With the increased public awareness of a deepening energy crisis, governments at all levels have begun to examine their ability to act meaningfully in response to forms of short- and long-term energy-related political pressures. Emergency preparedness, conservation programs, and contingency planning have become watchwords in our new energy bureaus. The existence of a model provides an element of objectivity to the agency's policy pronouncements and, through the overlap in the energy agency's scope with that of other departments, the views of the energy agency are now made a part of regional development plans.This volume provides the tools to shape and implement community plans and programs relating to energy use in vehicular travel. Fully documented and effective fuel consumption forecasting models are clearly presented. These models range from static and flow adjustment equations delineating fuel consumption to analyses that explain patterns of change for vehicular use.This book shows the statistical procedures used to estimate the models, as well as the procedures used to test the models' significance. The authors include computer algorithms along with full, working examples; both are presented together with an analysis of all the principal alternative approaches. Finally, problems such as the distribution of fuel reserves to meet needs in particular areas within a jurisdiction are explored.
Table of Contents
1 INTRODUCTION 2 AGGREGATE STATE AND NATIONAL GASOLINE FORECASTING MODELS: A REVIEW OF THE LITERATURE, 3 MOTOR FUEL MODELING EFFORTS BY STATE, 4 STATE MOTOR FUEL FORECASTING MODEL: HISTORICAL, 5 THE RESEARCH DATA BASE. 6 ESTIMATION OF THE TRAVEL BEHAVIOR EQUATION 7 TESTING THE MODEL 8 DEVELOPING THE FORECASTS 137 9 THE CUPR GASOLINE FORECASTING PROGRAM 10 MODEL USES 11 TRAFFIC COUNT DATA: SOURCES AND PROCEDURES 12 SUMMARY OF STATISTICAL AND MATHEMATICAL TECHNIQUES USED IN STATE ENERGY MODELING 13 DATA SOURCES FOR TRANSPORTATION ENERGY MODELING
Jon H. Weyland is assistant administrator of the Office of Planning and Policy Analysis in the New Jersey Department of Energy. He has directed development of a statewide energy data management system as well as worked on development of energy-demand forecast models.