Advancing Sustainable User-centric Mobility with Automated Vehicles. How can we reach a sustainable deployment of fully autonomous vehicles for shared public transportation? what are the economic and technical barriers?

1. Advancing Sustainable User-centric
Mobility with Automated Vehicles:
From AVENUE to ULTIMO
Prof. Dimitri Konstantas
University of Geneva
AVENUE project Coordinator
ULTIMO project associate Coordinator
dimitri.Konstantas@unige.ch

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The AVENUE project (2018 – 2022)
Several validation sites during the past few
years
Deployed Public Transportation
services with Autonomous
Vehicles
On-demand, Door-to-door public
transportation service
• no-bus stops (almost … large number
of virtual stops)
• no fixed itineraries,
• no time schedules,
• no intervention by the safety operator
(reached from 80 to 97%)

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Well known Issues faced and
lessons learned in AVENUE (and other AV projects!)
Legal and regulatory EU frameworks not adapted to public
transportation on-demand services
▫ Obligation to have fixed bus-stops, predefined itineraries
▫ Vehicle homologation is a complex process (from 8 months to 3 years)
▫ GDPR and application to public transportation
Driver suppression requires services’ replacement
▫ Vehicle status (cleanness, small incidents, ..)
▫ Passenger services (safety, aggressions, lost objects …)
Business model not yet well understood
▫ Pricing of rides, integration to existing models
▫ Changes of passenger behaviour (very short rides)
▫ Vehicle life time
Technology is still under evolution
▫ Improvements are introduced constantly

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BUT ..
Life is not so
simple…

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Operating an AV small
experimental public transport
service is just the tip of the
iceberg…
Going full scale commercial … is
the rest of the iceberg!!!
Commisioning
Legal and Regulatory
Passenger
acceptance
Citizen centric approach
Customer, PTO or PTA Lock-in
through the “winner takes it all”
Viable Business plans
Governance for the transport of
persons and goods towards
societal goals
Technical
issues
Environmental issues
Digital divide,
digital illiteracy
Interoperability through
open API, open Data and
open protocol
Safety &
security

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A dream of a future AV
urban public transportation
▪ Backbone of tram/metro service
▪ Localized transport with AVs
▫ Last-mile to/from backbone
▫ Full service for transport in
region or across regions
▫ Door-to-door service

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And what is Missing???
How can we create a commercially
viable, large scale public
transportation service with
autonomous vehicles???
The rest of the iceberg !!!

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Major Obstacle : Viable business
▪ There is no viable business model
▪ The AV business ecosystem does not
exist
▪ The business development choices of
the actors are almost irrelevant!!
▪ The operation policies of the
operators are difficult to be defined

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The ULTIMO Horizon Europe project
Set the foundations and deploy, the very first
economically realistic and viable Automated
Vehicles’- based, large scale on-demand, door-to-
door, inclusive and user-oriented shared public
transportation services
Taking an holistic approach, considering all
elements in a cross-sector business environment.

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The ULTIMO Horizon Europe project
4 years
23 Partners – 3 deployment cities : Germany, Norway, Switzerland
52 MEUR budget
40 MEUR financing (24 MEUR 16MEUR )
Started October 1st 2022
General Coordinator Associate Coordinator & Technical
Manager
Lars Abeler - DB Regio Bus (D) Dimitri Konstantas - Uni Geneva
(CH)
Scientific Manager : Guy Fournier - Hochschule Pforzheim
Towards large scale,
commercially viable AV
deployment in Public
Transportation

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ULTIMO Key Objectives
1. Validate integrated shared CCAM systems and services for people and goods
across Europe
2. Develop open source APIs for seamless integration of vehicles and fleet
management into a the MaaS/Laas systems
3. Incrementally reach large scale, multivendor deployments in all sites, using the
most adapted vehicle for each transport use case
4. Set the basis for a common and reusable model for HD maps for AVs
5. Provide automated passenger services for safety and service quality
6. Develop and validate cross-sectoral business models
7. Improve interaction with road users and infrastructure for improved safety
8. Realistic, long term transition planning design for the deployment of AVs in
MaaS and LaaS

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1. Investment Valorisation
Life time of Automated vehicles
▪ Design is not adapted for public transport
▪ Computer and sensor systems follow the law of
Moore
▪ Expected life today does not exceed 6 to 7 years
(compared with 15 to 18 for thermal vehicles).
ULTIMO Approach:
▪ Link vehicle capabilities to passenger use cases.
In the city center where the authorized
speed limit is 30km/h, why use a high speed
vehicle (that can drive 50-60 km/h)

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2. City mapping Scale-up
▪ Cost per Km more than 2-3 KEUR (commissioning)
▪ Commercial deployment will cover a few 1000’s
of Km in a city !!
▪ Keeping maps up to date (less then 24 h updates)
▪ Maps not compatible between manufactures –
double costs!!!
ULTIMO Approach:
▪ Develop a common AV-HD map model
Normalise semantic annotations,
representation models, ….

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3. Free choice of AV model
▪ Each AV model has different capabilities and interfaces
▪ Fleet-management systems are fine tuned for a
specific model and its capabilities
▪ No standardized interfaces
ULTIMO Approach:
▪ Develop an open API standard of vehicle-fleet mgt
and vehicle-services OBU
In the last year of the project swap fleet mgt provider in 2
days!
Add new vehicles in a plug-and-play (connect-and-operate)
mode

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4. Transport policies – Paradigm change
▪ On-demand, door-to-door automated public transportation :
paradigm change
▪ What to do when passenger :
blocks the door, did not show up, places order for
20m trip, vandalizes the vehicle, brings in large suitcase
▪ Minimal number of passengers per ride?
▪ What is the “right” trip price?
ULTIMO Approach:
▪ Develop automated passenger services for in-vehicle monitoring
▪ Study and define the implications and actions needed by the PTOs for
each service use case

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5. Scalability of technology and service
▪ AV management supports small scale deployments and
small AV numbers
▫ All data are centrally controlled by the AV
manufacturer – scalable to thousands of vehicles
▪ Fleet management systems have not been tested for
hundreds of AVs in a single site
▫ Complexity of the dynamic re-routing,
re-allocation of trips, dynamic road changes
▪ Public transportation requires long term planning
▫ Routes, budget, choice of new vehicles, City infrastructure
ULTIMO Approach:
▪ Incremental scale-up to large number of vehicles and routes
▪ Study of all deployment costs, use cases and required infrastructures
Fleet management with large numbers of AVs
Transition roadmap for infrastructure, services, vehicles, ….

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6. Cross-sector business
▪ AV public transportation means that we use the vehicles
only when there is a demand
▪ Large excess capacity in off-peak hours = vehicles stay parked
▪ A vehicle that is under-used is very costly
ULTIMO Approach:
▪ Innovative merge of Passenger and Logistic services
Dynamic vehicle chartering of excess AV capacity (in off-
peak hours) for Urban Logistics services
SLAs for smooth and competitive business development

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7. User-centric development
▪ The suppression of the human driver will inevitably reduce the
transport service quality
▫ In-vehicle incident management
▫ Passenger safety and information
▫ Special needs passengers
▫ Vehicle status
ULTIMO Approach:
▪ Innovative and inclusive User services
User co-creation of service with active engagement of user
from day one
In-vehicle standardized Passenger Services΄ OBU

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The road Ahead
Incremental development with deployment of
services from day and continuous feedback from
passengers (co-creation)
2023 : define use cases, passenger needs vs vehicle
capabilities
2024 : develop services, test scalability, define economic
models, define operator policies
2025 : validation in real life conditions
2026: full scale commercial deployment of min 15
vehicles per site

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