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Maarten Oonk MSc. Joakim SvenssonSr. Market Manager TNO
[ Automation in Road Transport Past, Present & Future
Date: 7th of March 2013
[Challenges• Structure the huge complexity of the domain, the different
possible angles to look at the problems and make optimum use of past efforts;
• Increase participation of specific stakeholders like road authorities, traffic industry and service providers;
• Align our work with established expert groups on relevant topics for development of automation (internationally);
• Translate the roadmap for automation into a working program that will be recognized and accepted by the ITS community
• Look for options and/or alternatives to overcome apparent problems and obstacles for deployment;
9
Use case definition “Intersection assistance”Scenario: Urban Environment
Function: Intersection assistance
Automation level Driver assistance
Description: This function enables drivers at intersections to get direction specific or direction dependent warnings (based on the combination of position at the intersection, the indicator use, the destination (based on travnav info) etc.) for potential conflicts with other cars or users (pedestrians, cyclists) and can also control the vehicle(s) with the objective of collision avoidance if necessary.
Benefits: Increased safety and comfort for the drivers, specifically at complex and unknown intersections with lot’s of potential conflicts;
Increased safety for VRU’s Possibilities of reducing the safety margins for intersection control with the benefit of higher efficiencies Options for more adaptive traffic control based on real-time intersection specific OD information.
Value proposition: • Reduction in societal costs of traffic casualties;
• Less waiting times for drivers and smoother traffic flows
Topic Issues & research area’s Maturity level [1-5]
Legal aspects
Technical developments
Reliable and real-time perception (incl. VRU detection) V2X communication Accurate digital maps Data fusion among sensors, maps and V2X communication Reliable and accurate positioning (lane level) Control/x-by-wire
3
C2C WIFI-p secure communication layer 1
Cognition & human factors User – center design (applicable for all automation levels) Management of the interaction between the driver and the vehicle (interaction strategies) Maintain the driver’s workload in an optimal level (automation has dual effects on mental workload and may lead to both underload / overload situations) – definition of the optimal level &
measurement procedure Over-reliance as a result of adaptation / trust Driver in the loop (applicable even in highly automation level cases), situation awareness & response time Human – machine dynamic balance for any automation level
Traffic management
Crowded and congested intersection detection, collection, processing and distribution service to other cars 1
This could be a useful function for more efficient signal control at intersections due to more precise real-time information. 2
Modeling & simulation
I don’t see any resulting driving behaviour change that would be amenable to a new model.
stakeholders
Car industry 2
Development proces
Deployment issues
Would the drivers really bother to receive such warnings at each and every intersection?
Verification & certification
Standardization
security
Major research topic, as car’s my be hijacked 1
[ EXAMPLE USE CASE
[Mapping of functions -IAutomated vehicles
Automated intersection
Urban platooning
Traffic jam assistance
Automated emergency stop
Dynamic speed adaptation
Automated Emergency Braking system
Cruise control
Lane keeping assistance
Collision Avoidance - Braking and Steering
Highway pilot
Energy Efficiency Intersection Control
Overtake assistance
platooning
automated mode translation
Driver only
Driver assistance
Partial automation
High automation
Full automation
Levels of
Automation*)
Urban area rural area Highway area
Scenario’s
*) Based on the definitions of BASt
Level of
au
tom
ati
on
Scenario’s
Urban platoonin
g
Automatedintersection
Intersection
assistance
Automated mode
translation
Dynamic speed
enforcement
Tech
nic
al d
evelo
pm
ents
Hum
an f
act
ors
& c
og
nit
ion
Leg
al asp
ect
s
Dedicated urban rural inter-urban
[ Mapping of functions - II
12
[ State of the Art and beyond…
• Technical developments
• Perception
• Cognition & human factors
• Traffic Management
• Modeling & simulation
• Reliable object recognition and tracking
• Situational awareness
• State estimation & prediction
• Accurate road representation
• Detection of free space
• Classification of objects
• Plug and Play concepts
[ Perception (vehicles & road operator)
• Open in-vehicle platform for I2V communication and functions
• Arbitration (negotiation between driver, on-board automation and TM
centre)
• Distributed traffic management & self organizing concepts (lane
assignment, smart ramp metering)
• Determine and advise on the level of automation that is applicable
• Supervision of automation by traffic management centres
• Development of smart logistics corridors with advanced transport
management
[ Traffic & transport
management
• Effects of automated driving over a long period of time
• Interaction with automation in own vehicle and other road users
• Mode transitions & Mode confusion
• Take-over ability & Controllability
• Integration of functions
• Merging of autonomous (vehicle based) sensors with cooperative
data acquisition and validation
• Human Machine Interaction strategies and concepts
[Cognition and Human factors
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2025 2030
Pilot or large Scale demonstrator
R&
D A
rea
- Perception
- Cognition and Human
Factors
- Sensors & Actuators
Activity
Industralisation
Regulation Standard
Interconnected trafficUrban Automated traffic
Cooperative transport systems for smart
Networked traffic
Full Automation
Milestone 3
CooperativeDynamic Speed
Cooperative Systems for energy efficient and sustainable mobility
HAVEit
Queue Assist
CW-EB
Milestone 1 Milestone 2
Urban platooning
Dynamic Speed enforcment
Full Automation
CM-EB
Full Automation
Automated Intersection
Energy Efficiency Intersection Control
Full VRUSafety
Co-operative mobility -Supervised Automated
Driving
Collaborative Automation Roadmap
Recommendation of Research & Innovation activities
[Draft roadmap
[ DefinitionsDefinition Description Key FunctionDriver Only Human driver executes manual driving task Warning
Driver Assistance The driver permanently controls either longitudinal or lateral control. The other task can be automated to a certain extent by the assistance system.
ACC, Crash mitigation, EBS, LKCooperative ACC (CACC)Active Blind Spot Detection / Active Lane Change AssistantAutomated lane keepingCooperative Merge Assistant
Partial automation The system takes over longitudinal and lateral control, the driver shall permanently monitor the system and shall be prepared to take over control at any time.
Queue assistCooperative Traffic Jam Assistant Road Work Assistant
High Automation The system takes over longitudinal and lateral control; the driver must no longer permanently monitor the system. In case of a take-over request, the driver must take-over control with a certain time buffer.
Emergency Stop AssistantCollision AvoidanceCooperative Overtake AssistantPlatooning by CACCHighway ―Chauffeur
Full AutomationThe system takes over longitudinal and lateral control completely and permanently. In case of a take-over request that is not carried out, the system will return to the minimal risk condition by itself.(Note this paper is does not deal with full automation, the definition is included merely for the clarity of the reader)
Automated corridor
More awareness with road authorities;
Statement on options for developing suitable legal framework;
Develop applicable models for simulating changing traffic
dynamics;
HMI & human factors
Implementation plan for technical feasible cooperative
applications in real life;
Make sure there is a clear business case and a prime
stakeholder;
[ Recommendations