User preferences regarding autonomous vehicles

By Chana Joanne Haboucha, R. Ishaq, Yoram Shiftan. 2017

885 citations recorded by the source corpus.

Subfields: Automotive Engineering, Physical Therapy, Sports Therapy and Rehabilitation, Social Psychology

View Paper: https://www.semanticscholar.org/paper/d4f179fcf14706befd460df28a27ddf8722a2889

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Guanqiu Qi
2. Lanhui Cai
3. Xueqin Wang
4. Kum Fai Yuen
5. Yuji Shi
6. Bin Ran
7. Sherali Zeadally
8. Hao Huang

In Physical Therapy, Sports Therapy and Rehabilitation

1. Miltos Kyriakidis
2. Riender Happee

In Social Psychology

1. Miltos Kyriakidis
2. B. van Arem
3. Sina Nordhoff
4. Riender Happee
5. R. Acheampong

Citations in the corpus

• Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory (2020, background): “Haboucha, Ishaq, and Shiftan (2017) conclude that early AVs adopters will likely be younger, more educated, and spend more time driving, based on an investigation of the acceptance of AVs in Israel and North America.”
• Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China (2019, background): “In the early stage of AV technology, traffic congestion might not be improved and even worsened due to congestion-inducing effects of shared fleets of AVs and mixed traffic fleet condition [12,13].”
• A multi-level model on automated vehicle acceptance (MAVA): a review-based study (2019, background): “(2017) who found that tech-savvy individuals are likely to be early adopters of AVs, and with Haboucha, Ishaq, and Shiftan (2017) who found that individuals with a higher interest in technology were more likely to choose AVs.”
• Capturing the behavioural determinants behind the adoption of autonomous vehicles: Conceptual frameworks and measurement models to predict public transport, sharing and ownership trends of self-driving cars (2019, background): “Previous studies (see e.g. Woldeamanuel and Nguyen, 2018; Sanbonmatsu et al., 2018; Daziano et al, 2017; Haboucha et al., 2017; Nair et al., 2017; Bansal et al., 2016; Lavieri et al., 2017; Bansal and Kockelman, 2017; Lavasani et al., 2016; Kyriakidis, et al., 2015; Adnan et al., 2018; Umberger, 201”
• Autonomous Cars: Research Results, Issues, and Future Challenges (2019, background): “being heavily discussed in the research community, needs to be able to handle issues such as a dashboard design, geometry, and space distribution for the hardware [84], [160]–[162].”