You say Congestion, I say Contention…

‘Transport’ describes the systems and methods for connecting people and places, goods and services, activities and opportunities. We study, plan, fund, and operate transport networks as a means to support economic growth and social interaction. It is a utility, a public good.

Substitute Information and Communication Technologies (ICT) for ‘Transport’ in the sentences above, and they still make sense. But ICT is not a direct replacement for transport. For example, increased use of ICT by businesses can result in longer-distance if less frequent business trips, and whilst shoppers may visit fewer stores, more delivery trucks are on our roads carrying goods ordered online.1 More generally, ICT loosens the bonds between commuting options and costs, and work and residential location choices, as the availability of local services, amenities, and social networks become more important in deciding where to live.2 Thus, virtual access complements physical access, and it may be more useful to view ICT as an alternative way to connect, another choice or manifestation of travel behaviour.

Like any mode of transport, the attractiveness and convenience of mobile or fixed ICT for making connections depends upon the quality of infrastructure and services in a particular geographical area. For fixed broadband, for example, digital accessibility depends upon characteristics like what type of connections are available in a given location, the length of any hybrid copper line, how providers manage different connections, and how connections are wired.3

Thus, like any other transport system, ICT networks comprise links and nodes with variable accessibility. Still, differences are worth noting. ICT users find routing much more fluid than do train passengers or car drivers or even cyclists planning how to reach to their destination. Speeds for ICTs are not fixed, but how they will impact on performance is often obscure.

Meanwhile, again like transport systems, demand-side factors can affect capacity. Transport planners may not be aware, but there are peak times for internet activity as much as for travel. OfCom, the ICT regulator in the UK, calls this dynamic “contention”. Basically, contention increases when too many people are trying to access too much data on the network at the same time and broadband download speeds fall from their maximum rates. The scale of contention also varies by type of connection technology, just as the scale of a traffic jam varies by the number of lanes on the carriageway. However, unlike the travel peak that occurs between 7am and 9am, contention is usually at its worst between 8pm and 10pm, due largely to video streaming.4

However, and this is where transport planners should take note, contention can occur at other times. Unexpected spikes in contention have been observed at unexpected times due to mass streaming of sporting and entertainment events that occur outside of ‘prime time’.5

My own research estimates significant contention in response to certain severe weather events, which may indicate an increase in internet activity for work purposes or telecommuting. On public holidays, it may suggest that outings are cancelled in favour of watching movies at home. In either case, such contention offers insight into the flexibility of travel behaviour, and the benefits of that flexibility.

Unlike congestion, which carries the risks of incidents and accidents as well as delays, contention need not discourage remote access. Slow download speeds are unlikely to result in the hours of unproductive time a commuter might experience due to unusual levels of congestion, closures, and cancellations, making ICTs the wisest modes during period of severe weather. True, high winds can knock down power lines as soon as block rail tracks with trees. Floods can cause water to seep into telephone cabinets as well as making roads impassable. Yet ICT infrastructure is generally more resilient to severe weather impacts than transport infrastructure.6 And newer broadband technologies not only deliver higher speeds, but are even more resilient than those that preceded them.

In conclusion, as society moves from the motor age into the digital age, ICT will become ever more important for accessing goods and services and for making connections. Transport planners should be incorporating ICTs into their forecasts and appraising them for their potential return on investment, and their ability, in contrast to other modes, to reduce risk, maintain productivity, improve flexibility, and change travel behaviour.

 

  1. Andreev  P, Salomon, Ilan and Pliskin, Nava. (2010) Review: State of teleactivities. Transportation Research Part C: Emerging Technologies 18: 17. And various other articles!
  2. Lyons G. (2015) Transport’s digital age transition. The Journal of Transport and Land Use 8: 1-19.
  3. Tranos E, Reggiani, A., Nijkamp, P. (2013) Accessibility of cities in the digital economy. Cities 30: 59-67. I am now focusing on fixed broadband technology, although there are also parallels in mobile technology.
  4. (2017) UK Home Broadband Performance. UK fixed-line broadband performance: Research Report. 1-82.
  5. (2014) Infrastructure Report 2014. OfCom, 1-188.
  6. Dawson R. (2016) Chapter 4: Infrastructure. UK Climate Change Risk Assessment 2017: Evidence Report. Committee on Climate Change, 1-111.

