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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Schwarz, Lucas; Keler, Andreas; Krisp, Jukka M.;

    Introduction: During the COVID-19 lockdown significant improvements in urban air quality were detected due to the absence of motorized vehicles. It is crucial to perpetuate such improvements to maintain and improve public health simultaneously. Therefore, this exploratory study approached bicycle infrastructure in the case of Munich (Germany) to find out which specific bicycle lanes meet the demands of its users, how such infrastructure looks like, and which characteristics are potentially important. Methods: To identify patterns of bicycle infrastructure in Munich exploratory data is collected over the timespan of three consecutive weeks in August by a bicycle rider at different times of the day. We measure position, time, velocity, pulse, level of sound, temperature and humidity. In the next step, we qualitatively identified different segments and applied a cluster analysis to quantitatively describe those segments regarding the measured factors. The data allows us to identify which bicycle lanes have a particular set of measurements, indicating a favorable construction for bike riders. Results: In the exploratory dataset, five relevant segment clusters are identified: viscous, slow, inconsistent, accelerating, and best-performance. The segments that are identified as best-performance enable bicycle riders to travel efficiently and safely at amenable distances in urban areas. They are characterized by their width, little to no interaction with motorized traffic as well as pedestrians, and effective traffic light control. Discussion: We propose two levels of discussion: (1) revolves around what kind of bicycles lanes from the case study can help to increase bicycle usage in urban areas, while simultaneously improving public health and mitigating climate change challenges and (2) discussing the possibilities, limitations and necessary improvements of this kind of exploratory methodology.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DOAJ-Articlesarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DOAJ-Articles
    Article . 2022
    Data sources: DOAJ-Articles
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    OPUS Augsburg
    Article . 2022
    License: CC BY
    Data sources: OPUS Augsburg
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DOAJ
    Article . 2022
    Data sources: DOAJ
    https://doi.org/10.17169/refub...
    Other literature type . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DOAJ-Articlesarrow_drop_down
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      Article . 2022
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      OPUS Augsburg
      Article . 2022
      License: CC BY
      Data sources: OPUS Augsburg
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DOAJ
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      https://doi.org/10.17169/refub...
      Other literature type . 2022
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      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Md Rakibul Alam; Arif Mohaimin Sadri; Xia Jin;

    The objective of this study is to mine and analyze large-scale social media data (rich spatio-temporal data unlike traditional surveys) and develop comparative infographics of emerging transportation trends and mobility indicators by adopting natural language processing and data-driven techniques. As such, first, around 13 million tweets for about 20 days (16 December 2019–4 January 2020) from North America were collected, and tweets closely aligned with emerging transportation and mobility trends (such as shared mobility, vehicle technology, built environment, user fees, telecommuting, and e-commerce) were identified. Data analytics captured spatio-temporal differences in social media user interactions and concerns about such trends, as well as topics of discussions formed through such interactions. California, Florida, Georgia, Illinois, New York are among the highly visible cities discussing such trends. Being positive overall, people carried more positive views on shared mobility, vehicle technology, telecommuting, and e-commerce, while being more negative on user fees, and the built environment. Ride-hailing, fuel efficiency, trip navigation, daily as well as shopping and recreational activities, gas price, tax, and product delivery were among the emergent topics. The social media data-driven framework would allow real-time monitoring of transportation trends by agencies, researchers, and professionals.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DOAJ-Articles
    Article . 2021
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Future Transportation
    Article
    License: CC BY
    Data sources: UnpayWall
    DOAJ
    Article . 2021
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DOAJ-Articles
      Article . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Future Transportation
      Article
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      DOAJ
      Article . 2021
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Foteini Mikiki; Andreas Oikonomou; Ermioni Katartzi;

    The mobility practices of students are largely dictated by their respective educational obligations. Students of physical education are an ostensibly physically active population, whose active lifestyle may include active travel. University student mobility research calls for behavioral approaches to ground relevant interventions. This work investigated the sustainability practices in the student community of the Physical Education Department in Serres, a medium-sized Greek city. Moreover, this paper aimed to shed light on the gender differences in the physical activity levels of 259 students, as well as their respective differences in mobility practices. A novel questionnaire, based on Ajzen’s theory of planned behavior and Godin–Shephard’s approach to physical activity, was used. The results confirmed higher levels of physical activity in male students, although their attitude toward physical activity was less positive than that of their female classmates. Further positive attitudes in women were recorded toward sustainable mobility choices, although the evidence demonstrated a similar gap between the answers of the two genders. Car possession was higher in men, whereas car purchase intention was slightly lower in women, who had a lower income in general. Moreover, income impacted gender mobility preferences. Recommendations can be guided by students’ sports preferences and can be gender-sensitive, taking income into account.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Future Transportation
    Article
    License: CC BY
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DOAJ-Articles
    Article . 2021
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    DOAJ
    Article . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Future Transportation
      Article
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DOAJ-Articles
      Article . 2021
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      Article . 2021
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jianqing Wu; Bo Du; Qiang Wu; Jun Shen; +5 Authors

