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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bodenheimer, Robert Brauer, Alexej Eckhoff, David German, Reinhard |
| Copyright Year | 2014 |
| Description | Author affiliation: Computer Networks and Communication Systems, Dept. of Computer Science, University of Erlangen, Germany (Eckhoff, David; German, Reinhard) || AUDI AG, Germany (Bodenheimer, Robert) || Technische Universität München, Germany (Brauer, Alexej) |
| Abstract | Green Light Optimized Speed Advisory (GLOSA) systems aim at giving ideal target speed recommendations to the driver when approaching a traffic light to lower CO2 emissions (and fuel consumption) and to reduce the number of unnecessary stops. These systems have been shown to work well with static traffic light programs, unfortunately, a large portion of traffic lights in inner cities are adaptive and can change their behaviour with almost no lead time. This paper presents and validates (using field tests and simulation) a method to help overcome this problem and forecast fully and semi-adaptive traffic lights. First, we transformed the state graph of the traffic light controller into a transition graph focusing on signal changes and their occurrence probability. We then reduced routing possibilities within the graph using real life observations and recorded detector data of the traffic light. We further optimized our system in terms of needed storage and computationally efficiency. Our results show that in 80% of all cases we could predict signal changes 15s in the future with a high enough accuracy to enable GLOSA for adaptive traffic lights. |
| Starting Page | 167 |
| Ending Page | 174 |
| File Size | 236430 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781479976607 |
| ISSN | 21579865 |
| DOI | 10.1109/VNC.2014.7013336 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-12-03 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Conferences Detectors Probability Cities and towns Prognostics and health management Equations Vehicles |
| Content Type | Text |
| Resource Type | Article |
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