Safety System Assessment Case Study of Automated Vehicle Shuttle

Abstract

Automated vehicle (AV) minibuses, i.e., AV shuttles, are gaining popularity in the testing of new types of transportation services in real traffic conditions. AV shuttles have moved from closed test areas to low-traffic public sites such as local residential areas, technology parks, university campuses, etc. These types of vehicles are usually low-speed and rely on a lidar-camera sensor set and a self-driving software stack. These new use cases are increasing these systems’ safety demands. In addition to functional safety, many other aspects need to be considered. In this study, a risk analysis model is developed, combining the fuzzy analytical hierarchy process and the Technique for Order of Preference by Similarity to Ideal Solution method. The proposed model is utilized to prioritize risks corresponding to the particular case study, based on real AV shuttle bus development, and focuses on the low-level hardware/software safety issues and improvements.

Towards Trustworthy Safety Assessment by Providing Expert and Tool-Based XMECA Techniques

“…[34], FMECA and its modification play an essential role in increasing reliability and safety, but they still undoubtedly have drawbacks regarding risk evaluation and uncertainties. A multicriteria decision-making risk evaluation model, as well as a prioritization of risks, may be used to simplify decision-makers' judgments and to handle uncertainty caused by these judgments [35]. Using security analysis results as a factor in increasing or decreasing the risk level could affect the introduced uncertainty of probabilistic model parameters [36].…”

“…Besides, the efficiency of the AXMEA tool application can be assessed by the expert involvement indicator presented in Refs. [49,50]: EID (expert involvement degree) is evaluated as the number of operations that are performed by expert(s) divided by the total number of operations: EID = NOE/TNO (34) EUD (expert uncertainty degree) is evaluated as number of operations with uncertainty that are performed by expert(s) divided by number of operations that are performed by expert(s): EUD = NUE/NOE (35) ETD (expert trustworthiness (certainty) degree) is evaluated using following expression:…”

A comparative analysis of Fuzzy AHP and Fuzzy VIKOR methods for prioritization of the risk criteria of an autonomous vehicle system

“…The autonomous vehicle known as the AV shuttle, which was developed by Astrov et al [25], Sell and Petritsenko [26], and Rassõlkin et al [27], serves as the case study for this investigation. Pikner et al [28,29] provide a detailed introduction to the criteria and risks of such a vehicle. In particular, [29] examines the risk analysis of this model by combining Fuzzy AHP with TOPSIS.…”

“…Pikner et al [28,29] provide a detailed introduction to the criteria and risks of such a vehicle. In particular, [29] examines the risk analysis of this model by combining Fuzzy AHP with TOPSIS.…”

Experimental Study Regarding Long Range LiDAR Capabilities in Sensing Safety Distance for Vehicle Application

“…One goal of driving automation is increasing traffic fluency while maintaining high safety. Regarding safety, most of the work is performed in developing autonomous vehicles based on several methods such as supervising the surrounding area for detection of imminent collision [ 1 ], precise location on map to define optimal route [ 2 ], automated interaction between cars for route optimization, and for automated braking system using time-to-contact detection [ 3 ].…”