The user time element in public transport service planning (Pt 2)
Can it be done?
Still think that substantial travel time reductions are impossible without building high-speed railways under each suburb?
The following examples show how significant travel time savings could be possible, largely with existing infrastructure.
Example 1: Inter-suburban bus trip
Consider a short bus trip where the bus runs every 40 minutes. This service level is typical for middle and outer suburban routes and even some major inner suburban routes (eg 246 on Sunday evenings).
The trip takes ten minutes, with five minutes allowed to reach and leave the stop at either end. That adds up to a best case 20 minutes travel time, if you arrive at the stop just as the bus arrives. The worst case, if a bus has just been missed, is 60 minutes. While the average, assuming random arrival is 40 minutes.
This comparison shows high variability, or +/- 20 minutes from the average. The 3:1 difference between maximum and minimum trip times is entirely due to the attempt to make a short trip by randomly arriving to catch a low frequency service.
Increasing frequency to 20 minutes reduces the average time to 30 minutes, or a 33% reduction. Variability is reduced to +/- 10 minutes, or 20 to 40 minutes. For a ten minute frequency the average drops to 25 minutes, or an average 37% time saving. Variability drops to +/- 5, or a ratio of maximum to minimum of 1.4:1.
The above example shows that frequency has a dramatic effect on random arrival end-to-end travel times. Higher frequency also cuts variability, or effectively increasing travel reliability. The minority willing to plan around timetables can enjoy the benefits today, without any frequency increase. That’s unless they depend on connections, which are discussed next.
Example 2: Bus + train trip
Consider a suburb about 20km from the CBD. Its local buses run every 30 minutes and the trains every 20 minutes. The passenger is 5 minutes walk away from the bus stop. The bus trip (via a meandering route) takes 15 minutes to a stop near the station. When passengers alight the bus they need to cross a busy road to the station, which has only one entrance at the far end of the platform (assume 5 min). After that the train takes 40 minutes to the city.
The best case travel time is 5 min (walk) + 0 min (wait for bus) + 15 min (bus travel) + 3 min (station access) + 0 min (wait for train) + 40 min (train travel). Or a total of 65 minutes for the 20km trip.
The worst case travel time is 5 min (walk) + 30 min (wait for bus) + 15 min (bus travel) + 5 min (station access – assuming 2 min traffic light cycle at crossing) + 20 min (wait for train) + 40 min (train travel). That’s a total of 115 minutes for the 20km trip.
There’s three things to note. Firstly the worst case represents an overall speed of just over 10km/h or about double walking speed. Secondly the variability is high – the worst case taking twice as long as the best case. And, in the worst case example, the passenger is in motion for barely half the time.
Now consider the same trip above, with the following modest service improvements:
· Bus frequency upgraded from 30 to 20 minutes, to provide a harmonised connection to each train, with a consistent 6 minute connection · Bus route made more direct, to reduce travel time from 15 to 10 minutes and fund the higher frequency, but with 5 minutes added walking time · Additional station platform entrance and zebra crossing installed (to reduce station access time from 5 to 2 minutes)
The best case travel time following these improvements is as follows: 10 min (walk) + 0 min (wait for bus) + (10 min bus travel) + 2 min (station access) + 4 min (wait for train) + 40 min (train travel). Or a total of 66 minutes for the 20km trip. The worst case following these improvements is as follows: 10 min (walk) + 20 min (wait for bus) + 10 min (bus travel) + 2 min (station access) + 4 min (wait for train) + 40 min (train travel). Or a total of 86 minutes for the 20km trip.
The difference is dramatic. The average travel time has fallen from 90 to 76 minutes, while the ‘worst case’ is nearly 30 minutes quicker. Variability also fell; from +/- 25 minutes of the mean to +/- 10 minutes. Better connectivity and higher bus frequency contributed most to the gain. However more direct bus routing and better pedestrian access also added smaller but no less cost-effective benefits.
Example 3: Bus + Bus trip
Finally we’ll examine a cross-suburban trip involving a change between two bus routes. This is typical for journey types in which public transport has a low modal share.
I’ll use similar assumptions to the first example. Eg 5 minute walk to and from the bus and 10 minute travel time in each bus. The first route runs every 60 minutes while the one being changed to is every 40 minutes.
The first leg involves 5 min (walk time) + 30 min (average wait) + 10 min (travel time), or a total of 45 minutes. The best case is 15 minutes, while worst case is 75 minutes. Or a variability of +/- 30 minutes.
