Alec Biehl

With mounting concerns over climate change and the environmental impact of fossil fuels, the United States has witnessed a growing interest in alternative fuel vehicles (AFVs). In 2021, approximately 1.5 million battery EVs (BEVs), 0.8 million plug-in hybrid EVs (PHEVs), and 5.5 million hybrid EVs (HEVs) were registered in the United States. In the state of New York, a total of 51,900 BEVs, 44,600 PHEVs, and 221,600 HEVs were registered in 2021. The current report presents the results of an analysis of AFV adoption patterns in New York State and the rest of the United States based on data from the 2017 National Household Travel Survey (NHTS). Overall, the report reveals the demographics and mobility factors (e.g., household income, homeownership, and trip length) that contribute to the adoption of AFVs. This study provides insights that can inform policy decisions aimed at promoting sustainable transportation solutions.The 2017 NHTS data showed that the percentage of households owning at least one AFV is lower in New York City compared with that in other regions of New York State. From the NHTS samples, of the 25 households that owned at least one BEV in New York State, 15 households (60%) lived within a 5-milemore » radius, based on the great circle distance, of the nearest charging station, and 23 households (92%) lived within a 10-mile radius of the nearest charging station. Furthermore, among the 40 households in New York State that own at least one PHEV, 48% (19 households) lived within a 5-mile radius of the closest EV charging station, and 83% (33 households) lived within a 10-mile radius of the nearest charging station. The rest of the United States had a higher percentage of households that own at least one AFV compared with that of New York State. A comparison was made between EV adoption levels using NHTS and EValuateNY, which is a tool that gathers statistics on the electric car market in New York State. The estimates obtained from New York State household samples in NHTS were slightly lower than the data provided by EValuateNY. In New York State and the rest of the United States, households with higher incomes tended to have a higher proportion of AFV ownership compared with those with lower incomes. For example, households in New York State earning $150,000 or more had an approximately 6% share of owning at least one AFV, which was markedly higher than those earning less than $100,000 (less than 3%). Additionally, homeowners in New York State and the rest of the United States also exhibited a significantly higher share of AFV ownership compared with that of renters. In New York State, households that own at least one AFV tended to travel farther and had longer travel times compared with their counterparts without an AFV. In terms of households with at least one AFV, households with HEVs tended to have more person trips, longer person miles of travel, and more vehicle miles traveled, resulting in longer travel times than that of households with BEVs or PHEVs. Notably, households with AFVs had a slightly lower share of family and personal business trips but a higher share of social and recreational trips compared with households without AFVs. Additionally, households with at least one AFV tended to have a slightly higher share of walking trips than their counterparts without an AFV. However, the comparisons were not statistically significant. These travel patterns observed in New York State were consistent with those observed in other regions of the United States. « less

The U.S. Department of Energy's Office of Scientific and Technical Information

Airport ground access mode choice is distinct from everyday mode choice decisions, necessitating context-specific choice model estimation. Understanding airport ground access mode choice decisions is not only important for developing infrastructure planning strategies, but also for assessing the impacts of emerging modes on airport revenues, particularly from parking. However, parking choice is an often-overlooked dimension in airport ground access choice modeling. This paper addresses this gap through the development of a joint model of airport access mode and parking option choice using a passenger survey conducted at Dallas-Fort Worth (DFW) International Airport in 2015. Compared with a traditional conditional logit model that does not consider parking options available at DFW airport, the joint model of mode and parking decisions was found to generate more realistic values of travel time and was shown to have better predictive performance, both of which are critical for obtaining better airport parking revenue estimates and identifying traveler cohorts who may respond more strongly to potential policies targeting curb congestion and parking demand.