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Live prediction of seat-availability for bus passengers from real time bus occupancy and location data

根据实时公交车占用率和位置数据实时预测公交车乘客的座位可用性

基本信息

批准号：
85818
负责人：
金额：
$ 12.7万
依托单位：
PROSPECTIVE LABS LTD
依托单位国家：
英国
项目类别：
Collaborative R&D
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=85818
关键词：
Live prediction seat availability bus

项目摘要

Social distancing measures have reduced the effective capacity of buses to 40% of regular capacity. Although many routes are not currently busy enough to be commercially viable overall, they can be too busy at certain times and passengers are being turned away as a result. With passengers already nervous about using public transport - such instances may prevent passengers from using the bus in the future.Operators must find ways to build confidence in bus services through improved passenger information that is reliable and constantly updated. Specifically, there is a need to provide passengers with information on the space available on buses, so passengers know if they will be able to board and if they will be comfortable with the experience. This information must go beyond advance planning tools, and provide real time, continuously updated predictions of the space on specific buses at specific stops.Our proposal will provide a real time data feed of expected arrival time and predicted passenger space for every vehicle and every bus stop on a bus route. This goes beyond existing solutions by combining real time occupancy sensing with real time prediction of boarding and alighting further down the route. The feed will be continuously updated and can be integrated into a wider range of passenger facing services, including passengers apps, digital bus stop signage and journey planning tools.

社交距离措施使公共汽车的有效容量减少到正常容量的40%。虽然许多路线目前还不够忙碌，不足以在商业上可行的整体，他们可以太忙碌在某些时候，乘客被拒之门外的结果。由于乘客已经对使用公共交通感到紧张-这种情况可能会阻止乘客在未来使用公共汽车。运营商必须找到方法，通过改进可靠和不断更新的乘客信息来建立对公共汽车服务的信心。具体而言，需要向乘客提供有关公共汽车上可用空间的信息，以便乘客知道他们是否能够上车，以及他们是否对这种体验感到舒适。这些信息必须超越先进的规划工具，并提供真实的时间，不断更新的预测空间的特定巴士在特定的车站。我们的建议将提供一个真实的时间数据饲料的预期到达时间和预测的乘客空间的每一辆车和每一个巴士站的巴士路线。这通过将真实的时间占用感测与沿路线进一步上下车的真实的时间预测相结合而超越了现有的解决方案。该Feed将不断更新，并可以集成到更广泛的面向乘客的服务中，包括乘客应用程序，数字公交站牌和旅程规划工具。