Abstract. In this paper, we propose a traffic management system with agents acting on behalf autonomous vehicle at the crossroads. Alternatively to existing solutions based on usage of semiautonomous control systems with the control unit, proposed in this paper algorithm apply the principles of decentralized multi-agent control. Agents during their collaboration generate intersection plan and determinate the optimal order of road intersection for a given criterion based on the exchange of information about them and their environment. The paper contains optimization criteria for possible routes selection and experiments that perform in order to estimate the proposed model. Experiment results show that this model can significantly reduce traffic density compared to the traditional traffic management systems. Moreover, the proposed algorithm efficiency increases with road traffic density. Furthermore, the availability of control unit in the system significantly reduces the negative impact of possible failures and hacker attacks.

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In this paper, we set forth a new longitudinal corpus and a toolset in an effort to address the influence of voice-aging on speaker verification. We have examined previous longitudinal research of agerelated voice changes as well as its applicability to real world use cases. Our findings reveal that scientists have treated agerelated voice changes as a hindrance instead of leveraging it to the advantage of the identity validator. Additionally, we found a significant dearth of publicly available corpora related to both the time span of and the number of participants in audio recordings. We also identified a significant bias toward the development of speaker recognition technologies applicable to government surveillance systems compared to speaker verification systems used in civilian IT security systems. To solve the aforementioned issues, we built an open project with the largest publicly available longitudinal speaker database, which includes 229 speakers with an average talking time exceeding 15 hours spanning across an average of 21 years per speaker. We assembled, cleaned, and normalized audio recordings and developed software tools for speech features extractions, all of which we are releasing to the public domain.