PRE2017 3 Groep16

Group Members

Rivelino Wattimena (0967390)

Jeroen van Meurs - 0946114

Tim Driessen (0954562)

Jorik Mols (0851883)

Lisanne Willems (0954451)

Week 1

Problem statement

Imagine a world in which autonomous vehicles fill the streets. For a lot of people this would be ideal trafic control. However, no human control over the car brings some setbacks. One of these setbacks is interaction with pedestrians that are crossing the road. In today's traffic, a car driver will usually wave at the pedestrians, to show that they have been seen and they can cross the road. However, with autonomous self driving cars, no humans are in control of the vehicle. Then how do pedestrians know that the vehicle has seen them? Also the opposite case is important, how do autonomous vehicles know the pedestrians have seen them? This human-vehicle interaction problem is of great importance for the general safety in trafic. For this problem, we will try to come up with some solutions.

Objectives: Create a safer environment An interaction between autonomous vehicles and pedestrians that increases safety (for all involved) in traffic.

Users

The system will have a set of users, each with their own requirements. These might vary among the different user types. The pedestrians are a group of users that will indirectly make use of the system, by interacting with the autonomous vehicle which has incorporated this system. These pedestrians are concerned about safety and will want to trust that this interaction does not fail. When wanting to cross the road, they should not have to perform actions that are too complex, so the system should be easy to work with (ease-of-use). The driver of the autonomous vehicle (or rather, passenger) also wants to be able to trust this system as well as the autonomous vehicle itself. Since we target fully autonomous vehicles and not vehicles that still require some control of the driver, we envision the passengers of such a vehicle to trust what the vehicle is doing. The driver is also concerned with safety, accidents are to be avoided of course. Our system should be able to deal with all necessary interaction between the vehicle and the pedestrian, therefore the driver might not have to be involved in this interaction. We will have to determine whether this is the case when designing our system. The autonomous vehicle itself also counts as a user (even though it is not human). The workings of these vehicles should be improved with our solution and in traffic (autonomous) vehicle-pedestrian interaction should be safer.

Society

Our society should benefit from our solution. Governments spend millions of dollars already to increase traffic safety. Although we are definitely not at the stage where everyone drives an autonomous vehicle, we expect this to be the future and safety is always a concern when it comes to traffic. What we have to research is where exactly our system will be a solution to the problem. Pedestrian-dense neighborhoods where people are used to crossing roads with little care might require a different tactic then places where there are a lot of pedestrian crossings which are properly used. Autonomous vehicles should be risk-averse and thus might be too careful when driving in environments like the center of Amsterdam, especially when we design a system that requires the vehicle to interact with each and every person that wants to cross the road.

Enterprise

Business-wise the system should be successful in that car production companies can buy and use it in their autonomous vehicles. To get autonomous vehicles more accepted by the public, they have to become safer so that people can trust them. Our system might have a positive effect on this, showing to the public that these autonomous vehicles can in fact be made safe. Car companies could market their cars with this idea and our solution in mind.

Approach

In this project we will determine the problems pedestrians face when crossing streets where autonomous vehicles drive and the other way around. Then we will look at numerous stakeholders and possible solutions. After that, questionnaires/interviews will be held with stakeholders to determine the needs of a system that offers a solution to the defined problem. After this, a design for our solution will be made and a prototype will show some of the working principles that need to be proven in order to give credibility to the final design.

Deliverables

We will write our findings in a report style on the wiki. We would like to deliver a prototype near the end of this project.

Who will do what?

For the first part of the project we will work together as much as possible so everybody has the same basis. In a later stage of the project we will split the work a little bit more. Since we have a student from software science, he will take the lead in the coding work. The mechanical engineers will take the lead in the hardware creation.

For this week the tasks are divided as the following:

Problem description: Tim Driessen

USE aspects: Jorik Mols, Jeroen van Meurs

State of the art research: Rivelino Wattimena, Lisanne Willems, Tim Driessen

Coaching Questions Week 1

What are you expecting to learn during the Robots course?

Learn to work together in an interdisciplinary group. Solving a problem while taking the USE aspects into account.

