Fraunhofer Chalmers Research Centre for Industrial Mathematics
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3D Object Classification using Point Clouds and Deep Neural Network for Automotive Applications
No full textObject identification is a central part of autonomous cars and there are many sensors to help with this. One such sensor is the LIDAR which creates point clouds of
the cars surrounding. This thesis evaluates a solution for object identification in 3D point clouds with the help of a neural network. A system named DELIS (DEtection
in Lidar Systems), which takes a point cloud generated from a LIDAR as input, is designed. The system consists of two subsystems, one non-machine learning algorithm
which segments the point cloud into clusters, one for each object, and a neural network that classifies this clusters. The final output is then the classes and
the coordinates of the objects in the point cloud. The result of this thesis is a system named DELIS that can identify between pedestrians, cars, and cyclists
A study of sitting posture and belt position in a travelling car: How do passengers sit in a travelling car?
No full textTo improve the future design of restraint systems, it is important to know how passengers’
sitting postures change over time and how the passengers interact with the
restraint systems. This master thesis at Chalmers University of Technology, focuses
on pelvis rotation, slouching and belt position while travelling in a front seat of a
car on regular roads. The information was collected during normal drive in the passenger
seat of a regular car, while the volunteers perform activities such as; resting,
e-socializing and conversing.
Twenty volunteers, ten male and ten female, participated in the study. Volunteers
were seated in the front row passenger seat, because this sitting posture is probably
similar to how passengers will sit in future autonomous cars. The inertial motion
measurement system MTw Awinda from Xsens, in total eight sensors, were used
in the study. They were placed on the volunteer’s sacrum, sternum, C7, T3, L5,
forehead and car. The data from the sacrum sensor, that corresponds with pelvis
rotation are mainly presented and discussed in this report. In addition, a surface
pressure sensing array (Tekscan mat) was placed on the car seat cushion. The
data from selected volunteers was analyzed with the TEMA to determine degree of
slouching. Photo analysis was carried out to assess belt positions before and after
the test. Additionally, the rotation of pelvis and sternum when changing seat back
angle in intervals of 5° between 23° and 48° were also investigated.
The results show that pelvis rearward rotation increases by average 10° when riding
in the car for about 45 minutes. Comparing the activities, the volunteers had similar
average pelvis rotation. Slouching could be measured only for three volunteers out
of 20 and it seemed to increase on average 3 cm during the ride. The belt position of
initial and final sitting posture indicates that the diagonal belt moved less than the
lap belt. To investigate the dynamic belt position, future video analysis is needed.
Increasing seat back angle appeared to have a correlation with increasing sacrum
and sternum pitch
A deep learning approach for modelling of the purge valve and lambda sensor in an EVAP system
No full textExploring correlation between the Aβ-peptide accumulation and endosome transport in Alzheimer’s disease using particle tracking
No full textEn sannolikhetsteoretisk behandling av diffusion baserat p˚a Einsteins modell av Brownsk r¨orelse
No full textI det här arbetet undersöker vi Brownsk rörelse och dess förbindelse med värmeledningsekvationen. Som förberedande material presenterar vi härledningen och lösningen till värmeledningsekvationen på R och den förutsättande termodynamiken som krävs för att förstå Albert Einsteins artikel om suspenderade partiklar i en utspädd lösning. Vi presenterar de huvudsakliga resultaten från Einsteins artikel, fyller i några matematiska tvetydigheter och gör vissa invecklade steg mera förståeliga för läsaren. Vidare undersöker vi en med Einstein samtida forskare, Smoluchowskis härledning av Brownsk rörelse. Avslutningsvis visar vi hur en enkel symmetrisk slumpvandring kan användas för att förklara Brownsk rörelse hos partiklar. I synnerhet visar vi egenskaperna för gränsvärdet för slumpvandringen, det vill säga att en slumpvandring konvergerar i fördelning till en normalfördelning. I beviset av detta faktum läggs extra vikt vid resttermerna som introduceras vid asymptotiska approximationer vilket ofta hoppas ¨over i litteraturen. Detta resultatet jämförs sedan med lösningen av värmeledningsekvationen och vi visar hur jämförelse av koefficienter kan ge en uppskattning av dimensionerna hos de Brownska partiklarn
