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AI research explores transportation behavior in smart cities

By PulseAugur Editorial · [1 sources] ·

This chapter explores the application of artificial intelligence (AI) to understand and manage transportation behavior within sustainable smart cities. It proposes a behavior-centered AI approach, treating mobility data and passenger feedback as evidence rather than absolute truth. The research outlines four key areas: predicting bus arrivals, discovering taxi mobility patterns, detecting abnormal behavior, and mining passenger-perceived risks. These are integrated into a closed-loop framework that emphasizes data quality, privacy, fairness, interpretability, and human accountability for successful deployment. AI

IMPACT This research outlines a framework for using AI to improve urban transportation efficiency and passenger experience.

RANK_REASON Academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI research explores transportation behavior in smart cities

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Academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Junbiao Pang, Muhammad Ayub Sabir, Fatima Ashraf ·

    Artificial Intelligence for Understanding and Managing Transportation Behavior in Sustainable Smart Cities

    arXiv:2607.17694v1 Announce Type: new Abstract: Urban transportation systems generate heterogeneous data, yet these data do not automatically become actionable management intelligence. This chapter adopts a behavior-centered perspective on artificial intelligence (AI), treating m…

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