    In many big cities, train delays are among the most complained-about events by the public. Although various models have been proposed for train delay prediction, prior studies on both primary and secondary train delay prediction are limited in number. Recent advances in deep learning approaches and increasing availability of various data sources has created new opportunities for more efficient and accurate train delay prediction. In this study, we propose a hybrid deep learning solution by integrating long short-term memory (LSTM) and Critical Point Search (CPS). LSTM deals with long-term prediction tasks of trains’ running time and dwell time, while CPS uses predicted values with a nominal timetable to identify primary and secondary delays based on the delay causes, run-time delay, and dwell time delay. To validate the model and analyse its performance, we compare the standard LSTM with the proposed hybrid model. The results demonstrate that new variants outperform the standard LSTM, based on predicting time steps of dwell time feature. The experiment results also showed many irregularities of historical trends, which draws attention for further research.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Future Transportation
    Article
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Article . 2021
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    Article . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Future Transportation
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      Article . 2021
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    Authors: Justin Mahlberg; Yi-Ting Cheng; Darcy M. Bullock; Ayman Habib;

    The United States has over 8.8 million lane miles nationwide, which require regular maintenance and evaluations of sign retroreflectivity, pavement markings, and other pavement information. Pavement markings convey crucial information to drivers as well as connected and autonomous vehicles for lane delineations. Current means of evaluation are by human inspection or semi-automated dedicated vehicles, which often capture one to two pavement lines at a time. Mobile LiDAR is also frequently used by agencies to map signs and infrastructure as well as assess pavement conditions and drainage profiles. This paper presents a case study where over 70 miles of US-52 and US-41 in Indiana were assessed, utilizing both a mobile retroreflectometer and a LiDAR mobile mapping system. Comparing the intensity data from LiDAR data and the retroreflective readings, there was a linear correlation for right edge pavement markings with an R2 of 0.87 and for the center skip line a linear correlation with an R2 of 0.63. The p-values were 0.000 and 0.000, respectively. Although there are no published standards for using LiDAR to evaluate pavement marking retroreflectivity, these results suggest that mobile LiDAR is a viable tool for network level monitoring of retroreflectivity.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
    License: CC BY
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    DOAJ-Articles
    Article . 2021
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Future Transportation
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    Article . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Transportatio...arrow_drop_down
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Future Transportation
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    Authors: Aggelos Soteropoulos; Paul Pfaffenbichler; Martin Berger; Günter Emberger; +2 Authors

    Developments in the field of automated mobility will greatly change our mobility and the possibilities to get from one place to another. This paper presents different scenarios for personal mobility in Austria, anticipating the possibilities and developments in the field of automated vehicles (AVs). The scenarios were developed using a systematically formalized scenario technique and expand the social and political discourse on automated mobility, which is currently characterized by a lack of experience and visibility as an established transport service. Using system dynamics modeling techniques, i.e., the Metropolitan Activity Relocation Simulator (MARS), impacts of the scenarios on the Austrian transportation system are estimated. The simulations show that, without suitable transport policy measures, automated mobility will lead to a significant increase in the volume of individual traffic and to modal shift effects with lower traffic volumes for public transport, walking and cycling. In addition, without a link between AVs and post-fossil propulsion systems, increases in pollutant emissions can also be expected. In contrast, the simulation results of an increased use of AVs in public transport show positive effects for the support of a more sustainable mobility. Hence, transport policy measures accompanying the introduction and development of automated vehicles will be needed in the future to reach a sustainable development.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
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    Authors: Mahmut Gezmish; Long T. Truong;

