To transform Australia’s cities, it should scrap its car parks

A Sydney car park from above. Image: Getty.

Parking may seem like a “pedestrian” topic (pun intended). However, parking is of increasing importance in metropolitan areas worldwide. On average, motor vehicles are parked 95 per cent of the time. Yet most transport analysis focuses on vehicles when they are moving.

Substantial amounts of land and buildings are set aside to accommodate “immobile” vehicles. In Australia, Brisbane provides 25,633 parking spaces in the CBD, Sydney 28,939 and Melbourne 41,687. In high-demand areas, car parks can cost far more than the vehicle itself.

However, parking is not just an Australian problem. By some estimates, 30,000 square kilometres of land is devoted to parking in Europe and 27,000 km² in the US. This parking takes up a large part of city space, much of it highly valued, centrally located land.

Traditionally, transport planners believed that generous parking allocations provided substantial benefits to users. In reality, excessive parking is known to adversely affect both transport and land use. These impacts, along with recent land-use, socioeconomic and technological trends, are prompting cities to start asking some important questions about parking.

Australian planners must engage with emerging trends to help cities work out the best way to reclaim and repurpose parking space in ways that enhance efficiency and liveability while minimising disruption.

Here we chart likely challenges and opportunities created by these trends over coming decades.

Key trends affecting parking space in cities. Image: author provided.

Land use

All Australian cities have policies to encourage densification, consolidation and infill development in their centres. In conjunction, some cities are setting maximum limits on parking to prevent it taking over valuable inner-city properties.

Transit-oriented development (TOD) has also become popular, at least on paper. This is another form of urban consolidation around transit nodes and corridors. It is known to benefit from high-quality urban design, “walkability”, “cyclability” and a mix of functions.

These developments mean that people who live in CBDs, inner-ring suburbs and near public transport stops will use cars less. Consequently, demand for parking will decrease.

Some non-TOD suburbs are trying to replicate inner-city features as well. For example, some suburban shopping centres have introduced paid parking. This is a significant shift from previous eras, when malls guaranteed ample free parking.

Suburbanites who lack easy public transport access will continue to rely on cars. But rather than driving all the way to a CBD, commuters will increasingly opt for park-and-ride at suburban stations, thereby increasing demand for park-and-ride lots at public transport interchanges. However, excessive capacity might hurt rather than help patronage.


Social trends

In addition to land use, several social trends will affect the need for parking.

First, young people are delaying getting drivers’ licences because driving is culturally less important to them than in previous generations.

Second, people of all ages are moving from outer suburbs to inner cities. For many, this means less driving because walking, cycling and public transport are more convenient in inner cities.

 

inally, the emergence of Uber, Lyft and vehicle-sharing arrangements means that people are not buying cars. Research suggests that each car-sharing vehicle removes nine to 13 individually owned vehicles from the road.

Together, these trends point to a reduced need for parking because there will be fewer cars overall.

Technology

The importance of technology in parking is rising – paving the way for “smarter” parking.

The emergence of a host of smartphone apps, such as ParkMe, Kerb, ParkHound and ParkWhiz, has begun to reshape the parking landscape. For the first time, users can identify and reserve parking according to price and location before starting their journeys.

Apps also make available a host of car parks that previously went unused – such as spaces in a residential driveway. This is because there was no mechanism for letting people know these were available.

In addition, smart pricing programs, such as SFPark in San Francisco, periodically adjust meter and garage pricing to match demand. This encourages drivers to park in underused areas and garages and reduces demand in overused areas.

The advent of autonomous vehicles promises to have dramatic impacts on transport and land use, including parking.

According to one school of thought, mobility services will own most autonomous vehicles, rather than individuals, due to insurance and liability issues. If this happens, far fewer vehicles and parking spaces will be needed as most will be “in motion” rather than parked most of the time.

More space for people and places

The Tikku (Finnish for ‘stick’), by architect Marco Casagrande, is a house with a footprint of just 2.5x5m, the size of a car parking space. Image: Casagrande Laboratory.

The next decade promises much change as emerging land-use, socioeconomic and technological trends reshape the need for, and use of, parking. Cities will devote less space to parking and more space to people and places.

Parking lanes will likely be repurposed as cycling lanes, shared streets, parklets, community gardens and even housing. Concrete parking lots, and faceless garages will likely be converted to much-needed residential, commercial and light industrial use.

The ConversationBy transforming parking, much urban land can turn from wasteland into vibrant activity space.

Dorina Pojani, Lecturer in Urban Planning, The University of Queensland; Iderlina Mateo-Babiano, Senior Lecturer in Urban Planning, University of Melbourne; Jonathan Corcoran, Professor, School of Earth and Environmental Sciences, The University of Queensland, and Neil Sipe, Professor of Urban and Regional Planning, The University of Queensland

This article was originally published on The Conversation. Read the original article.

 
 
 
 

Google knows you took the bus: on the creepy accuracy of Google Maps Timeline

You are here. And here. And here. And... Image: Google Maps.

