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Kortdistansradar för ACC-system
Linköping University, Department of Science and Technology.
2008 (Swedish)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesisAlternative title
Short Range Radar for ACC-systems (English)
Abstract [sv]

I denna rapport redogörs för en implementering av fusion mellan kortdistanssensorer. Syftet med denna implementering är att erhålla Stop & Go-funktionalitet till den adaptiva farthållaren som idag finns som tillval i Scanias lastbilar. Adaptiv farthållning, ACC, är en funktion som automatiskt anpassar fordonets hastighet ifall detta kommer ikapp ett annat fordon som färdas långsammare än den inställda hastigheten. Scanias system använder sig idag av en långdistanssensor som ser långt men har smalt synfält. Genom att komplettera denna med kortdistanssensorer, som ser kort men brett, kan önskvärt synfält i närområdet för att säkert kunna implementera Stop & Go-funktionen uppnås. Sensorfusion bygger på principen att två eller fler sensorer som ser samma sak ger en mer korrekt bild av verkligheten än en enskild. Fusionen kan genomföras på många olika sätt. I rapporten beskrivs tre metoder övergripligt; Bayesiska nätverk, auktionsalgoritmen samt Gating. I implementeringen används gatingmetoden.

Initialt implementeras en målspårningsalgoritm med kalmanfilter. Efter uppdatering av sensormjukvaran väljs dock denna bort eftersom sensorernas interna målspårning då anses som tillräcklig. En modell med sensorfusionen och målselekteringen byggs i Simulink och programmeras sedan in i en hårdvaruenhet. Syftet med detta är att kunna utvärdera funktionen i ett prototypfordon. Inledningsvis rapporteras enbart korrelerade mål från modellen. För mer kontinuerlig målföljning, främst i kurvor, implementeras därefter en algoritm som även tar hänsyn till enskilda sensorers observationer. Dessa accpeteras dock först efter en viss valideringstid eftersom denna information har lägre konfidens än korrelerade mål.

Provkörningar visar att målföljningen fungerar väl. En stor svårighet har varit att sålla bort stillastående mål från rörliga, främst i låga farter. Detta eftersom sensorernas hastighetsangivelse har låg precision vilket medför att ett stillastående mål kan rapporteras som ett långsamt rörligt.

Abstract [en]

In this thesis report an implementation of fusion between short range radars is described. The purpose of this implementation is to obtain Stop & Go functionality for the adaptive cruise control which is offered as an option in today’s Scania trucks. Adaptive cruise control, ACC, is a feature that automatically adapts the vehicle speed if it should catch up to another vehicle moving slower than the desired set speed. For this application Scania today use a long range sensor that has a long but narrow field of view. By complementing this sensor with short range sensors, which have short but wide fields of view, the desired field of view in the short range area can be obtained. This is necessary in order to be able to safely implement the Stop & Go functionality. Sensor fusion is based on the principle that two or more sensors overlooking the same area give a more accurate impression of reality than a single one. The fusion can be conducted in several ways. In the report three different methods are briefly described; Bayesian Networks, the Auction Algorithm and Gating. In the implementation the gating method is applied.

Initially a target tracking algorithm using Kalman filter is implemented. However, after software updates in the short range sensors this algorithm is no longer used. This is because the improved tracking made internally by the sensors is considered to be sufficient, hence making an external tracking algorithm redundant. The sensor fusion and the target selection are implemented in a Simulink model which is later programmed into a hardware unit. The purpose of the latter is to be able to evaluate the functionality in a prototype vehicle. Initially, only associated targets are reported from the model. In order to obtain a more continuous target tracking, mainly while driving in curves, observations made only by single sensors are also considered. However, these measurements have lower level of confidence than the associated targets. Therefore these measurements first have to be validated for a certain period of time before they are approved.

Test runs indicate that the target tracking works as intended. One major difficulty has been to separate stationary targets from slow moving ones, especially in low speeds. This is due to the fact that the sensors’ speed measurements are fairly inaccurate. Therefore a stationary target could be reported as a slow moving one.

Place, publisher, year, edition, pages
2008. , 41 p.
Keyword [sv]
kortdistansradar, sensorfusion, adaptiv farthållare, Stop & Go
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-11290ISRN: LiU-ITN-TEK-A--08/008--SEOAI: oai:DiVA.org:liu-11290DiVA: diva2:25048
Subject / course
Master of Science in Electronics Design Engineering
Presentation
2008-02-08, 13:15
Uppsok
Technology
Supervisors
Examiners
Available from: 2008-09-25 Created: 2008-09-25 Last updated: 2012-04-24Bibliographically approved

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