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  3. Monitoring localization safety will be necessary to certify the performance of robots that operate in life-critical applications, such as autonomous passenger vehicles or delivery drones because many current localization safety methods do not account for the risk of undetected sensor faults. One type of fault, misassociation, occurs when a feature extracted from a mapped landmark is associated to a non-corresponding landmark and is a common source of error in feature-based navigation applications. This paper accounts for the probability of misassociation when quantifying landmark-based mobile robot localization safety for fixed-lag smoothing estimators. We derive a mobile robot localization safety bound and evaluate it using simulations and experimental data in an urban environment. Results show that localization safety suffers when landmark density is relatively low such that there are not enough landmarks to adequately localize and when landmark density is relatively high because of the high risk of feature misassociation. 
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  4. This research project aims to achieve a future urban environment where people and self-driving cars coexist together while guaranteeing safety. To modify the environment, our first approach is to understand the limitations of GPS/GNSS positioning in an urban area where signal blockages and reflections make positioning difficult. For the evaluation process, we assume reasonable integrity requirements and calculate navigation availability along a sample Chicago urban corridor (State Street). We reject all non-line-of-sight (NLOS) that are blocked and reflected using a 3-D map. The availability of GPS-only positioning is determined to be less than 10% at most locations. Using four full GNSS constellations, availability improves significantly but is still lower than 80 % at certain points. The results establish the need for integration with other navigation sensors, such as inertial navigation systems (INS) and Lidar, to ensure integrity. The analysis methods introduced will form the basis to determine performance requirements for these additional sensors. 
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