What kind of coaching do you expect?

We expect the coaches to correct us when we are heading into a wrong direction. Furthermore we expect them to motivate us for the subject.

What kind of coaching would you prefer?

We prefer a kind of coaching that does not simply tell us what to do, but asks questions that makes us think about aspects that we hadn't taken into account.

What will the coaches expect of you?

For us to ask questions about things we run into, instead of passivly wait for the coach to figure our issues out. Also, they expect us to seriously work on this project, and work as a team.

State of the Art Research

• Millard-Ball, A. (2018). Pedestrians, autonomous vehicles, and cities. Journal of Planning Education and Research, 38(1), 6-12. 10.1177/0739456X16675674

- Short Summary of Abstract:

In this article the author uses game theory to analyse interactions between pedestrians and autonomous vehicles with a focus on crossing streets.

• Hulse, L. M., Xie, H., & Galea, E. R. (2018). Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age. Safety Science, 102, 1-13. 10.1016/j.ssci.2017.10.001

- Short Summary of Abstract:

in this article a study is discussed where almost 1000 participants have been surveyed their perceptions, particularly regarding the safety and acceptance of autonomous vehicles.

• Zhang, J., Vinkhuyzen, E., & Cefkin, M. (2018). Evaluation of an autonomous vehicle external communication system concept: A survey study10.1007/978-3-319-60441-1_63

- Short Summary of Abstract:

• Chang, C. -., Toda, K., Sakamoto, D., & Igarashi, T. (2017). Eyes on a car: An interface design for communication between an autonomous car and a pedestrian. Paper presented at the AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings, 65-73. 10.1145/3122986.3122989

- Short Summary of Abstract:

In this article an interface design has been tested in VR for communication between autonomous cars and pedestrians. The evaluation results show that pedestrians can make the correct decision more quickly when the approaching car has the novel interface “eyes” than in case of a normal car. Furthermore the results also show that they feel safer crossing a street if the approaching car has eyes and if they make contact with the.

• Mirnig, N., Perterer, N., Stollnberger, G., & Tscheligi, M. (2017). Three strategies for autonomous car-to-pedestrian communication: A survival guide. Paper presented at the ACM/IEEE International Conference on Human-Robot Interaction, 209-210. 10.1145/3029798.3038402

- Short Summary of Abstract:

in this article three strategies are discussed how autonomous cars could communicate with other agents for accident-free-traffic with the help of knowledge from social robots.

• Rothenbücher, D., Li, J., Sirkin, D., Mok, B., & Ju, W. (2015). Ghost driver: A platform for investigating interactions between pedestrians and driverless vehicles. Paper presented at the Adjunct Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive VehicularApplications, AutomotiveUI 2015, 44-49. 10.1145/2809730.2809755

- Short Summary of Abstract: In this article a simple test has been done to obtain how pedestrians will react to a “driverless vehicle”. A vehicle was prepared to make it look it was driverless and information could be obtained without really having an autonomous car.

• Rothenbucher, D., Li, J., Sirkin, D., Mok, B., & Ju, W. (2016). Ghost driver: A field study investigating the interaction between pedestrians and driverless vehicles. Paper presented at the 25th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2016, 795-802. 10.1109/ROMAN.2016.7745210

• Keferböck, F., & Riener, A. (2015). Strategies for negotiation between autonomous vehicles and pedestrians. Paper presented at the Mensch Und Computer 2015 - Workshop, 525-532. Retrieved from www.scopus.com

- Short Summary of Abstract:

In this article a study is discussed about comparing the actions of pedestrians with autonomous cars in two cases: when the car explicitly interacts with them or not explicitly interacts with them.

• David, C., Wim, V., Ingrid, M., & Piet, D. (2011). Architecture for vulnerable road user collision prevention system (VRU-CPS), based on local communication. Paper presented at the 18th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2011, , 7 5500-5509. Retrieved from www.scopus.com

- Short Summary of Abstract:

In this article a proposition is made to use position estimation based on neighbouring devices such as other cars or smart devices.

