The MERGE Greenwich project

REPORT 1A:

Anticipated uptake of Autonomous vehicle ride-sharing

MERGE GREENWICH CONSORTIUMOCTOBER 2017

ImmenseEnabling Intelligent Mobility

ImmenseEnabling Intelligent Mobility

MERGE Greenwich consortium partners

3

Table of Contents

Executive Summary 4

Introduction 6

About MERGE Greenwich 6

What this report aims to achieve 7

What is AV ride-sharing? 7

Advantages of AV ride-sharing 7

Market opportunity 9

Size of the total transport market in London 9

Target customers for AV ride-sharing 10

Potential market for AV ride-sharing 13

Likely uptake of AV-ride sharing by 2025 14

Go-to-market strategy for AV ride-sharing 16

Potential use-cases for AV ride-sharing 16

Bus type services 17

Mobility as a service replacing the private car 17

On-demand short-notice goods 17

Pricing and payment considerations 18

What challenges need to be overcome? 19

Technical 19

Infrastructure 19

Regulatory 20

Consumer demand 20

Scale 21

The role of people 21

Conclusion 23

Appendix

A. What are the levels of automation? 24

B. Price per mile assumptions – passenger transport 25

C. Potential uptake of AV ride-sharing based on trip distance 26

D. Use cases 27

E. Driving licence ownership demographics 31

4

Executive SummaryThe introduction of an Autonomous Vehicle (AV) ride-sharing service could transform the way passenger and goods trips are made. By integrating a new service alongside existing transport networks, AV ride-sharing could deliver significant benefits to cities and consumers by harnessing new technology and appealing to emerging customer trends.

This report explores what the potential market for AV ride-sharing could be, where the users might come from and what enablers will need to be in place for it to be successful.

Analysis by the MERGE Greenwich consortium indicates AV ride-sharing could reach 2.5 million passenger trips per day in London by 2025, equivalent to one-in-seven total trips taken in the capital. Private car and taxi journeys are expected to see the biggest reduction, with roughly a third of both categories expected to be replaced by a ride-sharing programme.

In total, a ride-sharing service could be worth as much as £3.5bn of the total amount spent on transport in London each year at today’s rates.

The research also highlights some of the additional benefits of such a service, including the potential for small goods delivery and improved safety on public roads and environmental benefits, as well as the overwhelming public support for autonomous vehicles with almost 80 per cent backing such technology.1

The MERGE Greenwich project comes at an exciting time, as the future of autonomous vehicles on Britain’s roads moves a step closer. It is one of a number of programmes, funded by government, which aim to put Britain at the forefront of mobility and transport technology innovation.

However, for AV ride-sharing to reach this level a service must be developed which can compete on price, convenience and availability. Whilst a new service will inevitably take some level of market share from other transport modes, the MERGE Greenwich project aims to show how AV ride-sharing can complement, rather than compete with, sustainable transport modes (public transport and active travel) and offer an alternative to privately owned vehicles.

With this in mind, this report examines distance and price offerings of multiple transport modes, with a focus on private car trips, to suggest ways in which the uptake of an AV ride-sharing service could have a positive impact on consumers and cities. The Mayor for London has stated that reducing the need to use cars will provide huge benefits for all Londoners2 and AV ride-share offers the opportunities to meet many of these objectives.

The two elements of “AV” and “ride-sharing” bring together the possibility of significant benefits to the consumer and transport authorities in the form of safety, greater accessibility, reduced parking and higher vehicle utilisation which could reduce congestion and emissions. However, the lack of a driver means secondary functions, such as assistance for passengers or goods, will need to be addressed in certain situations. Also, the success of a ride-sharing service depends

1 S Hyde, P Dalton, A Stevens, 2017. Attitudes to autonomous vehicles PPR823. Crowthorne, TRL2 https://consultations.tfl .gov.uk/policy/mayors-transport-strategy/?cid=mayors-transport-strategy

5

upon a critical mass of users to ensure vehicles are available to passengers in the right location and at the right time. The MERGE Greenwich project will explore these considerations and other barriers which will need to be overcome in order for an AV ride-sharing service to realise the many potential benefits associated with this new technology.

This report outlines the potential uptake, opportunities and challenges of an AV ride-sharing service and is MERGE Greenwich’s first step towards simulating a full scale AV ride-sharing service, integrated with public transport.

Full results from the MERGE Greenwich project will be available in the summer of 2018. Readers of this report are invited to regularly track the project’s progress at www.mergegreenwich.com

6

ABOUT MERGE GREENWICH

The MERGE Greenwich project will simulate the way the Royal Borough of Greenwich moves today and how it could move with an autonomous ride-share system, which is integrated with the public transport network. The results of this project will provide a crucial fi rst step towards mass roll out of autonomous vehicles (AVs). By thinking through, and simulating, how an AV ride-sharing service could operate MERGE Greenwich will pave the way for a commercial pilot, which could then develop into full-scale roll out of AVs.

MERGE Greenwich aims to investigate how to improve the way we travel around cities and reduce total vehicle trips and emissions. These developments offer the possibility of addressing the well documented social and environmental impacts of transport.3 The project will focus on how the social, commercial and infrastructure challenges of autonomous vehicles can be overcome, as well as considering consumer aspects such as; safety, ride-sharing, security, accessibility and environmental factors.

A critical component of the MERGE Greenwich project will be the application of next generation large-scale transport simulators to evaluate ride-share use cases. Persistent and predictive simulations will be used to deliver detailed and accurate pictures of the city-wide transport eco-system at different time periods, such as peak, off-peak and sudden changes in demand.

Developing an allocation and dispatch algorithm which is sophisticated enough to manage demand effectively for a ride-sharing service has been the subject of substantial research effort.4 5 6 Other research projects have investigated AV ride-sharing, such as Boston Consulting Group (BCG) and the World Economic Forum, in order to understand the strategic issues associated with Autonomous Vehicles and Mobility-as-a-Service.7 8 9 To build on lessons learned from such research and projects around the world, the MERGE Greenwich project will extend large-scale transport simulators to evaluate ride-share use cases.

