MARKET ADOPTION AND IMPACT OF ELECTRIC ROADWAYS ON CRITERIA POLLUTANTS AND GREENHOUSE GAS EMISSIONS
Traffic is inevitably a major source of air pollution, particularly in urban areas. Efforts are made towards reducing emissions by improving vehicle and fuel technology and promoting alternative, sustainable modes of transportation. Although the emergence of EVs has shown capabilities of decreasing energy use and emissions levels, the EV market is developing slowly mainly due to drivers’ range anxiety and charging time. Electric roadways (ERs) have been proposed as a solution to overcome the concerns related to EVs by converting road segments into powered lanes where vehicles can be charged as they move along the roadway. This technology has the potential to increase driving range, decrease battery size and thus, lower the weight and the cost of EVs. In this context, exploring the challenging concept of ERs comes natural.
Since data on the market acceptance and the environmental implications on this technology are limited to non-existent, this thesis has the following objectives: 1) identify the factors that affect the short- and long-term intention to use ERs, 2) estimate the level of adoption of the ER technology and identify characteristics of the market segments and 3) assess the impact of ERs on criteria pollutants and greenhouse gas emissions based on the market adoption results.
To achieve these objectives, a survey of the general population in Los Angeles, California was conducted, gathering 600 responses representative of gender and age in the area. Los Angeles is considered a leader in electro-mobility and thus, a natural choice for the implementation of ERs. The short-or long-term intentions to drive on ERs and purchase an EV knowing about the availability of ERs were found to be correlated and thus, were modeled simultaneously using a bivariate ordered probit model. The compatibility of the ER technology with respondents’ lifestyle and needs, respondents’ tendency towards using sustainable forms of transportation, respondents’ innovativeness and perceived environmental benefits were among the most significant variables found to affect the short-term and long-term intention to use ERs.
The level of adoption of the ER technology and corresponding market segments were identified using a combination of Principal Component Analysis (PCA) and Cluster Analysis. Three clusters emerged from the analysis: early adopters (48.5%), mid-adopters (27.67%) and late adopters (23.83%) that differed in terms of demographics and socioeconomic characteristics, travel and EV charging characteristics and level of awareness.
The adoption levels found were then used to estimate the emissions change due to the implementation of the ERs by 2050. Using the California Air Resources Board’s (CARB) 2017 EMissions FACtor model (EMFAC). Two scenarios were examined considering light-duty vehicles (LDVs) in a specific corridor: “with” and “without electrification” scenarios. The results suggested that the ER technology for light-duty vehicles has the potential to provide emission reductions of 4 to 24%. A sensitivity analysis was also conducted to examine the effect of speed on the results.
Turning to the practical implications, this thesis can provide a foundational framework for the evaluation of the ER technology in terms of environmental and economic viability and set the groundwork for future research. Ultimately, the short-term and long-term intention analysis can be used as a draft guide by state and local agencies and inform their strategic short- or long- range plans for mobility. By segmenting potential users, policy makers and transport operators can be informed about the main challenges regarding the promotion of the ER technology to distinct market segments and devise ways to accelerate its adoption. The findings from the impact analysis of ERs on criteria pollutants and greenhouse gases can also inform long-range transportation plans and existing regulations and policies in California and beyond.