Submitted: August 2019
Since 2014, millions of cars have been found to be equipped with tampered emission cleaning systems that are optimized for the official type approval process of cars and reduce the effectiveness of emission cleaning on the road. This diesel emissions scandal has shown that the emission tests at that time were not sufficient to evaluate real-world behavior and emissions of diesel cars. Therefore, the European Union recently defined a new testing procedure for Real Driving Emissions (RDE). The standard approach to execute RDE tests involves Portable Emissions Measurement Systems (PEMS). This is expensive and can not be done on a large scale. To make testing for Real Driving Emissions cheaper, Köhl et al. have recently formalized the RDE test procedure1 and presented a low cost variant of the test. However, to get statistically relevant results more driving data is necessary. This thesis presents an Android application that is able to crowdsource real world driving data of diesel cars. The needed equipment is cheap and usage is simple, so it is possible to deploy it on a large scale. To gather the necessary driving data, the app accesses the car’s diagnostics interface over bluetooth. Additionally, sophisticated mechanisms are provided to define what data should be tracked.
M. A. Köhl, H. Hermanns, and S. Biewer, “Efficient Monitoring of Real Driving Emissions,” in Proceedings. Lecture Notes in Computer Science, vol. 11237. Springer International Publishing, 2018. ↩