Picture this: it\u2019s 2030. You\u2019re sitting in your self-driving car on a wide road. While minding your own business, the car – programmed to bring you to your destination without any interaction on your part – wants to turn left into a narrow road. However, you\u2019re stuck: the narrow road is blocked by a car that is waiting for you, as you have right of way. In a fully automated world, with no humans ready to intervene, this would be a possibly unending impasse. \u201cI\u2019ve always been fascinated by cars, making sketches of them as a child, but I\u2019d never expected that working with cars would one day be a full-time job. One of the reasons that I decided to get involved in this field is a car accident I had some eight years ago, when I was working in the US as a software engineer. A car crashed into me at a T-junction. Although I suffered only slight injuries, the incident had a deep effect on me. Not only was I afraid to drive for some time, I also found out that the other driver had been distracted by his satnav. This kindled a deep interest in me for the interaction between humans and cars.\u201d Up till a few years ago most researchers in smart mobility were primarily interested in the interaction between drivers, or between car and driver. Dey and his colleagues in the NWO funded iCAVE<\/a> program, on the other hand, focus on situations where the driver is no longer in control, and the person in the car no longer represents the intention of the car.<\/p>\n\n\n\n \u201cOf course, we are some way from a situation where automated cars can do most of the driving (known as levels 3, 4 and 5 of car automation<\/a>), but we believe that eHMIs can play a crucial role in getting there. Once autonomous cars are able to automatically and effectively signal their intentions to other road users, drivers can finally sit back and fully enjoy the benefits of autonomous driving.\u201d<\/p>\n\n\n\n A good example of Dey\u2019s research, is the award-winning research<\/a> he and his colleagues did into distance-dependent eHMIs. \u201cHere we looked at the way people interact with a car when it approaches. From eye-tracking tests we did, we observed that people tend to look at a car not necessarily to make eye contact with the driver, but to assess its intentions.\u201d<\/p>\n\n\n\n \u201cAs a car approaches, they first look at a car\u2019s bumper, then move up to the grill and the hood, and finally on the windshield, looking for information about the situational awareness or intention of the driver. This inspired us to design an interface that dynamically communicates the car\u2019s intentions through lights on the bumper and the windshield, depending how far it is away from the pedestrian\u201d.<\/p>\n\n\n\n As we speak, Dey is involved in exciting new research that looks into using more abstract animal-based signals to communicate intention. \u201cWhen a cat or a hedgehog is angry, or aggressive, it puffs up, or makes itself bigger. Animal behavior like this shows the way to a more nuanced interactive language, that goes beyond directive symbols like stop signs, or text, that may be not visible or understandable to everyone.\u201d<\/p>\n\n\n\n Based on an inventory<\/a> Dey and his colleagues recently did of the research field, there are currently some 70 eHMI concepts for automated vehicles. They range from displaying text messages on external displays, over laser projections on the street, to personalized messages for smart and wearable devices. Often, these concepts are limited to demonstrations for promotion purposes, proof-of-concept prototypes, or purely virtual solutions. Standardization is one of the main challenges of eHMIs for self-driving cars. Automated cars will only be able to express themselves, if they speak a language that is understood by all other road users. It is one of the reasons why Dey\u2019s supervisor at TU\/e, professor Marieke Martens<\/a>, is actively involved with industry to develop common standards.<\/p>\n\n\n\n Standardization will also help acceptance of eHMI-equipped cars by the public. Dey sees this as one of the main goals of his work. There appears to be quite some hesitation and mistrust in the public perception of driving automation technology. Early protoypes of automated vehicles on the road have been met with skepticism<\/a>, and even antipathy \u2013 with some people even throwing stones<\/a> at the cars.<\/p>\n\n\n\n \u201cUp till now, experiments with self-driving cars have met with quite some pushback from other road users, with some people even throwing stones at them. It shows that people need to understand a new technology before they can accept it. I believe an effective eHMI that is clear and understandable can help in this.\u201d<\/p>\n\n\n\n
Fortunately, there are so-called external Human-Machine Interfaces<\/em> coming our way that use light, sound or any other means to indicate to the other road user that they can go first. Impasse solved!
eHMIs, as they are called in the world of smart mobility, are part of a relatively new and exciting research field that helps automated vehicles negotiate the outside world. One of the researchers involved in this field is Indian-born Debargha Dey<\/a>, part of the Future Everyday group in the department of Industrial Design. Dey, who is just about to finish his PhD and will continue to stay on as a post doc at TU\/e, has a very personal motivation for his involvement in this field.<\/p>\n\n\n\nCAR CRASH<\/h5>\n\n\n\n
\u201cAfter attending a conference on Automotive UI, I decided to apply for a PDEng<\/a> research position here at TU\/e with professor Jacques Terken<\/a> and I never looked back. It was one of the best decisions of my life!\u201d<\/p>\n\n\n\n![\"Technischen](\"https:\/\/www.sonnenseite.com\/wp-content\/uploads\/2020\/10\/TUE_Eindhoven_AutonomeAutosSprache2.jpg\")
Understanding the self-driving car<\/h5>\n\n\n\n
Bumper lights and more<\/h5>\n\n\n\n
Proof-of-concept<\/h5>\n\n\n\n
One of the few eHMI concepts that has gone beyond the drawing board, is Drive.ai, a small company founded in 2015 by students at Stanford University and now owned by Apple. As a pilot, in 2018 it tested a fleet of brightly colored self-driving vans<\/a> that use four external screens to communicate messages to other road users. Another example is Volvo\u2019s 360c<\/a> concept, that includes a standardized communication system enabling other road users and autonomous vehicles to understand what it will do next.<\/p>\n\n\n\nChallenges<\/h5>\n\n\n\n