Supporting Sustainable Transport Infrastructure Maintenance (Research In the Wild)

通过知情的个人旅行帮助解决可持续发展议程一直是密集研究活动的一个领域，对许多新形式的信息收集和传播进行了调查。以可持续的方式维护交通基础设施的问题研究得更少。在我们的工作中，我们希望探索如何利用旅行信息收集和传播方面的新发展来推动更可持续的方法来维护英国的交通基础设施。该项目建立在通过资助的研究项目(我们的旅行(TSB)、信仰(TSB/EPSRC)、智能街道(TSB))建立的成功合作的基础上，并希望在RCUK资助的第六感交通项目所代表的学术研究的新领域中测试新出现的狂野想法。我们的工作建立在最近的两个研究项目上，即我们的旅行和第六感。在我们的旅行项目中，该联盟展示了如何将众包运输信息与公路维修活动相结合，以帮助更好地协调工作活动，并确保及时向旅行者传播有关维修活动的信息。正在进行的第六感交通项目是一个多学科的学术研究项目，涉及南安普顿大学(交通)、爱丁堡大学(设计)、索尔福德大学(心理学)和伯恩茅斯大学(旅游)，旨在鼓励旅行者采用更可持续的旅行方式。为此，该项目正在开发应用程序，使旅行者能够看到其他用户对未来旅行模式的预测，使他们能够避免拥堵，并更好地利用旅行链接，特别是跨交通工具和旅行者之间的旅行链接。例如，该项目希望通过提供显示过去和未来旅行模式痕迹的简单互动地图，鼓励旅行者发现共享旅行的机会，将单一目的旅行转变为多用途旅行，参与协作物流，并转向混合模式运输。我们感兴趣的是探索使用这种预测性出行模式的想法是否可以帮助提供一种更可持续的方法来维护英国的交通基础设施。目前，许多公路维修活动在很大程度上是出于遵守合同关键业绩指标(KPI)的需要。这往往导致一种固有的不可持续的“最早截止日期优先”的调度方法，大大增加了与公路维护相关的环境管理费用。对未来出行模式的预测可能会在两个不同的方面有所帮助。首先，通过使公路维护工程师能够预测未来的出行模式，他们可以以最大限度地减少交通干扰的方式安排工作--特别是涉及多种交通方式的旅行(例如开车去车站赶火车)。这可以显著减少拥堵和相关排放。其次，通过预测自己的维修车辆未来的出行模式，高速公路维修工程师可以最大限度地利用机会改善工作流程的潜力。例如，有可能找出机会，让维修人员机会主义地共享工具和材料，如柏油路面，而无需在道路维修之间返回基地，从而减少运输成本和对环境的影响。更广泛地说，在这项研究中，我们希望能够实现从被动的、明显低效和环境代价高昂的调度模式向寻求将工作对环境的影响降至最低的预测性、机会主义模式的转变。

Helping to address the sustainability agenda through informed personal travel has been an area of intense research activity with many new forms of information collection and dissemination having been investigated. Much less well studied is the problem of maintaining the transport infrastructure in a sustainable fashion. In our work we wish to explore in the wild how new developments in travel information gathering and dissemination can be used to drive more sustainable approaches to maintaining the UK's transport infrastructure. The project builds on successful collaborations established through funded research projects (Our Travel (TSB), Faith (TSB/EPSRC), Smart Streets (TSB)) and looks to test in the wild ideas emerging from new areas of academic research as typified by the RCUK funded Sixth Sense Transport project. Our work builds on two recent research projects, i.e. Our Travel and Sixth Sense. Within the Our Travel project the consortium have shown how crowd-sourced transport information can be integrated with highways maintenance activities to help better coordinate work activities and to ensure timely dissemination of information regarding maintenance activities to travellers. The on-going Sixth Sense Transport project is a multidisciplinary academic research project involving the Universities of Southampton (transport), Edinburgh (design), Salford (psychology) and Bournemouth (tourism) that is looking to encourage travellers to adopt a more sustainable approach to travel. To this end the project is developing applications that allow travellers to see predictions of future travel patterns of other users, enabling them to avoid congestion and make more opportunistic use of travel links, particularly across transport modes and between travellers. For example, the project looks to encourage travellers to identify opportunities for shared travel, convert single-purpose trips into multi-purpose trips, engage in collaborative logistics and shift to mixed-mode transport by providing simple interactive maps that show traces of both past and future travel patterns. Our interest is in exploring whether the idea of using such predictive travel patterns can help provide a more sustainable approach to maintaining the UK's transport infrastructure. At present many highways maintenance activities are driven largely by a need to comply with contractual KPIs (Key Performance Indicators). This tends to lead to an inherently unsustainable "earliest deadline first" approach to scheduling that significantly increases the environmental overhead associated with highways maintenance. Prediction of future travel patterns may help in two distinct ways. Firstly, by enabling highways maintenance engineers to predict future travel patterns they can schedule work in a way that minimises traffic disruption - particularly with respect to journeys that involve multiple transport modes (e.g. driving to the station to catch a train). This can lead to a significant reduction in congestion and associated emissions. Secondly, by predicting future travel patterns of their own maintenance vehicles highways maintenance engineers can maximise the potential for opportunistic improvements to work-flows. For example, it may be possible to identify opportunities for maintenance operatives to opportunistically share tools and materials such as tarmac without the need to return to base between road repairs - reducing transport costs and environmental impact. More generally, in this research we are looking to enable a shift from a reactive, and distinctly inefficient and environmentally costly model of scheduling to a predictive, opportunistic model that looks to minimise the environmental impact of work.