Maria Jokela

• Researcher at VTT Technical Research Centre of Finland

Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing princi...

This article aims to outline the key results of testing and encountered challenges of various LiDARs, radar and stereo camera in arctic weather conditions. The test session was conducted in two different urban areas in Finland in the middle of January 2019. The arctic conditions turned out to be challenging for the sensors dedicated more to areas w...

Level crossing is an interface between road and rail environments. It is obvious that in the future autonomous cars cannot avoid level crossings. So far, very little attention is put on investigating how autonomous car can pass level crossings and especially the unprotected ones. Today the vast amount of level crossings are still unprotected. This...

This study focuses on discussing and analysing the results of the project steering group maturity review executed at VTT in 2012 and 2013. The first survey was conducted for 50 projects whose complexity level varied between medium and high. One of the major outcomes of the study is the definition and role of the project owner in multi-national proj...

This paper suggest a new schema for improving accuracy of estimation of traffic CO2 emissions. The emission estimation is implemented as a part of novel traffic surveillance system which is movable and uses data fusion of several sensors and databases. The system is able to determine the emissions in real-time based on the traffic flow observed and...

Road friction measurement is an important issue for active safety systems on vehicles; hence knowledge of this key parameter can significantly improve the interventions on vehicle dynamics. This study compares two different on-board sensors for the classification of road conditions with polarised infrared light. Several tests are performed on a ded...

This paper presents a method and evaluation results to monitor and detect road conditions (ice, water, snow and dry asphalt). The developed device bases on light polarization changes when reflected from road surface. The recognition capability has been improved with texture analysis which estimates contrast content of an image. Test drives were per...

This paper presents experimental results regarding road condition monitoring by machine vision techniques. The system will be further developed by VTT in the European INTERSAFE-2 project, focused on applications at road intersections. Knowing the presence of adverse conditions such as icy or wet roads, important effects can be obtained for intersec...

Rouhiainen, Veikko (ed.), Scientific activities in Safety & Security 2009, 96-97

This paper describes the preliminary results for detecting slippery road conditions. The detector will be implemented in a larger system intended to increase the safety margin for vehicle drivers, by utilising so-called co-operative driving where infrastructure to vehicle communications operate seamlessly. The ice detection system is based on inten...

It has been shown that in most accidents the driver is responsible due to being distracted or misjudging the situation. In order to solve such problems research has been dedicated to developing driver assistance systems that are able to monitor the traffic situation around the vehicle. This paper presents methods for recognizing several circumstanc...

This article focuses on monitoring a driver's cognitive impairment due to talking to passengers or on a mobile phone, daydreaming, or just thinking about other than driving-related matters. This paper describes an investigation of cognitive distraction, firstly, giving an overall idea of its effects on the driver and, secondly, discussing the pract...

Driver assistance systems and electronics (e.g. navigators, cell phones, etc.) steal increasing amounts of driver attention. Therefore, the vehicle industry is striving to build a driving environment where input-output devices are smartly scheduled, allowing sufficient time for the driver to focus attention on the surrounding traffic. To enable a s...