Pasi Pyykönen

Traffic monitoring and modeling for Intersection Safety

The INTERSAFE-2 project aims to develop and demonstrate a Cooperative Intersection Safety System that is able to significantly reduce injury and fatal accidents at intersections. The cooperative sensor data fusion is based on state-of-the-art and advanced on-board sensors for object recognition and relative localisation, a standard navigation map and information from other road users, infrastructure sensors and traffic lights. We created a traffic safety model for the INTERSAFE-2 system. The system incorporates a high level fusion module and local dynamic maps database that store static intersection topology. Furthermore, risk assessment from the infrastructure side has been performed in order to detect potentially dangerous situations, and to determine when the system should give a warning in order to prevent a possible collision. To evaluate the safety algorithm, video sequences of two intersections in Helsinki are used, which were processed with a generic tool for image processing and traffic monitoring.

IoT for intelligent traffic system

This paper suggests a new schema for applying the IoT (Internet of Things) to intelligent traffic systems. The intelligent traffic system is implemented using road side units (RSU) with friction monitoring, vehicles with environmental sensors and a database for data transfer through different platforms. The system is able to collect sensor data from stationary RSU stations or moving vehicles and store it to the database. The test results indicate that the developed IcOR friction monitoring unit is able to distinguish the different road weather categories (ice, snow, wet and dry asphalt) with sufficient accuracy. Communication is implemented using a V2I/I2V IEEE 802.11p communication between RSUs and vehicles or 3G/4G mobile connections. In this article, we describe an implemented IoT ITS concept with current real-life implementation and future plans.

Multi-camera-based smoke detection and traffic pollution analysis system

This article studies the smoke and exhaust detection system that has been developed for monitoring exhaust gases to enforce environmental laws and regulations. In many highly populated countries the HSU (Hart ridge Smoke Unit) grade is used to impose penalties. In many cases, HSU values over 40 ... 50 are leading to legal actions. This paper proposes a method that adopts two cameras, a far infrared camera and a high-resolution visible wavelength camera, as a detection system for smoky vehicle detection. The far infrared camera is used for detecting the location of the vehicle exhaust fumes. This thermal information is fused with visible spectrum information from the high-resolution camera. An algorithm evaluates if the identified vehicles are causing visible exhaust smoke. If smoke is detected, the system stores evidence for further actions. The first prototype version of the system needed an automatic adaptation procedure in order to calibrate far infrared and high-resolution images together. Mechanically, the system can be set up quickly in the chosen roadside location. A developed prototype system is one step towards future tools for authorities to automatically detect and classify vehicles emitting smoke. If a permanent set-up is desired, the system can be installed on a lamp post, beneath an overhead bridge or on other similar structures.

Automotive LIDAR sensor development scenarios for harsh weather conditions

This article focuses on development baseline for a novel LIDAR for future autonomous cars, which require perception not only in clear weather, but also under harsh weather conditions such as fog and rain. Development of automotive laser scanners is bound to the following requirements: maximize sensor performance, assess the performance level and keep the scanner component costs reasonable (<;1000 €) even if more expensive optical and electronic components are needed. The objective of this article is to review the existing automotive laser scanners and their capabilities to pave the way for developing new scanner prototypes, which are more capable in harsh weather conditions. Testing of scanner capabilities has been conducted in the northern part of the Finland, at Sodankylä Airport, where fog creates a special problem. The scanner has been installed in the airport area for data gathering and analyzes if fog, snow or rain are visible in the scanner data. The results indicate that these conditions degrade sensor performance by 25%, and therefore, future work in software module development should take this into account with in-vehicle system performance estimations concerning the visual range of the scanner. This allows the vehicle to adapt speed, braking distance and stability control systems accordingly.

