Jeremy Keith Hackney

LIFE CYCLE MODEL OF ALTERNATIVE FUEL VEHICLES: EMISSIONS, ENERGY, AND COST TRADE-OFFS

This paper describes a life cycle model for performing level-playing field comparisons of the emissions, costs, and energy efficiency trade-offs of alternative fuel vehicles (AFV) through the fuel production chain and over a vehicle lifetime. The model is an improvement over previous models because it includes the full life cycle of the fuels and vehicles, free of the distorting effects of taxes or differential incentives. This spreadsheet model permits rapid analyses of scenarios in plots of trade-off curves or efficiency frontiers, for a wide range of alternatives with current and future prices and levels of technology. The model is available on request. The analyses indicate that reformulated gasoline (RFG) currently has the best overall performance for its low cost, and should be the priority alternative fuel for polluted regions. Liquid fuels based on natural gas, M100 or M85, may be the next option by providing good overall performance at low cost and easy compatibility with mainstream fuel distribution systems. Longer term, electric drive vehicles using liquid hydrocarbons in fuel cells may offer large emissions and energy savings at a competitive cost. Natural gas and battery electric vehicles may prove economically feasible at reducing emissions and petroleum consumption in niches determined by the unique characteristics of those systems.

Predicting road system speeds using spatial structure variables and network characteristics

Spatial regression is applied to GPS floating car measurements to build a predictive model of road system speed as a function of link type, time period, and spatial structure. The models correct for correlated spatial errors and autocorrelation of speeds. Correlation neighborhoods are based on either Euclidean or network distance. Econometric and statistical methods are used to choose the best model form and statistical neighborhood. Models of different types have different coefficient estimates and fit quality, which might affect inferences. Speed predictions are validated against a holdout sample to illustrate the usefulness of spatial regression in road system speed monitoring.

Die Verbindung zwischen Verkehrsplanung und sozialen Netzwerken

Die Verkehrsplanung versucht die Entscheidung von Personen wahrend der Ausfuhrung von Aktivitaten des taglichen Lebens zu beschreiben, zu verstehen und zu modellieren (Ortuzar und Willumsen 2001). Das zugrunde liegende Paradigma dabei ist, dass das Individuum versucht, seine Bedurfnisse zu befriedigen, wahrend es seinen Nutzen durch die Ausubung von Aktivitaten maximiert. Dazu mussen unterschiedliche Orte aufgesucht werden. Dabei werden in der Verkehrsplanung hauptsachlich die Raumnutzungsstrukturen, welche Aktivitaten ermoglichen, die generalisierten Kosten der Nutzung der verfugbaren Infrastrukturen, welche Zugang zu den Raumnutzungsstrukturen schaffen und die Eigenschaften der Personen als Randbedingungen betrachtet. Lange Zeit waren Aspekte sozialer Interaktionen keine Erklarungsansatze fur das Verkehrsverhalten. Dies lag vor allem an den Schwierigkeiten, solche Daten zu erheben und der Darstellung von Verkehr als zonenaggregierte Herkunfts-Zielortflusse, welche fur die Bedurfnisse der Raumplanung als zufriedenstellend prazise angesehen wurden.