    This paper aims to estimate the potential of electric vehicles (EVs) in Melbourne, Victoria, using the Victorian Integrated Survey of Travel and Activity (VISTA) data. The investigation of whether EVs with different all-electric ranges (AERs) can replace car travel to work and education is the focus of this paper. The results showed that EVs would be able to replace most car travel to work (68.5% to 97.1%) and car travel to education (71.9% to 96.9%), with AERs increasing from 40 km to 100 km, assuming car drivers are willing to use an EV. It is estimated that the average operating cost savings per person would be up to AUD 3.12 and AUD 2.79 each day, regarding travel to work and education, respectively. Considering both travel to work and education, EVs could replace up to 33.8 million kilometres of car travel, consuming around 7.6 GWh and resulting in a reduction in carbon dioxide (CO2) emissions of about 610 tons each day.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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    Future Transportation
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      Future Transportation
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    Authors: Arias Molinares, Daniela; Julio, Raky; García Palomares, Juan Carlos; Gutiérrez Puebla, Javier;

    As shared mobility burst in different cities as one of the most innovative transport solutions, few efforts are found related to the exploration of dockless services and more specifically, to analysing opinions from those users that are subscribed to both, docked and dockless services simultaneously. Therefore, our study explores station-based bike-sharing users’ preferences for other dockless services. To that end, we firstly divide the sample into two groups: Group 1 being users that only use Bicimad (Madrid's station-based bike-sharing) and Group 2 being Bicimad users that are also subscribed to other dockless services. Results show that both groups have similar users’ profiles according to their socio-demographic characteristics (male, 35–49 years old, well-educated, medium income and employee), although Group 2 shows a slightly higher rate of under-26-year-olds, which could be supporting the idea that these services are more attractive for the youngest. Moreover, our findings show that approximately 12% of station-based bike-sharing users are also subscribed to dockless services. At a higher rate, those subscribed to dockless services live outside the city centre, where the bike-sharing system is not available, showing that the two models may essentially have a complemental relationship, especially in the peripheries. Finally, results point at the importance of bike-sharing systems having a positive impact on its users, as they are keener to try new dockless options and a reduced willingness to use private cars. Insights may help to better inform public policy and promote the use of shared micromobility.

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    Journal of Urban Mobility
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      Journal of Urban Mobility
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    Authors: Liu, Yang; Lyu, Cheng; Zhang, Yuan; Liu, Zhiyuan; +2 Authors

    Real-time traffic state (e.g., speed) prediction is an essential component for traffic control and management in an urban road network. How to build an effective large-scale traffic state prediction system is a challenging but highly valuable problem. This study focuses on the construction of an effective solution designed for spatio-temporal data to predict the traffic state of large-scale traffic systems. In this study, we first summarize the three challenges faced by large-scale traffic state prediction, i.e., scale, granularity, and sparsity. Based on the domain knowledge of traffic engineering, the propagation of traffic states along the road network is theoretically analyzed, which are elaborated in aspects of the temporal and spatial propagation of traffic state, traffic state experience replay, and multi-source data fusion. A deep learning architecture, termed as Deep Traffic State Prediction (DeepTSP), is therefore proposed to address the current challenges in traffic state prediction. Experiments demonstrate that the proposed DeepTSP model can effectively predict large-scale traffic states.

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    Communications in Transportation Research
    Other literature type . Article . 2021 . Peer-reviewed
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      Communications in Transportation Research
      Other literature type . Article . 2021 . Peer-reviewed
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    Authors: Abedi, Mohammadmahdi; Correia, A. Gomes; Fangueiro, Raúl;

    In this study, the geotechnical and piezoresistivity properties of a sustainable self-sensing cementitious stabilised sand reinforced with recycled fibres (self-sensing cementitious geocomposite, SCG) were extensively investigated. In this route, different concentrations of recycled glass, polypropylene, and ultra-high-molecular-weight polyethylene (GF, PP, and UHMWPE) fibres were incorporated into the conductive stabilised sand with 10% cement composed of 0.17% hybrid (1:1) carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs). The specimens were fabricated using the standard Proctor compaction method at optimum water content, and their mechanical, hydraulic, microstructural, durability, and piezoresistivity properties were investigated after 28 days of hydration using different laboratory test methods. The test results indicate that the maximum dry densities of all SCGs were obtained with a degree of saturation of approximately 85%. For these moisture conditions, there are well-defined relationships between the maximum dry density and strength, permeability, and ultrasonic pulse velocity for SCGs. The GF and UHMWPE fibres exhibited the best performances in terms of strength, durability in climatic cycles, as well as a reduction in permeability. A unique relationship between the ratio of tangent modulus and strength with the strain was defined for all the SCGs that can be of practical use in geocomposite. Furthermore, the piezoresistivity and sensitivity of the SCGs were also increased by reinforcing the geocomposites with fibres, due to increasing their ductility. In summary, we believe that this novel approach contributes to a new era of smart geocomposite materials in sustainable intelligent transport infrastructures. This work was supported by the European Commission-Shiff2Rail Program under the project “IN2TRACK2–826255-H2020-S2RJU-2018/ H2020-S2RJU CFM-2018′′. It was also partly financed by FCT/MCTES through National Funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Engineering Structures (ISISE) under reference UIDB/04029/2020, and under the R&D Unit Centre for Textile Science and Technology (2C2T).

