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San Francisco, CA, United States

Wu D.,Cambridge Systematics | Sall E.,San Francisco County Transportation Authority | Newhouse S.,AC Transit
Transportation Research Record | Year: 2012

Planners have developed an appetite for complex and multifarious models to match the intricacy of the questions being asked. For the most part, these new models, such as the currently popular activity-based modeling framework, are seamlessly backward compatible with all the previous questions that planners still ask from time to time. However, a seemingly simple question was recently raised in San Francisco, California, and the San Francisco County Transportation Authority's advanced, state-of-the-art activity-based model SF-CHAMP (San Francisco Chained Activity Modeling Process) was not equipped to handle it gracefully. This paper documents a methodology used to create a schedule of the auto trip rates from the SF-CHAMP activity-based travel demand model. The linear regression methodology uses outputs from the SF-CHAMP model along with simple accessibility variables to account for the wide variations in vehicle trip rates across the city and to provide a nexus between trip generation rates and the context of their origins or destinations. This approach combines the desired simplicity of auto trip generation rates in the local context of San Francisco and sensitivity to a set of accessibility variables comprehensible to humans. Source

Schneider R.,University of California at Berkeley | Henry T.,Fehr and Peers Transportation Consultants | Mitman M.,Fehr and Peers Transportation Consultants | Stonehill L.,San Francisco Municipal Transportation Agency | Koehler J.,San Francisco County Transportation Authority
Transportation Research Record | Year: 2012

The process of modeling pedestrian volume in San Francisco, California, refined the methodology used to develop previous intersection-based models and incorporated variables that were tailored to estimate walking activity in the local urban context. The methodology included two main steps. First, manual and automated pedestrian counts were taken at a sample of 50 study intersections with a variety of characteristics. A series of factor adjustments was applied to produce an estimate of annual pedestrian crossings at each intersection. Second, log-linear regression modeling was used to identify statistically significant relationships between the estimate of annual pedestrian volume and land use, transportation system, local environment, and socioeconomic characteristics near each intersection. Twelve alternative models were considered, and the preferred model had a good overall fit (adjusted R 2=.804). As identified in other communities, pedestrian volumes were positively associated with the number of households and the number of jobs near each intersection. This San Francisco model also found significantly higher pedestrian volumes at intersections (a) in high-activity zones with metered on-street parking, (b) in areas with fewer hills, (c) near university campuses, and (d) under the control of traffic signals. Because the model was based on a relatively small sample of intersections, the number of significant factors was limited to six. Results are being used by public agencies in San Francisco to understand the risks of pedestrian crossings better and to inform citywide pedestrian safety policy and investment. Source

Brisson E.,San Francisco County Transportation Authority | Sall E.,San Francisco County Transportation Authority | Ang-Olson J.,ICF International
Transportation Research Record | Year: 2012

Although several studies analyze strategies for reducing transportation's contribution to greenhouse gas (GHG) emissions, few do so at the local level, particularly for a city such as San Francisco, California, that is already a leader in climate-friendly transportation. This study examined nine GHG-reducing strategies within the San Francisco context, where local ordinance establishes a goal to reduce the city's GHGs 80% below 1990 levels by 2050. Strategies that were analyzed included infrastructure improvements, expansion of demand management policies including pricing, and accelerated penetration of electric vehicle technology. The study used a combination of travel demand model and sketch-planning methods to estimate the effectiveness and cost-effectiveness of strategies in reducing GHGs and their cumulative ability to achieve San Francisco's goal. The analysis results showed roadway pricing and electric vehicle strategies to have had the largest potential to reduce GHGs, although these two strategies differed significantly in cost-effectiveness. The results also showed that strategies involving share costs between public sector, private sector, and individuals had great promise in delivering reductions. Although investments in transit alone may not produce large GHG reductions, they are necessary to accommodate the mode shift of other strategies and can be paired strategically with pricing strategies. According to analysis results, San Francisco's policy goals appeared unachievable, even with ambitious assumptions about funding and policy change. These findings point to the need for policy change at a higher scale and for unprecedented changes in individual behavior to achieve GHG goals. Source

Gallivan F.,ICF International | Sall E.,San Francisco County Transportation Authority | Hesse E.,Tri County Metropolitan Transportation District of Oregon TriMet | Salon D.,University of California at Davis | Ganson C.,Governors Office of Planning and Research
Transportation Research Record | Year: 2012

Methods to attribute greenhouse gas emissions from transit vehicles across cities in a multijurisdictional region are explored. Four methods and one submethod are proposed, tested, and evaluated with real-world data from the Bay Area Rapid Transit District, serving the San Francisco Bay Area, California, and the Tri-County Metropolitan Transportation District of Oregon, serving the Portland area. Each methodology is evaluated on the basis of the likely availability of necessary data, ease of calculation, policy implications, and accuracy. Method 1 allocates emissions on the basis of each jurisdiction's total population and employment as a share of population and employment from all of the region's jurisdictions that have transit access. Method 2 allocates emissions on the basis of each jurisdiction's share of vehicle revenue miles traveled within the jurisdiction. Method 3 allocates emissions on the basis of each jurisdiction's share of linked transit trip origins and destinations weighted by trip distances. Method 4 allocates emissions on the basis of each jurisdiction's share of boardings and alightings. The methods have clear differences in the amount and type of data and the complexity of calculations required. These differences can be readily compared with the data and analytical resources available to a region to provide a partial ranking of methods. Questions of fairness, accuracy, and policy incentives are complicated by theoretical challenges in assigning responsibility for transit service as well as by the unique urban and transportation contexts of each region. Each region will need to select the method that is most appropriate for its unique circumstances in order to achieve intraregional consistency. Source

Dannenberg A.L.,University of Washington | Ricklin A.,Planning and Community Health Research Center | Ross C.L.,Georgia Institute of Technology | Schwartz M.,San Francisco County Transportation Authority | And 3 more authors.
Transportation Research Record | Year: 2014

A health impact assessment (HIA) Is a tool that can he used to inform transportation planners of the potential health consequences of their decisions. Although dozens of transportation-related HIAs have heen completed in the United States, the characteristics of these HIAs and the interactions between public health professionals and transportation decision makers in these HIAs have not been documented. A master list of completed HIAs was used to identify transportation-related HIAs. Seventy-three transportation-related HIAs conducted in 22 states between 2004 and 2013 were identified. The IHAs were conducted for projects such as road redevelopments, bridge replacements, and development of trails and public transit. Policies such as road pricing, transit service levels, speed limits, complete streets, and safe routes to schooLs were also assessed. Five HIAs In which substantial interactions between public health and transportation professionals took place during and after the HIA were examined in detail and included HIAs of the road pricing policy in San Francisco, California; a bridge replacement in Seattle, Washington; new transit lines in Baltimore, Maryland, and Portland, Oregon; and the BeltLine transit, trails, and parks project in Atlanta, Georgia. Recommendations from the HIAs led to changes in decisions in some cases and helped to raise awareness of health issues by transportation decision makers in all cases. HIAs arc now used for many topics in transportation. The range of involvement of transportation decision makers in the conduct of HIAs varies. These case studies may serve as models for the conduct of future transportation-related HIAs, becanse the involvement of transportation agencies may increase the likelihood that an HIA will influence subsequent decisions. Source

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