Contents Road safety in an uncertain technological future AVs and - - PDF document

Road safety in an uncertain technological future

Ana Martins – Ph. D. Student (CERIS, Instituto Superior Técnico, Universidade de Lisboa) anarmrmartins@tecnico.ulisboa.pt Filipe Moura (presenting author) – Associate Professor (CERIS, Instituto Superior Técnico, Universidade de Lisboa) fmoura@tecnico.ulisboa.pt Carlos Azevedo – Associate Professor (Technical University of Denmark) climaz@dtu.dk October 25, 2018

Contents

AVs and Expectations of positive impacts on road safety Six Dimensions for AVs and Road Safety

• A proposal for a Framework of Reference

Summary and Conclusions

.

1. 2. 3.

No automation

Human driver executes all tasks of driving

1

Driver assistance

Driver assistance system on steering or acceleration/deceleration

2

Partial automation

One or more driver assistance systems on both steering and acceleration/deceleration

3

Conditional automation

Monitoring of driving environment by the system but human driver should respond to a request to intervene

4

High assistance

Fallback performance of dynamic driving task by the system

5

Full automation

Full-time performance by an automated driving system (all modes)

Human driver monitors the driving environment Automated driving “system” monitors the driving environment “who does what, when”

(USDOT/ NHTSA, 2016)

Expected advantages…

representative but certainly not comprehensive

• User perspective

– Greater mobility freedom – From disutility to utility of travel time – Another mode of shared mobility (more flexibility) – Possibly, no or less car ownership costs – Fewer traffic collisions (elimination or minimization of human errors)

Expected advantages …

representative but certainly not comprehensive

• Operation perspective

– Reduced congestion – More effective navigation (less time losses and costs) – More effective use of vehicles (Shared AVs) – Reduced number of on-road vehicles (Shared AVs) – More efficient infrastructure (e.g., platooning) – Less infrastructure repair and maintenance costs (incl. those related to accidents)

Expected advantages …

representative but certainly not comprehensive

• Society perspective

– Better mobility for impaired and senior citizens – Reduced externalities (if electric and shared AVs) – Reduced accident rates and less societal losses – Increasingly feasible transportation services of enhanced safety, reliability, security, and productivity

Problems …

representative but certainly not comprehensive

• User perspective

– Costs – Privacy loss – Computer malfunctioning – Hacking of AV – Liability in case of accidents

Problems …

representative but certainly not comprehensive

• Operation perspective

– Upgrade for connected infrastructures and vehicles – Different patterns of pavement deformation – Hacking of the system – Weather (heavy rain) – Technology not fully mature – Relies heavily on satellite systems

Problems …

representative but certainly not comprehensive

• Society perspective

– Loss of jobs – Equity – Potential pollution increase (if not electric) – Terrorist attacks

– If just another technological change, more vkm potentially

The automation of driving task takes the human error out

• f the safety equation and it promisses to reduce the

number of accidents and victims.

(Fagnant & Kockelman, 2015; Hayes, 2011)

The human error is blamed for 90 % of road accidents.

(Maddox, 2012)

Possible cause of accident reported Total of victims (per year) 2013 2014 2015 2016 2017 Opening door 11 16 12 14 7 No lights (when mandatory) 10 7 11 6 9 Driving away from road side 46 29 30 46 51 No respect for traffic lights 103 77 106 86 85 No respect for vertical signs 484 447 537 557 530 No respect for safety distances 317 311 382 447 458 No respect for horizontal signs 85 66 74 74 79 Blinded by lights 118 94 107 139 186 Unlawful movements 505 483 490 599 641 Movements without previous warning 31 26 20 47 36 Excessive speed 1 795 1 786 1 550 1 726 1 731 Mechanical failure of the vehicle 71 68 78 68 68 Unforeseen obstacle 383 351 310 323 330 Falling objects 10 9 10 4 3 Tire bore 79 71 67 62 54 Non-classified 19 477 20 239 21 829 21 566 23 744 N.A. 335 218 218 278 201 Total 23 860 24 298 25 831 26 042 28 213

ANSR, 2014-2018: Road safety reports for Portugal

15%-17% of total accidents 87%-90% of total accidents classified

WSP | Parsons Brinckerhoff (2016): Making better places: Autonomous vehicles and future opportunities

Contents

AVs and Expectations of positive impacts on road safety Six Dimensions for AVs and Road Safety

• A proposal for a Framework of Reference

Summary and Conclusions

.

1. 2. 3.