Consumer and city-level research will also be carried out in order to understand how this new mobility service could be launched in the real world. The fi nal project report will provide a blueprint for an optimal operating model, to give the UK a head start in developing next generation ground transportation.

3 KPMG, 2015. Connected and Autonomous Vehicles – The UK Economic Opportunity.4 H. E. Hosni, J. . Naoum-Sawaya and H. . Artail, “The shared-taxi problem: Formulation and solution methods,” Transportation Research Part B-methodological, vol. 70, no. 0, pp. 303-318, 2014.5 N. . Agatz, A. L. Erera, M. W. P. Savelsbergh and X. . Wang, “Optimization for Dynamic Ride-Sharing: A Review,” European Journal of Operational Research, vol. 223, no. 2, pp. 295-303, 2012.6 J. . Alonso-Mora, S. . Samaranayake, A. . Wallar, E. . Frazzoli and D. . Rus, “On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment.,” Proceedings of the National Academy of Sciences of the United States of America, vol. 114, no. 3, pp. 462-467, 20177 What’s Ahead for Car Sharing? The New Mobility and Its Impact on Vehicle Sales. https://www.bcgperspectives.com/content/articles/automotive-whats-ahead-car-sharing-new-mobility-its-impact-vehicle-sales/8 Self-Driving Vehicles in an Urban Context, http://www3.weforum.org/docs/WEF_Press%20release.pdf9 Self-Driving Vehicles, Robo-Taxis, and the Urban Mobility Revolution, https://www.bcgperspectives.com/content/articles/automotive-public-sector-self-driving-vehicles-robo-taxis-urban-mobility-revolution/

Introduction

7

WHAT THIS REPORT AIMS TO ACHIEVE

This report outlines the potential size of the AV ride-sharing market and the likely uptake by 2025. To understand the market fully, the report will outline which users might be attracted to AV ride-sharing as well as explore the challenges this service may face. Understanding these elements will act as the foundation for the MERGE Greenwich project and assist in directing the future study both in terms of understanding the types of vehicles required and the kind of service they need to offer.

During the 12-month MERGE Greenwich project, a complex simulation will be developed which will provide an accurate forecast for the uptake of AV ride-sharing and model how it might work. Interested parties are invited to keep in touch with the project’s progress towards the fi nal project report which will be shared in the summer of 2018. 10

WHAT IS AV RIDE-SHARING?

Autonomous Vehicle ride-sharing is a concept which links new vehicle technology with an emerging service offering:

• Autonomous Vehicles (AV) are able to operate without a driver, thanks to a high level of computerised decision making.11 These vehicles are able to navigate journeys, obey traffi c rules and park themselves using the latest technology.

• Ride-sharing is a service which enables two or more passengers (and potentially goods items) to share the same vehicle. These passengers will have similar trip origins and destinations, but they do not have to be exactly the same. A trip may begin with one passenger and pick another passenger up on the way. Sophisticated dispatch and allocation software is now available which matches passengers to vehicles, optimises the route and applies rules such as maximum waiting times.

ADVANTAGES OF AV RIDE-SHARING

AVs and ride-sharing services have a signifi cant number of potential advantages which are simply multiplied when these two concepts are combined.

Autonomous vehicles have the potential to:

• Reduce road collisions due to human error – Department for Transport statistics suggest that the critical reason for around 95% of crashes was assigned to the driver12

• Reduce overall journey times for drivers who will no longer need to fi nd a parking space

• Increase accessibility for those who cannot drive and those who fi nd it diffi cult to reach

public transport hubs13

10 Please refer to www.mergegreenwich.com for project updates11 Further details of existing described levels of autonomy can be found in Appendix A12 https://www.gov.uk/government/statistical-data-sets/ras50-contributory-factors Accessed on 04 October 201713 https://tfl .gov.uk/info-for/urban-planning-and-construction/planning-with-webcat/webcat

8

• Replace uneconomical public services (e.g. low occupancy bus routes) whilst maintaining transport links for those in reduced transport accessibility areas

Ride-sharing advantages include:

• Reducing congestion and emissions by decreasing the number of vehicles required to move the same number of passengers

• Lower travel costs by sharing the trip with others

• Potentially reducing costs for consumers and removing maintenance and inconvenience associated with vehicle ownership

• Making space allocated for parking vehicles available for alternative purposes

• Reintroducing social engagement with neighbours and colleagues

The combination of these advantages means the introduction of an AV ride-sharing service has the potential to signifi cantly improve the public transport offering as we know it today. By simulating how this AV ride-sharing service could be integrated with current public transport systems, the MERGE Greenwich project will play its part in accelerating the path towards mass roll out of AVs and the realisation of so many benefi ts to the consumer and the city.

9

SIZE OF THE TOTAL TRANSPORT MARKET IN LONDON

The total transport market in London, including public and private modes, was worth an estimated £14.3bn in 2016, which represents over 18 million trips per day14 as summarised in Table 1 below.

15 16 17

The size of the market opportunity for AV ride-sharing has been estimated by suggesting how many passengers might be tempted to switch from current modes of transport. To understand passengers’ potential switching behaviour the motivations which infl uence the mode of transport chosen were compared, as illustrated in Table 2.