• Scaramuzza, D., Spinello, L., Triebel, R., & Siegwart, R. (2010). Key technologies for intelligent and safer cars - from motion estimation to predictive collision avoidance. Paper presented at the IEEE International Symposium on Industrial Electronics, 2803-2808. 10.1109/ISIE.2010.5636880

- Short Summary of Abstract:

In this article various techniques are discussed for safer autonomous driving in urban environments.

• Colley, A., Häkkilä, J., Pfleging, B., & Alt, F. (2017). A design space for external displays on cars. Paper presented at the AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Adjunct Proceedings, 146-151. 10.1145/3131726.3131760

- Short Summary of Abstract:

In this article ideas are discussed to present information on the exterior of cars.

• Schneemann, F., & Gohl, I. (2016). Analyzing driver-pedestrian interaction at crosswalks: A contribution to autonomous driving in urban environments. Paper presented at the IEEE Intelligent Vehicles Symposium, Proceedings, , 2016-August 38-43. 10.1109/IVS.2016.7535361

- Short Summary of Abstract:

In this article the interaction between drivers and pedestrians are analysed to define the behavioural requirements for future autonomous vehicles. A study has been conducted from both the driver’s perspective and the pedestrian’s perspective.

• Saleh, K., Hossny, M., & Nahavandi, S. (2017). Towards trusted autonomous vehicles from vulnerable road users perspective. Paper presented at the 11th Annual IEEE International Systems Conference, SysCon 2017 - Proceedings, 10.1109/SYSCON.2017.7934782

- Short Summary of Abstract:

In this article a computation framework has been proposed for modelling trust between Vulnerable Road Users and autonomous vehicles based on a shared intent understanding between the two of them.

• Wang, C. -., Liu, A., Wu, P., & Lu, P. -. (2017). A study in human-machine interaction through agent simulation: An application in pedestrian crossing. Paper presented at the 2016 International Automatic Control Conference, CACS 2016, 167-172. 10.1109/CACS.2016.7973903

- Short Summary of Abstract:

In this article research has been done by using agent simulation to realize Human-Vehicle interaction. The domain chosen is the Pedestrian-Vehicle in street crossing.

• Gupta, S., Vasardani, M., & Winter, S. (2016). Conventionalized gestures for the interaction of people in traffic with autonomous vehicles. Paper presented at the Proceedings of the 9th ACM SIGSPATIAL International Workshop on Computational Transportation Science, IWCTS 2016, 55-60. 10.1145/3003965.3003967

- Short Summary of Abstract:

In this article the question is answered whether there is an universal language to interact with traffic.

• Dey, D., & Terken, J. (2017). Pedestrian interaction with vehicles: Roles of explicit and implicit communication. Paper presented at the AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings, 109-113. 10.1145/3122986.3123009

- Short Summary of Abstract:

In this article road-crossing and communication behaviour of pedestrians and drivers in busy traffic situations are categorized. The evidence suggest that eye contact does not play a major role in manual driving and that motion patterns and behaviours of vehicles play a more significant role

• Florentine, E., Andersen, H., Ang, M. A., Pendleton, S. D., Fu, G. M. J., & Ang, M. H. (2016). Self-driving vehicle acknowledgement of pedestrian presence conveyed via light-emitting diodes. Paper presented at the 8th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2015, 10.1109/HNICEM.2015.7393208

- Short Summary of Abstract:

In this article a method is described equipping an self-driving golf cart with LED’s to convey information to nearby pedestrians. By equipping autonomous vehicles with a feature like this, their performance as social robots is improved by building trust and engagement with interacting pedestrians.

• Hussein, A., García, F., Armingol, J. M., & Olaverri-Monreal, C. (2016). P2V and V2P communication for pedestrian warning on the basis of autonomous vehicles. Paper presented at the IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2034-2039. 10.1109/ITSC.2016.7795885

- Short Summary of Abstract:

In this article a method is discussed to broadcast positions from vehicles nearby to other road users and vice versa to minimize potential dangers and increase the acceptance of autonomous cars on roads.

