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High Performance Road Lane Inspection for Safer Cycling

High Performance Road Lane Inspection for Safer Cycling
高性能道路车道检查,让骑行更安全
批准号:
10017009
负责人:
金额:
$17.96万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

项目摘要

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中文摘要
翻译
目标产品是一种成像系统,能够对自行车许可道路(英国为515,600车道英里)上的自行车道、人行道和附近的路边车道进行低成本的自动检查。它将支持优先进行道路维护,以实现更安全的骑自行车。一种独特的能力是识别因雨水积水而隐藏的坑洞。虽然这可能会损坏车轮,但可能会导致骑自行车的人重伤或死亡。骑自行车被认为是绿色、可持续和有益健康的,是新冠肺炎危机中的一条交通生命线,促使英国政府投资20亿英镑。英国交通部表示:“我们想让骑车和步行成为短途旅行或长途旅行的自然选择。”然而,尽管可用自行车里程有助于休闲和旅游,但2019年DOT的一项调查显示,67%的成年人认为道路太危险,不适合骑自行车。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,比1995年的502英里呈指数级增长。此外,考虑到所有可用自行车里程,英国大约有515,600英里。许多欧洲国家都有类似的大型自行车道,自行车道总里程超过1200万英里。这为负责轨道、道路和道路维护的机构提供了一个巨大的出口机会。虽然政府正在进行巨额投资,但这个庞大的网络将需要定期检查,以确保安全和为公众提供良好的服务水平。检查网络对于彻底了解其正在进行的状况至关重要,以便确定适当的维护活动的优先顺序并执行。目前,自行车道和人行道是人工检查的,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,以扫描、检测和测量缺陷,量化整体表面状况。这项创新将以现有成本的10%提供准确、一致和量化的遇险测量,速度比人工调查快10倍。此外,在自行车使用方面,它将取代在所有铺设的路面上使用昂贵的道路车辆部署的激光扫描方法。它将提供高水平的自动化和对质量控制的实时监督,并将测量完全数字化,可以与维护计划软件无缝集成。StradaImage将与阿斯顿大学合作,后者将为捕获的数据提供表征基础,如裂缝、凹陷、坑洞和雨水积水。
英文摘要
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.
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MANET on road网络智能信息传输模型和方法研究
  • 批准号:
    60502028
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2005
  • 负责人:
    江昊
  • 依托单位: