IN DEGREE PROJECT TECHNOLOGY,FIRST CYCLE, 15 CREDITS

, STOCKHOLM SWEDEN 2018

Estimating the Potential Spatial Implications of Shared Autonomous Vehicles

A Case Study of Stockholm

MARTIN GUTSCH

KTH ROYAL INSTITUTE OF TECHNOLOGYSCHOOL OF ARCHITECTURE AND THE BUILT ENVIRONMENT

TRITA TRITA-ABE-MBT-18434

www.kth.se

Foreword Since I started the bachelor program in Civil Engineering at KTH, I have been interested in

the future of cities and the possible disruptive phenomena that will change the way we think

about cities. From discussions with friends and teachers, as well as online lectures, I’ve

become interested in the potentially disruptive changes stemming from the introduction of the

autonomous vehicle, and especially the shared autonomous vehicle. This thesis is my

exploration of how this change could affect Stockholm, and what could be done with the

potential for reallocation of space. Through my work I have had great help from my supervisor Andrew Karvonen, whose

positive spirit and insightful comments both got me started and kept me going. Without

Andrew, this thesis had not been done, and I am very grateful for all his help. Norrköping, July 2018 Martin Gutsch

Abstract The area of autonomous vehicles is relatively new and not too many new studies have been

produced. Autonomous vehicles do however have an incredibly disruptive potential to alter

our cities. Through three scenarios constructed from the current literature on autonomous

vehicles, this study will examine the potential for reallocation of space from cars to pedestrian

or other uses made possible by the adoption of autonomous, and shared autonomous vehicles

in particular. Once the three scenarios were constructed, three areas were chosen to examine how they

would be impacted from each of the scenarios. Using examples of urban space reclamation

projects from other cities, examples of potential new uses were constructed. The results of this study are that the potential for reallocation is indeed substantial, but that it

varies with the adoption of autonomous vehicles and shared autonomous vehicles.

Abstract

Autonoma fordon är relativt nytt och antalet nya studier som har producerats på området är

lågt. Autonoma fordon har emellertid en oerhört stor potential att förändra våra städer. Genom

tre scenarier som bygger på den nuvarande litteraturen om autonoma fordon undersöker denna

uppsats potentialen för den omfördelning av utrymme från bilar till fotgängare eller andra

användningsområden som möjliggörs genom autonoma och autonoma fordon i synnerhet.

Tre scenarier konstrueras utifrån tillgänglig litteratur och tre områden väljs för att undersöka

hur de skulle påverkas av vart och ett av scenarierna. Med hjälp av exempel på projekt från

andra städer med syfte att återföra gatutrymme från bilar till andra ändamål skapades exempel

på potentiella nya användningsområden.

Resultaten av denna studie är att potentialen för omfördelning verkligen är stor, men att den

varierar med antagandet av autonoma fordon och delade autonoma fordon.

Table of contents Foreword ............................................................................................................................................. 1

Abstract ............................................................................................................................................... 2

Abstract ............................................................................................................................................... 2

Introduction ............................................................................................................................................. 1

Background .......................................................................................................................................... 2

Projects for reclaiming automobile infrastructure .................................................................................. 3

Barcelona’s Superblocks ...................................................................................................................... 3

Copenhagen’s Strøget ......................................................................................................................... 4

Stockholm’s summer walking streets (Levande Stockholm) ............................................................... 4

Literature review ..................................................................................................................................... 5

What are autonomous vehicles? ......................................................................................................... 5

Change in automobile use ................................................................................................................... 6

Benefits of highly automated vehicles ................................................................................................ 6

Impacts on Urban Space and Traffic Flow ........................................................................................... 7

Road use .............................................................................................................................................. 7

Highway ........................................................................................................................................... 7

Arterial streets ................................................................................................................................. 8

Parking ............................................................................................................................................. 8

Smaller vehicles ............................................................................................................................... 9

Summary of results.............................................................................................................................. 9

Arterial streets ................................................................................................................................. 9

Highways ......................................................................................................................................... 9

Parking ............................................................................................................................................. 9

Change in VMT ................................................................................................................................ 9

Methodology ......................................................................................................................................... 10

Selection of representative streets in Stockholm ............................................................................. 12

Odengatan/Sveavägen neighbourhood ........................................................................................ 13

Kungsgatan .................................................................................................................................... 13

Olofsgatan ..................................................................................................................................... 14

Findings ................................................................................................................................................. 15

Change in urban space due to AV implementation .......................................................................... 15

Possible scenarios .............................................................................................................................. 15

Stockholm today ................................................................................................................................ 15

Baseline scenario ............................................................................................................................... 16

Low adoption of SAVs ........................................................................................................................ 16

Moderate adoption of SAVs .............................................................................................................. 16

High adoption of SAVs ....................................................................................................................... 16

Summary ........................................................................................................................................... 17

GIS Analysis ........................................................................................................................................ 18

Odengatan/Sveavägen .................................................................................................................. 18

Kungsgatan .................................................................................................................................... 19

Olofsgatan ..................................................................................................................................... 20

Scenarios for the locations ................................................................................................................ 21

Odengatan/Sveavägen .................................................................................................................. 22

Kungsgatan .................................................................................................................................... 22

Olofsgatan ..................................................................................................................................... 22

Conclusion ............................................................................................................................................. 23

References ............................................................................................................................................. 24

Image sources .................................................................................................................................... 25

1

Introduction Our cities grew from a need to meet and trade with each other. They went from small

gatherings of houses with dirt roads, to larger cities with paved streets and separate districts,

into the cities we know and live in today, with hundreds of thousands to even millions of

inhabitants, covering vast areas with buildings, roads and public space. The transport need of

cities grew with them. From walking across the street to the next house or bringing your

wares to town on small roads, to horse and carriage on paved roads and the invention of trains

and streetcars all the way to the invention of the car. The car was a monumental shift in

transportation, allowing the average family to travel anywhere they wished and helping

commerce flourish. We owe a lot of our development to cars.

