Towards Autonomous Vehicles with Advanced Sensor Solutions

Matti Kutila, Pasi Pyykönen, Aarno Lybeck, Pirita Niemi, Erik Nordin

    Research output: Contribution to journalArticleScientificpeer-review


    Professional truck drivers are an essential part of transportation in keeping the global economy alive and commercial products moving. In order to increase productivity and improve safety, an increasing amount of automation is implemented in modern trucks. Transition to automated heavy good vehicles is intended to make trucks accident-free and, on the other hand, more comfortable to drive. This motivates the automotive industry to bring more embedded ICT into their vehicles in the future. An avenue towards autonomous vehicles requires robust environmental perception and driver monitoring technologies to be introduced. This is the main motivation behind the DESERVE project. This is the study of sensor technology trials in order to minimize blind spots around the truck and, on the other hand, keep the river's vigilance at a sufficiently high level. The outcomes are two innovative truck demonstrations: one R & D study for bringing equipment to production in the future and one implementation to the driver training vehicle. The earlier experiments include both driver monitoring technology which works at a 60% - 80% accuracy level and environment perception (stereo and thermal cameras) whose performance rates are 70% - 100%. The results are not sufficient for autonomous vehicles, but are a step forward, since they are in-line even if moved from the lab to real automotive implementations.
    Original languageEnglish
    Number of pages12
    JournalWorld Journal of Engineering and Technology
    Issue number3
    Publication statusPublished - 2015
    MoE publication typeA1 Journal article-refereed


    • autonomous driving
    • camera
    • driver monitoring
    • environment perception
    • automated vehicle
    • sensor
    • laser scanner
    • truck
    • radar
    • data fusion


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