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- Almlöf, Erik, 1985-, et al.
(author)
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Frameworks for assessing societal impacts of automated driving technology
- 2022
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In: Transportation planning and technology (Print). - : Taylor & Francis. - 0308-1060 .- 1029-0354. ; 45:7, s. 545-572
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Journal article (peer-reviewed)abstract
- Numerous studies have studied the impacts of automated driving (AD) technology on e.g. accident rates or CO2 emissions using various frameworks. In this paper we present an overview of previous frameworks used for societal impacts and review their advantages and limitations. Additionally, we introduce the Total Impact Assessment (TIA) framework developed by the Swedish Transport Administration and use this framework to evaluate three scenarios for AD bus services in Stockholm. We conclude that the reviewed frameworks cover different aspects of AD technology, and that e.g. cybersecurity and biodiversity are areas largely neglected. Furthermore, most frameworks assume effects to be homogenous, when there may be large variation in e.g. perceived security. The TIA framework does not manage to include all societal aspects of AD technology, but has great benefits and manages to provide important insights of the societal impacts of AD technology, especially how effects may wary for different actors.
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| 2. |
- Almlöf, Erik, 1985-
(author)
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Slutrapport - Självkörande fullängdsbuss på Tvärförbindelse Södertörn
- 2021
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Reports (pop. science, debate, etc.)abstract
- Föreliggande slutrapport är finansierad av Trafikverkets FoI portfölj, strategiska initiativ,för projekt Självkörande eldriven stombuss på Tvärförbindelse Södertörn – En skalbarfallstudie (TRV 2019/118695). Partners i projektet är Trafikverket, Scania, Volvo, Keolis,KTH samt Sweco där även Trafikförvaltningen Region Stockholm, Nobina och projektTvärförbindelse Södertörn har bidragit till arbetet som pågått från maj 2020 till mars 2021.Ansvarig för projektet inom Trafikverket har varit Stora projekt.För att skapa en förståelse för konsekvenser av tekniska utveckling i relation tillnödvändiga fysiska och digitala åtgärder har tre scenarier tagits fram: Bus Driver Plus,Automation with Adaption och Automation Utopia. Dessa scenarier beskriver olika nivåerav automation och behov av kringliggande stödsystem. I det första scenario finns enförare ombord på bussen som tar över körningen vid farliga situationer. Det andrascenariot avser en självkörande buss utan förare där den fysiska infrastrukturen haranpassats genom ett införande av ett eget busskörfält. Det sista scenariot beskriver enframtid där bussen helt förlitar sig på digital teknik och en operatör kontrollerar körningenav flera fordon från ett avsides kontrolltorn.De tre scenarierna utvärderades genom en samlad effektbedömning, Trafikverkets metodför att utvärdera åtgärder. Resultaten visar att den största vinsten av automatisering kanhandla om resenärernas bekvämlighet och inte nödvändigtvis om att minimera kostnaderför förare. Antaganden om att resenärerna kan uppleva resan bekvämare är troligtvisöverskattade, men resultaten visar att även små förbättringar i bekvämlighet kan ge storasamhälleliga vinster.Scenariot där bussen har ett eget körfält innebär mycket stora kostnader och är troligtvisinte ekonomiskt försvarbart. Dessutom kommer enbart en busslinje att trafikeramotorleden som dessutom består av 3 tunnlar. Vidare är det inte säkert att den aktör somgör nödvändiga investeringar är den aktör som får ta del av de samhälleliga vinsterna. Iscenariot skulle Trafikverket stå för stora delar av investeringskostnaden, medan vinsten för personalbesparingar uppstår för Region Stockholm och kollektivtrafikresenärerna somåker längs sträckan.Projektet har även undersökt hur multimodala hubbar (nod som möjliggör smidigt bytemellan olika transportmedel) längs med förbindelsen kan stödja eldrivna och självkörandebussar. Det är viktigt att ny väginfrastruktur bidrar till en attraktiv kollektivtrafik därresenärer i första hand väljer buss istället för bil. För att eldrivna och självkörande bussarska införas behöver Region Stockholm ställa nya krav i upphandlingar för attåstadkomma en förändring i transportsystemet. Nya krav som skapar ekonomiskaincitament för operatörer som utför den operativa verksamheten över lång tid. Det är dockproblematiskt att ställa krav på eldrift eftersom det saknas tillgänglig infrastruktur iStockholm.Avseende självkörande fullängdsbussar är tekniken helt enkelt inte tillräckligt mogen idag.Dock tror många experter att självkörande bussar kommer att införas, både i stadsmiljöoch glesbygd, när tekniken och samhället är redo för det, gissningsvis kring år 2030.
