Data Science and Machine Learning are playing a key role in our everyday lives, as is evident from its applications, such as voice recognition features in vehicles and on cell phones, automatic facial and traffic sign recognition etc. Analysing big data on the basis of searches, pattern recognition and learning algorithms provides deep understanding of the behaviour of processes, systems, nature, and ultimately the people. The already implementable idea of autonomous driving is nearly a reality for many drivers today with the help of lane keeping assistance and adaptive cruise control systems in the vehicle. The drift towards connected, autonomous, and artificially intelligent systems that constantly learns from the big data and is able to make best suited decisions is advancing in ways that are fundamentally important to many automotive industries. The paper envisages the future of connected-autonomous-urban-airtaxi (CUTs) as computers on wheels. These are pictured as sophisticated systems with on-board sensors as data sources and a lot of other functions and services running to support autonomous aerial driving/flying. These services are considered to be computationally expensive. The on-board computation unit has limited computing resources. On the other hand, the cloud-based architecture has unconstrained resources but it suffers from unexpected extended latency that leads to the large-scale Internet data transmission. To deal with this dilemma, Open Vehicular Data Analytics Platform (OpenVDAP) for CUTs may be used. This allows CUTs to dynamically detect status of each service, computation overhead and the optimal offloading destination so that each service could be finished within an acceptable latency. OpenVDAP is an open-source platform that offers free APIs and real-field aerial vehicle data to the researchers and developers in the community, allowing them to deploy and evaluate applications on the real environment.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Autonomous Connected Aerial Vehicles: Overview of Application of Open Source Vehicular Data Analytics Platform to Urban Air Taxi




    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Overcoming Challenges in Connected Autonomous Vehicles Development: Open Source Vehicular Data Analytics Platform

    Gupta, Himanshu / Krishna, Shreya / CUCEK-CUSAT et al. | SAE Technical Papers | 2019


    Exploiting Taxi Demand Hotspots Based on Vehicular Big Data Analytics

    Zhang, Lu / Chen, Cailian / Wang, Yiyin et al. | IEEE | 2016


    Using Autonomous Vehicles in a Taxi Service

    RAMANUJAM MADHUSOODHAN | Europäisches Patentamt | 2015

    Freier Zugriff

    Using autonomous vehicles in a taxi service

    RAMANUJAM MADHUSOODHAN | Europäisches Patentamt | 2017

    Freier Zugriff