Each year, traffic conditions continue to worsen around the world due to growing populations, denser concentrations in urban areas, and deteriorating road conditions. Traffic congestion contributes to negative outcomes on every scale of the economy -- global greenhouse gas emissions and atmospheric pollution, millions of dollars lost annually in commute times and vehicle repairs, and even stress-related health problems on the individuals affected. Of the ten major cities in USA that have the highest levels of congestion and impacted travel times, six are located in the western region of the country. This paper will analyze the contributing factors such as travel distance, urban and commuter populations, and public transportation utilization to correlate their effects on overall commute time, congestion percentages and costs, and the health impacts on the communities in those six cities. It is observed that these factors that contribute to congestion levels are interdependent, and therefore cannot be individually isolated for study. It is for this reason that a Data Envelopment Analysis approach was utilized to analyze the traffic system performances and their relative efficiency, in order to determine which cities perform better than others and for what reasons. However, it was discovered that all six cities perform the same, for good or bad, yielding a relative efficiency, E, of 1.0 each, implying that there is no distinguishing feature or pattern of any one city over another, as related to traffic performance.
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