Knowledge is power, they used to say. Nowadays, they say “data is power”, and they’re not wrong. Unlike many of the modern, high-value tradable goods in our society like oil or gold, data is a limitless resource that we’re constantly creating more of day after day.

What the actors who own this data choose to do with it can often be a point of vast contention: should I be happy for Google to reliably know where I am, where I’ve been, and most frighteningly, where I’m going? It’s not up for dispute that the scope of these tools can be immense – but how much of that scope should we take for granted?

Google Maps is a tool full of wonderful surprises. It can plan a journey for you, tell you what deals to get at the supermarket, and give you updates at the bus stop. Some of the things Maps can do, it does without us even asking; Google knows when we pop to the shops, or when we stand by a bus stop.

This concept is called “geofencing”: cross-referencing geolocation data with the services at that location, and issuing notifications to a device on that basis. Google knows I’m in the supermarket because my location matches up with the area the supermarket is known to occupy, and through a complex series of phone masts and wifi access points, it knows I’m between the vegetable aisles. Okay, maybe things aren’t quite that specific, but the detail is stellar – and often, slightly concerning.

A simple flick through the timeline feature of Google Maps reveals that Google can plot day by day where you were, when you went home, and, maddeningly, how you took that journey – or at least, it can make an educated guess. By applying geofencing programming, Google can calculate when we are near a bus stop, and cross-reference that data with bus routes and other bus stops to determine with a reasonable degree of certainty when its users are taking the bus. Google doesn’t go as far as to try and guess which bus, but it could make an educated guess.

The same is true of train stations; pause in one, follow the expected route of the railway line, and travel through additional train stations, and Google will have no trouble in informing you after the fact that you have travelled by train. A reminder that you don’t need to have planned a journey on Maps for Google to surmise this: it is all calculated based on shifting geolocation data, and nothing more.

Walking, cycling and driving are harder for Google to calculate, because there are no geofenced points of entry for these modes of transport. It is therefore likely that, once bus, train and metro have been eliminated from the mix, Google simply inspects the time taken between harvested geolocation data to calculate the transport mode used. But without geofencing, it’s harder to determine the exact route taken by a user: because they’re not following a prescribed route, and because geolocation data is much easier to take while stationary, routes on timeline taken independent of public transport can end up looking… messy.

Google fails to surmise that some of this journey was taken by train and presumes I took an unorthodox drive through Kent in the early hours. Image: Google Maps/CityMetric.

The system isn’t perfect. For one, it can’t account for anomalies. I took a rail replacement bus service recently, and Timeline was dumbstruck by how I’d managed to get home. But the ever-increasing availability of data surrounding transport timetables means that the assumptions Google can make about our transport choices are only bound to get more accurate. That’s important, because its information that few organisations beyond Google are likely to have real access to.

If we take London as an example, we know that Transport for London (TfL) can use data on traffic flows, ticket barriers, and incomes for bus routes to determine how people use a service. In fact, TfL has even used its own wifi services to calculate route maps on the Tube. However, without undergoing intricate surveys, they will struggle to plot exactly how journeys are taken beyond the Tube Map, especially with regards to buses, disparately owned NR services, and so on.


Google has exactly the information to remedy this – and it’s integrated into Timeline, simply because people consented to having their location data collected. If your local borough council asked to do the same, and the only provision it could grant was that you might get a better bus service, many people would probably opt-out. Part of the reason why we accommodate the location-harvesting of Google is because we consider Maps such a vital service, and its domain – at least in terms of its rights to record our geolocation – is hardly contested. Even those of us who use Citimapper regularly tend to have Maps downloaded on our phone.

Google Maps is in a unique position to mark the differences between journeys that are entirely spontaneous and journeys that are pre-planned, because it is measuring both. That information could be highly useful in designing timetables and shaping user-friendly services.

Moreover, as geolocation data grows more precise, it will be able to help us pin down the flows of pedestrians and cyclists in our cities. While it’s possible to gather this data in the public domain without geolocation, it’s economically prohibitive to do so in less densely populated areas. This data would help prioritise cycle-friendly and pedestrian friendly developments on the understanding of where demand is greatest.

This sort of data inevitably carries such a high risk factor, however – not only as far as personal privacy is concerned, but also surrounding efficacy. We presume that if we know every individual's travel patterns, we can design perfect travel services – but patterns change all the time. An algorithm can never incorporate the latest change before it is registered by the system. While data like that collected by Google Timeline could be put to better use by transport authorities, it shouldn't be abused, nor serve as a panacea for good design.

Worst of all, it’s hardly clear that this data is up for public consumption. The furore over data protection means it would be considered deeply unethical for Google to hand this location data over to anyone, let alone a local government body like TfL. It may be moot point; Google itself claims that Timeline is for our own amusement and little more.

But maybe we’d get better services if it wasn’t; after all, geolocation isn’t slowing down anytime soon.