Transportation Policies and Quality of Life: An Analysis of the Socioeconomic Effects of Implementing Ramp Metering, High Occupancy Vehicle (HOV) Lanes and High Occupancy (HOT) Lanes within an Urban Transportation Network
Date
2009-01-14T20:43:43Z
Authors
Jefferson, Katherine D.
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Abstract
Transportation policies affect a diverse group of stakeholders who depend on decision makers to provide a network within which they can achieve their travel objectives. Individuals and households with varying values of time and different levels of income expect to have access to a dependable transportation system. They expect reliable travel times to destinations, whether they are going to work or school, or engaging in leisure activities. Commercial interests hinge their success upon being able to move goods and provide services in a way that promotes sustainability and prosperity. When the travel activities of these disparate entities – individuals, households and businesses – occur in concert or in conflict with each other, traffic congestion is a common byproduct. Litman (2007) defines traffic congestion as the incremental delay resulting from interference among vehicles in the traffic stream as a roadway reaches its capacity. Weisbrod, Vary and Treyz (2001) also correlate vehicle delay and roadway capacity by asserting that traffic congestion is a condition of traffic delay that exists because the number of vehicles trying to use the roadway exceeds the traffic network’s capacity to handle them. These authors argue that traffic congestion has three dimensions of variation – spatial, temporal and stochastic. Cambridge Systematics (2005) links congestion to seven sources – traffic incidents, work zones, weather, fluctuations in normal traffic, special events, traffic control devices and physical bottlenecks or capacity. Three strategies that are used to mitigate the effects of traffic congestion are Ramp Metering, High Occupancy Vehicle (HOV) Lanes and High Occupancy Toll (HOT) Lanes. Ramp Metering is the use of traffic signals at freeway entrances to control the rate at which vehicles enter the freeway (Pearson, Black and Wanat 2001). HOV Lanes give priority for the use of entire roadways or specific travel lanes to vehicles with two or more occupants (and to motorcycles and hybrid vehicles in some instances). HOT Lanes allow Single Occupant Vehicles (SOVs) to access otherwise restricted roadways or travel lanes (typically HOV Lanes) by paying pre-established or variable tolls based on congestion conditions. Ramp Metering and HOT Lanes are categorized as Intelligent Transportation Systems (ITS)-enhanced strategies. All three strategies are purported to enhance freeway operations by decreasing travel time and improving trip reliability. However, Verhoef (1996) argues that there appears to be an inverse relationship between efficiency and effectiveness and the social feasibility of transportation regulation (policy approaches). Considering this assertion, one wonders how the three strategies mentioned above affect quality of life – safety, personal security and socioeconomic wellbeing. The socioeconomic effects of implementing Ramp Metering, HOV Lanes and HOT Lanes within an urban transportation network are examined to identify consequences, benefits and costs beyond (or in addition to) those typically obtained from traffic simulation models and field operational tests. Survey data and expert judgments (an electronic road user survey, a statistical analysis of survey responses, and a Planning Balance Sheet Assessment) are used to examine perceptions of and findings regarding the benefits and consequences of the three strategies. The analyses are also used to gather information to examine the premise that traditional tools and approaches (e.g. simulations of policy interventions and operational field test data) should be augmented with qualitative data to more adequately assess the quality of life concerns of transportation policy stakeholders. The results of the analyses reveal statistically significant associations between implementing Ramp Metering, HOV Lanes and HOT Lanes and quality of life considerations.
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Keywords
Ramp Metering, HOV Lanes, HOT Lanes, Quality of Life, Intelligent Transportation Systems, Socioeconomic Wellbeing