 

Mobility vs Accessibility: new evidence for an old debate

I was at a public exhibition many years ago where I was approached by a rather aggressive environmental campaigner. He told me that if public sector transport planners like me really wanted to promote sustainable travel, then we’d all live and work within the same Local Authority area. Everything we did should be local and we shouldn’t really need to go anywhere, and then we wouldn’t be emitting all that carbon travelling. As I lived in another District from where I was working, albeit only 10-12 miles away, I naturally did no more than nod and smile politely.

Inside, I was thinking: Yes I agree that we need to reduce our transport emissions and impacts on the climate, but my husband is the one that lives next to his work and I had to find a job nearby. Yes I’d like a shorter, more convenient commute, but there wasn’t a job in my field, never mind at the level I was looking for, advertised within my District at the time. Yes I prefer to travel by sustainable modes, but I do take the train to get here, whereas I might have to drive to other jobs at a similar or shorter distance. Yes, but…!

Ok, enough of the protests in my head that clearly have been yearning to break free for far too long. My point in recalling this story is that the man’s superficially inane, impractical argument does have a grounding in a fundamental principle of transport that many transport planners, never mind transport users, often overlook. Transport planners tend to focus on creating and promoting options (read new infrastructure or services) for mobility, rather than accessibility.

Yet people travel for the purpose of accessing a job or a shop or a friend’s house, and travel further if those things they are trying to access are further away. The further they travel, the less mobility options they have, which may result in a poor choice between car-dependence and isolation. The latter I add as we consider the impact of new online technologies on accessibility over mobility. See a great blog on this by @alikirkbride for #LTTMobilityMatters.

Moreover, I have recently discovered that the concept that humans seek accessibility rather than mobility can be backed up scientifically. In the last decade, researchers [1-4] have used big data from mobile phone call records and social media to show that human movement follows certain patterns, namely:

  • Most people can be found in a few predictable places (home, work) most days of the week at the times (night and day) where you’d expect to find them there.
  • Most people make more short trips than long trips, and the distribution of short trips follows a certain pattern, decreasing with distance, up to a threshold.
  • At which point you have a different pattern where people who travel further can be found in expected places more often and have fewer irregular trips.
  • And, those people who travel further tend to live where there is less density – of population, employment, opportunities, activities – than those who travel shorter distances.

It is this last point that is key. None of the studies are looking at mode of travel, but they say something very basic about travel behaviour. Namely, that people are not choosing which trips to make to minimise journey times or distance travelled, even if that may influence modal choice. No, they are choosing which trips to make based on where the destinations are which they are trying to reach. They will choose the nearest destination that meets their need or desire or nearest ‘intervening opportunity’ as one study calls it [2].

Thus, transport planners should be as aware as land use planners of the importance of place-making, of mixed-use development, of walkable neighbourhoods. Discussing those is a whole other blog, so I’ll leave it there, but in a twisted way, that man who chastised me long ago had a point. If we could work at the sort of job we wanted, shop for whatever we needed, socialise with our friends and family and have our children in decent schools, all in the same area as our home, we would probably choose to do so. Then we would have more options for sustainable mobility (e.g. walking and cycling), which would be better for the environment and our health and make us more resilient to unforeseen events. And so transport planners would be planning for accessibility rather than mobility.

  1. Gonzalez, M.C.H., Cesar A. & Barabasi, Albert-Laszlo, Understanding individual human mobility patterns. Nature, 2008. 453(7196): p. 779-782.
  2. Noulas A, S.S., Lambiotte R, Pontil M, and Mascolo C, A Tale of Many Cities: Universal Patterns in Human Urban Mobility. PLoS ONE, 2012. 7(5): p. 1-10.
  3. Isaacman S, B.R., Caceres R, Kobourov SG, Martonosi M, Rowland, J and Varshavsky, A. Identifying Important Places in People’s Lives from Cellular Network Data. in 9th International Conference on Pervasive Computing (Pervasive). 2011.
  4. Song, C.Q., Zehui Qu; Blumm, Nicholas and Barabási, Albert-László, Limits of Predictability in Human Mobility. Science, 2010. 327: p. 1018-1021.