Suggested Citation:
Jaller, Miguel, Leticia Pineda, Yasar Gueldas, Farzad Alemi, Irem Otay (2020) Fostering the Use of Zero and Near Zero Emission Vehicles in Freight Operations. Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-20-42

California is in the midst of improving its freight system. For example, the California Sustainable Freight Action Plan (CSFAP) established the goal of reaching a 25% increase in freight efficiency, the use of 100,000 zero emission vehicles and equipment (and maximize the number of near zero emission vehicles) in the system, and improving economic competitiveness. Although there are multiple strategies and approaches to help achieve these goals, this study focuses on analyzing the factors to foster the adoption of zero and near-zero emission vehicles. For example, the use of monetary and non-monetary incentives to elucidate behavioral changes (e.g., fleet purchase decisions). This study considered compressed (renewable) natural gas (CNG/RNG), hybrid electric (HE), battery electric (BE) and fuel-cell hydrogen (H2) vehicles. The research team collected information through a web-based stated preference survey sent (in two waves) to fleets and carrier companies to gather data about their economics, and their vehicle purchase preferences. However, the response rate was very small which limited the type of analyses conducted with the data. Alternatively, the study team developed a multi-criteria decision-making tool using a Spherical Fuzzy Analytical Hierarchy Process based on experts’ knowledge. The approach considered the variability in the technical and operational characteristics, market readiness, and other factors related to these technologies. The model helped provides insights about the most appropriate options for different uses (e.g., last mile, long-haul distribution). Specifically, the authors evaluate the alternatives using five criteria: economic; business, incentives & market-related; environmental & regulatory; infrastructure; and safety & vehicle performance factors. The analyses also consider twenty-one sub-criteria, e.g., total cost of ownership, payback period, brand image, financial & non-financial incentives, and public/private fueling/ charging infrastructure availability.

Key words: Last mile distribution, Behavioral modeling, Zero emission vehicles, Incentive programs, Expert decision modeling