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| 3. |
- Ji, Huazhen, et al.
(author)
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Relationship between leadership-member exchange (LMX) and flow at work among medical workers during the COVID-19 : the mediating role of job crafting
- 2023
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In: BMC Psychology. - : BioMed Central (BMC). - 2050-7283. ; 11:1
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Journal article (peer-reviewed)abstract
- Based on relational leadership theory and self-determination theory, this study aims to investigate the relationship between leader-member exchange (LMX), job crafting, and flow at work among medical workers in the context of the COVID-19 pandemic. Participants in the study consisted of 424 hospital employees. The results showed that: (1) the LMX positively predicted flow at work; (2) two types of job crafting (increasing structural job resources and challenging job demands) played a mediating role between the LMX and flow at work; and (3) gender did not moderate these mediating effects as suggested by previous studies. These results indicate that the LMX can not only directly predict flow at work, but also indirectly predict work-related flow through job crafting by increasing structural job resources and challenging job demands, thus providing new insights for enhancing flow experiences of medical workers.
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| 4. |
- Johari, Fatemeh, et al.
(author)
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Urban Building Energy Modeling : State of the Art and Future Prospects
- 2020
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In: Renewable & sustainable energy reviews. - : Elsevier BV. - 1364-0321 .- 1879-0690. ; 128
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Research review (peer-reviewed)abstract
- During recent years, urban building energy modeling has become known as a novel approach for identification, support and improvement of sustainable urban development initiatives and energy efficiency measures in cities. Urban building energy models draw the required information from the energy analysis of buildings in the urban context and suggest options for effective implementation of interventions. The growing interest in urban building energy models among researchers, urban designers and authorities has led to the development of a diversity of models and tools, evolving from physical to more advanced hybrid models. By critically analyzing the published research, this paper incorporates an updated overview of the field of urban building energy modeling and investigates possibilities, challenges and shortcomings, as well as an outlook for future improvements. The survey of previous studies identifies technical bottlenecks and legal barriers in access to data, systematic and inherent uncertainties as well as insufficient resources as the main obstacles. Furthermore, this study suggests that the main route to further improvements in urban building energy modeling is its integration with other urban models, such as climate and outdoor comfort models, energy system models and, in particular, mobility models.
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| 7. |
- Kristan, Matej, et al.
(author)
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The Ninth Visual Object Tracking VOT2021 Challenge Results
- 2021
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In: 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021). - : IEEE COMPUTER SOC. - 9781665401913 ; , s. 2711-2738
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website(1).
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| 8. |
- Lin, Zeyu, et al.
(author)
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Evaluating the electron beam spot size in electron beam melting machines
- 2021
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Conference paper (peer-reviewed)abstract
- Since electron beam (EB) is the main additive manufacturing (AM) tool in electron beam melting (EBM), EB spot size plays a significant role in the parts quality, surface roughness as well as the microstructure and corresponding properties. So far, the research on the relationship between the machine parameters and the EB spot size has been mainly based on the single track and powderless single track printing on a metal plate such as stainless steel. However, this method, due to material thermal properties as well as the melting phenomena, cannot reveal the actual value for the EB spot size. This research is carried out to establish a simple methodology on measuring the EB spot size in a more accurate way with a low cost. To do so, a ceramic surface coating was applied to the surface of a metal copper starting plate and stainless steel plate. Afterwards, the EB applied the tracks onto the coatings and regular metal plate. The analysis showed that the EB tracks on ceramic coated stainless steel plates could be the best replica for the electron beam among those materials tested in this work.
