Dutch Automated Vehicle Initiative – Dutch Automated Vehicle Initiative To investigate, improve and demonstrate automated driving on public roads Assess & improve technology Study human behaviour Prove safety Pursue legalisation Create public awareness
Dutch Automated Vehicle Initiative – DAVI in time InceptionMarch 2013 Official Launch Innovatie-estafette Nov 2013 Experiments with non-expert drivers2015 Demo with non-expert drivers2016
Dutch Automated Vehicle Initiative – key projects & partners DAVI open initiative TU Delft, RDW, TNO, Connekt, SWOV, UT, Fontys, Hanze, HAN, RUG, Toyota Motor Europe, NXP, Imtech, VisLab (IT), SKF, Technolution, Almende, V-tron, Trinité Mapscape, DLR, TRL, ITS-Leeds Human Factors of Automated Driving (HFAuto) Marie Curie FP7 TU Delft, TU München, Univ of Southampton, Univ of Twente, Chalmers Univ of Technology, IFSTTAR (France), VTI (Sweden), Volvo Truck, Volvo Car, BMW, Jaguar, Toyota Motor Europe, Continental, TNO, SWOV Truck Merging Support HTSM TU Delft, TU/e, DAF, SKF, TNO, NXP From Individual Automated Vehicles to Cooperative Traffic Management (IAVTRM) STW-OTP TU Delft, Toyota Motor Europe, TNO, NXP, Imtech Traffic & Infra, RDW, Connekt, SWOV, Technolution, Almende, V-tron, Trinité Automation, VisLab FoodvalleyProvince of Gelderland
Dutch Automated Vehicle Initiative – Hands free Cruise Control with automated steering Highway in 2020 Capable driver Autonomous No steer & pedals User only has to select the destination Mixed with normal traffic
Dutch Automated Vehicle Initiative – Vehicles 3 Priuses TNO / DITCM CACC Automated steering Prius Fontys Automated steering 2 Priuses TU Delft Towards 360 deg sensing
Dutch Automated Vehicle Initiative – Ambitions Vehicle automation Robust environment perception Safe control strategies Link automation to traffic management Human factors Transitions of control Acceptance, trust, use & misuse Interaction with other road users Benefit prediction Legalisation Public awareness & acceptance
Dutch Automated Vehicle Initiative – Environment Perception Cameras, Radar, Ultrasound, Lidar Cars, trucks, pedestrians, cyclists Road markings Road Signs Traffic lights Challenges Reliable detection in various weather conditions Intent recognition & motion prediction Integration environment sensing with communication and detailed maps
Dutch Automated Vehicle Initiative – Main Processing Unit PXIe-1062Q RTOS (NI) HDR vision systems (Melexis) High accuracy Digital maps & eHorizon systems (Mapscape – Maccom - Electrobit) ARS HS radars (Continental) Custom of the shelf sensors
ACC: no V2V communication CACC: full V2V communication Graceful degradation in case of packet loss: dCACC Graceful degradation of CACC CACCACCdCACC
Dutch Automated Vehicle Initiative – Automated lane changing & merging Shown in movies carmakers Proof of safety not found DAVI simulation studies Optimize gap & timing 1 Optimize collective benefits 1 Trajectory control with non-linear vehicle model 2 Next Sensors fusion & inaccuracy Role of the driver? 1.Wang M, Hoogendoorn SP, Daamen W, van Arem B, Happee R. Novel predictive approach for unified lane- changing and car-following control. Submitted ISTT21 2.Gottardis P, Manazza SS. Automated Controlled Vehicle Based on Non-Linear Model Predictive Control Connected to a Safety Path Planner with Online Collision Risk Estimation MSc thesis TUDelft / Polimi 3 Oct 2014
Dutch Automated Vehicle Initiative – Human Factors Literature survey 1 Extensive simulator studies Highly Automated Driving Workload affects HAD much larger than ACC Only expert drivers tested with HAD on public roads (3 studies) Challenges Monitor & Manage driver awareness Develop safe transition procedures & interfaces Investigate human interaction with HAD on public roads 1.de Winter JCF, Happee R, Martens MA, Stanton NA. (2014). Effects of ACC and highly automated driving on workload and situation awareness: A review of the empirical evidence. TRPF: Traffic Psychology and Behaviour.
Dutch Automated Vehicle Initiative – Opinions on automated driving 1 Diverse / extreme responses 22% unwilling to pay for fully automated driving 5% willing to pay more than $ 30,000 69% estimated fully automated driving to reach 50% market share before concerned about software hacking/misuse legal issues and safety 1.Kyriakidis M, Happee R, de Winter JCF. Public opinion on automated driving: Results of an international questionnaire among 5,000 respondents. Submitted.
Dutch Automated Vehicle Initiative – Automated Transport Foodvalley (Gelderland) “De eerste zelfsturende auto’s van Nederland moeten gaan rijden in Ede en Wageningen” (Gelderlander 1 Oct 14). Planstudie, suitable routes, sensors & control Innovation From closed track to public roads Safe interaction with pedestrians, cyclists, cars On demand public transport Safety by Low speed Conservative control strategies Control room monitoring
Dutch Automated Vehicle Initiative – Milestones testing automation on public roads Technical safety assessment Sensing reliability Safe operating conditions Automation linked to traffic management Behaviour non-expert drivers investigated Safe transitions of control Quantify how drivers will use automation Prove safety taking into account the human interaction Benefits predicted with traffic flow models Legalisation
Dutch Automated Vehicle Initiative – Questions
Dutch Automated Vehicle Initiative – DAVI Partnership Charter DAVI aims to implement automated vehicles, obtain permission for testing on public roads, link vehicle automation to traffic management, assess and improve automation technology, study human behaviour with automation, prove safety, optimise transport efficiency, create public awareness, and pursue legalisation of automated driving. DAVI pursues these objectives through complimentary research projects and demonstration activities with varying partnerships and national and international funding sources.
Dutch Automated Vehicle Initiative – Vacancies Vacancy 1 ( PhD Candidate ) Human interaction with automation Human machine interface, driver state monitor Investigate the human interaction with automation Vacancy 2 ( PhD Candidate ) Benefits & risks of automated driving Develop computer models capturing mixed traffic Predict & optimise benefits Vacancy 3 ( Post Doc ) Automation & safety assessment Automation algorithms, merging, lane changing and overtaking Safety assessment methods Vacancy 4 ( Engineer ) Environment sensing Systems architecture Sensors & fusion providing robust 360 degree environment perception