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Public transport networks are often evaluated through measures such as route length, number of stops or the share of residents living within a certain distance of a service.
These indicators describe network coverage, but they do not always reflect how useful that network is in practice.
A bus stop may be located close to a passenger, but if service is infrequent, ends early or requires poorly coordinated transfers, the destination may still be difficult to reach within a reasonable amount of time.
This makes time an important measure of accessibility.
The distinction between proximity and accessibility is important for public transport planning.
Proximity describes how physically close destinations are.
Accessibility describes how many destinations people can actually reach within a given amount of time using a particular transport mode.
Transport performance determines how effectively the network converts physical proximity into real access.
For bus operators, this means that frequency, operating hours, transfer coordination and waiting time can be just as important as the location of the route itself.
Two neighbourhoods may appear similarly connected on a map while offering very different levels of accessibility if one is served every ten minutes and the other only once per hour.
A public transport journey includes more than the time spent inside the vehicle.
Passengers may need to walk to a stop, wait for the bus, travel, transfer, wait again and then walk to their final destination.
Each stage contributes to total journey time.
Research cited in the original article also shows that passengers often perceive waiting and transfer time as more burdensome than time spent moving inside the vehicle.
This means that reducing waiting and improving transfer coordination can significantly improve the passenger experience even when the physical route remains unchanged.
Increasing service frequency can change how many destinations passengers can reach within a fixed amount of time.
The original article cites modelling in Washington, D.C., where increasing bus frequency on existing routes improved the number of jobs reachable within 30 minutes without adding new infrastructure.
The routes themselves did not change.
What changed was the amount of time passengers spent waiting.
This illustrates why frequency can be considered an accessibility metric rather than only a service quality indicator.
Providing more frequent service, extending operating hours or expanding coverage requires additional operational resources.
Funding, fleet availability, infrastructure and demand all influence what operators can provide.
Driver availability is another constraint.
Every additional departure or service hour requires additional driver capacity under conventional operation.
Where driver shortages are significant, operators may struggle to increase frequency or maintain service during lower demand periods.
Autonomous buses do not reduce the physical distance between passengers and their destinations.
Their potential impact lies elsewhere.
If autonomous operation reduces the extent to which each additional service hour depends on additional driver availability, operators may gain more flexibility to run buses more frequently, maintain service later in the day or operate routes that are difficult to sustain under conventional conditions.
This is particularly relevant for peripheral areas, lower demand routes and off peak periods, where service frequency may be limited by operating costs and workforce availability.
The value of autonomous public transport is therefore not necessarily that vehicles travel faster.
It is whether automation can help reduce the amount of time passengers spend waiting for service.
Longer operating hours can also improve accessibility by making destinations reachable earlier in the morning, later at night or during periods when conventional service is limited.
For passengers, this can change practical access to employment, education, healthcare and other essential services without altering the physical transport network.
Imagry develops AI based autonomous driving technology for public transport applications.
The company’s system uses vision based perception and operates without relying on HD maps.
According to Imagry, the technology can be integrated across different vehicle platforms and is intended to support autonomous operation in existing road environments.
For public transport operators, the relevance of this type of technology lies in how it could influence service planning.
Autonomous operation may give operators additional flexibility when considering frequency, operating hours and coverage, particularly in applications where driver availability limits service expansion.
Measuring public transport only through distance can overlook an important part of the passenger experience.
A route may exist, but its value depends on how quickly and reliably people can use it to reach the places they need.
Frequency, waiting time, transfer coordination and operating hours therefore play a direct role in accessibility.
Autonomous buses could become one tool for changing these variables.
Where destinations cannot be brought physically closer, better service can still bring them closer in time.
