Predictive Braking With Brake Light Detection-Field Test

Driver assistance systems, such as adaptive cruise control, are an increasing commodity in modern vehicles. Our earlier experience of radar-based adaptive cruise control has indicated repeatable abrupt behavior when approaching a stopped vehicle at high speed, which is typical for extra-urban roads. Abrupt behavior in assisted driving not only decreases the passenger trust but also reduces the comfort levels of such systems. We present a design and proof-of-concept of a machine vision-enhanced adaptive cruise controller. A machine vision-based brake light detection system was implemented and tested in order to smoothen the transition from coasting to braking and ensure speed reduction early enough. The machine vision system detects the brake lights in front, then transmits a command to the cruise controller to reduce speed. The current paper reports the speed control system design and experiments carried out to validate the system. The experiments showed the system works as designed by reducing abrupt behavior. Measurements show that brake light-assisted cruise control was able to start deceleration about three seconds earlier than a cruise controller without brake light detection. Measurements also showed increased ride comfort with the maximum deceleration and minimum jerk levels improving from 5% to 31%.Peer reviewe

Brake Light Detection Algorithm for Predictive Braking

There has recently been a rapid increase in the number of partially automated systems in passenger vehicles. This has necessitated a greater focus on the effect the systems have on the comfort and trust of passengers. One significant issue is the delayed detection of stationary or harshly braking vehicles. This paper proposes a novel brake light detection algorithm in order to improve ride comfort. The system uses a camera and YOLOv3 object detector to detect the bounding boxes of the vehicles ahead of the ego vehicle. The bounding boxes are preprocessed with L*a*b colorspace thresholding. Thereafter, the bounding boxes are resized to a 30 × 30 pixel resolution and fed into a random forest algorithm. The novel detection system was evaluated using a dataset collected in the Helsinki metropolitan area in varying conditions. Carried out experiments revealed that the new algorithm reaches a high accuracy of 81.8%. For comparison, using the random forest algorithm alone produced an accuracy of 73.4%, thus proving the value of the preprocessing stage. Furthermore, a range test was conducted. It was found that with a suitable camera, the algorithm can reliably detect lit brake lights even up to a distance of 150 m

Brake Light Detection Algorithm for Predictive Braking

There has recently been a rapid increase in the number of partially automated systems in passenger vehicles. This has necessitated a greater focus on the effect the systems have on the comfort and trust of passengers. One significant issue is the delayed detection of stationary or harshly braking vehicles. This paper proposes a novel brake light detection algorithm in order to improve ride comfort. The system uses a camera and YOLOv3 object detector to detect the bounding boxes of the vehicles ahead of the ego vehicle. The bounding boxes are preprocessed with L*a*b colorspace thresholding. Thereafter, the bounding boxes are resized to a 30 × 30 pixel resolution and fed into a random forest algorithm. The novel detection system was evaluated using a dataset collected in the Helsinki metropolitan area in varying conditions. Carried out experiments revealed that the new algorithm reaches a high accuracy of 81.8%. For comparison, using the random forest algorithm alone produced an accuracy of 73.4%, thus proving the value of the preprocessing stage. Furthermore, a range test was conducted. It was found that with a suitable camera, the algorithm can reliably detect lit brake lights even up to a distance of 150 m

Pheromonal and enzyme genetic characteristics of the Bombus lucorum species complex in northern Europe

Spatial and temporal distribution of the species in the Bombus lucorum species complex, B. lucorum (L.), B. cryptarum (Fabricius) and B. magnus Vogt, were studied in Finland. Morphological distinction between the species is not as clear as in Central Europe, but B. lucorum can be distinguished from the other two with the help of enzyme genetic markers. B. lucorum is the most common of the three species in most of Finland, and B. cryptarum is abundant in the southwestern coastal area and in northern Lapland. B. magnus was only rarely found among the spring queens in southwestern Finland, and its range possibly restricts to southern and central parts of Finland. A comparison of the chemical composition of the male labial glands and enzyme genotypes shows that males produce species-specific marking pheromones

The COVID-19 epidemic and its effects on Finland : Medium-term scenarios

This memorandum describes three potential evolution trends that the corona epidemic might follow in Finland, together with their economic and social impacts. The scenarios start from the coming summer and extend until the end of 2023. The analysis presented here is a follow- up to the short-term scenarios (covering approx. 6 months) published in December 2020 that examined the combined and mutual effects of the epidemic and its economic and social consequences. Compared with many other countries, Finland has so far survived the COVID-19 epidemic with relatively little damage in terms of health protection and the economy. By the beginning of February 2021, the lowest number of COVID-19 cases relative to the population than anywhere else in the EU/EEA area was recorded in Finland. In the early part of this year, the evolution has essentially followed the base case scenario of the models published last December. Since the second half of February, infections have increased rapidly, virus variants are spreading fast, and there is a growing demand for hospital beds. At present, at the turn of February and March 2021, Finland faces a very challenging epidemiological situation

