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Riener A.,Institute for Pervasive Computing | Zia K.,Institute for Pervasive Computing | Ferscha A.,Institute for Pervasive Computing | Ruiz Beltran C.,Sociedad Iberica de Construcciones Electricas SICE | Minguez Rubio J.J.,Sociedad Iberica de Construcciones Electricas SICE
Personal and Ubiquitous Computing | Year: 2013

Steering a vehicle is a task increasingly challenging the driver in terms of mental resources. Reasons for this include the increasing volume of road traffic and a rising quantity of road signs, traffic lights, and other distractions at the roadside (such as billboards), to name a few. The application of Advanced Driver Assistance Systems, in particular if taking advantage of Ambient Intelligence (AmI) technology, can help to increase the perceptivity of a driver, leading as a direct consequence to more relaxed mental stress of the same. One situation where we see potential in the application of such a system are merging areas on the expressway where two or more varying traffic streams converge into a single one. In order to reduce cognitive liabilities (in this work expressed as panic or anger), drivers are exposed to while merging, we have developed two behavioral rules. The first ("increased range of perception") enables drivers to change early upstream into a spare lane, allowing the merging traffic to join into mainline traffic at reduced conflicts, the second ("inter-car distance management" in the broader area of merging) provide drivers with recommendations of when and how to change lanes at the best. From a technical point of view, the "VibraSeat" a in-house developed car seat with integrated tactile actuators, is used for delivering information about perception range and inter-car distances to the driver in a way that does not stress his/her mental capabilities. To figure out possible improvements in its application in real traffic and at a meaningful scale, cellular automaton-based simulation of a specific section of Madrid expressway M30 was performed. Results from the data-driven simulation experiments on the true to scale model indicate that AmI technology has the potential to increase road throughput or average driving speed and furthermore to decrease the panic of drivers while merging into an upper (the main) lane. © 2012 Springer-Verlag London Limited.

Riener A.,Johannes Kepler University | Fullerton M.,TU Munich | Maag C.,University of Würzburg | Mark C.,University of Würzburg | And 3 more authors.
IEEE Transactions on Human-Machine Systems | Year: 2014

In this letter, we detail a modular approach for measuring the secondary physical and emotional effects of ambient intelligence (AmI) technology in traffic. Using the case of merges on to a highway, we assess the results of a system that advises the driver to change early to a lane on the left to create space for merging cars downstream (tested using a cellular automata simulation). The indirect impact of the system downstream, namely how the remaining lane changes from the merge lane to the innermost lane proceed, is then evaluated using a time-discrete, space-continuous microscopic traffic simulation tool. This yields detailed results concerning driver interactions that can also be used to derive an estimate of driver anger in the situation. We have used real geographic, traffic and psychological data to test the system, and different models are used to accomplish various tasks. The approach yields (surprisingly) negative results concerning the indirect emotional impact of this AmI intervention which may be due to the nature of the lane changing model used and the chosen parameters. We argue that such an approach is also applicable to similar types of systems, where different data and model types are suited to different scenario elements. © 2013 IEEE.

Riener A.,Institute for Pervasive Computing | Zia K.,Institute for Pervasive Computing | Ferscha A.,Institute for Pervasive Computing | Ruiz C.B.,Sociedad Iberica de Construcciones Electricas SICE | Rubio J.J.M.,Sociedad Iberica de Construcciones Electricas SICE
Proceedings - IEEE International Symposium on Distributed Simulation and Real-Time Applications, DS-RT | Year: 2010

A considerable increase in road traffic has provoked a total change in the operating paradigms of vehicles, shifting vehicle handling from "just steering" towards a complex adaptation task. With the emergence of wireless communication technology, vehicle operation can now incorporate for the first time ever beside the local driver-vehicle interaction also more significant information obtained from cars in the surrounding. With this foundation it would be possible to build collectively operating driver assistance systems, negotiating the interests of all road participants in a certain area with the final goal to improve global parameters such as road throughput or traffic fluidity, also having an effect on the individual car (driver), e. g. increased travel speed, less congestions, or a reduced level of cognitive load. The question addressed with this paper is whether or not the vehicle speed can be sustained while merging onto a motorway, leading to a more harmonious integration of the merging cars into the flowing traffic on the main road. To achieve this we propose the application of ambient intelligence (AmI) technology operating on the collective behavior of all cars in the periphery of the entrance ramp. To prove our hypothesis we applied the AmI technology to a data driven, true to scale simulation model of the Madrid motorway M30, one of the most busiest roads in Spain. The comparison of simulation runs with high volume of traffic showed that technology assistance could help to increase road throughput and minimize the variance of traffic flow, but on the other side demands solutions for one of the bigger problems of data driven simulation - missing or noisy data compromising simulation results. © 2010 IEEE.

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