• Zimmermann, R., & Wettach, R. (2017). First step into visceral interaction with autonomous vehicles. Paper presented at the AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings, 58-64. 10.1145/3122986.3122988

- Short Summary of Abstract:

In this article the need of communication between pedestrians and vehicles is explored and if it could be achieved through motion behaviour of that vehicle

• Florentine, E., Ang, M. A., Pendleton, S. D., Andersen, H., & Ang, M. H., Jr. (2016). Pedestrian notification methods in autonomous vehicles for multi-class mobility-on-demand service. Paper presented at the HAI 2016 - Proceedings of the 4th International Conference on Human Agent Interaction, 387-392. 10.1145/2974804.2974833

- Short Summary of Abstract:

In this article methods are described of conveying information and motion intention of autonomous vehicles to the surrounding environment.

• Vasic, M., Billar, A. (2013). Safety issues in human-robot interactions. Proceedings - IEEE International Conference on Robotics and Automation 6630576, pp. 197-204

- Short Summary of Abstract: In this article the safety in human-robot interaction is considered. First in industrial settings than with autonomous mobile robots operating in crowded environments (the most interesting part for us) and last with assistive robots.

• Le, H., Pham, T.L., Meixner, G. (2017). A concept for a virtual reality driving simulation in combination with a real car. AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Adjunct Proceedings pp. 77-82.

- Short Summary of Abstract:

Human-machine interaction for autonomous driving is still under development. This article is about the area of increasing the level of immersion of virtual reality driving simulation with a real car.

• Hacohen, S., Shvalb, N., Shoval, S. (2018). Dynamic model for pedestrian crossing in congested traffic based on probabilistic navigation function. Transportation Research Part C: Emerging Technologies 86, pp. 78-96.

- Short Summary of Abstract:

Pedestrians construct a virtual risk map that assigns the entire crossing area with probabilities for a collision with vehicles, and then select their actions based on their perceived probability for collision. A model is made which can serve as a standard tool in simulations for assessing accident risks in urban environments.

• Dominguez-Sanchez, A., Cazorla, M., Orts-Escolano, S. (2017). Pedestrian Movement Direction Recognition Using Convolutional Neural Networks. IEEE Transactions on Intelligent Transportation Systems 18(12),8006277, pp. 3540-3548.

- Short Summary of Abstract:

This paper focuses on deep learning techniques such as convolutional neural networks (CNN) to achieve a reliable detection of pedestrians moving in a particular direction. This link might be useful if we have to work with convolutional neural networks: http://cs231n.github.io/convolutional-networks/

• Deb, S., Strawderman, L., Carruth, D.W., (...), Smith, B., Garrison, T.M. (2017). Development and validation of a questionnaire to assess pedestrian receptivity toward fully autonomous vehicles. Transportation Research Part C: Emerging Technologies 84, pp. 178-195.

- Short Summary of Abstract:

This study analyzes pedestrian receptivity toward fully autonomous vehicles (FAVs) by developing and validating a pedestrian receptivity questionnaire for FAVs (PRQF).

• Kim, T., Han, W., Kim, H., Park, Y. (2017). Vulnerable road user protection through intuitive visual cue on smartphones. CarSys 2017 - Proceedings of the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular Systems and Services, co-located with MobiCom 2017 pp. 13-17.

- Short Summary of Abstract:

This paper discusses how the most distracted road user type, i.e., smartphone users, can use the Basic Safety Messages (BSMs) from nearby vehicles to notice approaching danger and take appropriate defensive actions.

• Dey, D., Martens, M., Eggen, B., Terken, J. (2017). The impact of vehicle appearance and vehicle behavior on pedestrian interaction with autonomous vehicles. AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Adjunct Proceedings pp. 158-162.

- Short Summary of Abstract:

In this paper, we present the preliminary results of a study that aims to investigate the role of an approaching vehicle's behavior and outer appearance in determining pedestrians' decisions while crossing a street.

• Dey, D., Terken, J. (2017). Pedestrian interaction with vehicles: Roles of explicit and implicit communication. AutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings pp. 109-113.

- Short Summary of Abstract:

This paper presents a study that aimed to identify the importance of eye contact and gestures between pedestrians and drivers.

Coaching Questions Group 16