Automation in Road Transport Past Present

[ Automation in Road Transport Past, Present & Future Maarten Oonk MSc. Sr. Market Manager TNO Date: 7 th of March 2013 Joakim Svensson

[ Agenda 2

[ Automation throughout the years 3

[ Patent development 4

[ Automation in the 21 st century 5

[ 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;

[ Process Challenges Functions Roadmap Scenario’s AUTOMATION IN ROAD TRANSPORT Research topics stakeholders

Scenario’s Highway Legal aspects Towards HAD Rural Mobility Towards HAD Modelling & simulation Technical development Mobility Safe Efficient Urban Autonomous systems Efficient Traffic management Dedicated Automation in Road Automation in Transport IMPACT Road Transport IMPACT Clean Safe Active safety Reliable Perception Clean Cooperative systems Cooperati ve Cognition & systems Human factors Reliable

[ EXAMPLE USE CASE Use case definition “Intersection assistance” Scenario: Function: Automation level Description: Urban Environment Intersection assistance Driver assistance 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) V 2 X communication Accurate digital maps Data fusion among sensors, maps and V 2 X communication Reliable and accurate positioning (lane level) Control/x-by-wire 3 C 2 C WIFI-p secure communication layer 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 I don’t see any resulting driving behaviour change that would be amenable to a new model. Modeling & simulation stakeholders Development proces Deployment issues 1 Car industry 2 Would the drivers really bother to receive such warnings at each and every intersection? 9

[ Mapping of functions -I Full automation High automation L e v e l s Automated vehicles Highway pilot Automated intersection automated mode translation Urban platooning Automated emergency stop o f Partial automation Driver assistance platooning Traffic jam assistance A u Collision Avoidance - Braking and Steering t o Energy Efficiency Intersection Control m a Dynamic speed adaptation t Overtake assistance i o Lane keeping assistance n *) Automated Emergency Braking system Cruise control Driver only Scenario’s Urban area *) Based on the definitions of BASt rural area Highway area

Level of automation Urban platooning Automated mode translation Intersection assistance Dynamic speed enforcement Scenario’s Dedicated urban rural inter-urban Legal aspects Human factors & cognition Automated intersection Technical developments [ Mapping of functions - II

[ State of the Art and beyond… • Technical developments • Perception • Cognition & human factors • Traffic Management • Modeling & simulation 1 2

[ Results § 6 meetings in 2012 resulting in § Draft roadmap document

[ Perception (vehicles & road operator) • Reliable object recognition and tracking • Situational awareness • State estimation & prediction • Accurate road representation • Detection of free space • Classification of objects • Plug and Play concepts

[ Traffic & transport management • Open in-vehicle platform for I 2 V 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

[Cognition and Human factors • 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

[ Draft roadmap Recommendation of Research & Innovation activities

[ Future • • • Personalised? Connected? Pseudo-modal? Professional drivers only?

[ Thanks for your attention

[ Definitions Definition Description Key Function Driver 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, LK Cooperative ACC (CACC) Active Blind Spot Detection / Active Lane Change Assistant Automated lane keeping Cooperative 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 assist Cooperative 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 Assistant Collision Avoidance Cooperative Overtake Assistant Platooning by CACC Highway ―Chauffeur Full Automation Automated corridor The 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)

[ Recommendations § 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;

[ Stakeholders Who are involved…. That is changing! Now Future

This is our past and future; We now a lot about it; We only need time to discover it all