But widespread car adoption comes with several costs and drawbacks. Every year about 1.3

million people die from car related accidents, and road accidents are estimated at a whopping

price tag of 518 billion dollars annually. Apart from accidents, cars pollute both the

environment and degrade local air quality by emissions of pollutants such as CO2 and

particles. They create noise pollution and encourage urban sprawl. But one overlooked factor

that we hardly ever reflect upon, because we have grown used to it, is the enormous space that

cars and their infrastructure require. Cars take up a lot of space. They need space for

highways. They need space for city roads. They even need space when we’re not using them,

sitting idle in parking lots. Except for parks, squares, sidewalks and the occasional bike or bus

lane, cities are either for buildings or cars.

Figure 1: The space occupied by cars highlighted in orange

The spatial impact of cars has only become stronger the more prevalent the car has become.

But there seems to be a possible paradigm shift coming up. Cities are becoming more and

more aware of the negative effects of cars, and car reclamation projects are on the rise.

Barcelona is implementing superblocks to reduce the space dedicated to cars and Stockholm

recently started the summer walking streets initiative, closing some streets to traffic and

parking and dedicating the streets to pedestrians, bicyclists, and parklets or outdoor seating for

restaurants and cafés. Copenhagen has had a major street dedicated to pedestrians and

bicyclists for decades, with infrastructure suited to those needs.

With the invention of the autonomous car, there is hope that we can drastically alter the

impact of car travel on our cities. The shared autonomous vehicle in particular promises big

changes, removing the idle time the vehicle has while parked. Autonomous vehicles could

drive more efficiently than humans. They could park at a different location than where the

passenger exits the car, moving parking spaces from high traffic areas to peripheral areas.

And if we’re prepared to share, we could reduce the number of cars drastically, since

autonomous cars will rarely have to stay parked. All in all, these are changes that are poised to

drastically alter the way we experience our cities.

2

The purpose of this thesis is to examine the potential spatial implications of autonomous

vehicles on the urban landscape. It will examine how potential reductions in vehicle miles

travelled, number of cars in the fleet and required parking spaces, as well as increases in lane

capacities and ride sharing, will affect urban space. It will use the findings of the literature

review to create scenarios with varying degrees of adoption of shared autonomous vehicles

and use the examples of Barcelona, Copenhagen and Stockholm to suggest alternative uses

for reallocated land from vehicular transportation and parking. This thesis will only be

concerning the automation of cars for transport of people, other forms of transportation such

as freight trucks, delivery vehicles etc., while interesting, will be left to other studies.

Questions that will be researched:

How will shared autonomous vehicles change automobile use?

How will the implementation of shared autonomous vehicles change the use of urban

space?

What can be done with the potential reallocation of space from vehicular transport to

other uses?

Background The car has been a great driver of progress throughout the 20th century, but we are now

waking up to the hangover. Cars take up a lot of space both when in use on the road, when

parked on the side of it, or in dedicated parking structures. They emit pollutions that both

reduce the quality of life and even shorten it. Every year, people are hurt, crippled or killed in

car accidents. Roads are barriers that have to be crossed on dedicated crossings, impairing the

flow of pedestrians. All in all, the negative aspects of the car are abundant. But we are

beginning to find solutions to this problem. In cities around the world, local planning

authorities are trying to limit the impact of cars on urban space.

Barcelona is working on a project called “Superblocks”, a project whose aim is to group

together adjacent city blocks into a superblock, prohibiting through traffic and reducing on

street parking on streets within the superblock, directing it to the outskirts of the superblock.

This frees up space inside the superblock to other uses such as expanding pedestrian space or

providing space for outdoor seating.

Copenhagen’s high street Strøget was among the first streets in the world to be transformed

from a street for cars into a pedestrian street. Today, Strøget is a popular shopping street, with

many of the more luxurious store located there. It is also a popular tourist attraction.

The Stockholm initiative “Levande Stockholm” is the city’s attempt at reclaiming urban space

from vehicles and giving it back to pedestrians as walking streets, outdoor seating for

restaurants or parklets. One of the components of the project, called “Sommargågator”

(summer walking streets) is closing streets for car traffic, placing furniture and green plants,

and encouraging bars and restaurants to set up outdoor seating, making the street a livelier

place.

3

Autonomous vehicles and shared autonomous vehicles could give these kinds of projects a

helping push. Autonomous vehicles could drive more efficiently than human drivers,

increasing the capacity of roads and therefore making it easier to divert traffic from one street

to other streets to reallocate the space as pedestrian, park space or other. Shared autonomous

vehicles wouldn’t have to be parked, instead continuing to drive passengers, reducing the

need for parking. Ride sharing would reduce the total number of cars and vehicle miles

travelled. But very few studies have been done to research potential spatial implications of

AVs. This study will attempt to contribute to this area.

