost of congestion over time.

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