| 1. |
- Almlöf, Erik, 1985-, et al.
(författare)
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Frameworks for assessing societal impacts of automated driving technology
- 2022
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Ingår i: Transportation planning and technology (Print). - : Taylor & Francis. - 0308-1060 .- 1029-0354. ; 45:7, s. 545-572
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Tidskriftsartikel (refereegranskat)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. |
- Eriksson, Per Erik, et al.
(författare)
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How gaze time on screen impacts the efficacy of visual instructions
- 2018
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Ingår i: Heliyon. - : Elsevier BV. - 2405-8440. ; 4:6
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Tidskriftsartikel (refereegranskat)abstract
- This article explores whether GTS (gaze time on screen) can be useful as an engagement measure in the screen mediated learning context. Research that exemplifies ways of measuring engagement in the on-line education context usually does not address engagement metrics and engagement evaluation methods that are unique to the diverse contemporary instructional media landscape. Nevertheless, unambiguous construct definitions of engagement and standardized engagement evaluation methods are needed to leverage instructional media's efficacy. By analyzing the results from a mixed methods eye-tracking study of fifty-seven participants evaluating their visual and assembly performance levels in relation to three visual, procedural instructions that are versions of the same procedural instruction, we found that the mean GTS-values in each group were rather similar. However, the original GTS-values outputted from the ET-computer were not entirely correct and needed to be manually checked and cross validated. Thus, GTS appears not to be a reliable, universally applicable automatic engagement measure in screen-based instructional efforts. Still, we could establish that the overall performance of learners was somewhat negatively impacted by lower than mean GTS-scores, when checking the performance levels of the entire group (N = 57). When checking the stimuli groups individually (N = 17, 20, 20), the structural diagram group's assembly time durations were positively influenced by higher than mean GTS-scores.
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| 3. |
- Nordström, Carin, 1971-, et al.
(författare)
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Working with Swedes
- 2018
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Bok (övrigt vetenskapligt/konstnärligt)
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| 4. |
- Sadeghian, Paria, et al.
(författare)
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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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Ingår i: Transportation. - : Springer. - 0049-4488 .- 1572-9435.
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Tidskriftsartikel (refereegranskat)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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| 5. |
- Sadeghian, Paria
(författare)
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A Multi-Dimensional Approach to Human Mobility and Transportation Mode Detection Using GPS Data
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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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| 6. |
- Sadeghian, Paria
(författare)
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Human mobility behavior : Transport mode detection by GPS data
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- GPS tracking data are widely used to understand human travel behavior and to evaluate the impact of travel. A major advantage with the usage of GPS tracking devices for collecting data is that it enables the researcher to collect large amounts of highly accurate and detailed human mobility data. However, unlabeled GPS tracking data does not easily lend itself to detecting transportation mode and this has given rise to a range of methods and algorithms for this purpose. The algorithms used vary in design and functionality, from defining specific rules to advanced machine learning algorithms. There is however no previous comprehensive review of these algorithms and this thesis aims to identify their essential features and methods and to develop and demonstrate a method for the detection of transport mode in GPS tracking data. To do this, it is necessary to have a detailed description of the particular journey undertaken by an individual. Therefore, as part of the investigation, a microdata analytic approach is applied to the problem areas, including the stages of data collection, data processing, analyzing the data, and decision making.In order to fill the research gap, Paper I consists of a systematic literature review of the methods and essential features used for detecting the transport mode in unlabeled GPS tracking data. Selected empirical studies were categorized into rule-based methods, statistical methods, and machine learning methods. The evaluation shows that machine learning algorithms are the most common. In the evaluation, I compared the methods previously used, extracted features, types of dataset, and model accuracy of transport mode detection. The results show that there is no standard method used in transport mode detection. In the light of these results, I propose in Paper II a stepwise methodology to detect five transport modes taking advantage of the unlabeled GPS data by first using an unsupervised algorithm to detect the five transport modes. A GIS multi-criteria process was applied to label part of the dataset. The performance of the five supervised algorithms was evaluated by applying them to different portions of the labeled dataset. The results show that stepwise methodology can achieve high accuracy in detecting the transport mode by labeling only 10% of the data from the entire dataset. For the future, one interesting area to explore would be the application of the stepwise methodology to a balanced and larger dataset. A semi-supervised deep-learning approach is suggested for development in transport mode detection, since this method can detect transport modes with only small amounts of labeled data. Thus, the stepwise methodology can be improved upon for further studies.
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| 7. |
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| 8. |
- Sadeghian, Paria, et al.