Projects for reclaiming automobile infrastructure

Barcelona’s Superblocks

Barcelona has begun implementing their plan for what they call “Superilles”, superblocks.

The concept of a superblock comes from stringing together several normal city blocks and

prohibiting through traffic, creating a space for pedestrians and cyclists. The newly created

space can then be filled with green plants, cafés and parklets, enhancing the pedestrian

experience and lessening pollution effects. The project is an effort to reduce vehicle travel in the city, and to give back space to

pedestrians. One of the major reasons that the project started was that Barcelona repeatedly

failed to meet air quality targets set by the EU. The pollution from cars was so severe that an

estimated 1200 deaths could be avoided if the EU targets were reached. The superblocks in the Eixample neighbourhood would be about 400 by 400 meters large,

consisting of 3 by 3 regular city blocks. The population of such a superblock would be around

5500 people. With an average road width of about 10 meters, that would free up around

15600 square meters, an average of about 3 square meters per resident. If even a fraction of

this newly recovered space was used for new green areas or parklets, this would be a major

improvement for Eixample’s 1.85 square meters of green space per inhabitant.

Figure 2: Superblock structure

4

Copenhagen’s Strøget

Strøget is a large main street in Copenhagen, consisting of four streets; Nygade,

Vimmelskaftet, Fredriksbergsgade and Østergade. There are also three squares, Gammeltorv,

Nytorv and Amagertorv. It’s been an historically important street, but with the adoption of the

automobile in the early 20th century the street became more and more car oriented. However,

following the example of other projects where streets were turned back into pedestrian streets,

Strøget was closed to car traffic in 1962, thus creating a pedestrian street. To emphasize the

change from a car dominated street towards a pedestrian street, planners used new paving and

cobblestone.

Figure 3: Section of Strøget

Stockholm’s summer walking streets (Levande Stockholm)

Since 2016, the city of Stockholm

closes some streets to cars every

summer, dedicating the street to

pedestrians, cyclists, green space

and outdoor seating for restaurants

and cafés. This is a step in trying

to make the city more attractive

for pedestrians, while it also

lessens both pollution and noise

pollution in the area. The concept

of summer walking streets has

been expanding every year since

its start, so a potential for

reallocation of roads to pedestrian,

cycling and commercial uses from

the inception of autonomous

vehicles would fit well with the

expansion of “Levande Stockholm”.

Figure 4: View of Rörstrandsgatan, a summer walking street

5

Literature review

What are autonomous vehicles?

Autonomous vehicles (AVs) are vehicles that to some degree can handle the tasks that a

human driver normally takes care of. According to SAE (SAE INTERNATIONAL and

J3016, 2014), there are 5 levels of autonomous cars, as well as level 0 which is the

conventional driven vehicle (CDV) fully operated by a human. In summary, level 1 might

have systems like adaptive cruise control (ACC), which is a function that could adjust the

speed to the vehicle in front. Level 2 can control steering and speed at the same time, but only

for shorter periods. Level 3 is essentially autonomous but will give back control to the human

driver if the system can’t function properly in a situation. A working example of this level is

Tesla’s Autopilot. Level 4 is even more autonomous, and requires no human input, instead

bringing itself to a halt if a situation becomes too difficult. Level 5 is complete autonomy and

requires no human input whatsoever. It isn’t until levels 4 and 5 that many of the benefits

discussed in this thesis will begin to emerge.

Figure 5: Levels of automation

6

Change in automobile use

AVs and SAVs are theorized to increase car VMT by enabling people who can’t drive to use

cars, as well as by reducing the cost of travel time, making the car a more attractive mode of

transport. For those who don’t want to invest in a car, automation of taxis would reduce their

cost of travel, thus making it a more affordable option (Litman, 2018, p. 9).

As people reach retirement age, they drive less. They also drive less due to age related

illnesses. They might still travel by car, but they will be driven by chauffeurs. The decrease in

elderly travel that stem from illness or the cost/inconvenience of chauffeurs might disappear

when AVs eliminates those barriers to vehicle travel (Wadud, et al., 2016, p. 9). The study

estimates AVs could also increase VMT due to a reduction in cost of driver’s time. The

increase is found to be about 60% for full (level 4) automation (Wadud, et al., 2016, p. 9).

Today, adolescents too young to drive or people with disabilities who can’t drive themselves

have to be chauffeured or find other means of travel. AVs will enable them to travel by car,

increasing total VMT. However, even though these two demographics represent about 10-

30% of the population, the increase from AVs are predicted as just a few percent.

This suggests a pent-up demand for vehicle trips that could serve kids, adolescents and

elderly. The implementation of AVs could enable these age groups to travel more. Wadud, et

al. (2016, pp. 9-10) estimates that the increase in vehicle travel of the elderly and adolescents

over the age of 16 from the implementation of AVs to be around 2-10%. Adding to that the

estimated increase of about 2-5% for disabled people and adolescents below 16, AVs would

increase the total VMT by about 4-15%.

Fagnant & Kara (2015, p. 172) estimates that increases in capacity will increase VMT by 26%

at a 90% adoption of AVs. (Bierstedt, et al., 2014) estimates the VMT increase from AV

adoption at 95% to be 35% on some parts of the transport network. While AVs are likely to

increase overall VMT, SAVs could lessen the effects of that increase. According to (Litman,

2018, p. 21), households who enter car sharing arrangements reduce their VMT with about

25-75%.