14 Forecast trend data for 2016/17 derived from London Travel Demand Survey (LTDS) https://tfl .gov.uk/corporate/publications-and-reports/london-travel-demand-survey.15 Appendix B16 Appendix B17 TRL Estimate based upon a broad assumption of the costs of worn shoes and clothing

Table 2: Infl uences in transport modal choice

Motivation for choosinga mode of transport

Und

ergr

ound

/ D

LR

Bus

/tra

m

Taxi

/ ot

her

Car

dri

ver

Car

pa

ssen

ger

Mot

orcy

cle

Cycl

e

Wal

k

AV

rid

e-sh

arin

gCost per mile Y Y - Y Y Y Y Y YConvenience Y - Y Y Y Y Y Y YPersonal space - - Y Y Y Y Y Y -Start/ stop location - - Y Y Y Y Y Y YReliability (journey time) Y Y - - - Y Y Y YSpeed - - Y - - Y - - YShort journey Y Y Y - - Y Y Y YLong journey - - - Y Y Y - - Y

Represents the modes most likely to be comparable with an AV ride-sharing service

Table 1: Total transport market in Greater London

Year 2016/17London trips per day

(LTDS)15

Average cost per trip (£)16

Value of London market (£/ day)

Value of London market (£/ year)

Underground/ DLR 1,772,559 £2.90 £5,140,421 £1,876,253,702

Bus in London 2,925,570 £1.50 £4,388,355 £1,601,749,575

Taxi/ Other 283,864 £23.50 £6,670,804 £2,434,843,460

Car/van driver 4,467,215 £3.79 £16,930,745 £6,179,721,870

Car/van passenger 2,338,212 £1.99 £4,653,042 £1,698,360,286

Motorcycle 75,088 £2.66 £199,734 £72,902,939

Cycle 573,272 £0.70 £401,290 £146,470,996

Walk (of a mile or more) 5,756,147 £0.1417 £805,861 £294,139,112

TOTAL 18,191,927 £39,190,252 £14,304,441,940

Market Opportunity

10

TARGET CUSTOMERS FOR AV RIDE-SHARING

An AV ride-sharing service would be expected to cater for short and longer trips within London (or any metropolitan area). Whilst the longer trips would typically target current private car users (with average distance over 8 miles/ trip18), shorter journeys might attract passengers in transport black spots, or connect people to transport hubs which serve long distance modes such as rail stations and airports.

In addition to targeting passengers based on average trip distance, the MERGE Greenwich consortium analysed average costs per trip to identify which passenger segments would be most likely to consider an AV ride-sharing service. The two most costly modes of transport in London are taxis, private hire vehicles and privately driven cars which incur congestion and parking charges19, as shown in Figure 1 below.

20

By combining insights from the motivation criteria and average trip comparison, the MERGE Greenwich consortium estimated the likely market penetration of AV ride-sharing for each current mode of transport, once the new service was well established, as shown in Figure 2.21

18 Average trip length by main mode: England, 1995/97 to 2016 Table NTS0306 – See Appendix C19 Congestion charge of £11.50 per day, 2 hours of parking at Q-park Chinatown at £14.50, bringing total for car trip to £29.79. Note this might normally only be applicable to an outward-bound trip20 Data derived by cost per mile calculations (Appendix B) and average trip length (National Travel Survey data for England, table NTS0306 for 2016)21 The MERGE Greenwich project will develop a more accurately estimate of the likely switching behaviour and the impact it will have on market share by conducting market research and simulating potential demand.

Figure 1: Average trip cost 20

11

These assumptions are based on research into the uptake of mobility services, experience of transport planning and customer behaviour. Switching from private vehicles to mobility services is estimated to be up to 34% according to Capgemini22 and switching from taxis could be around 30%23, according to a study in Los Angeles. These estimates may prove to be conservative according to a BCG report which, looking specifi cally at AV ride-sharing, found that 37% of consumers said that they would be likely to share a ride in a self-driving taxi with strangers.24

Switching from motorcycles is expected to be far lower, around 5%, as the relative advantages of AV ride-sharing are minimal, apart from the increased safety and avoidance of adverse weather conditions. Similarly, underground and bus users are not expected to switch to using an AV ride-sharing service as the low cost of bus routes and the reliability of underground journey times remain compelling motivations for these modes of transport.

For these reasons, we anticipate that current private car drivers and taxi users would be the primary targets for an AV ride-sharing service.

Analysis of the Department for Transport National Travel Survey (NTS) and London Travel Demand Survey (LTDS) revealed an overall downward trend in personal transport trips per person per year (Figure 3). The headline trends below reinforce the hypothesis that private car and taxi users, particularly women, should be the target audience for an AV ride-sharing model:

22 https://www.capgemini.com/gb-en/news/new-capgemini-study-reveals-the-disruptive-impact-of-car-hailing-and-ride-sharing-services/ Accessed on 26.09.1723 Nelson, Laura J. Uber and Lyft have devastated L.A.’s taxi industry, city records show, Los Angeles Times (online 14th April 2016), http://www.latimes.com/local/lanow/la-me-ln-uber-lyft-taxis-la-20160413-story.html accessed 6th Sept 2017.24 BCG (2016). Self-driving vehicles, robo-taxis, and the Urban Mobility Revolution. Available at: https://www.bcgperspectives.com/content/articles/automotive-public-sector-self-driving-vehicles-robo-taxis-urban-mobility-revolution/ Accessed 28 September 2017

Figure 2: Estimated AV ride-share switching from current modes

12

• Car and van driver and passenger trips are declining; however the number of trips using this mode is still far in excess of other forms of motorised transport. This means that capturing even a small proportion of passengers in this market could mean a signifi cantly large number of trips for an AV ride-sharing service.

• Taxi and private hire trips in London are a small proportion of all trips and are gradually declining. The extent to which autonomous taxi-type services might impact this trend will be explored as part of the MERGE Greenwich simulation.

• Women will continue to represent a slightly larger number of travellers than men in cars, taxis, and buses (which might be seen as substitutes for AV ride-sharing) by 2025 (see Figure 4). This suggests that an AV ride-sharing service should be designed with a slight emphasis on female consumers in order to have the greatest impact on the transport system.

25

25 Based upon extrapolated data from LTDS 2015/ 16

Figure 3: Trips in London per day by mode

25

13

All market penetration assumptions will be reviewed as part of the MERGE Greenwich project and a complex simulation will be developed in order to more accurately estimate the potential size of the market. Adding to this, changes in transport behaviour according to time of day, day of the week and weather patterns will be analysed in order to build up an accurate picture of demand for an AV ride-sharing service by 2025.

