Improving Public Transport Planning Using Smart Card and MaaS Subscription Data

在这个提案中，我想开发优化框架，使用智能卡和移动即服务订阅数据来解决战略（交通路线网络设计问题）和（如果时间允许）战术（频率设置和时间表）公共交通规划问题。除伦敦外，英国各地的公共交通使用量每年都在减少。去年，英国超过80%的路程是由私家车完成的。人们对公共交通缺乏热情的原因可能有很多，例如交通差、服务不频繁或成本高。让公共交通再次成为主要的交通方式是很重要的，原因有很多。首先，英国到2050年实现零碳排放的承诺要求使用更节能的模式。英国超过16%的排放量来自私家车。其次，汽车浪费道路空间，与公共汽车相比，它们每个乘客所需的空间几乎是其8倍。私家车的过度使用是我们每天经历的交通拥堵的最大原因之一。我们需要找到方法，将交通方式的选择从私人交通转向公共交通。将用户行为从私人交通转变为公共交通的一种方法是将移动作为一种服务（MaaS），并提供可以为用户提供不同选择的套餐。MaaS并不是一个新概念，在世界各地都有不同的使用形式。然而，这些系统要么只是一个设计概念，一个为用户提供多种选择和统一支付方式的平台，要么只允许用户使用大型公共交通工具的订阅包。在这个项目中，除了智能卡数据外，我还将能够使用基于订阅的MaaS数据，该数据为用户提供大规模和个人公共交通（例如共享单车，共享汽车，乘车，共享乘车，叫车）。智能交通系统（ITP）的应用帮助我们监控和控制公共交通系统。我们还使用收集到的ITP数据来分析和改进这些系统。然而，现有的经典模型通常无法利用ITP系统每天产生的大量数据。我们需要开发更好的方法来处理高精度数据。在这个提案中，我的目标是开发模型，通过使用智能卡和MaaS订阅数据来改善公共交通规划。在我的方法中，除了大规模的公共交通线路，我想在公共交通网络设计的发展中考虑个人的公共交通选择，以及（如果时间允许的话）频率设置和时间表问题。随着移动技术的进步和共享经济的趋势，我们在城市中看到更多的个人公共交通方式。特别是大城市鼓励他们为居民提供其他交通方式。我们每天看到越来越多的人使用这些交通方式。在设计公交线路网络时考虑到各种类型的公共交通方式，可以在有限的资源下提供更好的公共交通方案，最终提高城市居民的平均福利。

In this proposal, I want to develop optimisation frameworks that will use smart card and mobility-as-a-service subscription data to address strategic (transit route network design problem) and (if time allows) tactical (frequency setting and timetabling) public transport planning problems.The use of public transportation is decreasing all around the UK, except London, every year. Last year, more than 80% of the distances are travelled by private cars in Britain. There may be many reasons for the lack of enthusiasm for public transport, e.g. poor connections, infrequent service or high cost. Making public transport again the main mode of transport is important for many reasons. First, the UK's zero carbon emission by 2050 pledge requires to use more energy-efficient modes. More than 16% of the emissions in the UK are from private cars. Second, cars waste road space, they need almost eight times more space per passenger compared to busses. Excessive private car use is one of the biggest reasons for traffic congestion we experience every day. We need to find ways to move mode choice from private to public transport.One way of altering user behaviour from private to public transport could be frameworking mobility as a service (MaaS) and provide packages that could provide different options to users. MaaS is not a new concept and is in use of different forms all around the world. However, these systems either are just a design concept a platform that provides multiple options and unified payment method for any trip to its users or only allows subscription packages that allow users to access mass public transport modes. In this project, in addition to smart card data, I will be able to work with a subscription-based MaaS data that provides mass and personal public transport (e.g. bikesharing, carsharing, ride-hailing, shared ride-hailing, dial-a-ride) to its users together.Intelligent transportation systems (ITP) applications help us monitor and control public transport system. We also use the collected ITP data to analyse and improve those systems. However, the existing classical models are usually not capable of utilising the mass data produced by the ITP systems every day. We need to develop better methods to deal with high precision data.In this proposal, I aim to develop models that will improve public transport planning by using smart card and MaaS subscription data. In my approach, in addition to mass public transit lines, I want to consider personal public transport options in the development of public transport network design and (if time allows) frequency setting and timetabling problems.With the advancement in mobile technologies and trend towards sharing economy, we see more personal public transport modes in cities. They are encouraged by especially the big cities to provide alternative modes of transportation to their dwellers. We see more people use these transport modes every day. Considering all types of public transportation modes in designing transit route networks could provide better public transport plans for limited resources and eventually increase average welfare for the urban dwellers living in these cities.