The wait to the second bus will be anywhere between 0 and 40 minutes. Because the frequencies are unharmonised the best connections will recur every two hours. We’ll assume an average of half its frequency, or 20 minutes.
The second leg involves 20 min (average wait) + 10 min (travel time) + 5 min walk time, or a total of 35 minutes average. But it could range from 15 to 55 minutes, or a variability of +/- 20 min from the average.
The very shortest time that the overall trip can be made is 30 minutes, with the longest 130 minutes. The average time is 80 minutes. Because time savings and delays average out, the traveller is unlikely to experience the extreme shortest and longest trip times. But if they do, that’s a ratio of over 4:1, or a variation of +/- 50 minutes.
While people may tolerate a higher variability for a short trip (Eg a 10 minute trip taking 20 minutes), it is probably true that tolerance declines for longer trips (especially if routine). Hence the letters in the paper complaining about suburban trips that take an hour by public transport but only 20 minutes driving.
There’s a couple of things that can be done to reduce variability.
Firstly the passenger could forego flexibility and use a timetable. Instead of waiting an average of 30 minutes for the first bus, they wait an average 5 minutes. This reduced variability of +/- 20 minutes is solely due to the connection between the first and second bus, which is beyond the passenger’s control. Average travel time is also reduced – by 25 minutes, which is the difference between the planned wait and the random arrival wait (ie half the frequency of the first service).
There’s also the contribution of service planning, which unlike the first response, assumes no accommodation on the part of the passenger.
Suppose the frequency of the first service was upgraded from 60 to 40 minutes. The first benefit of this is to reduce the average wait, from 30 to 20 minutes. Variability contributed by the wait for the first service is thus reduced.
The second benefit is that it matches the frequency of the second service. Such matching does not guarantee good connections but does dramatically slash variability. Let’s look at the numbers.
The first leg involves 5 min (walk time) + 20 min (average wait) + 10 min (travel time), or a total of 35 minutes. The best case is 15 minutes, while worst case is 55 minutes. Or a variability of +/- 20 minutes.
The wait to the second bus will be anywhere between 0 and 40 minutes. Because the frequencies are now harmonised the connections will recur every 40 minutes. We’ll assume there’s been no special planning and the wait for the second service is half its frequency, or 20 minutes.
The second leg therefore involves 20 min (average wait) + 10 min (travel time) + 5 min walk time, or a total of 35 minutes. Because the first leg has been harmonised to it the wait for it is now constant, variability has been reduced to zero.
Add the two legs and we have an average of 70 minutes. That’s 10 minutes down on the first case of 80 minutes. But the real gain has been in reduced variability. At best it’s 50 minutes and at worst it takes 90 minutes. This is a variability of +/- 20 minutes – well down on the earlier +/- 50 minutes. Also the ratio of maximum to minimum journey time has fallen from over 4:1 to under 2:1. Although average travel times are still slower than many would like, the improvement made from adjusting one route from a non-harmonised 60 minutes to a harmonised 40 minutes cannot be underestimated.
Again, with the earlier example one can do better. If one sacrifices flexibility and uses a timetable to catch the first service, the average travel time falls by 15 minutes (70 to 55 minutes) and variability virtually eliminated. Secondly, if planners consider that the connection between the two services is sufficiently important to be worth adjusting timetables, the connection time could be reduced from the 20 minutes average assumed here to 10 minutes. This contributes another 10 minutes, meaning a total average trip time of 60 minutes for those who don’t use a timetable and a reliable 45 minutes for those who do.
Summary and Conclusion
I have demonstrated the effect of frequency on cutting journey time. It is at first dramatic, with a point of diminishing returns being reached as frequency rises to around ten minutes. Beyond that point, unless it needed for capacity or for very short trips, its impact drops.
Also discussed has been travel time variability. Public debate on this normally concerns train reliability, and this is especially important for those connecting to less frequent buses. However the examples demonstrate indicate it can be very high for bus trips, especially those involving random arrival and connections between non-harmonised services. Harmonised bus frequencies can greatly reduce variability and make public transport more useful for trips where it’s currently weakest.
The planning approach presented here focuses most on service frequency and its harmonisation. There is less attention to infrastructure and capacity.
The former is cheap and quick, while the latter is expensive and long-term.
Both have their place in a growing city. But introducing the latter without the former means that use of the latter is poorly utilised and public transport’s potential to fully contribute to the overall transport effort is unrealised.