POTENTIAL MARKET FOR AV RIDE-SHARING

The MERGE Greenwich analysis suggests an AV ride-sharing service in London could cater for 2.5 million trips per day by 2025, as shown in Table 3. This is the equivalent to transport spend worth in the region of £3.5 billion26 (at today’s rates) and represents 25% of the total London transport market. This estimate may turn out to be conservative, according to a study which modelled potential modal shift and found that AV ride-sharing could make up 27% of all trips, with the majority of these (90%) coming from previously private car journeys.27

This market estimate is deliberately optimistic and the extent to which it becomes reality will depend on overcoming a number of challenges, which this report will explore. However, this estimate may turn out to be conservative as it does not factor in the potential impact of population growth and therefore the increased number of total trips which will be carried out daily in London by 2025.

26 Note if car/van passengers, and walk are costed as free, the overall value of journeys changes from £3.5 billion to £3 billion.27 Chen, T. D. & Kockelman, K. M. (2016). Management of a Shared, Autonomous, Electric Vehicle Fleet: Implications of Pricing Schemes, Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin

Figure 4: Forecast modal trip share by gender in 2024/25 in London25

14

LIKELY UPTAKE OF AV-RIDE SHARING BY 2025

The rate of market growth for an AV ride-share service will depend on its ability to be more attractive to passengers than other modes of transport, which will be explored further during the MERGE Greenwich project.28

For this report a market uptake over 5 years, starting in 2020, was estimated using the new product adoption curve, as shown in Figure 5. This curve assumes the market reaches 100% of the target size (i.e. 2.5 million trips per day) by year 5, by which time “laggards” are using the service. In year 1 however, innovators only account for 1% of the target market size, increasing to 15% in year 2 (as early adopters join the market), 49% in year 3 (introducing the early majority) and 83% in year 4 (adding the late majority).

Alternate models may also be possible, including a transition phase with non-AV ride-sharing, moving towards AV ride-sharing when the market matures.

28 Please check www.mergegreenwich.com for more details on passenger decision criteria.

Table 3: Attractiveness of transport modes

Year 2024/25Estimated AV

ride-share Market penetration (2025)

AV ride-share trips per day (2025)

Potential value of the AV ride-share market (2025)

Underground/ DLR 5% 109,646 £116,060,694

Bus/tram 5% 159,796 £87,488,571

Taxi/ Other 30% 100,856 £865,094,976

Car driver 34% 1,369,603 £1,895,591,907

Car passenger 34% 771,004 £559,352,079

Motorcycle 5% 3,234 £3,134,520

Cycle 0.5% 3,904 £1,002,384

Walk 0.5% 29,580 £1,483,054

TOTAL 14% 2,547,623 £3,529,208,186

15

The likely adoption rate of customers, and therefore likely market uptake, will be assessed and simulated in more detail during the MERGE Greenwich project to test these assumptions and the market potential.

Figure 5: Anticipated uptake of AV ride-sharing in London by 2025

16

For an AV ride-sharing service to be successful, a number of elements will need to be carefully thought through. This section of the report goes into more detail about who the target audience could be (use cases), crucial service delivery considerations (payment methods and pricing) as well as explaining a number of challenges which an AV ride-sharing service will need to overcome. The MERGE Greenwich project will build up a complete picture of the go-to-market strategy, including a detailed business model and customer offering.29

POTENTIAL USE-CASES FOR AV RIDE-SHARING

A key element when considering a service using autonomous vehicles is to understand the potential roles AVs could fulfi l in order to develop viable use-cases.

The diagram below illustrates how potential use cases can be developed, based on whether the transported item is self-propelled (a typical foot passenger) which may only need transport from A to B, and other items (people or goods) for which a driver also performs a secondary function.

The use cases which appear most viable are highlighted in Figure 6 and are explored further in the section below.30

29 Please refer to www.mergegreenwich.com for more information30 A complete description of the various use cases (including those which were rejected) can be found in Appendix D

Go-to-market strategy for AV ride-sharing

Figure 6: Development of potential AV ride-share use cases

17

1. Bus type services

Bus services typically operate with large vehicles in order to benefi t from economies of scale. However the commercial viability of this model relies on a certain scale of passenger numbers and there may be cases where this number is too small to justify a service.

Smaller, autonomous, ride-sharing vehicles may offer the opportunity to complement public transport by replacing low-volume, uneconomical, bus services. This type of service could use existing bus infrastructure (bus stops, bus lanes) but operate on an on-demand basis to avoid running vehicles at times when the occupancy would be very low, and could utilise the ride-share functionality with route fl exibility.

A typical user of this service may be similar to a current bus passenger but live in areas of reduced passenger transport accessibility.31

2. Mobility as a service replacing the private car

Private car usage creates a range of issues such as congestion and reduced road space due to parking. The average private car journey is 4.9 miles longer than the average London bus journey; therefore an alternative service will need to be able to cater for passenger requirements which go beyond those of journeys fulfi lled by traditional bus services. This pool of passengers would be an ideal target for an AV ride-sharing service thanks to the fact there is unlikely to be a need for a driver to assist at the start and end stages of the journey.32 Adding to this, the advantages of reducing time and cost associated with parking, without compromising convenience, could mean AV ride-sharing becomes a very attractive alternative.

A typical person who might use this service falls into several groups, and this may require a differentiation of service. The fi rst is the executive-level traveller who requires a high level of comfort and service. Additionally there is a cohort of individuals who might use the service instead of their own car for a variety of uses (commuting, leisure, shopping). There may also be a group which use the vehicle because they do not have a driving licence,33 which tends to be women and the younger and older age group.

3. On-demand short-notice goods

The parcel delivery market is large and expected to grow in the region of 7 to 10% per annum in mature markets due to e-commerce.34 This could represent a signifi cant opportunity for an AV ride-sharing service among tradespeople, thanks to the convenience of not having to take time away from their core function in order to transport goods (e.g. a plumber could order short-notice goods to be delivered, rather than travel to collect them).

