London, it is said, still has a long way to go before reaching its smart mobility goals. I myself was able to get a first-hand impression of this last year, when I was straying about Victoria Station at 11 in the night among the throngs, looking for a means of transport that would take me to my hotel and the others to their homes. The reason: a signal problem at the other end of London.
If you can’t afford London, I suggest you come over to Stuttgart. In Germany’s traffic jam capital, you can experience this every day: canceled trains, suburban train delays, stationary (and honking) cars desperately looking for a parking spot. Buses that can’t get through streets barricaded by parked cars, commuters who are squeezed into suburban trains (we’re now deploying personnel on the suburban trains to stop those trying to squeeze themselves in at the very last minute – that’s the opposite of the Japanese oshiya). Strange, because so many different modes of transport are available (including on-demand electric rental cars). The public transport network though is cramped and dense. The level of satisfaction of those who (have to) commute to work is moderate (especially if they have to commute from outside the metropolitan region).
Stuttgart and London are not unique cases. Every larger city in the world has to struggle with the consequences of excessive mobility. Overstrained public transport systems, too many cars, miserable air (incidentally, fine particle levels in the air is yet another problem in Stuttgart). Established concepts are not effective in the developed cities of Central Europe and North America.
Urban (smart) mobility is still a dream. Which is odd because data for optimizing the flow of traffic is available. In abundance, in fact. Moovit, an Israeli startup, works with local public transport companies and with its own community of Mooviters, who enter as yet unavailable data into Moovit’s systems. As of now, around 330 million people around the world use Moovit. Data on pedestrian traffic can be captured by smartphones, hotspots or GPS. Above all, municipal administrations and transport companies have valuable data at their disposal – which is often kept in inaccessible silos (in a business context, this would probably be called “intellectual property”). Data from sensors (such as induction loops and cameras), operating data from control stations. And now, another silo has come into the picture, thanks to connected cars.
Connected cars do offer added value in two directions. Over-the-air updates are a typical example of what’s “in”, predictive maintenance techniques of what’s “out”. But even simple position detection (possibly also in conjunction with Car2X technologies) can be valuable for urban development projects. And OEMs can use connected cars to develop new business models. Because they own the data.
VW is a classic example. The OEM uses anonymized mobility data for a new traffic management system and determines the status quo. An algorithm on a quantum computer deals with designing a model on how to optimize the situation. In Beijing (formerly called Peking), the VW model has already optimized the driving schedules of taxi services. In theory, at least. Barcelona is next on the list of the VW developers. VW plans to offer the model as a chargeable service – and has thereby added a new digital business model to the prospering list of OEMs.
Moovit, Sweco UK, VW or TfL in London (who have released their live data for app developers) all demonstrate interesting strategies for making the flow of traffic smoother. However, several more steps need to be taken to achieve an optimized system. In my view, holistic approaches that include ALL public and private modes of transport (including pedestrians) offer the best prospects for fundamental improvements. And, secondly, transport providers (such as local public transport, taxis, rental cars or the much-talked-about autonomous transporters) must be able to maintain the necessary capacities for peak loads and deploy them promptly. What good would a cool deployment system do without having the necessary trams, suburban trains or taxis? Would it be any better if they were available but could not be deployed because the routes or traffic junctions are “allocated” anyway?
Capacity planning is raised to a new level of complexity in flexible deployment scenarios that are predefined by a cloud solution or a quantum computer. Data analysis and models are one thing, physical implementation is another – we in the IT industry tend to forget this in our virtual world. And we haven’t yet spoken about the costs and data protection issues. It will probably take a while before my dream of seamlessly flowing urban traffic and intermodal transportation comes true. Maybe I’ll stay at my home office today. You have a safe trip.
