Social distance management on public transport
In this report, Journeo seek to demonstrate how a series of disparate technologies can be brought together to provide a robust methodology to provide Social Distancing Management in public transport applications on-board buses, trains, trams, at stops and stations throughout the UK.
The UK economy relies on moving large numbers of people to centres of economic benefit, enabling them to fulfil their roles as key workers in our hospitals, construction sites, offices and more. The most effective and environmentally friendly way to do this was, and remains, mass public transit.
COVID-19 and the fear of contracting a virus in contained and often crowded public spaces has resulted in a requirement to rebuild confidence in the safety of public transport. This document will focus on how operators and authorities can demonstrate occupancy through the accurate collection of data and the processing of that data so it can be displayed to potential passengers, to show that public transport is open for business. The report primarily looks at on-vehicle data collection and at-stop data collection.
Operators and authorities will then be able to display that there is safe capacity on their network and within their vehicles.
In turn, it is hoped that this will contribute to an increasing level of confidence within public transport.
For data capture on-vehicle, Journeo has found over-door APC sensors to provide unrivalled accuracy when held in comparison against other methodologies, such as MAC harvesting and ticket factoring. When simultaneously ensuring that a vehicle remains safely socially distanced yet open to provide an essential service for key workers, accuracy is paramount.
For data capture off-vehicle, accuracy is more challenging as members of the public will not necessarily be passing through a focal point such as a doorway meaning technologies that rely on line of sight (such as APC sensors and video analytics) become less useful. In these circumstances, the challenge becomes to gauge the best level of approximation available and, in this case, the most suitable technology would be MAC harvesting. Not only will it provide a good level of estimation, the price and rapid deployment of the solution makes it an attractive solution.
The communication of this occupancy data to the right person at the right time presents another challenge. It is, however, a challenge that can be met by leveraging existing data standards prevalent in the UK and deployment through existing infrastructure. Occupancy data of a vehicle in isolation will not, by itself, provide enough information for a passenger to make an informed decision, so there is a requirement to associate vehicle occupancy with trip and service information. This document will also highlight how this can be achieved, both on a vehicle/at a stop and in the back office. Data consumers will then be able to easily ingest this data and interpret it for display within their platforms.