Benefits of highly automated vehicles

Litman (2018) discusses several benefits of implementing AVs. Among them are increased

mobility for individuals who for some reason can’t drive themselves, potential reductions in

crashes and accidents due to the removal of human error, decreases in pollution from

increased fuel efficiency and, one of the most important factors for this study, the facilitation

of carsharing and ridesharing. So how does AVs change anything from conventionally driven vehicles? Personally owned

AVs would still use as many cars to do the transport work of conventionally driven vehicles.

The strength of AVs come from their ability to communicate with each other and react to

events faster than humans can. This means they can drive in a more coordinated way,

particularly in a formation called platooning (Litman, 2018, p. 12). Platooning minimizes

wind resistance by having several vehicles drive closely behind each other. This enables for

decreased fuel consumption from drag related inefficiencies, as well as packing more cars in a

smaller space, thus increasing lane capacity.

7

But the real advantages come from shared autonomous vehicles (SAVs). SAVs are AVs that

are shared between several individuals or owned and operated by a company. One of the most

efficient forms is a sort of ride hailing service like Uber and Lyft, but operated with AVs, thus

eliminating the cost of the trip that goes towards the driver’s salary. SAVs would be

summoned to whatever time and place you would like your trip to start and then take you to

your destination. Litman (2018, p. 9) estimates that the average cost of an AV taxi (a SAV

owned by a company) would be roughly 1$/mile.

Another interesting aspect is the potential of SAVs for use in first mile/last mile problems.

First mile/last mile in transit is, as the name suggests, the first and last legs of your journey. If

you for example walk from your door to a commuter train, take the train to the central

business district and then take a cab from there to your destination, e.g. your workplace, the

first mile trip is the walk to the commuter train and the last mile trip is the cab trip to your

workplace (Best, 2017). SAVs could help in this problem by chauffeuring people to transit

hubs. Furthermore, once you buy a car you are likely to use it more than strictly necessary,

since you want to maximize the benefit of the investment (Litman, 2018, p. 21).

Impacts on Urban Space and Traffic Flow

Road use

Highway

According to a study by Shladover, et al. (2012) AVs can increase highway capacity by up to

80%. A recent study from Stockholm (Trafikanalys, 2017, p. 12) has found that Essingeleden,

an important highway, could see capacity increases of up to 70%. However, all these studies

assume high (>90%) adoption of AVs. That increase in capacity could be utilised either for a

higher flow of vehicle trips, or for some lanes to be converted into bike lanes, or to reduce the

size of future highways (Trafikanalys, 2017, p. 5). A study by Tientrakool, et al. (2011) concerning cars using “Adaptive cruise control” (ACC),

vehicle sensors and vehicle to vehicle communications (V2V) suggests that if the vehicle fleet

consisted of just these types of vehicles (no conventional vehicles at all), highway capacity

could see a remarkable increase of 273%. Another positive effect of AVs on traffic is their potential for lessening so called “Phantom

Jams”. A phantom jam is a phenomenon that occurs when cars are traveling close to each

other and one car for some reason suddenly brakes, causing the following car to react quickly

and brake harder, this sequence then traveling further down the line and increasing until one

car must come to a complete stop, causing a traffic jam behind it as all other cars are forced to

brake to a standstill (Calver, et al., 2011, p. 614). AVs could potentially help this by acting as

a buffer with better reaction time and coordination with other AVs through platooning

behaviour. A platoon of AVs communicating with each other could realize that the first car in

the platoon is braking and then brake together in a way that would enable the last car in the

platoon to hardly break at all, therefore eliminating the phantom jam before it even happened.

Calver, et al. (2011, p. 618) estimates this to lead to a 68% increase in throughput, however,

for this effect to emerge, complete AV adoption is necessary.

8

Arterial streets

At the arterial level, i.e. city roads, not all studies are as optimistic. Fagnant & Kara (2015, p.

174) expects the benefits to be much smaller for the city streets than for the highway, with a

mere 15% reduction in congestion at a 90% adoption of AVs. This is due to increases in lane

capacity. However, a model from Trafikanalys (2017, p. 12) gives a more optimistic view,

finding that if every vehicle on the road was autonomous, the streets of lower Kungsholmen,

Stockholm, could see their capacity doubled. The difference in the findings of these studies is

likely to be that even a few human drivers in the road network could hinder the AVs a lot by

interrupting platooning behaviour or interactions at intersections.

What is important to note is that these two previous studies consider personally owned AVs,

as opposed to SAVs with ride sharing. The major difference to the resulting traffic and

congestion between the two versions of AV is that the ride shared SAVs could reduce overall

vehicle trips by a lot. According to a study from KTH, a scenario of ride shared SAVs could

reduce the overall VMT by 89% from the baseline case of private cars with single passengers

(Rigole, 2014, p. 28).

Parking

According to a 2014 study (Fagnant & Kockelman, 2014), SAVs could reduce the total

number of cars in the fleet by about 90-92%. This is because SAVs are not privately owned,

and would rarely have to park, instead going to the next passenger instead of parking. Rigole (

2014) calculates that since the average car in Sweden drives 12000km per year, at an average

speed of 60km/h it has a utilization rate of just 2.3%. That means that the average Swedish car

(as of 2014) is parked about 97.7% of the time.

