Towards Fairness-aware Crowd Management System and Surge Prevention in Smart Cities

TL;DR

This paper introduces fairness-aware crowd management strategies in smart cities, including inclusive evacuation plans and proactive crowd dispersion techniques, validated through simulations to improve safety and fairness during large events.

Contribution

It presents novel methodologies for fair evacuation and surge prevention in crowd management, addressing inclusivity and safety in smart city environments.

Findings

Fair evacuation strategy increases fairness by 41.8%.

Adjusting attraction locations reduces surges by 34%.

Proposed methods improve overall crowd safety.

Abstract

Instances of casualties resulting from large crowds persist, highlighting the existing limitations of current crowd management practices in Smart Cities. One notable drawback is the insufficient provision for disadvantaged individuals who may require additional time to evacuate due to their slower running speed. Moreover, the existing escape strategies may fall short of ensuring the safety of all individuals during a crowd surge. To address these pressing concerns, this paper proposes two crowd management methodologies. Firstly, we advocate for implementing a fair evacuation strategy following a surge event, which considers the diverse needs of all individuals, ensuring inclusivity and mitigating potential risks. Secondly, we propose a preventative approach involving the adjustment of attraction locations and switching between stage performances in large-crowded events to minimize the occurrence of surges and enhance crowd dispersion. We used high-fidelity crowd management simulators to assess the effectiveness of our proposals. Our findings demonstrate the positive impact of the fair evacuation strategy on safety measures and inclusivity, which increases fairness by 41.8% on average. Furthermore, adjusting attraction locations and stage performances has shown a significant reduction in surges by 34% on average, enhancing overall crowd safety.