By including goods delivery in the AV ride-sharing service (potentially with a mix of people and goods in separate compartments) vehicle utilisation could be dramatically increased. This means the total

31 https://tfl .gov.uk/info-for/urban-planning-and-construction/planning-with-webcat/webcat32 Please refer to the section on Challenges: Replacing the driver for further detail on this33 Please refer to Appendix E34 Joerss, M et al (2016). Parcel delivery – The future of last mile. McKinsey & Company

18

number of vehicles on the road could be reduced further, which would have an even greater impact on congestion and emissions.

As long as the sender and receiver are able to meet a delivery vehicle on street, the key issue of a driver not undertaking the fi nal metres of delivery function is absolved. This is presently being explored in the GATEway delivery trial project and early indications are that users would welcome this type of service. One consideration which may be required to enable this service is the availability of box-bodied vehicles which can securely store the goods during transit and be easily accessed at the point of delivery.

A typical persona for the users of this service could be tradespeople (plumbers, builders etc.) and shoppers (e-commerce).

PRICING AND PAYMENT CONSIDERATIONS

As with any competitive market, pricing for modes of transport is a critical factor infl uencing consumer decision making. In addition to the price point, the payment method can signifi cantly infl uence passengers choices, with nearly half (47%) of people already preferring digital to cash payment options.35

This section of the report sets out the considerations a new AV ride-sharing service would need to address in order to be successful:

1. How to set pricing: Pricing bands for transport modes (other than private car usage) vary by distance, time of day, availability and service level. For example, taxis are charged per mile travelled as well as having different rates for peak/ off-peak travel times. Some operators add surge pricing as another way to regulate demand and/ or optimise return.

Adding to this, tiered offerings can offer different prices for different levels of service and therefore cater for different customer expectations. Premium services, such as Addison Lee, will have a different price point to mass transit.

An AV ride-sharing service should develop a model which factors in these parameters (distance, time of day, availability and service level) as well as considering a tiered level of service (e.g. sole occupancy, sharing with one other, sharing with many others).

2. Which payment methods to use: Current transport payment methods vary by modal type, with tickets/contactless typical in mass transit, app payments or cash/card typical for taxis and private hire, and not at point of use payment for private vehicles. Each offer advantages and disadvantages for the consumer and transport supplier. During the MERGE Greenwich project, each of these considerations and more will be thought through in order to develop the optimum business model. A cost/revenue model will be developed, alongside simulation of a service with different price points. This will build up a picture of what an appropriate pricing model could be for AV ride-sharing.

35 US Bank cash survey 2017

19

WHAT CHALLENGES NEED TO BE OVERCOME?

As with the introduction of any new technology and service, a new AV ride-sharing service will face a number of challenges. These challenges include; technical (does it work?), infrastructure (can it work here?) regulatory (is it permitted to work?), consumer demand (do we want what it offers?), scale (will it be commercially viable?) and the service (e.g. is a driver essential?) This section will discuss how each of these challenges could be overcome in order to successfully launch an AV ride-sharing service.

1. Technical

Autonomous vehicles are not yet a mature technology, although there is an existing set of defi nitions for the expected levels of vehicle autonomy that may be developed (Appendix A) and vehicle manufacturers suggest that high automation (L4) vehicles may be available between 2019 and 2025.36 This timescale suggests that an AV ride-sharing service could be launched and scaled up by 2025 if the current pace of testing, collaboration and business model development continues.

2. Infrastructure

There are many forms of infrastructure required for autonomous vehicles, which are presently being addressed by a range of government funded projects37 and research papers.38 The anticipated infrastructure requirements include;

• Communications infrastructure (between the vehicle and the roadside, and the route assignment system)

• Accurate mapping of the drivable area

• Vehicle refuelling (most likely to be electric charging points)39

• Locations to stop the vehicle for secondary activities, such as loading or unloading people or goods (see below)

• Locations to stop the vehicles during downtime, maintenance and servicing

These infrastructure requirements will be explored further in work package 2 of the MERGE Greenwich project.40

36 Prodham, G. March 16th 2017. Auto industry diverges on timeline for self-driving cars. Automotive News. http://www.autonews.com/article/20170316/MOBILITY/170319870/auto-industry-diverges-on-timeline-for-self-driving-cars. Accessed 20th September 201737 CAV competition leverages over £25 million for eight R&D projects to help build infrastructure for connected and autonomous vehicles, 4th February 2016. https://connect.innovateuk.org/web/intelligent-mobility/article-view/-/blogs/cav-competition-leverages-over-25-million-for-eight-r-d-projects-to-help-build-infrastructure-for-connected-and-autonomous-vehicles accessed 19th September 201738 Johnson, C, 2017. Readiness of the road network for connected and autonomous vehicles. RAC Foundation.39 The interdependency of autonomous electric vehicles and wireless charging, 22nd March 2017. http://www.greencarcongress.com/2017/03/20170322-wpt.html accessed 19th September 201740 Please check www.mergegreenwich.com for further details

20

3. Regulatory

The UK Government has anticipated the arrival of connected and autonomous vehicles and is actively engaged in supporting the market growth as part of an Industrial Strategy.41 As with any new technology, regulatory guidance will be an important part of shaping the future market and ensuring any developments are safe for consumers and the city environment. There are currently many unanswered questions with regards to appropriate regulatory frameworks for AVs and these issues will need to be addressed swiftly in order to avoid delaying the uptake of this benefi cial new technology.

4. Consumer Demand

Autonomous vehicles are in a developmental stage and studies have, so far, indicated different levels of public acceptance largely focussed upon the perceived safety of these systems, ranging from the somewhat positive42 (in the UK) to the somewhat negative43 (in a range of other countries). This is likely to have an impact upon the potential uptake of AVs and a solid understanding of how to overcome consumer concerns will be critical to the success of any AV ride-sharing model.

Encouragingly, a recent TRL study found that 78% of the public are generally positive about the prospect of autonomous vehicles, with some reservations regarding the safety case.44 In addition to this, a report by Capgemini indicated 81% of people would be willing to pay more for autonomous-driving features.45 These statistics indicate that autonomous vehicle technology may not be an overriding barrier to uptake.