(författare)
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Testing feasibility of using a hidden Markov model on predicting human mobility based on GPS tracking data
- 2024
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Ingår i: Transportmetrica B. - : Taylor & Francis. - 2168-0566. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Human mobility behaviour is far from random and can be predictable. Predicting human mobility behaviour has the potential to improve location selection for facilities, transportation services, urban planning, and can be beneficial in providing more efficient sustainable urban development strategies. However, it is difficult to model urban mobility patterns since incentives for mobility is complex, and influenced by several factors, such as dynamic population, weather conditions. Thus, this paper proposes a prediction-oriented algorithm under the framework of a Hidden Markov Model to predict next-location and time-of-arrival of human mobility. A comprehensive evaluation of these two schemes for the representation of latent and observable variables is discussed. In conclusion, the paper provides a valuable contribution to the field of mobility behaviour prediction by proposing a novel algorithm. The evaluation shows that the proposed algorithm is stable and consistent in predicting the next location of users based on their past trajectories. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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| 9. |
- Vaddadi, Bhavana, Ph.D. Student, et al.
(författare)
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Measuring System-Level Impacts of Corporate Mobility as a Service (CMaaS) Based on Empirical Evidence
- 2020
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Ingår i: Sustainability. - : MDPI AG. - 2071-1050. ; 12:17, s. 7051-
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Tidskriftsartikel (refereegranskat)abstract
- Corporate Mobility as a Service (CMaaS) is a type of MaaS that enables mobility within as well as to and from a worksite for employees. The expected benefits of CMaaS are to support a shift towards more sustainable and more effective work-related transport activities. There is a lack of knowledge regarding the impacts of CMaaS and how its performance should be measured. This paper proposes an evaluation framework to measure CMaaS impacts at a system level. The proposed evaluation framework is then applied to evaluate a real CMaaS deployment in Sweden. This paper contributes to knowledge building and guidance to support policy and decision making for CMaaS development and implementation in the future.
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| 10. |
- Zhang, Xingxing, et al.
(författare)
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Heat Pump Technologies and Their Applications in Solar Systems
- 2019
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Ingår i: Advanced Energy Efficiency Technologies for Solar Heating, Cooling and Power Generation. - Cham : Springer. - 9783030172824 - 9783030172831 ; , s. 311-339
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Bokkapitel (refereegranskat)abstract
- As the well known that global energy demand is on a trend of continuous growth, reducing energy demand and making good use of renewable energy are thought to be the major routes toward low carbon and sustainable future, in particular for the building sector. Compared to traditional gas-fired heating systems, heat pumps have been proved to be an energy-efficient heating technology which can save fossil fuel energy and consequently reduce CO2 emission. However, the most outstanding challenges for the application of heat pumps lie in their high demand for electrical power, and the insufficient heat transfer between the heat source and the refrigerant. To overcome these difficulties, a solar-assisted heat pump has been proposed to tackle these challenges. A solar-assisted heat pump combines a heat pump with a solar collector, enabling the use of solar energy to provide space heating and hot water for buildings. This chapter introduces heat pump technologies and their applications in solar systems. Two types of solar-assisted heat pump, direct and indirect expansion, are illustrated in details. This work has provided the fundamental research and experience for developing a solar heat pump system and contributing to a significant fossil fuel saving and carbon reduction in the global extent.
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| 11. |
- Zhang, Xingxing, et al.
(författare)
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Solar System Design and Energy Performance Assessment Approaches
- 2019
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Ingår i: Advanced Energy Efficiency Technologies for Solar Heating, Cooling and Power Generation. - Cham : Springer. - 9783030172824 - 9783030172831 ; , s. 417-451
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Bokkapitel (refereegranskat)abstract
- Recently, solar system has gained a rapid development in many countries because it is clean and sustainable. Many solar systems including the solar photovoltaic/loop-heat-pipe (PV/LHP), solar loop-heat-pipe (LHP), solar photovoltaic/micro-channel heat pipe (PV/MCHP) system, and solar thermal facade system (STF) have been designed for energy saving. To assess these systems’ performance, there are many approaches such as energy and exergy assessment which is used in this chapter to analyze their performance. Besides the system design, the authors set up dedicated experimental models in combination with computer models to test the systems’ performance. Furthermore, some systems are compared with the conventional system, and the performance of these solar systems is better than the conventional system. In addition, these solar systems are applied in many real buildings and their performance is examined, the results show that the solar systems have more potential to boost the building energy efficiency and create the possibility of solar development in buildings. © 2019, Springer Nature Switzerland AG.
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| 12. |
- Zhang, Xingxing, et al.
