FRAMEWORK FOR EVALUATING TRANSPORTATION CONTROL MEASURES: ENERGY, AIR QUALITY, AND MOBILITY TRADEOFFS

Transportation planners, engineers, and air quality analysts are increasingly understanding the need for coordinated efforts in providing efficient and effective transportation systems while addressing serious energy and environmental concerns. Policies must be issued based on broad, coordinated efforts in transportation, air quality, and energy consumption so that optimal strategies for all three components can be implemented. At present, however, transportation planning and air quality analysis models are rather incompatible. Emissions models require detailed inputs which are not generally provided by transportation planning and analysis tools. Traditionally, transportation planning is comprised of four stages: trip generation, trip distribution, mode choice, and network assignment. In general, a forecast population, auto ownership, employment, and land use are inputs into the stages sequentially. This planning process does not adequately account for the manner in which individuals make travel decisions. The only travel-related decision that can be predicted using this traditional planning method is the mode of travel, while transportation control measures (TCMs) affect trip generation and trip distribution as well as route and mode choice. Variables required for emissions estimation have not routinely been components of transportation planning models. What is needed is a methodology for combining transportation planning and analysis models with emissions factor models for predicting the effectiveness of various TCMs. A matrix of strategies that produce the greatest savings in air emissions and energy consumption can then be developed. The project first reviews different types of emissions and TCMs, and then develops a macro-analysis model--a unified framework--that links the transportation planning and air quality analysis models. The framework can then be used to evaluate, comparatively, the impact of various transportation control measures, which influence either travel time or travel cost, on transportation-related emissions and energy consumption. The application of the macro-framework is demonstrated through analyses of two sample networks. The results show that the effectiveness of a TCM depends on the characteristics of the urban environment in which it is implemented. Failure to analyze the implication of a TCM prior to its implementation may yield results inconsistent with environmental and energy policy objectives. In addition, the results show that the choice of an emissions model is very critical in air quality analysis. The inclusion of an inferior emissions estimation model may result in biased conclusions.

• Supplemental Notes:
  • Supported by a grant from the Office of the Governor of the State of Texas, Energy Office.
• Corporate Authors:

  University of Texas, Austin

  Center for Transportation Research, 3208 Red River Street
  Austin, TX  United States  78705

  Southwest Region University Transportation Center

  Texas A&M University
  3135 TAMU
  College Station, TX  United States  77843-3135
• Authors:
  • Euritt, M A
  • Qin, Jin
  • Meesomboon, J
  • Walton, C M
• Publication Date: 1994-7

Language

• English

Media Info

• Features: Appendices; Figures; References; Tables;
• Pagination: 112 p.

Subject/Index Terms

• TRT Terms: Air quality; Air quality management; Alternatives analysis; Energy consumption; Environmental policy; Mobility; Pollutants; Simulation; Transportation planning; Travel demand management
• Uncontrolled Terms: Emissions models
• Old TRIS Terms: Macro-analysis models
• Subject Areas: Energy; Environment; Highways; Planning and Forecasting; Policy; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 00669061
• Record Type: Publication
• Report/Paper Numbers: SWUTC/94/60034-1
• Contract Numbers: 0079
• Files: TRIS
• Created Date: Nov 30 1994 12:00AM