Harnessing AI-driven behavioral analytics for sustainable urban mobility: an interdisciplinary approach to policy, planning, and user adaptation

Transportation in urban settings has undergone a revolution due to advances in technology, as well as the imperative to adopt eco-friendly transportation solutions. In this paper, we investigate the effectiveness of adopting artificial intelligence-powered behavioral analysis in promoting an effective transportation revolution in urban settings, combining an interdisciplinary approach that considers transportation research sciences and the perspectives of economic and transportation behavior. The effectiveness of artificial intelligence solutions in transport within the realm of research relates to understanding whether transport decision-making methodologies can create an ecosystem of intelligent transport by introducing artificial intelligence elements. We critically analyze whether machine intelligence solutions within artificial intelligence can enhance transport decision-making processes and encourage transport users to adopt eco-friendly transportation. Our findings indicate that artificial intelligence solutions can play a crucial role in creating an efficient transportation system by adapting to users’ preferences for more user-friendly transport solutions. At the same time, the limitations of artificial intelligence solutions, stemming from algorithmic challenges and data privacy concerns, underscore the need for an imperative solution that incorporates transport intelligence within an artificial intelligence framework. The paper provides an empirical analysis suggesting that artificial intelligence solutions in an environmental transport system should play a significant role in shaping users toward intelligent transport solutions. Our research supports the assumption that artificial intelligence solutions within intelligent transportation systems should prioritize the imperative of artificial intelligence in transportation solutions.