by Clem Robertson.
In this blog, we are looking at changes in consumer behaviour in the car market, developments in our urban communities and mapping these against autonomous technology progress. We’ve listed our top 10 scenarios on how consumers are going to change the way they move in the future:
Top 10 trends:
- Human movements are shorter: people are travelling shorter distances, ie the urban daily commute may be long in time but is short in distance. By 2030 it is predicted that 80% of the Global population will live in an urban area (many in megacities). With shorter travel distances and greater human density, the risk and frequency of collisions will greatly increase. Autonomous vehicles will become the safer solution to the daily commute.
- No space to park: as our communities become denser, there will be less room to park your own vehicle. But what if a vehicle just dropped you off at home, and then travelled autonomously to a nearby car park for overnight storage?
- Rent vs Buy: In all industries there is a move away from ownership of larger goods and towards licencing models. Hire purchase and the leasing of cars is already becoming commonplace (last year in Germany, one fifth of new cars were leased not purchased). We predict that in urban areas, consumers will move from leasing one car to vehicle sharing – it’s an easy leap once you don’t own a car. Zip Car is an example of a company already in this space.
- People still like to have their independence: Having access to data gives people the feeling of choice and independence. A taxi is great, but the Uber model goes one further where you have information about your driver, where the car is and control over the type of journey you take, private or pool. An autonomous pool of cars may well replace car ownership entirely and people buy an app, not a car.
- Fewer young people are learning to drive: why learn if you don’t need a car or can‘t afford to run a car. At some point autonomy may mean you won’t have to drive the car you sit in? This means future generations of people will be reliant on shared public modes of transport which will in turn need to cater for huge rises in numbers using their network. Automation is fundamental to ensuring scale up is possible.
- Speeds are not high: The maximum average speed of an autonomous car is predicted to be 30 mph. Current average traffic speed in London is already under 20 mph and very often under 10 mph so the urban population will not notice the speed limitations of autonomous cars. In rural areas and connecting highways however, the current average speed is closer to 40 mph in the UK and can obviously get to 70mph. In the shorter-term, we therefore predict a higher take up of autonomous vehicles in urban areas.
- Sensor & communication technology: the sensor and communication technology required to implement an autonomous system is far easier to realise in urban areas where infrastructure deployment is far easier and cost effective to introduce and maintain. Practically, urban areas have the economies of scale to get autonomy first. This means that anyone wanting to travel outside of an urban area cannot purchase a totally driverless car for at least the first couple of phases of an autonomous infrastructure rollout.
- Detection distances: in urban areas, detection distances for autonomous systems are short due to low speed which plays to the strengths of current camera/ LiDAR technology. Also the high density of WIFI and cellular infrastructure will provide the communications platform necessary for the effective operation of V2X (Vehicle to everything) communications.
- Congestion: in urban areas there are a lot of things happening at the same time and a lot of unknowns. Potential hazards can move in many different directions (i.e. pedestrians at an intersection), whereas on highways and rural roads they are more likely to be travelling in the same or opposite direction (i.e. bicycles, motorcycles, cars, lorries). Urban is one of the hardest environments to predict due to not having control over pedestrian decision-making. Automation companies will have to develop systems to accurately detect, classify and respond to the harsh urban ecosystem. Will this encourage urban planners to design future cities where pedestrians, electric scooters and public transport don’t share the same spaces?
- Climate change: who can predict the weather? We can’t, but you need an autonomous system that can cope with all weather conditions. Current camera and LiDAR technologies have been shown to suffer reduced performance in severe or variable weather conditions. DSRC WIFI and cellular V2X technology may also suffer from a reduced or drop in service dependant on atmospheric conditions. This, combined with our increasing appetite for remote working means that less workers may use the transport network. This could negate the need for their own transport and where we only summon transport when required.
There is no doubt that autonomous systems will change the way we interact with our environment. Check back on this blog in 5 years’ time to see if we were right!