Human behavior Human behavior Software develop- ment Travel behavior Technology maturity Technology deploymen t Innovation and develop- ment

Road safety

& AV

Road safety & AV

Human behavior Ethics Offsetting behavior New realities

• Less control by humans => less human-related mistakes

– Ethics: non-ethical human behavior towards AV (e.g., imagine an AV in a circle; bullying?) – Offsetting behavior: higher perceived safety => more careless behavior (e.g., belts) – New realities:

• automation reduces driving experience => reduce capacity of reaction
• Transition period when drivers will share the road with driverless cars or with

pedestrians and 2-wheelers

Travel behavior New realiities New scenarios Rebound effect

Road safety & AV

• More flexibility & comfort => more VKM?

– New realities : Travel time becomes a positive utility => More urban sprawling – Rebound effect: More flexible and easy-to-use (no parking issues) => More trips – New scenarios: Empty trips in passenger transportation; new congestion patterns with

fierce taxiing competition and private AV

Time New development Technology maturity New scenarios

Road safety & AV

• Proof and validation of new

technologies

– New scenarios : AV’s software

capabilities might change with new traffic patterns in the future

– Time: New technologies must prove they

are reliable, especially in these circumstances where safety is a cornerstone issue

– New development: Technological

development is fast and new technological solutions must be tested constantly (new validation methodologies are required)

New development Diffusion Technology deployment Segregation

Road safety & AV

• Better hardware, sensors and software capacity for new problems

– New development: New technological solutions solve problems at a fast pace – Diffusion: Challenges (such as safety) depend on rapid diffusion of new technologies

(bad experiences can slow down the pace of diffusion – Tesla accident)

– Segregation: Diffusion of innovation must not depend on standard technological

penetration of the automotive industry, i.e. new technology with new cars (software updating and hardware standardization)

Data Points of conflit Innovation and development Segregation

Road safety & AV

• Integration of innovation into

society

– Segregation: Vehicles with drivers and

driverless vehicle will coexist (at least at intersections). In the beginning, segregate

• AV. In the future, segregate old (current)

technologies

– Points of conflicts: Intersections are

always a major problem, also with AV (in potential conflict with all other modes)

– Data: Standard protocols have to be

defined in a connected road environment (V2V or V2I) for the consistency of the system.

Ethics Liability Data Software development

Road safety & AV

• The decision-maker

– Data: Software must be robust to resist

hacks; It must be interoperable between makes and across countries

– Liability: Liability in AV is from the car

producer; seller; software developer; software distributor? Implication for insurance companies?

– Ethics: Moral decisions can’t be learned.

They must be programmed according to

• idiosyncrasies. These vary from country to

country and culture to culture.

Contents

AVs and Expectations of positive impacts on road safety Six Dimensions for AVs and Road Safety

• A proposal for a Framework of Reference

Summary and Conclusions

.

1. 2. 3.

Human behavior Ethics Liability Data Offsetting behavior Time New development Points of conflit Diffusion Software development Travel behavior Technology maturity Technology deployment Innovation and development New calls New scenarios Rebound effect Segregation

Road safety & AV

Policies

Legislation

Regulation

Human behavior Human behavior Software develop- ment Travel behavior Technology maturity Technology deployment Innovation and develop- ment

Road safety & AV

Conclusion

The future is being built now:

• To prepare the society for the diffusion of the AV

And before that:

• To define regulation for AV

Do not forget that the human being is in the center of development

Selected References

• Human behavior

1. Dieusaert, T. (2017) Computer Crashes : When Airplane Systems Fail. Prensa Nueva. 2. Hauer, E. (2012) In defence of older drivers. Cmaj, 184 (6), pp 305–306. https://doi.org/10.1503 /cmaj.110814 3. Millard-Ball, A. (2016) Pedestrians, Autonomous Vehicles, and Cities. Journal of Planning Education and Research, pp 1–7. https://doi.org/10.1177/0739456X16675674 4. Sivak, M.; Schoettle, B. (2015) Road safety with self-driving vehicles: general limitations and road sharing with conventional vehicles. Report No. UMTRI-2015-2