The car mostly sits idle, occupying a parking lot somewhere, space that could be better used

for other purposes. The cost of a parking spot in a garage could be as high as 13,000-18,000

dollars/spot (Boulais, 2017). The cost of street parking is obviously lower due to the cost of

constructing multi-storey car parks, but the space it takes up, especially in the city centre,

could be worth far more if the land was available for other purposes such as buildings or

outdoor seating etc.

Fagnant & Kockelman (2014, p. 8) suggests that there could be potential reductions of about

11 parking spaces for every SAV. (Rigole, 2014, p. 24) also believes the reduction of parking

spaces could be significant, stating that only 5% of today’s parking spaces would be

necessary. Zhang, et al. (2015) is a little more conservative, estimating a decrease in parking

demand of around 90%. Even if the actual reduction of parking spaces would be much

smaller, if we are prepared to accept some empty vehicle driving, we could move parking

spaces from the central business districts and high streets to more peripheral areas of the city.

Fagnant & Kara (2015, p. 174) has found that moving a parking spot from the central business

district will save land owners in the central business district upwards of 2000 dollars, moving

it all the way to the suburbs would save upwards of 3000 dollars.

9

Smaller vehicles

The studies above consider normal vehicles, e.g. 5 seat sedans and larger vehicles. One of the

reasons that cars are heavy and bulky today is due to passenger protection in the case of

accidents and crashes. Considering that 90% of all automobile accidents are caused by human

error, AVs could potentially reduce the risk of crashes to almost a tenth of today’s levels. This

means that AVs could eschew heavy physical safety features for advanced AI driving

(Morrow, et al., 2014).

Figure 6: Size comparison for a firefly and an average SUV

For the city based SAV companies, there’s no reason all cars have to be larger than necessary,

considering many trips will be just one-person trips. In 2013, Google’s daughter company

Waymo started designing a compact pod car that they called “Firefly”. This smaller pod car

carried two persons at top speeds of 25 miles per hour, roughly 40 kilometers per hour. This

car would be ideal for city environments, taking up less space and fuel, and the 40 kilometers

per hour speed limit wouldn’t be a problem in the city’s slower road network (Ahn & Waydo,

2017).

Summary of results

Arterial streets

The literature review indicated that the improvements to arterial road capacity could range

from between a 15% to a 100% improvement, depending on the adoption of AVs

Highways

The results for highways were an increase in capacity between 80% and 273%. The difference

in the results stem from the adoption rate of AVs. With lower adoption rates, the capacity

improvements could be as small as around 10%.

Parking

As for parking, the reduction of parking spots needed would range between a 0-95% decrease.

This depends on the ratio of SAVs to personally owned vehicles, autonomous or not. Only

SAVs that rarely stop to park, instead constantly chauffeuring customers, would reduce the

demand for parking. With only 1 SAV needed to do the work of 12 CDVs, the parking space

needed for a scenario with complete SAV adoption would be just above 8% compared to an

all CDV scenario.

Change in VMT

VMT is very likely to increase with a switch to AVs, however reductions from switching to

shared vehicles and Stockholm congestion pricing might lessen the impact. Probable

estimates of VMT increases range between 20% and 35%.

10

Methodology The thesis started with going through the available literature on the subject and compiling a

list of facts about the parameters in question, such as parking reductions, VMT increase etc.

Once better grasp of the subject had been achieved, the relevant quotes and numbers were

used in the literature review. The findings in the literature review and the examples of urban

space reclamation was used in conjunction with GIS analysis of representative streets and

blocks around Stockholm to examine the potential for reallocation of urban space from

vehicular infrastructure to green spaces, pedestrian streets and bike lanes etc.

A wealth of projects of urban reclamation projects was reviewed. Three specific candidates

were chosen for their simplicity, effect and applicability. Once the projects had been chosen,

extensive walks around the city began, as a way to find areas and streets, between them a

somewhat good representation of different types of Stockholm streets.

The locations chosen were a neighbourhood close to Odengatan and Sveavägen, a section of

Kungsgatan and a section of Olofsgatan.

The Odengatan/Sveavägen area was chosen specifically as a candidate for applying the

superblock concept of Barcelona, as it has major roads on the outside of the area but smaller

mostly unused roads in its interior.

Kungsgatan was chosen specifically as a good candidate for applying the “Ströget” concept of

Copenhagen, as it is an old major road with an abundance of shops and a central location.

Olofsgatan was chosen as a good candidate for applying the “summer walking streets” of

Stockholm, as it is a small road with a good location close to the metro and Sveavägen, which

will bring in people. The road is also rather narrow, giving it a cosy feeling.

When the Stockholm locations had been chosen, more detailed surveyings were made in the

areas. Things such as proximity to transit stops, types and number of businesses, subjective

measures of area potential for conversion to pedestrian and bicycle uses, as well as the

distribution and location of roads, parking and sidewalks. The measurements of the different

types of uses were taken with a measuring tape and recorded. These site visits were made in

May 2018, spending about 60-120 minutes in each location.

The GIS analysis was done by using the measurements taken in situ, as well as using aerial

photos from Lantmäteriet (the Swedish surveying organisation). Polygons were made

covering the different uses, with the width from measurements in situ and the length from the

aerial photo and site photos. This was then used to quantify the amount and distribution of

parking, road and sidewalk.

Visualisations of street cross sections (the entire road from building to building) were created

from photos and measurements to illustrate the exact width of the space between buildings

and their use as of today and their potential use after a reallocation from vehicular

infrastructure.

