Adaptive Cruise Control (ACC), which is a smart combination of pre-existing cruise control and time gap control, plays a major role in rendering driving comfort for the
drivers. Currently available ACC system allows the vehicle to maintain the set speed and to automatically adjust the speed to keep up the fixed distance to the vehicle
ahead. Here, the speed and the distance are set as per user preferences. Each individual user has their own perceptions and preferences but the existing ACC system
lacks the property of user adaption. Hence, this thesis focuses on automatizing the distance settings of the ACC system, which can be adapted to each individual users.
In order to incorporate the property of user specific distance setting for ACC, the most relevant contexts in which a change in ACC distance needed is sorted out and
a standard distance setting is assigned. Reinforcement-Learning strategies are handled where by the pre-existing distance settings can be modified and adapted to the
user once they start driving.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79006 |
| Date | 29 April 2022 |
| Creators | Joganantham, Rubina |
| Contributors | Hardt, Wolfram, Hänchen, Felix, Schlicht, Peter, Schneider, Jens, Technische Universität Chemnitz |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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