Self-Driving Technology and Its Acceptance: Explaining Differences in Reactions of the Heterogeneous Population to Potential Policies
研究视觉提示和认证要求两项政策如何通过影响信任来改变不同政治立场人群对自动驾驶汽车的接受度，发现联合政策最有效。
Self-driving vehicles have the potential to drastically reduce accidents caused by human errors, saving significant amounts of money in damages as well as human lives. However, public acceptance of the technology operating on public roads still needs to improve, as most Americans are uncomfortable sharing the road with a self-driving vehicle. The challenge for policymakers is to craft regulations that not only enhance the safety of self-driving technology but also foster public trust and acceptance. This study examines how specific policies—requiring visual cues to indicate when a vehicle is operating in self-driving mode and certification requirements for users—impact public acceptance of self-driving vehicles. To evaluate the impact of the policies, we theorize how policies may influence people's trust and how trust, in turn, may affect acceptance of the technology. Furthermore, we examine how these effects vary across political affiliations, as prior research suggests that Republicans and Democrats differ in their trust in government oversight and technological innovation. Our findings confirm that Republicans are generally less willing to share the road with self-driving vehicles than Democrats, largely due to lower trust in the government to regulate the technology effectively. We find that a visual cue policy increases trust in government but decreases trust in the technology, leading to increased acceptance among Republicans but a neutral or negative effect for Democrats. Conversely, a certification requirement increases trust in government and in other drivers, positively impacting acceptance for both Republicans and Democrats. Finally, additional analysis revealed that a combined policy implementing both measures proves to be the most effective at increasing overall public acceptance by strengthening trust across multiple dimensions. These insights provide valuable guidance for policymakers seeking to improve the integration of self-driving vehicles into public roadways.