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| 9. |
- Sadeghian, Paria, et al.
(author)
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A deep semi-supervised machine learning algorithm for detecting transportation modes based on GPS tracking data
- 2024
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In: Transportation. - : Springer. - 0049-4488 .- 1572-9435.
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Journal article (peer-reviewed)abstract
- Transportation research has benefited from GPS tracking devices since a higher volume of data can be acquired. Trip information such as travel speed, time, and most visited locations can be easily extracted from raw GPS tracking data. However, transportation modes cannot be extracted directly and require more complex analytical processes. Common approaches for detecting travel modes heavily depend on manual labelling of trajectories with accurate trip information, which is inefficient in many aspects. This paper proposes a method of semi-supervised machine learning by using minimal labelled data. The method can accept GPS trajectory with adjustable length and extract latent information with long short-term memory (LSTM) Autoencoder. The method adopts a deep neural network architecture with three hidden layers to map the latent information to detect transportation mode. The proposed method is assessed by applying it to the case study where an accuracy of 93.94% can be achieved, which significantly outperforms similar studies.
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| 10. |
- Sadeghian, Paria
(author)
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A Multi-Dimensional Approach to Human Mobility and Transportation Mode Detection Using GPS Data
- 2024
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Doctoral thesis (other academic/artistic)abstract
- GPS tracking data is an essential resource for analyzing human travel patterns and evaluating the effects on transportation systems. The primary challenge, however, is to accurately identify the modes of transportation within unlabeled GPS data. These approaches range from simple rule-based systems to advanced machine-learning techniques. This dissertation aims to bridge this gap by examining the critical features and techniques of these methods and proposing a novel approach for detecting transportation modes in GPS tracking data. To achieve this goal, a comprehensive understanding of individual journeys is crucial. Thus, this research adopts a microdata analytic approach, encompassing data collection, processing, analysis, and decision-making stages. Doing so contributes to advancing human mobility research and transportation mode detection. Paper I undertook a systematic review of transport mode detection methodologies to fill the research gap, emphasizing the predominance of supervised learning algorithms and highlighting the need for further research to address the limitations of small datasets. Paper II introduced a stepwise methodology, integrating unsupervised learning, GIS, and supervised algorithms to detect transport modes while minimizing reliance on labelled data. The Random Forest algorithm emerged as a precise but time-intensive solution. Paper III showcased a novel approach to transport mode detection using deep learning models, outperforming traditional machine learning methods. This paper signals the potential of deep learning in the field and demonstrates the importance of raw GPS data in enhancing accuracy. Paper V addressed the challenge of predicting human mobility patterns under the Hidden Markov Model (HMM) framework, highlighting the applicability of HMMs to understanding and predicting complex mobility behaviour. This paper emphasized the need for GPS tracking data in developing advanced mobility models. Paper IV ventured into hybrid methodology by combining K-means clustering with the ANP-PSO algorithm to enhance transportation mode classification. This pioneering approach improved classification accuracy while reducing dependence on labelled datasets. Collectively, these papers underscore the opportunities and limitations in human mobility research, offering insights into future directions for mitigating data quality issues and improving the accuracy of transportation mode detection. These innovative methodologies have practical implications for transportation planning, resource allocation, and intelligent transportation system development, ultimately shaping the future of transportation research and decision-making. Standardized data collection, processing, and labelling methods are crucial and need attention in future research. Future research can focus on developing such benchmarks and validation protocols to enhance the reliability and comparability of results.
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