Covid-19-epidemin och dess konsekvenser i Finland : Scenarier på medellång sikt

I denna promemoria redogörs för tre möjliga scenarier för hur covid-19-pandemin kommer att utvecklas och vilka ekonomiska och sociala konsekvenser den får. Scenarierna omspänner tiden från den inkommande sommaren till slutet av år 2023. Analysen som presenteras här är en fortsättning på de scenarier på kortare sikt (ca 6 mån.) som gavs ut i december 2020 och som på samma sätt gällde de sammanlagda och inbördes effekterna av pandemin och de ekonomiska och sociala konsekvenserna . Tills vidare har Finland klarat av covid-19-pandemin med relativt små skador i jämförelse med andra länder med hänseende till hälsoskyddet eller ekonomin. Fram till början av februari hade det till exempel i Finland i förhållande till befolkningen konstaterats minst covid-19-fall inom hela EU/EES-området. Utvecklingen har i början av året huvudsakligen följt scenariot för basnivån av de alternativ som offentliggjordes i december. Från mitten av februari har antalet smittfall börjat öka, och olika virusmutationer har snabbt börjat sprida sig. Samtidigt har behovet av vårdplatser på sjukhus börjat öka. I skrivande stund i början av mars är den epidemiologiska situationen i Finland mycket utmanande

COVID-19-epidemia ja sen vaikutukset Suomessa : Keskipitkän aikavälin skenaarioita

Tässä muistiossa on kuvattu kolme mahdollista korona-epidemian kehityskulkua taloudellisine ja sosiaalisine vaikutuksineen. Skenaariot alkavat kuluvan vuoden kesästä ja jatkuvat vuoden 2023 loppuun. Tässä esiteltävä analyysi on jatkoa joulukuussa 2020 julkistetuille lyhyemmän (n. 6 kk) aikavälin skenaarioille, joissa tarkastelun kohteena oli yhtäläisesti epidemian, talouden ja sosiaalisten seurausten yhteis- ja keskinäisvaikutukset . Toistaiseksi Suomi on selvinnyt COVID-19 -epidemiasta sangen vähäisin vaurioin, jos tarkastellaan asiaa terveyden suojelun tai talouden näkökulmasta ja verrataan muihin maihin. Esimerkiksi helmikuun alkuun mennessä Suomessa oli todettu väestöön suhteutettuna vähiten COVID-19 tapauksia koko EU/ETA alueella. Kehitys on alkuvuonna pääpiirteissään noudattanut joulukuussa julkistettujen skenaarioiden perusvaihtoehtoa. Helmikuun jälkipuoliskolta alkaen tartunnat ovat lisääntyneet nopeasti, virusmuunnokset ovat yleistyneet nopeasti ja sairaalapaikkojen tarve on alkanut kasvaa. Suomen epidemiologinen tilanne on helmi-maaliskuun vaihteessa erittäin haastava. On kuitenkin mahdollista, että epidemiatilanteen merkittävä huonontuminen voidaan vielä pysäyttää helmi-maaliskuun vaihteessa käyttöön otetuilla tiukoilla rajoitustoimilla. Tällöin joulukuussa hahmoteltujen kielteisempien skenaarioiden taloudelliset ja sosiaaliset vauriot olisivat vältettävissä. Pitkittyvät rajoitustoimet voivat aiheuttaa erittäin merkittäviä hyvinvoinnin ongelmia ja negatiivisia taloudellisia seurauksia etenkin suoraan rajoitusten kohteeksi joutuvilla toimialoilla. Joulukuun skenaariotarkastelussa oli kuitenkin päädytty empiirisen tutkimuksen nojalla arvioimaan, että epidemian hallinnassa pitämisen yhteiskunnalliset ja taloudelliset hyödyt ylittävät rajoitustoimista koituvat haitat. Näin olisi erityisesti tilanteessa, jossa voimakkaat rajoitustoimet ajoitettaisiin siten, että pystytään estämään epidemian kiihtyminen hallitsemattomaksi ennen rokotusten ja vuodenaikavaihtelun odotettua vaikutusta

Cholesterol Crystals Activate the NLRP3 Inflammasome in Human Macrophages: A Novel Link between Cholesterol Metabolism and Inflammation

Chronic inflammation of the arterial wall is a key element in the pathogenesis of atherosclerosis, yet the factors that trigger and sustain the inflammation remain elusive. Inflammasomes are cytoplasmic caspase-1-activating protein complexes that promote maturation and secretion of the proinflammatory cytokines interleukin(IL)-1beta and IL-18. The most intensively studied inflammasome, NLRP3 inflammasome, is activated by diverse substances, including crystalline and particulate materials. As cholesterol crystals are abundant in atherosclerotic lesions, and IL-1beta has been linked to atherogenesis, we explored the possibility that cholesterol crystals promote inflammation by activating the inflammasome pathway.Here we show that human macrophages avidly phagocytose cholesterol crystals and store the ingested cholesterol as cholesteryl esters. Importantly, cholesterol crystals induced dose-dependent secretion of mature IL-1beta from human monocytes and macrophages. The cholesterol crystal-induced secretion of IL-1beta was caspase-1-dependent, suggesting the involvement of an inflammasome-mediated pathway. Silencing of the NLRP3 receptor, the crucial component in NLRP3 inflammasome, completely abolished crystal-induced IL-1beta secretion, thus identifying NLRP3 inflammasome as the cholesterol crystal-responsive element in macrophages. The crystals were shown to induce leakage of the lysosomal protease cathepsin B into the cytoplasm and inhibition of this enzyme reduced cholesterol crystal-induced IL-1beta secretion, suggesting that NLRP3 inflammasome activation occurred via lysosomal destabilization.The cholesterol crystal-induced inflammasome activation in macrophages may represent an important link between cholesterol metabolism and inflammation in atherosclerotic lesions