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    Transportation Engineering
    Other literature type . Article . 2021 . Peer-reviewed
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    Universidade do Minho: RepositoriUM
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      Transportation Engineering
      Other literature type . Article . 2021 . Peer-reviewed
      License: Elsevier TDM
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      Universidade do Minho: RepositoriUM
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Schwarz, Lucas; Keler, Andreas; Krisp, Jukka M.;

    Introduction: During the COVID-19 lockdown significant improvements in urban air quality were detected due to the absence of motorized vehicles. It is crucial to perpetuate such improvements to maintain and improve public health simultaneously. Therefore, this exploratory study approached bicycle infrastructure in the case of Munich (Germany) to find out which specific bicycle lanes meet the demands of its users, how such infrastructure looks like, and which characteristics are potentially important. Methods: To identify patterns of bicycle infrastructure in Munich exploratory data is collected over the timespan of three consecutive weeks in August by a bicycle rider at different times of the day. We measure position, time, velocity, pulse, level of sound, temperature and humidity. In the next step, we qualitatively identified different segments and applied a cluster analysis to quantitatively describe those segments regarding the measured factors. The data allows us to identify which bicycle lanes have a particular set of measurements, indicating a favorable construction for bike riders. Results: In the exploratory dataset, five relevant segment clusters are identified: viscous, slow, inconsistent, accelerating, and best-performance. The segments that are identified as best-performance enable bicycle riders to travel efficiently and safely at amenable distances in urban areas. They are characterized by their width, little to no interaction with motorized traffic as well as pedestrians, and effective traffic light control. Discussion: We propose two levels of discussion: (1) revolves around what kind of bicycles lanes from the case study can help to increase bicycle usage in urban areas, while simultaneously improving public health and mitigating climate change challenges and (2) discussing the possibilities, limitations and necessary improvements of this kind of exploratory methodology.

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    OPUS Augsburg
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    Authors: Md Rakibul Alam; Arif Mohaimin Sadri; Xia Jin;

    The objective of this study is to mine and analyze large-scale social media data (rich spatio-temporal data unlike traditional surveys) and develop comparative infographics of emerging transportation trends and mobility indicators by adopting natural language processing and data-driven techniques. As such, first, around 13 million tweets for about 20 days (16 December 2019–4 January 2020) from North America were collected, and tweets closely aligned with emerging transportation and mobility trends (such as shared mobility, vehicle technology, built environment, user fees, telecommuting, and e-commerce) were identified. Data analytics captured spatio-temporal differences in social media user interactions and concerns about such trends, as well as topics of discussions formed through such interactions. California, Florida, Georgia, Illinois, New York are among the highly visible cities discussing such trends. Being positive overall, people carried more positive views on shared mobility, vehicle technology, telecommuting, and e-commerce, while being more negative on user fees, and the built environment. Ride-hailing, fuel efficiency, trip navigation, daily as well as shopping and recreational activities, gas price, tax, and product delivery were among the emergent topics. The social media data-driven framework would allow real-time monitoring of transportation trends by agencies, researchers, and professionals.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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    Future Transportation
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
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      Future Transportation
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    Authors: Foteini Mikiki; Andreas Oikonomou; Ermioni Katartzi;