Ride-sharing has long been a feature of mass transit (bus, rail), and social rules46 have undoubtedly developed regarding interaction between co-passengers. A key paper47 outlining public attitudes to using autonomous vehicles for ride-sharing noted that discomfort with sharing is a known phenomenon in traditional large ride-share vehicles (such as buses or trains), and that caution will be required when developing a service which uses smaller vehicles which could exacerbate issues relating to personal space. Potential differences in attitudes based on gender

41 Pathway to driverless cars: Consultation on proposals to support Advanced Driver Assistance Systems and Automated Vehicles Government Response, January 2017 https://www.gov.uk/government/uploads/system/uploads/attachment_data/fi le/581577/pathway-to-driverless-cars-consultation-response.pdf42 S Hyde, P Dalton, A Stevens, 2017. Attitudes to autonomous vehicles PPR823. Crowthorne, TRL43 Deloitte, January 2017. What’s ahead for fully autonomous driving - Consumer opinions on advanced vehicle technology.https://www2.deloitte.com/content/dam/Deloitte/us/Documents/manufacturing/us-manufacturing-whats-ahead-for-fully-autonomous-driving.pdf44 S Hyde, P Dalton, A Stevens, 2017. Attitudes to autonomous vehicles PPR823. Crowthorne, TRL45 https://www.capgemini.com/gb-en/news/new-capgemini-study-reveals-the-disruptive-impact-of-car-hailing-and-ride-sharing-services/46 What are the unspoken rules of using public transport in your city? 23rd June 2017, Guardian. https://www.theguardian.com/cities/2017/jun/23/unspoken-rules-public-transport-etiquette-your-city accessed 19th September 201747 Merat N, Madigan R, Nordhoff, S, July 2017. Human Factors, User Requirements, and User Acceptance of Ride-Sharing in Automated Vehicles. International Transport Forum. https://www.itf-oecd.org/sites/default/fi les/docs/human-factors-ride-sharing-automated-vehicles_0.pdf

21

are also signifi cant, and these consumer demand factors will be considered during the MERGE Greenwich project when developing the blueprint for an AV ride-sharing service.

5. Scale

In order for an AV ride-sharing service to be commercially viable, a critical mass48 (or perhaps more accurately overcoming a minimum trip demand density operating level) is crucial. Trip origins and destinations must be close enough to allow the combination of otherwise separate trips, which reduces overall mileage without signifi cant time penalties. This minimum density level is not yet known but will be explored within the MERGE Greenwich project simulation. In order to provide an improvement, average occupancy should exceed that of the modes it replaces.

6. The role of people

Despite the automated nature of an AV ride-sharing service, the value of people to support the service must not be overlooked. The business model will still require people to support customers remotely as well as supporting some customers in the vehicle.

1. Remote customer support: To deliver an end-to-end customer experience which meets expectations, and can respond to any urgent situations, a human interface will still be crucial. For example, if a passenger has trouble opening or closing the AV pod they will expect to be able to speak to someone who can resolve the situation in real time. The challenge for the operator is to understand how to deliver this in a way which meets customer expectations and is commercially viable. This might be through in-vehicle screens or interfaces to ensure the customer feels they have a direct link to customer support agents.

2. In-vehicle support: For some use cases, the driver plays a secondary role which would need to be replaced in order for an AV ride-sharing model to be adopted, as shown in Figure 7 below, where AV is capable of performing the A to B journey, but not the fi rst or fi nal metres.

48 Lopez-Bernal, G. Wright, G. Dynamic Ridesharing Technologies – Opportunities for the MBTA’s The RIDE Paratransit Services.

22

For example, taxi drivers often help young, elderly or disabled passengers into and out of the vehicle. The same is true for Patient Transfer Services (PTS). For these passengers to switch to a service using AVs there would need to be an alternative to the driver, perhaps in the form of a meet and greet service, at the beginning and end of certain trips.

Similarly, in a courier context, the driver is a critical element of the service as they transport goods to/from the vehicle, known as the ‘fi rst and fi nal metres’ of the trip (such as delivering goods to reception). Replacing this activity would also require a meet and greet style service if AVs were to be used.

Figure 5: Anticipated uptake of AV ride-sharing in London by 2025

23

ConclusionTransport demand is changing, but continues to be dominated by car journeys with low occupancy rates, which is a signifi cant contributor to congestion, pollution, and reduced road space due to parking. As urban populations increase major cities like London are under increasing pressure to ensure people move around in an ever more effi cient and environmentally sound way.

Autonomous vehicles and ride-sharing models could provide an ideal solution for cities, if integrated with existing public transport systems. The combination of this new technology and emerging business model has the potential to bring about exciting benefi ts to the consumer and transport authorities in the form of safety, greater accessibility, reduced parking and higher vehicle utilisation, which could reduce congestion and emissions.

The MERGE Greenwich project will be at the forefront of the growth of the autonomous vehicle ride-sharing market. Delivering the vital step of developing the necessary simulation to show how this new service could operate and prove the positive impact it could have on a city like London.

Furthermore, with the UK seeking to secure its position as a global leader in developing connected and autonomous vehicle technology, the project comes at an opportune time to support the government’s and industry’s ambitions.

MERGE Greenwich analysis indicates AV ride-sharing in London could reach 2.5 million passenger trips per day by 2025, accounting for one-in-seven of all journeys. For car journeys the fi gures is higher, where AV ride-sharing could account for one-in-three of all trips taken. This represents a passenger market worth around £3.5 billion per annum at today’s rates.

There are a number of challenges that must be addressed in order to enable such a service to be rolled out successfully. These include developing reliable technology, having the right regulations in place which enable development, delivering the service to the appropriate scale and having the support and acceptance from the customers who will use this new service.

