An approach to analyzing adaptive intelligent vehicle system using SMT solver

Self-adaptive intelligent vehicle system has become more attractive due to its capability of adaptation to varying and stochastic environments in an efficient and autonomous manner. The dynamic demeanor in adaptation and reconfiguration of intelligent vehicle systems will facilitate the existing federal and civil construction in better planning as well as in abbreviating the huge amount of budget of government and will ameliorate and impoverish the day to day lifestyle of mass generation with enhanced efficiency in green-energy oriented transportation systems. However, such systems may be prone to runtime failures when the overall environmental dynamics as well as the required parameters cannot be adequately considered during design time. In this project, we have examined and investigated the typical safety critical issues using SMT solver on a speed synchronization racing car example in both design and implementation level. In the design level, a Petri Net model is adopted as the high level abstraction of the racing car. In the implementation level, the system was developed in Java and Lejos package since the application toolkit is LEGO mindstorm EV3 robotic kit. In addition to this, both a set of safety properties and Petri Net model was rewritten in Z3 specification, where the safety properties are verified against the system model. The observed results of the specified properties have demonstrated that all required system constraints for hardware and firmware were analyzed and verified on an optimized version of Petri Net model of the system. This is the first time, from our literature review, to see the validation of the both design and implementation level using SMT Solver. Furthermore, this result has provided strong and rigid foundation for the runtime verification of cyber physical systems.