The information from the GIS analysis was then used in conjunction with the findings of the

literature review to estimate the potentials for reallocation of space from vehicular purposes

(i.e parking and roads) to space for pedestrians and bikes (i.e bike lanes or parks and car free

streets). This was done through the creation of three scenarios with varying degrees of SAV

12

Selection of representative streets in Stockholm For the GIS analysis, three areas were chosen. The areas were chosen because they could be

considered representative of the different types of streets and areas that are found in

Stockholm, as well as having a big potential for road reclamation projects. These criteria were

distance to major roads, prevalence of shops, distance to metro or other major transportation

routes, as well as a very subjective measure of how inviting the area is to walk in. With these criteria in mind, three locations were chosen to demonstrate the impact of urban

space reallocation from vehicular traffic and parking. The locations were also chosen by the

types of streets widths and uses.

Figure 7: Location of the chosen areas. Odengatan/Sveavägen in blue, Kungsgatan in red and

Olofsgatan in yellow.

13

Odengatan/Sveavägen neighbourhood

This area consists of the 6 city blocks just

southeast of the intersection of Sveavägen

and Odengatan. The area is enclosed by

the roads Döbelnsgatan, Kungstensgatan,

Sveavägen and Odengatan. The area is

roughly 150 meters by 310 meters,

measured on Odengatan and Sveavägen

respectively. The area was chosen since it contains

several different types of road widths, its

close proximity to Sveavägen and

Odengatan and the nearby bus station

with major lines 2, 4 and 6. Shops are

plentiful along Sveavägen and Odengatan,

and there are more shops and restaurants

inside the area.

Kungsgatan

This section of Kungsgatan was chosen

since it is a major road, roughly 410 meters long. This section has a lot of shops and

proximity to both the green metro line, the red metro line and buses 1 and 2. Kungsgatan is a

larger street, but not as large as other main thoroughfares such as Sveavägen or Odengatan. It

is well used by pedestrians as well as bikes and has the 1 bus running the length of it. The

middle of the street is dedicated to cars and buses, with three to four lanes and some parking.

The daily traffic is about 15100 vehicles.

Figure 9: Kungsgatan

Figure 8: Odengatan/Sveavägen

14

Olofsgatan

The section of Olofsgatan chosen is

between Adolf Fredriks Kyrkogata and

Olof Palmes Gata. It is roughly 130

meters long. Olofsgatan is a small street

with one lane of traffic and parking

running the entire length on one side,

with narrow sidewalks on each side.

Shops and potential shop locations are

plentiful, the street is in close proximity

to Sveavägen and only two blocks away

from the Hötorget metro station. The

daily traffic is 745 vehicles.

Figure 10: Olofsgatan

15

Findings Change in urban space due to AV implementation The literature review concludes that the need for parking could approach just 5% of today's

needs. Even with the slightly more conservative estimate of 10% or even higher, that is a very

significant reduction in the number of parking spots needed to serve the community. Seeing

that most arterial streets consist of one or two lanes, street parking and sometimes a bike lane,

the removal of the parking area would free up a very large area for use by other modes of

transportation or something unrelated to traffic, like green space, parklets, larger bike lanes

etc. The increases in lane capacity vary from rather small, to a doubling of capacity for arterial

streets. The study concerning Kungsholmen is very relevant in this case, seeing as Stockholm

is the subject of this study. Regardless of the increase in capacity, the reduction of total

number of vehicles due to ridesharing should still be able to reduce the number of vehicles on

the road. That means that maybe even some driving lanes could be converted towards other

purposes. But it all depends on the level of adoption of AVs and especially shared AVs. It is therefore

important that any predictions made in this thesis are balanced and nuanced enough to reflect

different possible futures. Therefore, three scenarios with different degrees of AV and SAV

adoption, as well as some policy decisions, will be created to try and address the variations.

Possible scenarios With the results in the literature review some possible scenarios can be formed, depending on

the adoption of SAVs. The difference between AVs and SAVs will be their impact on the

number of cars, and therefore parking. Every SAV will replace 12 privately owned vehicles.

Stockholm today

In Stockholm today, there are about 375 cars/1000 inhabitants in 2017. These cars and other

together make about 504 000 trips every 24 hours in the city in 2017. Stockholmers from the

whole county travelled about 5580 kilometres by car per inhabitant in 2016. The minimum requirements for curbside parking is 2.3 meters times 6 meters, which,

allowing for measuring errors, was encountered while doing the studies of the respective

areas.

Stockholm today

Cars/1000 inhabitants 375

Road requirements (relative to today, %) 100%

VKT (kilometres/inhabitant and year) 5580

Parking demand (relative to today, %) 100%

In all scenarios, AV adoption is set to 100%, meaning that highways will see a capacity

increase of 273%, whereas arterial streets will see capacity doubling to 100% of today’s

levels. This increase in capacity, combined with the reduction in value of time from

autonomous vehicles freeing the passenger from focusing on driving, an increase in the

number of drivers on the roads is likely. Pent up demand from elderly and people without

driver’s licenses will also increase cars in traffic.

16

However, congestion pricing and car sharing could lessen the increase. This study will, based

on the results in the literature review, assume that car traffic, the number of cars, parking

requirements and VMT could see an increase of around 20% with complete adoption of AVs.

