Consumer Preferences and Willingness to Pay for Advanced Vehicle Technology Options and Fuel Types

At the time of publication J. Shin and C.R. Bhat were at the University of Texas at Ausitn. V.M. Garikapati and D. You at Arizona State University, and R.M. Pendyala at Georgia Institute of Technology.The automotive industry is witnessing a revolution with the advent of advanced vehicular technologies, smart vehicle options, and fuel alternatives. However, there is very limited research on consumer preferences for these types of vehicles. But the deployment and penetration of advanced vehicular technologies in the marketplace, and planning for possible market adoption scenarios, calls for collection and analysis of consumer preference data related to these emerging technologies. This study aims to address this gap, offering a detailed analysis of consumer preference for alternative fuel types and technology options using data collected in choice experiments conducted on a sample of consumers in South Korea. The results indicate that there is considerable heterogeneity in consumer preferences for various smart technology options such as wireless internet, vehicle connectivity, and voice command features, but relatively little heterogeneity in the preference for smart vehicle applications such as real-time traveler information on parking and traffic conditions.Civil, Architectural, and Environmental Engineerin

On the needs and requirements arising from connected and automated driving

Future 5G systems have set a goal to support mission-critical Vehicle-to-Everything (V2X) communications and they contribute to an important step towards connected and automated driving. To achieve this goal, the communication technologies should be designed based on a solid understanding of the new V2X applications and the related requirements and challenges. In this regard, we provide a description of the main V2X application categories and their representative use cases selected based on an analysis of the future needs of cooperative and automated driving. We also present a methodology on how to derive the network related requirements from the automotive specific requirements. The methodology can be used to analyze the key requirements of both existing and future V2X use cases