Reducing the ice hazard on smart motorways

减少智能高速公路的结冰危险

• 批准号: NE/P008976/1
• 负责人: Lee Chapman
• 金额: $ 8.2万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FP008976%2F1
• 关键词: Reducing; ice; hazard; smart; motorways

This co-designed project with Highways England will reduce the ice hazard on motorways. As part of a nationwide trial of smart motorways, 'all lane' and 'hard shoulder running' are being used to increase capacity on critical sections of the GB motorway network. However, this approach, along with traditional road widening, has implications for winter road maintenance strategy. Significant surface temperature differences exist between lanes on motorways and it is not uncommon to find a difference of 2C between the inside and outside lane of the motorway. For example, in the case of hard shoulder running, differences between the inside lane and the previously un-trafficked hard shoulder of the motorway will be significant. A consequence of this, is when the hard shoulder is first opened to traffic (e.g. during the morning rush hour), an ice hazard may exist on this lane, whilst the other lanes remain above freezing. There is a need to better understand, and monitor, these differences in temperature so that it can be incorporated into the winter maintenance strategy used by Highways England.This project will translate existing technology developed on previous research projects to quantify the temperature difference between motorway lanes. The data will be available in real time, using an 'internet of things' approach alerting engineers of the need to conduct gritting operations on cooler lanes. Hence, this project will not only impact on the actions of the project partners (potentially saving money on gritting operations), but will also improve the safety of the network for all road users. The project is particularly timely given the ongoing inquiry into 'all lane running' by the commons select transport committee.The overall aim of this project is to produce a prototype decision support system that will provide information regarding the surface temperature of all motorway lanes which can be used to make efficiency savings as well as being consulted prior to opening the hard shoulder to traffic. This aim will be realised by the following objectives:1. Installation of transects of networked low-cost sensors across motorway gantries, providing surface temperature information across all lanes.2. Development of a cloud based data hub to process and visualise data3. Integration of data into existing winter maintenance / smart motorways strategies.This short project has two key deliverables. Firstly, the project will provide tacit knowledge of temperature differences on multi-laned roads. This information can then be used inform winter maintenance strategy more generally across the network without significant further investment. Secondly, the prototype decision support system will provide detailed and reliable real-time measurements on the selected road section leading to efficiency savings for the project partner. This approach could readily be extended across the network, given the compatibility of this approach with the 'smart motorway' approach. The project will last for 7 months to cover a substantial part of the winter season (November 2016 - May 2017) and will cost in the region of £70k (£56k 80% FEC).

这个与英格兰高速公路共同设计的项目将减少高速公路上的冰害。作为全国范围内智能高速公路试验的一部分，“全车道”和“硬路肩运行”正在被用来增加GB高速公路网络关键路段的通行能力。然而，这种方法，沿着传统的道路拓宽，冬季道路养护策略的影响。高速公路上的车道之间存在显着的表面温度差异，并且在高速公路的内部和外部车道之间发现2C的差异并不罕见。例如，在硬路肩行驶的情况下，高速公路的内侧车道和之前未交通的硬路肩之间的差异将很大。这样做的后果是，当硬路肩第一次开放给交通（例如，在早上高峰时间），冰的危险可能存在于这条车道上，而其他车道保持在冰点以上。有必要更好地了解和监测这些温度差异，以便将其纳入英格兰高速公路的冬季维护策略。该项目将转化先前研究项目开发的现有技术，以量化高速公路车道之间的温差。这些数据将是真实的时间，使用“物联网”的方法，提醒工程师需要在较冷的车道上进行砂砾作业。因此，该项目不仅将影响项目合作伙伴的行动（可能节省砂砾作业的资金），而且还将提高所有道路使用者的网络安全性。该项目是特别及时考虑到正在进行的调查'所有车道运行'由下议院选择运输委员会。该项目的总体目标是产生一个原型的决策支持系统，将提供有关的表面温度的所有高速公路车道，可用于提高效率的节约，以及被咨询前开放的硬路肩交通。这一目标将通过以下目标实现：1.在高速公路龙门架上安装网络化的低成本传感器，提供所有车道的表面温度信息。2.开发基于云的数据中心，以处理和可视化数据3。将数据集成到现有的冬季维护/智能高速公路策略中。这个简短的项目有两个关键的交付成果。首先，该项目将提供多车道道路温差的隐性知识。然后，这些信息可以用于在整个网络中更普遍地通知冬季维护策略，而无需大量的进一步投资。其次，原型决策支持系统将提供选定路段的详细和可靠的实时测量结果，从而为项目合作伙伴节省效率。考虑到这种方法与“智能高速公路”方法的兼容性，这种方法可以很容易地在整个网络中推广。该项目将持续7个月，以涵盖冬季的大部分时间（2016年11月至2017年5月），并将在该地区的£ 70 k（£ 56 k 80% FEC）的成本。

项目成果

Building Urban Climate Resilience: An Urban Observatory Approach

建设城市气候适应能力：城市观测方法

• 发表时间: 2019
• 作者: Chapman, L

High-Resolution Monitoring of Weather Impacts on Infrastructure Networks.

天气对基础设施网络影响的高分辨率监测。

• 发表时间: 2017
• 作者: Chapman L

High-Resolution Monitoring of Weather Impacts on Infrastructure Networks Using the Internet of Things

• DOI: 10.1175/bams-d-17-0214.1
• 发表时间: 2018-06
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: L. Chapman;S. Bell

Network design considerations for high resolution RWIS

高分辨率 RWIS 的网络设计注意事项

• 发表时间: 2018
• 作者: Chapman L

Observations, monitoring, modelling and artificial intelligence? What does the future hold?

观察、监测、建模和人工智能？

• 发表时间: 2019
• 作者: Chapman, L