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Planning and Management of Connected and Autonomous Vehicles (CAVs) Implementation for Dense Event

Zaheer Ahmed

Planning and Management of Connected and Autonomous Vehicles (CAVs) Implementation for Dense Event.

Rel. Giovanni Belingardi. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2021

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CAVs are a subject of enormous interest internationally, as transportation agencies and cities try to understand what the future holds when deploying these vehicles widely. They provide many benefits not just to the automotive sector but also to the urban landscape and society. Pilot projects of CAV deployments for mass transit have shown that these vehicles, being equipped with autonomy and connectivity, can improve safety, efficiency, mobility, productivity, and fuel consumption. For the adaptation of CAVs for dense events, it is vital to assess first the impacts of such deployment in the safety, environment, and health sector so that their inevitable deployment is as smooth and advantageous as possible. The scope of this thesis was to model a CAV application in a dense event, selected as FIFA-2022 Lusail, Qatar. The primary aspect of the study comprises deploying CAVs in the selected event providing a suitable service model ensuring mobility demand, population density distribution, location profile, and road network. Different scenarios based on demand data set simulated and critical performance measures assessed to validate network performances. The selected deployment service effectively addresses the criteria for heterogeneous traffic, emissions from more driving, and on-street congestion that may result in the case of a dense event. Finally, a case study developed considering CAV deployment as a business case, considering the two main stakeholders, city management and CAV deployment company.

Relators: Giovanni Belingardi
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 91
Corso di laurea: Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo)
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Aziende collaboratrici: University of Ontario, Istitute of Tech.
URI: http://webthesis.biblio.polito.it/id/eprint/18874
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