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Year - 2010

Defining the Shared Goals of the NYMTC Principals andRelated Future Trends

<p>NYMTC?s Princ ipals reached consensus on f ive Shared Goals to guide regional t ransport a t ion investment deci s ionmaking. The Shared Goa l s ref l ect broad agreement on the need f o r reg iona l approaches to compl e x issues facing the region. The Shared Goal s a re : ? Buil d t h e case for obt ai ni ng resources to impleme n t reg ional investmen t s; ? Enhance t h e regional environme n t ; ? Improve the reg ional e conomy; ? Improve the r egional qual i t y o f l ife; a n d ? Provide conveni en t , f lexible t r a nsportation access wi t h in the r egion.

Sensitivity Analyses of the Best Practice Model (BPM) in the New York Metropolitan Region (Part II)

<p>New York Metropolitan Transportation Council (NYMTC), an association of governments, transportation providers, and environmental organizations, handles the metropolitan transport ation planning throughout New York City, Long Island and the Lower Hudson Valley. In the early 1990s, NYMTC developed a transportation model, the New York Best Practices Model (NYBPM),&nbsp; in response to federal regulations on surface planning, specifically the Intermodal Surface Transportation Efficiency Act (ISTEA) and the Clean Air Act (CAA).

Multimodal Transportation Safety/Road Traffic Safety in African Countries - Status, Trend, Contributing Factors, Counter Measures and Challenges - Journal

<p>Road traffic crashes and injuries constitute major health, economic, and developmental challenges to African countries. For its 4 per cent of the world?s motor vehicles, the fatalities on African roads exceed 10%. With further motorization, the number of road traffic crashes, injuries and fatalities are expected to continue to grow. The road carnage has severe impact on the human, social and economic development. The present study intends to update the status, trends, causes, existing countermeasure, and issues in traffic safety, facing African countries.

Evaluating the feasibility of a passive travel survey collectionin a complex urban environment: Lessons learned fromthe New York City case study

The combination of increasing challenges in administering household travel surveys and advances in global positioning systems (GPS)/geographic information systems (GIS) technologies motivated this project. It tests the feasibility of using a passive travel data collection methodology in a complex urban environment, by developing GIS algorithms to automatically detect travel modes and trip purposes.

Modeling Air Quality and Energy Impacts of NYSDOT Highway ROW Management

Mowing the highway right-of-way is important for the safety of roadway users and maintaining
the highway infrastructure. However, little quantitative data are available on the energy use and air quality
impacts of highway mowing activities. In this report, fuel usage and exhaust emission rates are reported from
a study that monitored tractors operating in real-world conditions by the New York State Department of
Transportation. The emissions and fuel consumption from the mowing practices of twelve tractors were

Advanced Applications of Person-based GPS in an Urban Environment

Traditional travel surveys provide essential information on travel patterns, but are time-consuming, expensive, and have seen declining rates of participation. Recently global positioning systems (GPS) technologies have been introduced to facilitate the data collection process. While GPS traces can provide accurate information on the location and time of travel, these traces do not contain explicit information on the mode used (e.g., walking, biking, transit or auto).

Advanced Applications of Person-based GPS in an Urban Environment

Traditional travel surveys provide essential information on travel patterns, but are time-consuming, expensive, and have seen declining rates of participation. Recently global positioning systems (GPS) technologies have been introduced to facilitate the data collection process. While GPS traces can provide accurate information on the location and time of travel, these traces do not contain explicit information on the mode used (e.g., walking, biking, transit or auto).

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