Active infrared illumination in fog for driver assistance

We report preliminary results on the use of a far infrared emitting quantum cascade laser for active illumination in foggy conditions. The applications would be e.g. in cooperative driving and improvement of visibility for car drivers in adverse road weather conditions. It has long been known that the infrared wavelengths in the thermal band of 9 - 13μm allow better visibility in foggy conditions, compared to near infrared or visible bands. Therefore already thermal cameras have been installed in cars, with dashboard displays, in order to improve safe driving. However, these units are only utilising the emittance of the targets themselves, without the possibility of active illumination. This is because until recent years, no practical solid state laser illuminators have been available for the purpose. Recent increase of availability and powers of quantum cascade or distributed feedback lasers has changed the situation. We show some preliminary results on the use of a high peak power, pulsed quantum cascade diode laser in an experimental fog chamber for active illumination, viewed with a compound semiconductor, direct bandgap infrared camera.

The DESERVE project: Towards future ADAS functions

This article introduces the objectives and structure of the European research project DESERVE that is co-funded by the ARTEMIS-JU and national funding bodies. The project started in September 2012 with a duration of 3 years. The project aims to establish a new embedded SW and HW design by using a more efficient development process (including the enabling general platform concept and tool chain) in order to overcome challenges in reducing component costs and development time of future ADAS functions for modern vehicles. Both the process and the platform concept will be demonstrated with innovative ADAS functions in 3 passenger cars, 1 truck and 1 motorcycle. Embedded hardware and software units have been developed for improving electronic horizon band of vehicles by detecting objects in front. Moreover, driver/motorcycle rider awareness is analysed by monitoring his/her actions online. The systems need to be robust and reliable in different environment conditions (night time, rain, etc.). The DESERVE platform distinguishes three layers of intelligence: perception, application and intervention&warning control. The demonstrators will be based on software development tools from Elektrobit (ADTF) and Intempora (RTmaps). These tools are used to create 10 innovative ADAS applications as part of an integral ADAS development platform, following a new design and development process. Since the project is highly application oriented, the requirements have been adapted mainly from the ISO 26262 standard and the AUTOSAR framework which ensures compatibility with the existing automotive software environment.

In-vehicle sensor data fusion for road friction monitoring

This study presents the in-vehicle road friction estimation module to provide information for the driver to adapt his/her driving style. Our main aim is to enable support for saving fuel, minimising ecological impact and improving traffic safety. The module is based on the IcOR camera system developed by VTT which has been combined with inertia unit. Moreover, GPS receiver has been implemented to provide geographical position of the vehicle which is important for the infrastructure side of cooperative traffic services. The test results indicate clear correlation with the lateral accelerations and IcOR road state measures. The most important outcome is the chance to reduce number of false alarms of the IcOR system with acceleration based measurement. Moreover, the benefit of the acceleration data is the possibility to maintain the detection reliability of IcOR system in level of 70 % when driving in dark environment such as tunnels or night time.

A machine vision based working traffic emission estimation and surveillance schema

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 this provides advantages over the current methods. The emissions are often approximated by using estimates of average traffic flow and emission rates but this produces very unreliable results. Another way is to use gas sensors but they are expensive and provide only point measurement data. In this paper, we show the feasibility of the novel schema.

Cooperative Intersection Infrastructure Monitoring System

This article proposes an advanced roadside monitoring sub-system for future cooperative intersection infrastructure. The sub-system consists of the camera for road condition monitoring, traffic light controller, Laserscanners, local dynamic maps database and V2I communication module. These components are interfaced to the high level fusion platform which is intended extract information and enable risk assessment if the situation is turning safety critical. The system is part of the European INTERSAFE-2 project which focuses on introducing cooperative traffic safety in intersection environment. Approximately every third of traffic incidences are intersection related. The project is expected emerge technology to influence beneficiary in 80% of the intersection related accidents with injuries and fatalities.

Spectral attenuation in low visibility artificial fog: Experimental study and comparison to literature models

The ECSEL joint undertaking RobustSENSE focuses on technologies and solutions for automated driving in adverse weather conditions. One of the main technology challenges is to improve laser scanner performance in fog where the existing 905 nm LIDAR reliability degrades below tolerances. This report briefly summarizes the results of experimental fog absorbance measurements, which were conducted in test laboratories located in VTTs premises. The content of the presentation will focus on spectral absorbance at low visibility artificial fog in near infrared band.