• Travel behavior

1. Childress, S.; Nichols, B.; Charlton, B.; Coe, S. (2015) Using an Activity-Based Model to Explore Possible Impacts of Automated Vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2493, pp 99–106. https://doi.org/10.3141/2493-11 5. Ewing, R.; Hamidi, S.; Grace, J. B. (2016) Urban sprawl as a risk factor in motor vehicle crashes. Urban Studies, 53 (2), pp 247–266. https://doi.org/10.1177/0042098014562331 6. Fagnant, D. J.; Kockelman, K. M. (2014) The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transportation Research Part C: Emerging Technologies, 40, pp 1–13. https://doi.org/10.1016/j.trc.2013.12.001 7. Gruel, W.; Stanford, J. M. (2016) Assessing the Long-term Effects of Autonomous Vehicles: A Speculative Approach. In Transportation Research Procedia. https://doi.org/10.1016/j.trpro.2016.05.003

Selected References

• Technology maturity

9. Kalra, N.; Paddock, S. M. (2016) Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transportation Research Part A: Policy and Practice, 94, pp 182–193. https://doi.org/10.1016/j.tra.2016.09.010

• 10. Zhao, D., & Peng, H. (2017). From the Lab to the Street: Solving the Challenge of Accelerating

Automated Vehicle Testing. arXiv preprint arXiv:1707.04792.

• Technology deployment
• 11. Geistfeld, M. (2017) A Roadmap for Autonomous Vehicles: State Tort Liability, Automobile

Insurance, and Federal Safety Regulation. California Law Review, 105 (6). https://doi.org/10.15779/Z38416SZ9R

• 12. Kockelman, K.; Avery, P.; Bansal, P.; Boyles, S. D.; Bujanovic, P.; Choudhary, T.; ... Stewart, D. (2016)

Implications of Connected and Automated Vehicles on the Safety and Operations of Roadway Networks: A Final Report (FHWA 0-6849-1).

• 13. Kyriakidis, M.; Van De Weijer, C.; Van Arem, B.; Happee, R. (2015) The deployment of Advanced

Driver Assistance Systems in Europe. In 22nd ITS World Congress. Bordeaux.

• 14. Morando, M. M.; Tian, Q.; Truong, L. T.; Vu, H. L. (2018) Studying the Safety Impact of Autonomous

Vehicles Using Simulation-Based Surrogate Safety Measures. Journal of Advanced Transportation, 2018 (Article ID 6135183), pp 1–11. https://doi.org/10.1155/2018/6135183

• 15. Shariff, A.; Bonnefon, J. F.; Rahwan, I. (2017) Psychological roadblocks to the adoption of self-

driving vehicles. Nature Human Behaviour, 1 (10), pp 694–696. https://doi.org/10.1038/s41562- 017-0202-6

Selected References

• Innovation and Development
• 16. Kahn, M. E. (2011) Do liberal cities limit new housing development? Evidence from California.

Journal of Urban Economics, 69 (2), pp 223–228. https://doi.org/10.1016/j.jue.2010.10.001

• 17. Milakis, D.; Snelder, M.; van Arem, B.; van Wee, B.; Correia, G. H. de A. (2017) Development and

transport implications of automated vehicles in the Netherlands: Scenarios for 2030 and 2050. European Journal of Transport and Infrastructure Research, 17 (1), pp 63–85.

• 18. Sivak, M.; Schoettle, B. (2015) Road safety with self-driving vehicles: general limitations and road

sharing with conventional vehicles. Report No. UMTRI-2015-2

• Software Development
• 19. Bonnefon, J. F.; Shariff, A.; Rahwan, I. (2016) The social dilemma of autonomous vehicles. Science,

352 (6293), pp 1573–1576. https://doi.org/10.1126/science.aaf2654

• 20. Collingwood, L. (2017) Privacy implications and liability issues of autonomous vehicles. Information

& Communications Technology Law, 26 (1), pp 32–45. https://doi.org/10.1080/13600834.2017.1269871

• 21. Fleetwood, J. (2017) Public health, ethics, and autonomous vehicles. American Journal of Public
• Health. https://doi.org/10.2105/AJPH.2016.303628
• 22. Schroll, C. (2015) Splitting the Bill: creating a national car insurance fund to pay for accidents in

autonomous vehicles. Northwestern University Law Review, 109 (3), pp 803–833.

Ana Martins – Ph.D. Student (CERIS, Instituto Superior Técnico - IST, Universidade de Lisboa) anarmrmartins@tecnico.ulisboa.pt Filipe Moura (presenting author) – Associate Professor (CERIS, Instituto Superior Técnico - IST, Universidade de Lisboa) fmoura@tecnico.ulisboa.pt Carlos Azevedo – Associate Professor (Denmark Technical University - DTU) climaz@dtu.dk

Road safety in an uncertain technological future