(författare)
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Solar Systems’ Economic and Environmental Performance Assessment
- 2019
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Ingår i: Advanced Energy Efficiency Technologies for Solar Heating, Cooling and Power Generation. - Cham : Springer. - 9783030172824 - 9783030172831 ; , s. 453-486
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Bokkapitel (refereegranskat)abstract
- The economic and environmental performance assessment of the solar system plays a critical role in building design, operation and retrofit. A dedicated economic model is necessary to assess the investment feasibility on a new technology, which allows investors to decide on a profitable investment, compare investment projects and know about the benefits of the best investment. An environmental model is adopted to predict carbon emission reduction in the solar system relative to the traditional heating and electronic systems. This chapter introduced three up-to-date solar system models and corresponding assessments related to their applications, including solar photovoltaic/loop heat pipe (PV/LHP) heat pump water heating system, loop heat pipe-based solar thermal facade (LHP-STF), heat pump water heating system as well as solar thermal facade (STF). The research results will be able to assist in decision-making in implementation of the proposed PV/T technology and analyses of the associated economic and environmental benefits, thus contributing to realization of regional and global targets on fossil fuel energy saving and environmental sustainability.
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| 13. |
- Zhao, Xiaoyun, Ph.D., et al.
(författare)
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An evaluation of the reliability of GPS-based transportation data
- 2017
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Ingår i: Proceedings of IAC in Vienna 2017. - 9788088203049 ; , s. 323-334
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Konferensbidrag (refereegranskat)abstract
- GPS-based data are becoming a cornerstone for real-time transportation applications. Tracking data of vehicles from GPS receivers are however susceptible to measurement errors. The assessment of the reliability of data from GPS receiver is a neglected issue, especially in a real road network setting and in the phase after data transfer but before information identification. An evaluation method is outlined and carried out by conducting a randomized experiment. We assess the reliability of GPS-based transportation data on geographical position, speed, and elevation from three varied receivers GlobalSat BT-338X, Magellan SporTrak Pro and smart phone for three transportation modes: bicycle, car, and bus. The positional error ranging from 0158 meters, and 74% to 100% with an error within 5 meters depending on the transportation mode and route, there is also a non-negligible risk for aberrant positioning. Speed is slightly underestimated or overestimated with errors around 5km/h except for SporTrak Pro which had an error of -10 km/h. Elevation measurements are unreliable with errors bigger than 100 meters.
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| 14. |
- Zhao, Xiaoyun, et al.
(författare)
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Key barriers in MaaS development and implementation : Lessons learned from testing Corporate MaaS (CMaaS)
- 2020
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Ingår i: Transportation Research Interdisciplinary Perspectives. - : Elsevier. - 2590-1982. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- To reach the full potential of Mobility as a Service (MaaS), especially its projected positive environmental impacts, the barriers to development and implementation processes must be identified. However, studies identifying such MaaS barriers are rare. Following an interdisciplinary approach, this paper aims to bridge this gap by adding knowledge on barriers to MaaS development and implementation using four perspectives (service design, business model, user travel attitude and behavior, and system impacts). Following a systems thinking approach, the barriers are investigated at three levels (individual, organizational and societal) to show their relationships. This paper investigates a specific type of MaaS, namely Corporate Mobility as a Service (CMaaS). The results obtained by investigating a large-scale CMaaS pilot provide implications of general barriers to MaaS development and implementation. The findings presented in this paper provide knowledge and guidance to MaaS stakeholders.
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| 15. |
- Zhao, Xiaoyun, 1990-, et al.
(författare)
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Potential values of maas impacts in future scenarios
- 2021
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Ingår i: Journal of Urban Mobility. - : Elsevier BV. - 2667-0917. ; 1, s. 100005-100005
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Tidskriftsartikel (refereegranskat)abstract
- Mobility as a Service (MaaS) is considered a strategy that can provide potential solutions for a sustainable transport system. The current literature claims that MaaS can deliver net positive impacts for the transport system. However, whether these impacts are marginal or significant is unclear, as estimations typically are based on a few pilot tests. The lack of understanding of these impacts could create barriers for decision-making on policy and regulation in adopting MaaS strategy. The paper proposes a feasible evaluation to explore how and to what extent MaaS leads to, for example, reduced emissions, reduced fossil energy consumption, reduced car ownership and vehicle kilometres travelled on a large scale. The aim of this paper is to provide potential values of MaaS impacts based on analysis of future scenarios. The potential values of MaaS impacts can be used to support decision-making within both public organisations and among service developers for MaaS implementation and development.
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| 16. |
- Zhao, Xiaoyun, Ph.D.
(författare)
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Road network and GPS tracking with data processing and quality assessment
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application.This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost.The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.
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