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Detection of sound from AVAS in urban environments
(2024) Demirci, Bircan; Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE); Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE); Forssén, Jens; Bolin, Karl
Functionality of AVAS (Acoustic Vehicle Alert System) faces challenges in urban environments, where background noises may mask AVAS sounds. From a safety perspective, designing AVAS sounds that effectively warn vulnerable road users (without causing extensive environmental noise) is even more crucial in heavy vehicles since they have longer braking distances, greater momentum, and more blind spots than light vehicles. This study aims to contribute to the safety aspects of battery electric trucks (BEV trucks) by exploring their detectability in urban areas and their classification rate, which shows whether they can be distinguishable from cars. In this regard, listening tests were conducted with 51 participants: eight distinct vehicle sounds, five of which belong to a BEV heavy truck, one to an ICE (Internal combustion engine) truck, one to a BEV passenger car, and one to an ICE passenger car. Each vehicle sound was presented both at 10 and 20 km/h. In the first session of the test, participants were tasked with classifying approaching vehicles as either trucks or cars, without additional urban background noise (the equivalent levels are about 45 dB(A)). During the second session, they were tasked with detecting approaching vehicles amidst continuous urban background noise (the equivalent levels are in the range between 57 and 62 dB(A)) and then classifying the detected ones. The results revealed that in the first session of the test, where there was no additional background noise, 50% of the vehicles were correctly classified within the safe zone. The vast majority of the vehicles approaching at 10 km/h were classified within the safe zone, while those approaching at 20 km/h were classified within the unsafe zone. In the second session, with continuous urban background noise, 30% of the vehicles were detected and then correctly classified within safe distances. Unlike the first session, a large portion of the vehicles approaching at 20 km/h were detected and then correctly classified within the safe zone, while those approaching at 10 km/h were detected and then classified within the unsafe zone. While the ICE truck outperformed at both speeds and in both sessions, the accuracy of the BEV truck results varied depending on the session and vehicle speed. Moreover, the accuracy rates of the tasks’ results were mainly affected by whether the AVAS sound was in active mode or not, the modulation of the AVAS sound, and whether the tonal components of the BEV truck were dominant or not. These findings may provide insights into the current and future needs of designing AVAS sounds for electrified trucks.
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Learning-Based Detection of Events in Eye-Tracking Data: An Investigation Into Small-Scale Models for Automotive Applications
(2024) Due, Martin; Chalmers tekniska högskola / Institutionen för matematiska vetenskaper; Ringh, Axel; Molin, Vincent; Zemblys, Raimondas
Detection of eye movement events in eye-tracking data is integral to various research fields and commercial applications. Traditionally, the detection has been accomplished either by hand or with threshold based detectors with the inherent drawback that thresholds levels and other parameters had to be hand picked for each scenario. In recent years machine learning methods have been employed for eye movement event detection that do away with that requirement. However, these models tend to be too large to run on limited resources in embedded applications, particularly automotive ones. This thesis focuses on creating models that are smaller but with retained performance. Five machine learning methods were evaluated and hyperparameters were tuned to create well performing small models. Furthermore, the usage of synthetic data for training was investigated, both as a supplement to real data and as a sole source of training data. The study found that a Multilayer Perceptron model (MLP) trained on a combination of real and synthetic data struck the best balance between size and performance. Additionally, results show that models trained purely on synthetic data also performed reasonably well. The findings of this thesis suggest that small, efficient models can effectively detect eye movement events, with potential applications in automotive contexts.
