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Artificial Intelligence for Transport - Car Parking Departure Optimisation

Artificial Intelligence for Transport - Car Parking Departure Optimisation
交通人工智能 - 停车场出发优化
批准号:
10078901
负责人:
金额:
$6.37万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
已结题
起止时间:
2023 至 --

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中文摘要
翻译
该项目旨在应用基于人工智能的数据决策技术来辅助和改善交通,特别是停车场的高密度车辆移动。该项目将由两个组织承担:Eloy和Mosimsis(他们是人工智能技术的提供商)。埃洛伊将成为人工智能的采用者,莫西米斯将成为人工智能的提供者。想象一下,你买了一张赛马、大型赛车比赛(F1)或航展的门票。很有可能,你一天中的大部分时间都在排队等待停车,然后在一天结束时再次排队离开。我们的商业理念是与活动组织者合作,提供停车应用程序,以改善交通流量,减少等待时间,并可能减少活动场地周围的拥堵和排放。这一想法是为了鼓励(例如,通过优先停车、更便宜的车票或其他搭售福利)使用一款提供停车指导的应用程序(在哪里停车,走哪条路线去场馆,以及通过场馆,何时离开,以及何时离开)。反过来,该应用程序(通过GPS等)提供交通流量和出行时间的数据,以及用户是否遵守其指引。该应用程序提供的建议使用交通流量模型(本质上是大型停车电脑游戏)来提供建议。这些模型可以使用从应用程序收集的数据进行更新。在传统的交通控制中(例如,在伦敦等大城市),这种交通控制将由坐在一组CCTV显示器前面的控制室中的人工操作员来监督。这个项目的想法是使用AI.Eloy有一个名为EloyEvent的活动交通管理解决方案,根据该解决方案,进出场馆的车辆通过卫星导航(SATNAV)进行管理。该解决方案使用卫星导航系统产生的实时数据,并寻求在车辆沿进场和发车路线行驶时获得最大吞吐量。具体地说,这个解决方案包括通过分配停车位和提供顺序和结构化的清空计划来管理停车场内的车辆流量。由于创建高度可扩展的软件以适用于所有停车场设计、布局和流动路线的复杂性,探索新的人工智能解决方案有很大的好处。
英文摘要
This project aims to apply AI-based data decision making technology to assist and improve transportation, specifically with high density car movement in car parks. The project will be undertaken by 2 organisations: Eloy and Mosimsis (who are providers of the AI technology). Eloy will be the AI adopter and Mosimsis will be the AI provider. Imagine you have bought a ticket to the horseracing, a big motor race (F1), or an airshow. Quite likely, you'll spend a good part of your day queuing to park for the event, and again queuing to leave at the end of the day. Our business idea is to collaborate with the event organiser to provide parking apps that will improve traffic flow, reduce waiting time, and probably, reduce congestion and emissions around the event venue. The idea is to incentivise (e.g., via priority parking, cheaper tickets, or other tie-in benefits) the use of an app which provides parking guidance (where to park, which route to take to the venue, and through the venue, when you leave and depart, and indeed when to depart). The app in turn (via GPS etc) provides data on traffic flow and travel times and whether users are complying with its guidance. The advice that the app provides uses traffic flow models (essentially, big car parking computer games) to inform its advice. These models can be updated using the data collected from the app. In traditional traffic control (e.g., in major cities such as London), this traffic control would be supervised by a human operator sitting in a control room in front of an array of CCTV displays. The idea in this project is instead to use AI.Eloy has an event traffic management solution called EloyEvent, whereby vehicle movement to and from venues is managed by a satellite navigation (SatNav). This solution uses live data generated from the SatNav system and seeks to obtain maximum throughput as vehicles travel along the approach and departure routes. Specifically this solution includes managing the flow of vehicles within the car park, by allocating parking bays and delivering a sequenced and structured emptying plan. There is a substantial benefit to explore new artificial intelligence solutions due to the complexity in creating highly scalable software to be applicable for all car park designs, layouts and flow routes.
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