Pothole Identification and Management Autonomous System

ICM Research在2016年对KwikFit进行的一项调查估计，英国驾车者每年因坑洞造成的总损失为6.84亿英镑。沥青工业联盟（ALARM 2016）的研究发现，2015/2016年英格兰和威尔士地方当局的赔偿索赔总额为2840万英镑，其中76%直接归因于坑洞。虽然地方当局负有处理道路损坏的法律的责任，但它们在很大程度上依赖于公众向其报告的问题，以便进行评估和修复。坑洞报告、评估和修复的被动性质效率低下，而且基本上没有效果。目的和目标：该项目的目的是开发技术，改进地方当局识别和管理坑洞的方式，使他们能够改善道路并降低成本。主要目标是：1. 2.开发价格合理的传感器技术，使车载传感器能够以高达65公里/小时的速度行驶，以识别和捕捉路边石和中线之间的道路损坏情况。对道路损坏情况进行分类，以便进行事故报告。提供损坏的图像。4.提供道路损坏的准确位置。建立典型损伤参数的“学习数据库”。以存储转发或实时的方式报告道路损坏情况。在基于云的服务上捕获和存储数据。8.为了映射数据，使其易于理解。提供对地图产品的网络访问。该项目最初将侧重于提供一个用于识别、分类、报告和共享坑洞信息的原型。应用和效益：该项目将提供车载传感器，可以识别和分类坑洞和其他道路损坏，提供道路损坏的准确位置，通过转发到云存储报告发生的情况，并使数据能够通过网络浏览器访问，在地图上显示数据。我们认为，为地方当局道路提供全面地图的最有效机制是在避难和回收废物收集车辆上安装传感器。这可以由独立的调查车辆加以补充。结合来自地方当局的数据将提供一个地区的综合地图，可能是英国。为公路机构、地方当局和私人用户创建一个详细的基于网络的道路坑洞地图源。这些数据将包括损害分类、成像和准确定位。这将使公路当局和地方当局能够就道路维修的优先顺序做出明智的决定，并为私人用户提供一种工具，以避免私人车辆的道路损坏。在有简易爆炸装置袭击风险的作战环境中为军事用户实时采集和报告地面扰动数据;使潜在威胁得以缓解。实时数据采集和报告无人驾驶精准农业车辆的自然和人为危害;在影响之前采取避免行动。

Context:A 2016 survey for KwikFit by ICM Research estimated the annual total cost of pothole damage to UK motorists was £684m. Research by the Asphalt Industries Alliance (ALARM 2016) identified that the total cost of compensation claims against local authorities in England and Wales for 2015/2016 was £28.4m - 76% of which was directly attributable to potholes. Whilst local authorities have a legal responsibility for dealing with damage to roads, they are heavily dependent on issues being reported to them by the general public to enable assessment and repair. The reactive nature of pothole reporting, assessment and repair is inefficient and largely ineffective.Aims and Objectives:The aim of the project is to develop technology improving the way local authorities identify and manage potholes, and is designed to enable them to improve roads and reduce costs. The key objectives are:1. To develop affordable sensor technology to enable a vehicle mounted sensor travelling at speeds of up to 65Km/hr to identify and capture road damage between road kerb and centre line.2. To classify the road damage for reporting purposes.3. To provide an image of the damage.4. To provide an accurate location of the road damage.5. To create a "learning database" of typical damage parameters.6. To report the road damage on a store-and-forward or real-time basis.7. To capture and store data on a cloud based service.8. To map data so that it is easily understood.9. To provide web-based access to map based products.The project will initially focus on delivering a prototype for identifying, classifying, reporting and sharing information on potholes. Real-time applications will be developed following successful demonstration on the initial capability.Applications and benefits:The project will provide vehicle mounted sensors which can identify and classify potholes and other road damage, provide an accurate position for the damage to the road, report the occurrence by forwarding to cloud storage and enable the data to be accessed through a web browser showing the data on a map. We believe the most effective mechanism to deliver comprehensive mapping of local authority roads will be by mounting the sensors on refuge and recycling waste collection vehicles. This could be supplemented by standalone survey vehicles. Combining data from local authorities would provide comprehensive mapping of a region and potentially the UK.Benefits include:1. The creation of a detailed web-based mapping source of potholes in roads for highways agencies, local authorities and private subscribers. The data would include classification of damage, imaging and accurate positioning. This would enable highways authorities and local authorities to make informed decisions on the prioritisation of road repairs and provide private subscribers with a tool to avoid road damage to private vehicles.2. Real-time data capture and reporting of ground disturbances for military users in operational environments with a risk of improvised explosive device (IED) attack; enabling potential threats to be mitigated.3. Real-time data capture and reporting of natural and man-made hazards for unmanned precision farming vehicles; enabling avoidance action to be taken before impact.