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Avfallsförordningen; ett ideal eller verklighet
(2024) Bergkvist, Malin; Sabel, Ebba; Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE); Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE); Gustafsson, Mathias Petter
Agenda 2030 presenterades den 1 januari år 2016 av FN:s och innehåller de gemensamma målen för en hållbar utveckling. Byggsektorn står ansvarig för 22 procent av nationens totala växthusgasutsläpp. Det är därmed av stor betydelse att förstå hur beslut och val som tas i byggsektorn påverkar utvecklingen mot en hållbar byggsektor. I projekteringsskedet finns det stora möjligheter och utvecklingspotential att göra val som minimerar byggandets klimatpåverkan. Den nya versionen av Avfallsförordningen (SFS 2023:936) reglerar bygg- och rivningsavfall i Sverige med syftet att främja ekologisk hållbarhet. Förordningen innebär att krav ställs på byggföretagen, inklusive möjligheten till dispens från vissa lagkrav under specifika omständigheter. Syftet med examensarbetet är att undersöka och utreda vilka specifika omständigheter som genererar dispens enligt avfallsförordningen SFS 2020:614 inom byggsektorn. Genom att analysera och konkretisera dessa omständigheter ämnar arbetet att skapa insikter och kunskap för framtida riktlinjer med hänsyn till att främja hållbart agerande. Undersökningsstrategi utgår från en flermetodsforskning som ansats där dokumentstudier och semistrukturerade intervjuer tillämpas som undersökningsmetoder. Resultatet indikerar att omständigheterna som genererar dispens från Avfallsförordningen SFS 2020:614 är unika för varje enskilt fall. Varje dispensansökan bedöms individuellt och en skillnad som identifierats beror på byggprojektets geografiska plats. Det finns även brister som genomsyrar hela byggsektorns värdekedja, där tillgång till resurser och kompetens hos aktörerna påverkar sektorns hållbarhetsinsatser. Det finns behov av tydligare riktlinjer för att styra aktörernas arbete med byggavfall. Detta har resulterat i den framtagna handlingsplanen FRAMSTEG - Framtidens Samverkan och Tillvägagångssätt för hållbart byggande, vilket syftar till att främja ekologisk hållbarhet.
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Analysis of GNSS signal measurement accuracy
(2024) Rachman Harfian, Alif; Chalmers tekniska högskola / Institutionen för rymd-, geo- och miljövetenskap; Chalmers University of Technology / Department of Space, Earth and Environment; Haas, Rüdiger; Bergstrand , Sten
eceiver-related errors significantly influence the accuracy of GNSS signal measure ments. One of these errors pertains to the antenna phase center correction. Several antenna calibration techniques, such as robot calibration, can mitigate the impact of such errors. However, there is a possibility that calibration corrections may not completely eliminate the errors in the antenna phase center. To address this issue, calibrated antenna phase center corrections were investigated by measuring GNSS signal observations at four different stations, each tilted to various angles in specific directions, involving up to six baseline length formations. This experiment was dis tinct from previous studies, which only involved one baseline length between two different stations with antennas physically tilted towards each other. Observation data from the four different stations were retrieved and processed using GipsyX with the Precise Point Positioning (PPP) method, and Bernese with the single dif ference technique (DGNSS). Additionally, a laser tracker was utilized to measure the station positions and baseline lengths, providing more precise measurements. The phase residual error models were derived from L1, L2 and L3 frequency observations. The error models indicate that all three frequency observations are influenced by er rors corresponding to antenna phase center corrections, with an error of -0.8867 mm for L1, -1.5728 mm for L2, and -0.3901 mm for L3.
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Improving Transportation Efficiency: Cost Comparison Between Single Trailer and High- Capacity Transport in Container Road Freight
(2024) Zhu, Yixue; Li, Junyang; Chalmers tekniska högskola / Institutionen för teknikens ekonomi och organisation; Chalmers University of Technology / Department of Technology Management and Economics; Cardenas Barbosa, Ivan Dario; Von Corswant, Fredrik
This thesis examines the use of High-Capacity Transport (HCT) vehicles in container logistics, as well as the use of dry ports and last mile efficiency. The study focuses on comparing single and double trailer configurations, examining their respective advantages in terms of cost-effectiveness, operational efficiency, and environmental sustainability. Meanwhile dry ports, as key hubs for relieving congestion in seaports and streamlining the distribution process, focus on specific situations suitable for implementation. The thesis assesses the economic viability of HCT vehicles and dry ports in transport scenarios through a combination of literature review, case studies, and data analysis. The results of the study show that the combination of HCT vehicles and strategically located dry ports can significantly reduce transport costs, improve supply chain efficiency, and support more sustainable logistics operations. The study provides insights into optimizing container transport for long-haul and last-mile movements, contributing to the development of more efficient and environmentally friendly freight transport solutions.