Optimising passenger flows through stations

优化车站客流

• 批准号: 10002738
• 金额: $ 12.23万
• 依托单位: HITACHI EUROPE LIMITED
• 依托单位国家: 英国
• 项目类别: Small Business Research Initiative
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10002738
• 关键词: Optimising; passenger; flows; through; stations

**Background**Railway companies have introduced zone marking on some station platforms to assist passenger boarding; although it is not clear that the way this is currently implemented is either understood by passengers or proving effective. Consequently, passengers are frequently not distributed optimally along the platform; and this results in congestion at train doors and longer than necessary boarding times as embarking passengers need to wait for disembarking passengers to leave the carriage before they can board. This issue is compounded when trains are delayed, especially at busy interchange stations. Our proposed solution will visually guide embarking passengers to demarcated zones on the platform based on the number of passengers leaving each carriage, to minimise the overall train boarding time and avoid “herd behaviour”. This will help to reduce train delays, minimise congestion and passenger discomfort, and improve platform safety by avoiding high passenger densities.**Solution**The proposed solution includes:1. A method to detect passenger flows on the station platform using existing infrastructure including sensor and other data. The method will depend on linear algebra to deduce passenger flows that are not directly monitored.2. A dashboard visualising current passenger flows and congestion levels. This will significantly increase the visibility of passenger congestion on the platform for operational station staff and enabling them to take informed decisions e.g. where to dispatch staff, where to nudge passengers; and for passengers to know where to move on the platform.3. Development of an origin/destination matrix of passenger flows on the platform (i.e. disembarking and embarking passenger of arriving trains) from PFM RF beacons historical data in conjunction with open train arrival and occupancy data.4. A method to calculate positioning of passengers along the platform, such that train boarding operations is optimised. The method is based on the predicted number of passengers embarking and disembarking. This will provide dynamic recommendations to passengers and station staff to facilitate a redistribution of passengers along the platform.**Differentiation**We believe that our proposed solution approach will convey three key advantages over those currently available:1. 3D simulated CCTV images as an alternative real CCTV data which could be used to model scenarios and extreme events without compromising data privacy or having access to CCTV footage of extreme events. 2. We aim to use algorithmic approaches to infer flows across sensor "blind-spots"; thereby minimising the need for investment in significant new sensor infrastructure.3. Generating semi-real passenger volumes using RF beacons installed at the station in conjunction with open train arrival and occupancy data.4. Novell user interface to “nudge” passengers avoiding herd behaviour to exacerbate situation.**Commercialisation**Opportunities exist to scale the proposed solution across the UK and global rail industries and into other transportation sectors, including airports, that are facing similar challenges in facilitating the safe and smooth flow of passengers.

** 背景 ** 铁路公司在一些车站站台上引入了区域标记，以帮助乘客上车;尽管目前尚不清楚乘客是否理解这种方式，或者是否证明有效。因此，乘客经常不能沿站台沿着最佳地分布;这导致列车车门处的拥挤和比必要的上车时间更长，因为上车乘客需要等待下车乘客离开车厢才能上车。当火车晚点时，尤其是在忙碌的换乘站时，这个问题就会变得更加复杂。我们提出的解决方案将根据每节车厢的乘客人数，直观地引导上车乘客前往站台上的划定区域，以尽量减少整体上车时间，避免“羊群行为”。这将有助于减少列车延误，减少拥挤和乘客的不适，并通过避免高乘客密度来改善站台安全。解决方案 ** 建议的解决方案包括：1.一种使用现有基础设施（包括传感器和其他数据）检测车站站台上客流的方法。该方法将依赖于线性代数来推导未直接监测的客流.可视化当前客流量和拥堵程度的仪表板。这将大大提高车站工作人员对站台上乘客拥挤情况的可见度，使他们能够做出明智的决定，例如向何处派遣工作人员，在何处轻推乘客;以及让乘客知道在站台上移动的位置。根据PFM RF信标历史数据以及开放式列车到达和占用数据，开发站台上客流（即到达列车的下车和上车乘客）的始发/目的地矩阵。一种计算乘客沿站台沿着定位的方法，使得列车登车操作得到优化。该方法是基于预测的乘客上下车人数。这将为乘客和车站工作人员提供动态建议，以促进乘客沿着站台重新分配。**差异化 ** 我们相信，与目前的解决方案相比，我们提出的解决方案方法具有三大优势：1. 3D模拟CCTV图像作为替代真实的CCTV数据，可用于模拟场景和极端事件，而不会影响数据隐私或访问极端事件的CCTV镜头。2.我们的目标是使用算法方法来推断传感器“盲点”上的流量;从而最大限度地减少对重要的新传感器基础设施的投资需求。使用安装在车站的RF信标结合开放式列车到达和占用数据生成半真实的乘客量。4. Novell用户界面“轻推”乘客避免群体行为，使情况恶化。**商业化 ** 有机会将拟议的解决方案扩展到英国和全球铁路行业以及其他交通部门，包括机场，这些部门在促进乘客安全和顺畅流动方面面临类似的挑战。