Mobility 1 – Grounding Ambition

The Grand Challenge

In my about section I mention a “Grand Challenge” of mobility. What is that exactly? It starts with being dissatisfied with the way we get around cities, local towns and suburbs. For most of us within commuting distance of central London,  we spend nearly an hour each way to work and back, door to door – depending on your source. This is 10 hours a week, or a working week per month, of travel.

What about the quality of those 40 hours every month? If you use public transport, such as the central line, your brain is shaken out of your skull as the carriages shriek and hurtle, and the atmosphere in the carriage is suitable for studying tropical disease; roughly 20% of public transport commuters take urban trains like the tube according to Department for Transport statistics from 2017.

Another 20% of British public transport users are  on the overcrowded and regularly-delayed national rail, with the remaining 60% taking the bus. It may be possible to read or listen to a podcast on your commute, but doing anything remotely productive is out of the question. That’s a loss to your well being and to the economy.

A lot of this blog will be focusing on solutions. If I whinge too much about the problem, caution me in the comments! It’s easy to criticize public transport, as any biased commuter would. But it is also important to remember that London’s public transport is among the world’s best. Maybe not so much in vehicle and passenger ergonomics, but in how well it works as a system. At the end of the day, it is quite intuitive, reliable, convenient, and for the most part bearable. I’ve met TfL with work a few times to discuss mobility, and their people only reinforce my view that it’s a competent, caring and progressive organisation – positive change is coming!

There has been no significant increase in total public transport travel for 40 years

Outside of public transport, point-to-point car travel still dominates as the British mode of transport. Remarkably, the amount of public transport passenger-kilometers are nearly unchanged over the last 40 years. In the same time however, car, van and taxi passenger-kilometers have doubled – with the obvious consequence of congestion, noise and emissions in our neighbourhoods.

Source: Department for Transport 2017 Report

The Grand Challenge is a term that the Department of Transport has coined in their most recent call for evidence. It’s about making transportation easier, cheaper and healthier. Technology can play a huge part, from autonomous vehicles, to smart ticketing and intelligent cities. There is a recognised need to design new components and an improved system to integrate them.

One of the best things I learned in our design course at engineering school was about problem definition and abstraction; before we fixate on a particular solution and its engineering, it’s important to frame the problem and  decide how much (or little of it) we want to focus on. We need an abstract problem statement for the system and some measure of a good solution.

Energy and Well-being

Most policy decisions, and most decision problems in general can be represented as: how can we maximize a desirable outcome while minimizing its cost. We could further condense this into maximizing some score like: score = \frac{good~outcome}{cost}.

Seems simple, but we have so many variables affecting “desirable outcome”. In my mind these all maximize well-being. For transport this could be the speed, the quietness, the reliability, the safety, the cleanliness, the level of noise and vibration, but also the degree to which the mode of transport encourages a healthy posture and/or activity (e.g. cycling) so that we don’t all become sedentary and end up costing the public in mobility scooters. Making less decisions is also crucial to well-being, which is why it’s a lot less stressful to be a passenger than a driver, or to take a single mode for the entire journey rather than change 3 times (more about Mobility-as-a-Service later).

For cost, there is the direct energy consumption of the vehicle, but also the energy required to build and maintain it and its infrastructure. It’s cost to the environment and hence ultimately to us include pollutants and also NOISE. I’m a little perplexed that noise is not mentioned in DfT’s recent call for evidence: seriously, the word “noise” is not even in the document. There is a separate article on noise coming, you can believe that. For now believe me when I say that chronic exposure to background traffic noise can cause anxiety in children, degeneration of the brain and a weak immune system.

We could put the energy-equivalent of economic costs from noise into the energy part of the equation, or detract it from the wellbeing part.

So, the Grand Challenge can be thought of as the abstract problem of taking today’s Mobility System Score: score = \frac{wellbeing}{energy} and increasing it by a certain amount.

The Mobility Grand Challenge can be framed as taking today’s “national mobility score” and increasing it by a certain amount


Okay, so we have a Mobility System Score that we’d like to maximise. Next we need to realise that national mobility is a sum of the individual journeys that people make; there are many types of journey, and each will have an optimal local solution or mode of transport, but often we may need to rely on a combination of these modes for an end to end journey. Let us define segments with Segment Scores and a system to pull them together with a Mobility System Score.

Source: Department for Transport 2017 Report

A good system will have seamless high-level integration between different modes of transport. Mobility as a service (MaaS) can be though of as a service where you just say you want to get from A to B, and it joins up the cycle hire, bus and train journeys you need into a single price and seamless connected journey. That’s the service level. The product level could be something like a cycle lane from a suburb that terminates in a local train station, where you ramp onto a dedicated cycle-carrying train carriage. The train hauls all the cyclists into central London, and you cycle the last few miles into work. That’s another one for the government or a high-level integrator like TfL. Decentralization and private enterprise is needed to encourage innovation from the bottom-up for certain journey types, but doing so in isolation from each other can result in poor integration. A framework for how different modes fit, like lego, is a good idea in my books. Sort of like a set of guidelines for developing an iOS app – you can do whatever you like as long as it works seamlessly on any Apple device, and talks nicely to the other services on the OS.

