应用手机数据监测赛车重大赛事期间的上座率。伊莫拉一级方程式大奖赛案例

IF 2.4 Q3 TRANSPORTATION Case Studies on Transport Policy Pub Date : 2024-08-28 DOI:10.1016/j.cstp.2024.101287
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引用次数: 0

摘要

近年来,智能手机等联网设备的出现对城市面貌产生了变革性影响。一旦隐私问题得到解决,就可以对数据进行熟练的处理和分析,深入了解其模式和移动情况,从而对城市政策产生影响。在手机大数据领域,与流动性和交通相关的主题很可能是最广泛的调查对象。虽然许多作者对通勤模式这一主题进行了广泛研究,但有关大型赛车活动期间观众人数监测的文献却很少。尽管人流具有可预测性(门票提前售出,赛程固定且严格),但多日赛车活动在交通、过度拥挤和令主办城市不安等方面具有破坏性。本文旨在通过对 2022 年 4 月 22 日至 24 日在意大利伊莫拉举行的一级方程式艾米利亚-罗马涅和意大利制造大奖赛期间观众人数的监测案例研究,填补上述空白。研究结果表明,数据可以为预测交通选择和规划适当的交通相关政策提供信息,从而减少未来赛事的影响。这对公共管理部门和利益相关者来说是一项重大挑战。
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Application of cell phone data to monitor attendance during motor racing major event. The case of Formula One Gran Prix in Imola

The advent of connected devices, such as smartphones, has had a transformative impact on the landscape of recent years. Once privacy concerns have been addressed, data can be handled and analysed in a proficient manner to gain insights into patterns and movements, thereby influencing urban policies. It is likely that mobility and transport-related topics have been the subject of the most extensive investigation in the field of cell phone big data. While the topic of commuting patterns has been extensively researched by numerous authors, there is a paucity of literature on the monitoring of attendance during major motorsport events. Despite the predictability of crowding (tickets are sold in advance and the schedule is fixed and rigid), multiday motorsport events are disruptive in terms of traffic, overcrowding and uneasiness for hosting cities. This paper aims to address the aforementioned gap by presenting a case study of monitoring attendance during the Formula One Emilia-Romagna and Made in Italy Grand Prix, held in Imola, Italy, from 22nd to 24th April 2022. The results demonstrated the potential of data to inform the prediction of mobility choices and the planning of appropriate mobility-related policies, with the aim of reducing the impact of future events. This represents a significant challenge for public administrations and stakeholders.

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CiteScore
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12.00%
发文量
222
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