The Value Of Public Transport Punctuality For Passengers

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How valuable is public transport punctuality to passengers and how does Big Data help public transport become more punctual?

Clock at the train station
What train arrival time do passengers consider as punctual?
Image Source: Brandon Hoogenboom

What punctuality means to passengers

Our previous article about public transport occupancy data explained the dilemma between the importance of public transport and the potential health risk of using public transport. There’s also another problem plaguing public transport users: Passengers have to wait for delayed trains and buses, which can often be a frustrating experience.

Several studies have been done to discuss the topic of public transport punctuality and how valuable it is to public transport passengers. Among them is a study done in 2014 by Passenger Focus, which gathered opinions of bus passengers about bus schedules and punctuality in the UK.

Depending on the frequency of the bus services, the passengers mentioned tolerating some flexibility and taking some responsibility for their journey by turning up at the bus stop early but only to a certain extent. If a bus service was more frequent (interval time is roughly 10 minutes), passengers were more tolerant about missing buses that leave the stop early since they could catch the next bus very soon.

However, if a bus service was less frequent (interval time is over 20 minutes), passengers were more likely to feel devastated about missing buses that leave the stop early since they would have to wait longer for the next bus until they lose their patience and feel the urge to punch something resort to e-hailing.

Woman sitting on a bench at a bus stop
She’s probably wondering when the bus will finally arrive.
Image Source: Vidar Nordli-Mathisen

According to them, the bus operators and drivers should make a conscious effort to be punctual, improve on any issues and communicate well with the passengers using schedules. Schedules with higher accuracy of departure and arrival times during peak and non-peak hours can help passengers make optimal decisions about when to arrive at the bus stop without missing the early bus or waiting too long for the late bus.

Whereas, a 2015 research paper by Transport Focus and the Office of Rail and Road studied the value of train punctuality to most passengers in the UK. Among the views presented in this paper is that passengers generally saw a punctual public transport service as the key success criterion.

Most passengers considered a train’s arrival within 1 minute of scheduled time as being ‘on time’. Meanwhile, some passengers considered a short-distance train arriving 10 minutes later and a long-distance train arriving 20 minutes later as ‘significantly late’.

Such high standards for punctuality could be why there have been numerous studies about analysing the punctuality of public transport services over the years.

Using Big Data to improve public transport punctuality

In order to improve the punctuality of public transport, Big Data technology can be used to find ways to minimise public transport delays.

A 2020 master thesis in Vrije Universiteit Amsterdam proposed a way to compute punctuality using smart card and vehicle location data in a multimodal network. The smart card and vehicle location data come from Amsterdam’s public transport company, GVB.

QR Code
Actually, have public transport operators considered a QR code scan approach instead of a smart card?
Image Source: Markus Winkler

The smart card data set is a record of GVB’s automated fare collection system, whereby the national public transport smart card, OV-Chipkaart, is tapped on a card reader in the bus or at an auto-gate in the train station. The smart card data can be considered as the passenger counter data.

On the other hand, the vehicle location data set is a record of the scheduled and actual arrival and departure times of the vehicles at the different stops. These smart card and vehicle data sets are then combined using the appropriate method to derive the percentage of passengers that arrived just in time to board the vehicles.

Perhaps, the idea for this Big Data application came from a master thesis in 2016 to analyse the service reliability of bus line 550 in Helsinki using automated vehicle location and passenger counter data from Helsinki’s regional transport authority, HSL. The study stated the following as the possible factors of unreliability:

  • line length of the route
  • bus driver behaviour
  • not enough traffic signal priority at intersections
  • too many passengers boarding through the middle door
  • bus design
  • other traffic blocking the way

On the other side of the world, a 2013 study by Malaysian researchers looked at the punctuality of Malaysia’s largest intercity train service, KTMB. Using KTMB’s trains felt like a step back in time compared to KTMB’s competitors when the research was being done. KTMB’s trains did not have the latest train operation system technology, used a single-track system and suffered from network infrastructure issues, hence resulting in delays.

KTMB intercity trains
The outdated technology of KTMB’s intercity trains might not come as a huge surprise to the locals though.
Image Source: Min Joo

2 years before, there was a joint study by UTP Malaysia and Gadjah Mada University Indonesia about the punctuality of stage bus operation in mixed traffic and passenger’s waiting time using historical GPS data in the Ipoh-Lumut corridor, Perak, Malaysia. This study attributed the buses’ lateness to the lack of a bus-only lane, which means that the buses have to share the road with other road users and will be stuck in a traffic jam during peak hours.

What is expected of public transport operators?

By analysing the punctuality using the vehicle location and passenger counter data, public transport operators can determine what measures are needed to address the delays and minimise waiting times. As recommended by the studies mentioned above, some of these measures include:

  • using up-to-date operation system technology
  • switching to an automated data collection system for continuous development
  • optimising arrival and departure schedules
  • acquiring low-floor bus fleets
  • providing bus driver training and inspection
  • providing more traffic signal priorities at intersections
  • providing bus-only lanes
  • revising the middle door boarding policy

Of course, without the data analysis, these measures wouldn’t have been proposed. Therefore, what matters most is that the passengers’ views are taken into highest consideration and acted upon as passengers are the ones experiencing the commute.

“It is vital that passengers’ views are at the heart of the process – and with passengers paying over 60 per cent of the cost of the railway through fares, their views must count in decisions on how rail service improvements and investments are prioritised.”

plucked from the 2015 research paper co-funded by Transport Focus and the Office of Rail And Road (UK).

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