AV ride-sharing is likely to suit certain transport demands, particularly where the role carried out by a driver today is not essential. The MERGE Greenwich analysis identifi ed three possible use cases as:

1. Bus type services2. Mobility as a service replacing the private car3. On-demand short-notice goods

The passenger elements of these have been explored to understand the potential scale of services. Scale is important in ride-sharing services as there is a need to match rides in both location and time – this requires a density which will be explored in later modelling exercises.

The uptake and enablers to an AV ride-sharing service will be explored further in the MERGE Greenwich project. By summer 2018 the project will not only have thought through many more considerations which would infl uence the introduction of such a service, but will also have started to answer some of the key questions about what the impact of the new transport mode could be. Readers of this report are invited to keep in touch with the project as it progresses by visiting www.mergegreenwich.com.

24

There are a number of slightly different definitions of levels of automation used in literature, but the most commonly used is the six defined by the Society of Automotive Engineers (SAE) International in their Automated Driving: levels of driving automation are defined in new SAE International Standard J3016 (see SAE International, 2014). These are the levels which this project will refer to:

No automationVehicle is completely controlled by human driver

Driver assistanceSmall tasks which assist with steering or changing speeds are partially automated

Partial automationPartially automated tasks assisting steering and changing speeds can run simultaneously

Conditional automationIn a certain environment, vehicle control, but not route choice are automated, but human intervention is still required for some tasks.

High automationIn a certain environment, all driving activities (vehicle control and route choice) are automated and the vehicle can operate without human intervention when required.

Full automationThe vehicle operates with full automation in all conditions and environments. There is no need for human intervention

Appendix A. What are the levels of automation?

1

2

3

4

5

6

25

Appendix B. Price per mile assumptions – passenger transport

Table 4: Cost assumptions for passenger transport

ModeCost per

mileAssumptions

Taxi £4.70 Based on London Taxi tariff 1 with median of the 6 miles upper (£31) and 4 miles lower (£16) estimates to obtain an average cost (£23.50)

for the average 5 mile trip

Bus in London £0.43 Based upon average of 3.5 mile trip at a £1.50

contactless Oyster card payment

Bicycle £0.20 Based upon the HMRC allowable amounts per mile

Walk (of a mile or more) £0.10 Based upon a broad assumption of the costs of worn shoes and

clothing

Car/van driver £0.45 Based upon the HMRC allowable amounts per mile, but does not

include the cost of parking.

Car/van passenger £0.23 Based upon an assumption of paying half the mileage costs, but

does not include the cost of parking. In reality the additional costs may be close to zero.

Motorcycle £0.24 Based upon the HMRC allowable amounts per mile.

London underground £0.45 Based on a single trip from North Greenwich Station to Waterloo

Underground station in peak using Oyster card (£2.90), a distance of around 6.5 track miles on the Jubilee line

The assumptions used to create per-mile modal costings are given below. Where parking and congestion costs are included for cars the cost may resemble more closely that of taxis. However this may vary depending upon location.

Note that costs exclude the value of time and are either based upon direct out-of-pocket expenses (such as tickets) or allowable HMRC rates.

26

Appendix C. Potential uptake of AV ride-sharing based on trip distance

To understand the transport market, and where AV ride-share may choose to sit within it, an analysis of trip distances was undertaken. Figure 8 below indicates the average trip length in England for 2016 from the National Travel Survey (NTS0306).1 This indicates that sustainable modes (walking, cycling, bus) tend to sit at the lower end of trip distance, and non-sustainable modes (private car) tend to be slightly longer journeys. In order to not compete with sustainable modes (except where the system will complement sustainable modes), it appears that longer trip distances should be the target market.

1 The outlier of non-local bus (average 91.1 miles) was excluded

Figure 8: Average trip lengths

27

Self-moving away from vehicle. Regular transport to known locations. Mass transit – bus type services.

Vehicles could fulfi l a low-volume bus-type role in areas where demand is generally low. Bus services are generally run by TfL in London (however a London Service Permit can be used to run buses in London). There is an opportunity to run small-scale bus services under contract to TfL as a London bus route. This would need to be a regular service throughout the day.

Determining a regular bus service route for low-volume transport and maintaining it profi tably may be challenging, as bus services such as this are regular and not on-demand so there may be times when the vehicle is far below profi table capacity. Bus services in London are run on a service level agreement basis, therefore occasional low demand may not be an issue.

The vehicle would need to be registered as a bus to use red-route (TfL) bus stops, and determine if any other bus stops (on borough areas) can be used.

Some form of payment mechanism would be needed whereby passengers could not avoid paying, and costs may need to be comparable to buses.

Use case – there appears to a potentially viable option as a London-bus contract passenger route service the vehicle could be a mini-bus style in the typical London bus red, taking Oyster card payments and running services in which full sized buses are uneconomical. The vehicle would probably need to be adapted to be DDA compliant, including wheelchair ramp and seating area.

Self-moving away from vehicle. Regular transport to known locations. Low volume – travel between key origins and destinations.

Vehicles could fulfi l a typical taxi-type service, where at least one of either the origin or destination are popular (train station etc.). Vehicles might be ordered via an app.

Regularised places for the vehicles to stop may be required, which can be challenging in congested areas and may only be open to registered black cabs rather than Private Hire Vehicles.

Payments are for the vehicle, so not an issue unless ride-share whereby some mechanism for separate charging and anti-fraud would be required.

Use case – This use case closely matches that of a regular black cab and there may be signifi cant issues with operating this way if the autonomous vehicle is a PHV. There may be a challenge in matching demands from different passengers, and then approaching the regular transport hub on a PHV basis.

Appendix D. Use Cases

28

Self-moving away from vehicle. Irregular transport. Low volume – travel from random place to random place.

Vehicles could fulfi l a typical taxi-type service, where neither the origin nor destination is regular. Vehicles might be ordered via an app. Whilst research shows that members of the public are willing to trust autonomous vehicles, it is not known to what extent they will forego the additional services of a driver.

A key differentiator of taxi-type services from other transport is that of price and the ability to offer out of vehicle services (such as direction, local advice, and bag loading/unloading). Unless price is signifi cantly lower than present taxi rates this market is unlikely to dramatically change.