Okay, we’ve opened up the abstraction funnel; we have an awareness of the context, the overall system and a way of scoring solutions. Now to start converging on a particular segment.

The 30 Mile, 90 Minute Trip

As an aerospace engineer and lover of aircraft I am no doubt biased. I am particularly interested in a segment that appear well suited for an aerial solution – hub to hub travel between major suburbs, major ports and work centres; for example Watford to the City, Gatwick to West London or Surrey to Westminster. Let’s call it the 30-mile, 90 minute trip. A common yet nasty commute which is horrible to drive due to traffic, constant starting and stopping, and stressful as hell to do by public transport as you will likely change two trains, stand for most of your trip, and encounter some form of delay.

Uber calculates that for a 50-mile trip, a vertical take off and landing aircraft (VTOL) travelling at 125mph has the same motion efficiency as a car travelling at 65mph, which is a close enough segment for me to be encouraged that VTOL can be a good solution for cutting many people’s commutes by half. Imagine 20 hours a week back to you to spend on your well being, with family, pets or on pet projects.

Not the most intuitive chart, but in simple terms the further you are from the origin, the faster or more energy-efficient your vehicle. Diagonally up to the right is best. Source: Uber Elevate White Paper

Uber further estimates that the per mile cost of a VTOL would start off about 10% more expensive than taking an Uber X, dropping in the medium term to about half of an Uber X trip and in the long term comparable to using your own car for travel. Obviously Uber wants to offer their own flying taxis, so all of these figures should be taken with a pinch of salt, however they have performed a quite comprehensive and structured analysis to get to these figures in the paper and it’s worth looking through the methodology and plugging your own numbers in.

Passengers and Bystanders

“Having lots of whirring motors flying above my head… isn’t exactly an anxiety reducing situation – is that blade going to come loose and guillotine me?” – Heavily paraphrased Elon Musk Quote

Okay, so I have arrived at a possible solution after considering the bigger picture, abstracting the problem, choosing a segment and making a start at evaluating its score using direct energy costs. If we think back to our scoring system, we realise that these cold numbers are just the beginning. We also need to consider other proposed solutions to the same problem before fixating on one and defending it dogmatically. This is where it gets quite challenging, and where cities will likely diverge in their final choice because of local preferences and details.


Virgin’s Hyperloop One

Let’s consider some land based proposals like Hyperloop, High Speed Tunnels and HS2, assuming they cost the same per mile (which they most probably wont). I’ll have to do a detailed comparison for a particular city pair one day, but here are some initial considerations:

Local Noise and Emissions: Tunnels and tubes are largely hidden from people’s senses. Elevated tubes less so. Flying vehicles inevitably noisy.

Passenger experienced: Lurched into the heavens or accelerated into a dark tunnel at mind boggling speed? Both out of human comfort zones, but the latter can be made comfortably gradual, especially without windows.

Infrastructure: Initial tunnelling expensive, and raised rail eye-sore and difficult to obtain optimal land. Train and hyper-loop need high precision rails to be regularly maintained. Flying cars need nearly no infrastructure as most concepts intend on re purposing rooftops, local airfields or service stations near highways.

System integration: Tunnels and hyperloops could allow bikes or cars to slot right on, but stations few, far between and likely in built up areas too far from suburbs. Flying taxi ports could be anywhere and less constrained by say the route of the rail.

Capacity: Train initially starts higher but ultimately constrained and difficult to scale without new tracks. A single vehicle or track failure shuts down the whole line for everyone. Flying cars start lower capacity and more expensive but in theory very saleable through parallel air lanes in 3D.

Failure Mode: Flying car falls from the sky, parachuting to ground if lucky, tumbling uncontrollably into a crowd if not. Not inconceivable. A train or hyper-loop car is stuck in a tunnel. Claustrophobic. Fire catastrophic. Derailment causes extensive damage to infrastructure. Very unlikely given significant human experience in high speed rail.

For the same network, a system of tubes and tunnels appears much more desirable than a route network of flying vehicles, but with today’s technology the time and cost to implement the infrastructure for a ultra high speed train/tube network is likely crippling beyond a few key town/city pairs.

Up Next

Initial research suggests that flying cars could be a good solution for the 30-mile, 90-minute trip, giving up to 20 hours a week back to greater London commuters, reducing road traffic and helping people live more spaciously and away from the urban centre. Whilst a lot of the human factors aren’t as favourable as a hyperloop, the time and cost to introduce VTOLs compared to a hyper loop or high speed underground network is a fraction, with a much higher ability to customise and scale.

The Segment Score of a flying car appears to be a multiple better than driving, assuming the noise can be kept at least close to highway levels and that safety is a multiple higher than driving which Uber believe is possible. The effect on the Mobility System Score will depend on the accessibility of the ports to suburban commuters, the reliability of the service and the degree of integration with local and national transport schemes. For widespread adoption many local factors would need to be overcome including public acceptance, regulation and safety demonstrations.

To get a better handle on the scores, we proceed to conceptual design and evaluation – the fun bit! Stay tuned.



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