TY  - JOUR
PY  - 2019//
TI  - A big testing framework for automated truck driving
JO  - Urban transportation and construction
A1  - Elgharbawy, Mohamed
SP  - e27
EP  - e27
VL  - 4
IS  - 1
N2  - Long-distance commercial vehicles are predestined for automated driving due to their high performance and long monotonous routes. Automation offers the prospect of improved road safety, increased fuel efficiency, optimised vehicle utilisation, higher driver productivity and lower freight costs. Even if the widespread use of full automation is not imminent, the vision of accident-free driving accelerates the further development of driver assistance functions to autonomous vehicle stages on the global market. Thestatus quo evaluation refers to large-scale verification as one of the decisive challenges for the economical, reliable and safe use of automated driving functions in truck series development. In this scheme, the evaluation of software releases must be carried outin different phases up to the Start of Production (SoP) to provide an argument that the residual risk is below an acceptable level. In driving simulator tests, various system concepts of a truck series are first evaluated. The verification and validation strategythen performs X-in-the-Loop tests, proving grounds and long-term endurance tests. Finally, homologation meets the market-specific type-approval requirements based on the evidence collected during development. This paper summarises previous works dealingwith the large-scale verification requirements and challenges of intelligent transportation systems. The basis of large-scale verification is presented, including the verification andvalidation procedures commonly used in large-scale verification schemes. The criteria of test completion are specified for assessing the performance of automated driving functions. The quality measures are presented to achieve sufficient reliability within thesoftware quality management process. The several possible topics for future research are identified.<p />  <p>Language: en</p>
LA  - en
SN  - 2424-8452
UR  - http://dx.doi.org/10.18686/utc.v0.27
ID  - ref1
ER  -