AI-Based Vehicle Systems for Mobility-as-a-Service Application

Mikko Tarkiainen, Matti Kutila, Topi Miekkala, Sami Koskinen, Jokke Ruokolainen, Sami Dahlman, Jani Toiminen

Research output: Chapter in Book/Report/Conference proceedingChapter or book articleScientific

Abstract

Achieving sufficient safety measures is among the major challenges in developing automated vehicles that can operate safely in an urban environment. Data fusion between an in-vehicle camera and a LiDAR sensor can be used for detection and tracking of other road users in an automated vehicle. In addition, simulated environments together with high-level deterministic, supervised and reinforcement learning-based autonomous control could provide traffic safety benefits in the future. These AI-based technologies have been studied in the AI4DI project to enable the Mobility as a Service (MaaS) operators fleet management of automated vehicles. The development and testing of these methods are presented in this chapter with the first promising results. The Camera - LiDAR fusion algorithm provided very good results with the accuracy evaluation using the KITTI dataset.The real-time applicability of the fusion algorithm was also successfully verified.
Original languageEnglish
Title of host publicationArtificial Intelligence for Digitising Industry
PublisherRiver Publishers
Chapter5.1
Pages363-373
ISBN (Electronic)9788770226639
ISBN (Print)9788770226646
Publication statusPublished - 27 Sep 2021
MoE publication typeB2 Part of a book or another research book

Keywords

  • automated driving
  • sensor data fusion
  • 3D object detection and tracking
  • reinforcement learning
  • CNN
  • simulation

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