Automatisch rijden, het gedrag van bestuurders en verkeersstromen

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1 Automatisch rijden, het gedrag van bestuurders en verkeersstromen Bart van Arem EVU Symposium, 9 september 2016, Postillion Hotel Amersfoort Veluwemeer

2 Rivium Buses (Rotterdam)

3 2013: DAVI on the road

4 2016: WURby hits the road

autocruise Vehicle in control in special

5 Automated driving Driver assistance/ Partial automation Conditional/ High automation Driver needs to be able to intervene at all times Automated parking, autocruise Vehicle in control in special conditions Taxibots, platooning, automated highways Comfort, efficiency, safety, costs Mode choice, location choice, urban and transport planning

Fundamental changes in driving behaviour

6 Fundamental changes in driving behaviour Driver in control Vehicle in control Driver supervision Workload, driving performance, attention, situation awareness risk compensation, Driver Vehicle Interface, acceptance, mode transition, purchase and use Responsibility, accountability?

Acceptance Drivers state that they prefer warnings over control Control could be acceptable in special conditions such as congestion driving

7 Acceptance Drivers state that they prefer warnings over control Control could be acceptable in special conditions such as congestion driving Acceptance of (different levels of) automation increases after (positive) experience Scepticism has been declining Effect of hyping Concerns because of accidents

11 The congestion assistant Detects downstream congestion Visual and auditive warning starting at 5 km before congestion Active gas pedal at 1,5 km to smoothly slow down Takes over longitudinal driving task during congestion

12 Impacts on driving behaviour Motorway scenario with congestion Impacts on driving behaviour Acceptance

13 Effects on mean speed

14 Effects on time headway May 31, 2006

Potential impacts on traffic Solve traffic jams by increased outflow Prevent traffic jams by better stability Less congestion delay Better distribution of

15 Potential impacts on traffic Solve traffic jams by increased outflow Prevent traffic jams by better stability Less congestion delay Better distribution of traffic over network Non connected Large penetration Decreased throughput by larger headways Decreased stability by lack of anticipation Increased risk of congestion

congestion Active gas pedal at 1,5 km to smoothly slow

16 The congestion assistant Detects downstream congestion Visual and auditive warning starting at 5 km before congestion Active gas pedal at 1,5 km to smoothly slow down Takes over longitudinal driving task during congestion

17 Traffic flow simulation: merging area A12 motorway, Woerden, the Netherlands start end upstream detector downstream detector 4.1 km 2.1 km

18 Results 120 Speed upstream - 10% CA Speed (km/h) Reference 1500 m 500 m 1.0 s 0.8 s Time (min) Speed upstream - 50% CA Speed (km/h) Reference 1500 m 500 m 1.0 s 0.8 s Time (min)

19 A20: bottleneck motorway, no more space to expand 3+2 cross weaving Short on-ramp How can AVs relieve congestion here?

20 General findings on motorway capacity ACC can either have a small negative or a small positive effect on capacity (~ -5% to +10%) Bottlenecks: increase <10% Positive effect stability and capacity drop Lower level roads?

activities by better accessibility Redesign of urban, commercial, touristic

21 Spatial implications Geometric redesign of roads and junctions Functional Increasing sprawl residential and employment locations Concentration activities by better accessibility Redesign of urban, commercial, touristic areas Spatial No on street parking Combinations with car sharing, electric driving

regional, city authorities, public transport operators, Multimodal hubs (ports, airports) Automated

22 Policy relevance Congestion and accessibility Safety Travel patterns Freight transport Public transport Socio-economic development Urban design Spatial structure Investment policies National, regional, city authorities, public transport operators, Multimodal hubs (ports, airports) Automated cars can improve traffic efficiency and safety Netherlands to facilitate large scale testing of automated cars

23 Exploration using LMS Automated Autonomous 5% capacity decrease on primary road network Automated Cooperative 15% capacity increase primary road network 10% capacity increase secondary road network 10% decrease value of time commuting and business car trips Index km travelled Train Car driver 99.8 Car passenger 99.7 Bus, tram, metro Cycling Walking Total Index congestion Train 98.8 Index km travelled Car driver Car passenger Bus, tram, metro 99.2 Cycling 99.3 Walking 99.4 Total Index congestion 69.1

24 Scientific challenges: understanding the spatial and transport changes Travel and location choice behaviour Freight and Logistics applications Automated Driving Infrastructure service networks Spatial structure and economy Accessibility Economy Traffic Safety Urban quality Urban design and traffic safety Regional spatial and transport system

25 STAD: Spatial and Transport Impacts of Automated Driving

26 The road to automated driving Develope efficient and reliable technology Collect, analyse and publish large scale real-world experience Study spatial, transport and societal impacts Regulations, type approval Awareness, ambitions, expectations, reality checks

27 Research Lab Automated Driving Delft

28 THANK YOU!

Reducing randomness: the advent of self driving cars

Reducing randomness: the advent of self driving cars Prof Dr Ir Bart van Arem TU Delft, Faculty of Civil Engineering and Geosciences Department Transport & Planning 1 Your speaker 1982-1986 MSc, Qeueing