Baseline scenario

Baseline case

Cars/1000 inhabitants 450

Road requirements (relative to today, %) 60%

VKT (kilometres/inhabitant and year) 7540

Parking demand (relative to today, %) 120%

Low adoption of SAVs

With a SAV adoption of 25%, the number of vehicles needed to do the baseline scenario’s

transportation will be decreased by 23%, translating to a reduction to about 346 cars/1000

inhabitants. The need for parking would also be reduced by 23%

Low SAV adoption

Cars/1000 inhabitants 346

Road requirements (relative to today, %) 60%

VKT (kilometres/inhabitant and year) 7540

Parking demand (relative to today, %) 92%

Moderate adoption of SAVs

With a SAV adoption of 50%, the number of vehicles needed for the baseline scenario’s

transportation will be decreased by 45%, translating to a reduction to about 203 cars/1000

inhabitants. The need for parking would also be reduced by 45%.

Moderate SAV adoption

Cars/1000 inhabitants 203

Road requirements (relative to today, %) 60%

VKT (kilometres/inhabitant and year) 7540

Parking demand (relative to today, %) 66%

High adoption of SAVs

With a SAV adoption of 100%, the number of vehicles needed for the baseline scenario’s

transportation will be decreased by 92%, translating to a reduction to about 38 cars/1000

inhabitants. The need for parking would be reduced by about 90%.

High SAV adoption

Cars/1000 inhabitants 38

Road requirements (relative to today, %) 60%

VKT (kilometres/inhabitant and year) 7540

Parking demand (relative to today, %) 10%

17

Summary

As we can see from the different scenarios, only the Cars/1000 inhabitants and parking

demand change with the adoption rate of SAVs. They are linked because the parking demand

is a result of how many cars need parking.

0

50

100

150

200

250

300

350

400

450

500

Baseline Low adoption Moderate adoption High adoption

Cars/1000 inhabitants

Cars/1000 inhabitants

0

20

40

60

80

100

120

140

Baseline Low adoption Moderate adoption High adoption

Parking demand relative to today, %

Parking demand relative to today, %

18

GIS Analysis

The different types of use are marked

with green for pedestrian use, orange for

roads and grey for on street parking.

Odengatan/Sveavägen

In the blocks at the Odengatan/Sveavägen

location, 2547 m2 is dedicated to parking,

7117 m2 to sidewalks and 7992 m2 to

roads. The total space in between

buildings is 17656 square meters. That

gives a ratio of about 15% parking, 40%

sidewalk, and 45% road.

Figure 12: A representative section of Markvardsgatan.

Figure 11: GIS analysis of the

Odengatan/Sveavägen area

19

Figure 13: A representative section of Rehnsgatan.

Kungsgatan

On Kungsgatan, 72 m2 is dedicated to parking, 4523 m2 to sidewalks and 6266 m2 to roads.

The total space is 10864 square meters. That gives a ratio of less than 1% parking, 42%

sidewalk, and 57% road.

Figure 142: GIS analysis of the Kungsgatan section

20

Figure 15: A representative section of Kungsgatan

Olofsgatan

On Olofsgatan, 265 m2 is dedicated to parking, 436

m2 to sidewalks, and 378 m2 to roads. The total space

is 1078 square meters. That gives a ratio of 25%

parking, 40% sidewalk, and 35% road.

Figure 16: GIS analysis of

Olofsgatan

21

Figure 17: A representative section of Olofsgatan.

Spatial Distribution

(%)

Odengatan/

Sveavägen

Kungsgatan Olofsgatan

Sidewalk 40% 42% 40%

Road 45% 57% 35%

Parking 15% <1% 25%

Scenarios for the locations

Summary Baseline Low

adoption

Moderate

adoption

High

adoption

Cars/1000 inhabitants 450 346 203 38

Road usage (relative to

today, %)

60% 60% 60% 60%

VKT

(kilometres/inhabitant and

year)

7540 7540 7540 7540

Parking demand (relative

to today, %)

120% 92% 66% 10%

22

Odengatan/Sveavägen

In the low SAV adoption scenario, parking is essentially unchanged at 92% of today’s

demand, which means that the roads need to be open to traffic to keep the parking available.

Through traffic could be prohibited, but due to the proximity to Sveavägen and Odengatan, no

change is really expected from this scenario.

In the moderate SAV adoption scenario, parking requirements is reduced to 66% of today’s

demand. This frees a lot of land up for other uses, and the interior of the blocks where

Markvardsgatan and Luntgatan meet could probably be made into a superblock with no

parking or traffic. The rest of the area would be left as is to meet parking and driving

demands. The newly formed small superblock could be populated with pedestrian friendly

benches and pop up parks, and restaurants could be allowed to have outdoor seating in the

summertime.

In the high SAV adoption scenario, parking requirements would be virtually non-existent

compared to today. The 255 m2 required could easily be accommodated on the outside of the

area and the entire 6 blocks could be turned into a superblock with through traffic and parking

banned on the inside of the area. This superblock structure would see pedestrian area almost

double, adding a lot of space for parklets, outdoor seating, perhaps a playground or other

pedestrian and bike friendly uses. A lack of trees could be fixed with space between buildings

not needed by car traffic.

Kungsgatan

Seeing as Kungsgatan has hardly any parking, the three SAV adoption scenarios would all

affect the street the same way. However, the complete adoption of AVs would reduce the

need for road area by 40% compared to today, which means some of the lanes could be

removed and used for other purposes, such as trees, smaller parks, bike parking or perhaps

new buildings such as fast food or smaller shops. It is however unlikely, and perhaps even

unwanted that the entire street should be closed off to car traffic and buses, since it is a major

road from the eastern parts of town to the western. Simply closing one lane in each direction

would make each of the sidewalks almost as wide as the cross section of Strøget.