A core potential market is as a replacement for the private car (with mobility as a service) for trips such as travel to work as this does not require many of the taxi type add-on benefi ts. This constitutes a very large market and is therefore worth exploring. One potential key offering as mobility as a service is to offer a monthly fee for an all-you-can-ride service (similar to a monthly Oyster). An option is to tie this in with new build developments in order to offset local authority concerns regarding parking.

Challenges are increased vehicle positioning mileage and the time this takes and the additional cost of this. Further challenges are the marrying of disparate origins or destinations within a ride-sharing vehicle whilst keeping to journey times acceptable to the client.

Use case – this is a marginal use case as a taxi but largely matches that of existing Private Hire Vehicles so will be a service type recognisable to Addison Lee. As a private car replacement the appeal is of volume given the size of the market.

Self-moving away from vehicle. Mass transit – special bus type service.

Vehicles could fulfi l a mass-transit bus type service for special services (group travel). These services are likely to be rarer in frequency (potentially pre-booked) and require larger vehicles, so may not be cost effective.

Use case – this is a marginal use case whereby the market is for private hire mini-bus.

Assisted movement away from vehicle or safeguarding. People transport. Mass transit - School children.

Vehicles could fulfi l a school bus type service, following a known route via several pick-up locations to a school or return. Travel to and from schools is a known issue for car congestion and providing transport is a cost pinch-point for local authorities which are legally required to provide transport to certain pupils (based on distance or mobility issues). There is an opportunity to move in to this market if the costs and benefi ts are attractive to local authorities.

Children require safeguarding and the driver also fulfi ls a role of protecting the children. There may also be behavioural challenges to contend with.

29

Use case – with the vehicles in a taxi or mini-bus confi guration this is a potentially a good use case for autonomous vehicles if the issue of safeguarding can be overcome.

Assisted movement away from vehicle or safeguarding. People transport. Low volume – vulnerable adults and patient transport.

Vehicles could fulfi l a patient transport type service. Patients may require special handling on and off the vehicle (potentially extending in to their house or a hospital) which is a role a driver may normally undertake. Some method of resolving this would be required. Patients may require special care for any medical emergency which might occur during their transport.

Patient transport services are usually undertaken via long-term contract, therefore there would be a need to win this contract or offer services to an existing supplier.

Use case – this is a potentially good use case with the vehicles adapted to take the mobility needs of passengers (wheelchairs etc.), if the issue of safeguarding can be overcome.

Assisted movement away from vehicle or safeguarding. Low value, low weight goods. Single item irregular goods.

Vehicles could carry small goods from a supplier to an end destination. This could include items such as takeaway food, or service parts required urgently (plumbing parts for example).

There is a need for the supplier to locate the vehicle and load goods in to it, then for the consignee to locate the vehicle and receive those goods. There is a need to factor the possibility that goods will be rejected meaning a need to return the vehicle to its origin, which impacts upon cost and vehicle availability.

There will be a challenge in fi nding suitable places for the vehicle to stop, and then ensuring that the consignee comes to the vehicle to unload it within a reasonable time period. Other practical considerations are that payment mechanisms would need to be explored, and the need to determine if goods are suitable for transport.

This type of service may work better where the consignee is more fl exibly disposed to coming out to meet the delivery vehicle, so for example a plumber or builder may have the opportunity to down tools and meet a vehicle, however a receptionist or goods-in steward may not have the fl exibility to leave their station.

Vehicles may be able to undertake multiple pick-ups and drop offs on any given outing.

Use case – this is an excellent use case which offers very high benefi ts and does not compete with sustainable transport modes. Vehicles may need to be adapted to allow for the carriage of goods, and for those goods to be only accessible to the consignee. It is envisaged that service contracts could be reached with goods suppliers (car parts, plumbing/electrical).

30

Assisted movement away from vehicle or safeguarding. Low value, low weight goods. Regular items.

Vehicles could be used for regular carriage between two known locations on a contract basis. Contracts would need to be set up as a courier service. A regular stopping location would need to be determined, such as a goods-inward bay or car park, and a method of loading and unloading goods would be required. As a regular delivery there would be more opportunity to ensure that the collection of goods once the vehicle has stopped can be arranged.

Use case – this is a very good opportunity and could replace a large number of existing general deliveries in London, for example regular food deliveries to the catering business.

Assisted movement away from vehicle or safeguarding. High value goods. Cash in transit.

Cash in transit vehicles are presently double-manned so are expensive to operate. Vehicles could be used to carry high value items such as cash or other banking items. A risk with all cash in transit is aggravated theft and the impact upon staff and the public. Autonomous vehicles could remove the risk of impact to staff, but may increase the propensity for theft.

Whilst items may be placed in the vehicle at a secure depot, there is a challenge of getting goods from the vehicle to a premises (this is the key risk phase for theft), and bank staff may not be appropriate to do this. Therefore some form of secure docking with the end destination may be required. Automated docking with a bank outer wall is an option which would require the vehicle to stop on the footway (not ideal), however a fl oor-level dock in the carriageway (or kerbside loading bay) may provide a viable secure method of carriage and may provide a viable model for other types of deliveries to occur without human intervention.

This form of operation may require specialist vehicles with in-built security items (such as safes, location devices, and cameras).

Use case – this is an excellent use case provided that the destination docking issue can be resolved.

31

Appendix E. Driving licence ownership demographics

Data is for England and derived from Department for Transport data table NTS0201 data for 2016. This reveals few younger people with licences, and a lower number of women with licences than men.2

2 Berrington A, Mikolai J, 2014. Young Adults’ Licence-Holding and Driving Behaviour in the UK. RAC Foundation.

Figure 9: Driving licence ownership

ImmenseEnabling Intelligent Mobility

MERGE Greenwich consortium partners

To keep in touch with the MERGE Greenwich project please visit www.mergegreenwich.com or contact merge@addisonlee.com