Systematic Literature Review on Automotive Diagnostics - Oliveira, Leonardo Presoto de; Wehrmeister, Marco Aurélio; Oliveira, André Schneider de (Anais do Simpósio Brasileiro de Engenharia de Sistemas Computacionais (SBESC), 2017)
Automotive diagnostics processes tend to progress along with the evolution of automotive technology, since with more systems embedded in a vehicle it becomes harder to coordinate all components in order for them to work harmoniously. Beyond the complexity of systems, it is also necessary to account for customer demand for vehicles that offer greater commodity and safety. This paper reviews the literature system, identifies the most common topics, the most used tools and approaches, the difficulties found in each tool, and the issues still pending in the field of automotive diagnostics. This information was obtained based on survey questions, and inclusion, exclusion, and rating criteria for quality requirements. Over 1000 article titles were reviewed in repositories and from those, 40 were kept for a more thorough review through the systematic review process. The methods most often used by articles are using the OBD to extract data on the vehicles, cellular interfacing and sending those data to an online server (internet connection). Voice recognition techniques are interesting as they decrease driver distractions, as they are not required to avert their eyes from the road in order to interact with the system. The issue to be explored is the lack of approaches to issues related to human-machine interfaces. In general, the papers are of a technical nature and discuss the quality of their models based on errors found during tests, without discussing the adaptability of their systems for driver use.