Olofsgatan

The low SAV adoption scenario permits almost no change from today, as the almost

unchanged parking requirements will allow for no space allocation from parking or the road

that enables parking. A pocket park or bike rack could probably be installed.

The moderate scenario would enable the removal of a third of all the parking spaces. It would

therefore be possible to turn the northern parts of the road into a car free street, connecting it

with the park. It would also be possible to use some of the parking spaces for pop up parks or

other smaller changes such as bike racks.

The high adoption scenario essentially enables full conversion of the street into a walking

street. Potential restaurants could have outdoor seating and space for greenery would be freed

up.

23

Conclusion

As the literature review reveals, the potential for urban space reallocation is substantial, but

when or if these changes will happen is uncertain, both from a technological perspective, as

well as depending on policy decisions, public acceptance and the time that adoption of AVs

and SAVs take.

Depending on what scenario would play out, the resulting potential for space reallocation

differs greatly. The low adoption scenario would barely make a dent in parking space, the

moderate scenario would remove about a third of the parking demand, and the high adoption

scenario would almost eliminate the parking need in the city, cutting it by 90%

Odengatan/Sveavägen and Olofsgatan could both see a large change from the moderate and

high adoption scenarios, turning the converted parking spaces into parklets, bike racks or

complete walking streets complete with outdoor seating etc. Kungsgatan would be equally

affected by all three scenarios due to the low amount of parking. Because of the increase in

road capacity, some roads could be removed, especially those supporting parking spaces,

perhaps enabling a narrowing of Kungsgatan or conversion of lanes into bus or cycling lanes.

This study has been specifically about whether it is possible to use SAVs as a means to reduce

the space that cars require in our cities. However, we don’t really need advanced technology

to reduce the number of car infrastructure. We’ve had buses since the beginning of the 20th

century, and it is highly probable that SAVs would reduce the share of commuters due to a

more convenient commute. A study of how to maximize the societal benefits of SAV

adoption by policy making would be highly interesting.

This study, due to time constraints, has not looked at parking in garages or under buildings. It

is very possible that in the high adoption scenario, all parking demand could be serviced by

garages instead of curbside parking, almost completely removing car parking from the city

surface.

This study has tried to illustrate how SAV adoption could change the urban landscape in our

cities and given suggestions as to how those changes could be utilized and leveraged for a

better city. The potential for reallocation is substantial and there are plenty of good ideas for

what to do with the space taken from car infrastructure. But we can’t wait for SAVs to just

arrive. We have to start planning for them right now, to make sure that we make the most of

this big opportunity.

25

Trafikanalys, 2017. Självkörande fordon och transportpolitiska mål, Stockholm: Trafikanalys.

Wadud, Z., MacKenzie, D. & Leiby, P., 2016. Help or hindrance? The travel, energy and carbon

impacts of highly automated vehicles. Transportation Research Part A: Policy and Practice, Volym 86,

pp. 1-18.

Zhang, W., Guhathakurta, S., Fang, J. & Zhang, G., 2015. Exploring the impact of shared autonomous

vehicles on urban parking demand: An agent-based simulation approach. Sustainable Cities and

Society, Volym 19, pp. 34-45.

Image sources

Figure 1: Barcelona, how cities are taking streets back from cars, Vox media, viewed 20 june 2018

<https://www.vox.com/2016/8/4/12342806/barcelona-superblocks>

Figure 2: Superblock illustration, BNC Ecologica, viewed 7 june 2018

<https://www.vox.com/2016/8/4/12342806/barcelona-superblocks>

Figure 3: Cross section, Global Design Cities, viewed 13 june 2018,

<https://globaldesigningcities.org/publication/global-street-design-guide/streets/pedestrian-priority-

spaces/pedestrian-only-streets/pedestrian-streets-case-study-stroget-copenhagen/>

Figure 4: Private Photo

Figure 5: SAE International’s Levels of Driving Automation for On-Road Vehicle, © SAE

International.

Figure 6: Firefly and minivan, n.d, image, viewed 15 june 2018

<https://www.designweek.co.uk/issues/12-18-june-2017/waymo-drops-self-driving-car-firefly-new-

autonomous-minivan/>

Figure 7: Aerial photo of the chosen areas, 0.25 RGB raster © Lantmäteriet 2018.

Figure 8: Aerial photo of Odengatan/Sveavägen, 0.25 RGB raster © Lantmäteriet 2018.

Figure 9: Aerial photo of Kungsgatan, 0.25 RGB raster © Lantmäteriet 2018.

Figure 10: Aerial photo of Olofsgatan, 0.25 RGB raster © Lantmäteriet 2018.

Figure 11: GIS image of Odengatan/Sveavägen, made in ArcMap.

Figure 12: Sketchup rendition of Markvardsgatan, private image.

Figure 13: Sketchup rendition of Rehnsgatan, private image.

Figure 14: GIS image of Kungsgatan, made in ArcMap.

Figure 15: Sketchup rendition of Kungsgatan, private image.

Figure 16: GIS image of Olofsgatan, made in ArcMap.

Figure 17: Sketchup rendition of Olofsgatan, private image.