Peter Davidson & Anabelle Spinoulas

1. DRIVING ALONE VERSUS RIDING
TOGETHER - HOW SHARED
AUTONOMOUS VEHICLES CAN
CHANGE THE WAY WE DRIVE
Tesla Model S

2. Key topics to cover
 How quickly will they be adopted?
 How can we model AV?
 How will they change our transport
networks?
 What are the effects of shared AV?
 How will they change our cities?
 What are the implications for what we
do now?

3. HOW QUICKLY WILL THEY BE
ADOPTED?

4. AV % of new sales – Aggressive

5. Projected growth in AV fleet

6. Adoption rate of other technologies
Others
Airbags: 0-100% in 25 years (1973-1998)
Automatic transmission: 0-80% in 70 yrs (1940’s)
Hybrid vehicles: 0-5% in 25 years (1990’s)
Smartphone: 0-80% in 9 years (2007)

7. MODELLING APPROACH

8. 4S
Structure
Stochastic:
● Monte Carlo methods to draw
values from probability
distributions
● Random variable parameters
● Number of slices can be
varied
SIMULTANEOUS
Segmented:
● Comprehensive
breakdown of travel
markets (20 private + 40
CV segments)
● Behavioural parameters
vary by market segment
EXPLICIT RANDOM UTILITY
Slice:
● Takes slices of the travel
market
○ across model area
○ through probability
distributions
● Very efficient – detailed
networks, large models
Simulation:
● Uses state-machine with
very flexible transition rules
● Simulates all aspects of
travel choice
● Complex public transport
● Multimodal freight
● Easily extended

9. Key features of 4S model
 No matrices, no skims, no zones, no centroid
connectors
 All travel is from node to node
 Models constructed with MUCH less manual effort
 Usually include all roads, all paths, timetabled transit
 Can build from OpenStreetMap and GTFS
 Population and employment can come from multiple
sources with different zoning, including point data
(schools, hospitals etc)
 Multimodal with all modes assigned
 Continuous time and simultaneous choice (DTA)
 Easily include any demand based effects and capacity
constraints (not just roads and transit)
 Much more detailed outputs (volumes by purpose)

10. South East Queensland Network
Population: 3.4m
Growth rate: 2.4%

11. Network detail – Brisbane CBD

12. Stages of AV Modelling
 Stage 1: Driver must be present but
inattentive
 Stage 2: No driver required, can
sleep etc
 Shared AV Taxi: single passenger
vehicles
 Shared multi-occupant AV: allows
for car-sharing, however not picking
up people along a journey

13. Mobility-as-a-Service
 ‘Mobility-as-a-Utility’ - have a right to this service
 Complete re-think of how we think of travel
 Door-to-door transport service
 Different payment plans - pay-as-you-go or a monthly
fee
 Supports shared AV use
 Huge potential to reduce car ownership
 Likely to increase the efficiency and utilisation of
transport providers
 Possibility for public transport to become more
competitive and affordable due to increase efficiency of
the network and the use of AVs
 The model used in this analysis considers fully multi-
modal travel so in affect we already consider a basic
model for MaaS.

14. ASSUMPTIONS

15. Assumptions

16. Assumptions: Value of time
 Stage 1: Driver present but
inattentive
 VOT multiplier: 75%-100% c.f.
standard
 Stage 2: No driver required
 VOT multiplier: 60%-100%
 Shared AV Taxi: Assume same as
Stage 2
 Shared multi-occupant AV: 65%-
100%

17. Assumptions: Trip rates
 Multiple reasons for more travel
 Reduced cost (perceived and actual)
 Easier sharing of car within family
 Reduced parking hassles
 Travel by non-drivers (children, elderly,
unlicensed, disability)
 Travel in non-driving state (drunk, tired)
 Assume 10% increase in Stage 1
15% in Stage 2
10% for Shared AV Taxi
15% for Shared multi-occupant AV

18. Assumptions: Veh. operating costs
 AV are likely to be plug in electric
 Significantly lower energy cost and
maintenance costs
 Even traditional ICE cars will have lower
costs due to better driving
 Stage 1: 50%-75% of current VOC
 Stage 2: 50% of current VOC

19. Assumptions: Capacity
 Stage 1: Mixed AV and Manual
 5% capacity increase
 reduced crash rates and improved
operations from connected vehicles
 Stage 2: 100% AV
 no manually driven cars - significant
operational improvements; high density;
higher speeds; improved intersection
operations
 20% capacity increase
 20% improvement in free flow speeds
 25% decrease in intersection delays

20. HOW WILL THEY CHANGE OUR
TRANSPORT NETWORKS?

21. Mode Share Impacts

22. CHANGES IN DISTANCE
TRAVELLED

23. Changes in average driving
speed
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%110%120%
Cumulative%oftimespentdriving
Congested speed factor (% of posted speed)
Base11 Base36 Av36High Av46Mod

24. Speeds in 2046
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 110% 120%
Cumulative%oftimespentdriving
Congested speed factor (% of posted speed)
Base11 Base46 Av46Mod Av46High Av46HighShared

25. CHANGES IN NET UTILITY

26. WHAT ARE THE EFFECTS OF
SHARED AUTONOMOUS VEHICLES

27. Behavioural Response to
Shared Autonomous Taxis
 Change from an up front model (buy a car,
annual registration and insurance) to a pay-as-
you-go model
 Lower annual cost, but higher trip cost (for
most trips)
 For modelling, assume that people make
travel choices based on marginal costs
 This may overstate the impact of shared AV
 If people only consider annualised costs then
they will do more travel

28. Effects of shared Autonomous
Taxis on mode share

29. Other effects of shared
Autonomous Taxis
 25% drop in time spent travelling: 8.4 to 6.3 m
h/d or 76 to 56 min/person/day
 55% drop in distance travelled: 269 to 147 m
km/d or 40.4 to 22 km/person/day
 Increase in daily costs and drop in per capita
net utility
 But annual costs are equivalent to $14-
$24/day
 40% cost savings: $38 to $23/person/d
 Net utility increases by $9.60/person/day

30. Effects of Multi-occupant
Shared AVs
 Reduced cost leads to increased car
demand, but higher vehicle occupancy
 Reduced public transport
 More efficient use of road space
 Better environmental outcomes (due to
higher efficiency and smaller vehicle
fleet)

31. HOW WILL AV CHANGE OUR
CITIES?

32. Differential effect of improvements

33. WHAT ARE THE IMPLICATIONS FOR
WHAT WE DO NOW?

34. Overall consequences
Operate AV as
improved
private cars
Big problems!
100% AV
Capacity +
speed
improves
Mitigate extra
demand
100% AV with
shared
autonomous taxis
Better operations
Reduced demand

35. Overall Consequences
 Best with shared vehicles and mobility-
as-a-service
 Reduce car footprint, share released road
 Revolutionise transport and big changes
in urban form

36. Conclusions on Infrastructure
 Will need to justify infrastructure spending based
on much shorter projected benefit streams
 Best approach (as usual) would be to implement
road pricing - it could take us over the hump
 Need more modelling
Time
infrastructure
requirements