There are 15 billion devices currently connected to the Internet of Things (IoT) with 5.5 million new ones being connected daily. This tech expansion, designed to spread across and augment existing cities to change what transport means. From automated buses, to the next-gen of ride-sharing, cities connected by IoT will make getting from A to B more accessible, less frustrating, and safer than ever, if we allow it.
Big data for big cities
Traffic jams cost more than just time; they burn through fuel, productivity, and happiness costing Australians around $16.5 billion in the last financial year. Big data has the power to stop this in its tracks, finding congestion points, common routes, and accident sites which are fed into an automated grid used to devise solutions.
We can do this in a few ways. The first is vaguely traditional – GPS maps, user data, statistics and anecdotal evidence is used to re-map transport routes and choose which solutions suit us best. For Rio De Janerio, this approach led to the creation of a 98-foot Volvo bus, which wouldn’t last one minute in the mean streets of Bondi.
The other is more future-leaning. Internet of Things sensors, artificial intelligence, and sensors on cars themselves inform how planners design public transport routes – constantly updated and adaptive to its environment. For example, by placing cameras and sensors on every car in a city, we can create a network of real-time measuring tools that can identify empty parking spots/car accidents/traffic disruptions/less busy roads and allocate them to other drivers in real time. This doesn’t have to be purely quantitative either – a map project from a Barcelona Yahoo lab created maps based on more emotional qualities like the types of smells, sounds, or beauty of streets. These can help suggest routes that are more emotionally pleasant than others, keeping people happier on their daily commute. In the USA, data collection company Transitland keep an open record of public transport data for developers to create tools with. Studies across the United States have shown that people who have access to real-time data on when their transport will depart and arrive are more likely to use it, so this open approach helps make this more of a reality. Essentially, there’s a big shift on the horizon, and it all begins with data.
If you have a phone, you are a bus stop
Public transport in urban communities is a constant tug-of-war, where cities like Sydney and Melbourne face a transport network on the brink of capacity with a population rising beyond its means. This is not a unique problem: dense urban centres across the globe face similar challenges with gridlock chewing away at the sanity of its inhabitants. The solution may rely on connected cities using data to shift public transport from fighting a city to being the veins of it.
In 2014, Mercedes-Benz attempted to revolutionise mass-transit design with ‘CityPilot’, an ongoing project that uses connective technology for an automated, safe, and efficient mode of transport. Equipped with a dozen cameras (for traffic light, pedestrian, and vehicle recognition), the bus uses sensors and GPS tech to ‘learn’ its route and drive autonomously. Though equipped with a driver, it successfully drove with virtually no human intervention on a 20km test journey around a tight Amsterdam city environment. Here, the benefits speak for themselves: a smoother driving style which anticipates braking, a longer lifespan of vehicles, lower maintenance costs, and reduced fuel consumption (so the ride costs less for you).
The other contender is Local Motors, who, fresh from creating the world’s first 3D printed vehicle, are developing what it hopes will be the gap between large-scale buses and self-driving cars. It’s an autonomous ‘ecosystem’ of public transport vehicles they’ve named ‘Olli’. Small, compact, minimal, and backed by IBM Watson AI technology, the self-driving vehicles are designed to ‘fill the gaps’ in transport methods via a ‘fleet management system’ controlled by a central operation system, plus a user app. CityPilot and Olli, when integrated with city-wide sensors and data, could work with a city’s traffic plans, lights, and traffic conditions to make public transport the fastest, most obvious way to move.
Ride-sharing: beyond 2020
If Elon Musk has anything to say about it, the notion of ‘private vehicle ownership’ is about to become a lot more public. Already, Tesla cars are fitted with the hardware required to move without a driver, they’re just ironing out the kinks in the AI. When they do, the notion of how we use our cars will change completely. In the aforementioned Master Plan, Musk outlines a vision where cars are owned by few and used by many; once your car drops you off at work, it can join the ‘Tesla Shared Fleet’ and spend the day driving passengers around the city generating revenue – before picking you up again at the end of your work day.
“Since most cars are only in use by their owner for 5% to 10% of the day, the fundamental economic utility of a true self-driving car is likely to be several times that of a car which is not.” – Elon Musk, Tesla Master Plan, Part Deux
In the future, public and private transport might merge into one; transport that moves seamlessly through the places we live. Or we could all just buy our own personal drones and never worry about road traffic again.
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