This thesis was carried out at Scania CV AB, at the cab software testing group, RCIV. One of RCIV’s responsibilities includes testing of the instrument cluster used in Scania’s heavy trucks and buses. Today, this is done semi-automated. The tests are executed automatically in Vector’s CANoe software but are verified manually by a tester who needs to observe the instrument cluster. We have investigated the possibility to automate this testing procedure with the use of a camera based vision system and have studied different solutions available on today’s market. We studied five company’s solutions for a complete, or partial, automated test environment solutions as well as the possibility to have Scania develop a system of their own. The pros and cons we have found along with the cost of the systems are listed in this report. We also built a prototype with one of the image processing software alternatives. Our investigation showed that an automated test environment with a camera based vision system could be very beneficial for RCIV and could support much of the current testing but the system must be fully verified before replacing today’s semi-automated tests.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-70119 |
Date | January 2011 |
Creators | Molin, Linus, Mucchiano, Gabriel |
Publisher | Linköpings universitet, Institutionen för datavetenskap, Linköpings universitet, Institutionen för datavetenskap |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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