High Performance Road Lane Inspection for Safer Cycling

目标产品是一个成像系统，提供低成本，自动检测自行车道，人行道和附近的路边车道上的自行车允许的道路（515，600车道英里，在英国）。它将支持优先考虑道路维护，以实现更安全的自行车。一个独特的能力是识别被雨水积水隐藏的坑洞。尽管这些可能会损坏车轮，但它们可能导致骑自行车者严重受伤或死亡。骑自行车被认为是绿色、可持续和有益健康的，是COVID-19危机中的交通生命线，促使英国政府投资20亿英镑。英国交通部表示，“我们希望使骑自行车和步行成为短途旅行的自然选择，或作为长途旅行的一部分”。然而，虽然可用的自行车里程有助于休闲和旅游，但2019年交通部的一项调查显示，67%的成年人认为道路对于骑自行车来说太危险了。根据2018年的估计，英国国家自行车网络（NCN）的规模估计为16，670车道英里，从502英里（1995年）呈指数增长。此外，考虑到所有可用的自行车里程，英国约有515，600英里。许多欧洲国家都有类似的大型自行车道，总自行车道里程超过1200万英里。这为负责轨道、道路和道路维护的机构提供了巨大的出口机会。虽然政府正在进行巨额投资，但这一庞大的网络需要定期检查，以确保安全和为公众提供良好的服务水平。检查网络对于全面了解其持续状况至关重要，因此可以优先考虑并执行适当的维护活动。目前，自行车道和人行道是手动检查的，这是一个缓慢且不准确的过程。目前的建议是建立一个自动化系统，由摄像头和其他传感器以及人工智能和软件组成，用于扫描、检测和测量缺陷，量化整体表面状况。这项创新将提供准确、一致和量化的遇险测量，速度比人工调查快10倍，成本仅为现有成本的10%。此外，它将取代使用昂贵的道路车辆部署激光扫描方法在所有路面上的循环使用。StradaImaging将与阿斯顿大学（Aston University）合作，后者将为采集的数据（如裂缝、凹陷、坑洞和雨水积水）提供表征基础。

The target product is an imaging system delivering low-cost, automated inspection of cycleways, footways and the near kerb lanes on cycling permissible roads (515,600 lane-miles in the UK). It will support prioritizing road maintenance towards safer cycling. One unique capability is the identification of potholes that become hidden by rain ponding. Whereas these may damage a vehicle wheel they can lead to serious injury or death for cyclists.Cycling is recognised as green, sustainable, and health beneficial, a transportation lifeline in the COVID-19 crisis, prompting the UK government to invest £2 billion. UK DOT has stated, "we want to make cycling and walking the natural choices for shorter journeys, or as part of a long journey". However, whilst available cycling miles contribute to leisure and tourism, a 2019 DOT survey records that 67% of adults view roads to be too dangerous for cycling.According to a 2018 estimate, the size of the National Cycle Network (NCN) of the UK is estimated at 16,670 lane-miles, increased exponentially from 502 miles (1995). Furthermore, considering all available cycling miles, UK has approximately 515,600 miles. Many of Europe's countries have similarly large cycleways and more than 12 million total cycling lane-miles. This presents a substantial export opportunity to bodies responsible for the track, path, and road maintenance.While governments are making huge investments, this vast network will require regular inspection to ensure safety and a good level of service to the public. Inspecting networks is vital to get a thorough understanding of their ongoing condition, so appropriate maintenance activities can be prioritised and executed.Cycleways and footways are currently inspected manually, which is a slow and inaccurate process. The present proposal is for an automated system, consisting of cameras and other sensors in conjunction with AI and software, to scan, detect, and measure defects, quantifying the overall surface condition. The innovation will provide accurate, consistent, and quantified distress measurement 10 times faster than manual surveys at 10% of the existing cost. Furthermore, it will displace the use of expensive road vehicle deployed laser scanning methods on all paved-surfaces in respect to cycle use. It will give high levels of automation with real-time overseeing for quality control, and completely digitize measurements that can seamlessly integrate with maintenance planning software.StradaImaging will collaborate with Aston University who will deliver a characterisation basis for the captured data such as cracks, depressions, potholes, and rain ponding.