It’s Hard To Connect Public Transport Occupancy And Punctuality

I initially wanted to find out how much of a delay a certain number of passengers experience whenever there is one. As in, does a 1-minute delay for 50 passengers feel like a 50-minute delay? But I really had a hard time finding studies or any source solely exploring the relationship between public transport occupancy and punctuality.

Seriously. Here’s a short story.

People waiting for the train at a train platform in Brussels.
Is there a relationship between occupancy and punctuality in public transport?
Image Source: Alex Wong

The truth about attempting to make that connection

These studies prove why it’s hard to explore the relationship between public transport occupancy and punctuality.

Økland and Olsson (2020) revisited an investigation of Punctuality development and delay explanation factors on Norwegian railways in the period 2005–2014. To understand the original study’s patterns behind the increasing delays in the Norwegian railway network, punctuality data including the possible causes of delays was collected.

The increased number of passengers used to be a factor of increased delays but this relationship later weakened, among many other factors! Perhaps, the explanation for this could be found in a 2008 doctoral thesis called Aspects of Improving Punctuality: From Data to Decision in Railway Maintenance by Birre Nyström.

Nyström’s thesis spoke about unpunctuality cost (the cost of the consequences of unpunctuality/delay) and used the domino model to explain that one factor can affect another factor which affects an additional factor and so on, hence making it difficult to pinpoint one particular cause of unpunctuality since there are multiple factors.

Dominos
The domino effect applies in the difficulty in identifying the actual cause of a delay.
Image Source: Bradyn Trollip

But there is no doubt that passengers, whether it’s the numbers or their behaviour, have some impact on punctuality.

“Even passengers’ behaviour affects punctuality. One example concerns the Arlanda Airport train, where the automatic doors are closed some seconds before timetabled departure time. Passengers, accustomed to other TOCs, have complained about this, as they see it as having caused them to miss the train (Nyström & Karlsson, 2006). However, by closing the doors in time, A-Train communicates to its passengers and personnel that timetabled departure time is to be respected, thereby instilling a certain attitude.”

Nyström about tying passengers’ behaviour to punctuality (or unpunctuality).

In fact, the only mentions of the 2 issues within a sentence or paragraph in A Development Of Punctuality Index For Bus Operation by Seung-Young Kho and his former postgraduate student team (2005) were:

“The effects of passenger occupancy could not be considered because necessary data was not available. Only the daily number of passengers on each route was available. Generally, it seems like that the more the passengers were, the lower the punctuality index was.”

“In addition, longer route length, more number of stops and more number of passengers cause the punctuality to be worse.”

Seung-Young Kho at el (2005) about being unable to consider occupancy as a factor of bus delays in Seoul due to a lack of necessary data and that other factors such as route length and number of stops also contribute to delays.
Old London poverty geospatial map.
Factors such as route design and route demand can also contribute to delays.
Image Source: LSE Library

If we can’t deduce how exactly occupancy affects punctuality, then there could be another way to deduce this relationship. Perhaps, it’s the other way around whereby punctuality affects occupancy instead.

In Regularity analysis for optimizing urban transit network design by Niels van Oort and Rob van Nes (2009), the duo said that a better service regularity (which could be a sign of punctuality) leads to lower occupancy peaks due to an even distribution of passengers, a higher appreciation for public transport service among existing passengers and a higher attraction level of new passengers.

In other words, if a vehicle is punctual (assuming the service is frequent enough), then the vehicle is less likely to be crowded since there won’t be a huge accumulation of waiting passengers. Such low occupancy levels make public transport more appealing than it currently is.

Punctuality’s relationship status

Confusing flow map display at 21_21 Design Sight, Minato-ku, Japan.
Punctuality’s relationship status could either be “It’s complicated” or “In an open relationship” like this confusing flow map.
Image Source: Charles Deluvio

If Facebook asked punctuality about its relationship status, it would choose “It’s complicated” since it’s not sure if occupancy is the one.

Or maybe even “In an open relationship” due to its multiple simultaneous relationships with route lengths, number of stops, passenger behaviour and other possible causes of delays.

And when it thinks that it needs occupancy to be happy, sometimes, it’s punctuality that makes occupancy happy.

We see a better possibility of making the connection by assessing how punctuality makes public transport more attractive through better service and distribution of passengers and hence increases overall demand and occupancy.

Nevertheless, whichever relationship status punctuality lies in, we can conclude that attempting to determine the relationship between occupancy and punctuality is not as straightforward as we think.

Public Transport Occupancy Data For Social Distancing

The Value Of Public Transport Punctuality For Passengers

The Complexities Of Public Transport Delays

The Truth About Public Transport Routes With Recurring Delays

In Focus: An In-Depth Look at Public Transport

Big Data is the Eureka to Public Transport Problems

The Evolution of Transport Data Collection Methods

The Value For Each Public Transport Line Per Passenger

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