    The mobility practices of students are largely dictated by their respective educational obligations. Students of physical education are an ostensibly physically active population, whose active lifestyle may include active travel. University student mobility research calls for behavioral approaches to ground relevant interventions. This work investigated the sustainability practices in the student community of the Physical Education Department in Serres, a medium-sized Greek city. Moreover, this paper aimed to shed light on the gender differences in the physical activity levels of 259 students, as well as their respective differences in mobility practices. A novel questionnaire, based on Ajzen’s theory of planned behavior and Godin–Shephard’s approach to physical activity, was used. The results confirmed higher levels of physical activity in male students, although their attitude toward physical activity was less positive than that of their female classmates. Further positive attitudes in women were recorded toward sustainable mobility choices, although the evidence demonstrated a similar gap between the answers of the two genders. Car possession was higher in men, whereas car purchase intention was slightly lower in women, who had a lower income in general. Moreover, income impacted gender mobility preferences. Recommendations can be guided by students’ sports preferences and can be gender-sensitive, taking income into account.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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    Future Transportation
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
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      Future Transportation
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    Authors: Jianqing Wu; Bo Du; Qiang Wu; Jun Shen; +5 Authors

    In many big cities, train delays are among the most complained-about events by the public. Although various models have been proposed for train delay prediction, prior studies on both primary and secondary train delay prediction are limited in number. Recent advances in deep learning approaches and increasing availability of various data sources has created new opportunities for more efficient and accurate train delay prediction. In this study, we propose a hybrid deep learning solution by integrating long short-term memory (LSTM) and Critical Point Search (CPS). LSTM deals with long-term prediction tasks of trains’ running time and dwell time, while CPS uses predicted values with a nominal timetable to identify primary and secondary delays based on the delay causes, run-time delay, and dwell time delay. To validate the model and analyse its performance, we compare the standard LSTM with the proposed hybrid model. The results demonstrate that new variants outperform the standard LSTM, based on predicting time steps of dwell time feature. The experiment results also showed many irregularities of historical trends, which draws attention for further research.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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    Future Transportation
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
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    Authors: Justin Mahlberg; Yi-Ting Cheng; Darcy M. Bullock; Ayman Habib;

    The United States has over 8.8 million lane miles nationwide, which require regular maintenance and evaluations of sign retroreflectivity, pavement markings, and other pavement information. Pavement markings convey crucial information to drivers as well as connected and autonomous vehicles for lane delineations. Current means of evaluation are by human inspection or semi-automated dedicated vehicles, which often capture one to two pavement lines at a time. Mobile LiDAR is also frequently used by agencies to map signs and infrastructure as well as assess pavement conditions and drainage profiles. This paper presents a case study where over 70 miles of US-52 and US-41 in Indiana were assessed, utilizing both a mobile retroreflectometer and a LiDAR mobile mapping system. Comparing the intensity data from LiDAR data and the retroreflective readings, there was a linear correlation for right edge pavement markings with an R2 of 0.87 and for the center skip line a linear correlation with an R2 of 0.63. The p-values were 0.000 and 0.000, respectively. Although there are no published standards for using LiDAR to evaluate pavement marking retroreflectivity, these results suggest that mobile LiDAR is a viable tool for network level monitoring of retroreflectivity.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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    Future Transportation
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
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    Authors: Aggelos Soteropoulos; Paul Pfaffenbichler; Martin Berger; Günter Emberger; +2 Authors

    Developments in the field of automated mobility will greatly change our mobility and the possibilities to get from one place to another. This paper presents different scenarios for personal mobility in Austria, anticipating the possibilities and developments in the field of automated vehicles (AVs). The scenarios were developed using a systematically formalized scenario technique and expand the social and political discourse on automated mobility, which is currently characterized by a lack of experience and visibility as an established transport service. Using system dynamics modeling techniques, i.e., the Metropolitan Activity Relocation Simulator (MARS), impacts of the scenarios on the Austrian transportation system are estimated. The simulations show that, without suitable transport policy measures, automated mobility will lead to a significant increase in the volume of individual traffic and to modal shift effects with lower traffic volumes for public transport, walking and cycling. In addition, without a link between AVs and post-fossil propulsion systems, increases in pollutant emissions can also be expected. In contrast, the simulation results of an increased use of AVs in public transport show positive effects for the support of a more sustainable mobility. Hence, transport policy measures accompanying the introduction and development of automated vehicles will be needed in the future to reach a sustainable development.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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      Future Transportation
      Other literature type . Article . 2021 . Peer-reviewed
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    Authors: Mahmut Gezmish; Long T. Truong;

    This paper aims to estimate the potential of electric vehicles (EVs) in Melbourne, Victoria, using the Victorian Integrated Survey of Travel and Activity (VISTA) data. The investigation of whether EVs with different all-electric ranges (AERs) can replace car travel to work and education is the focus of this paper. The results showed that EVs would be able to replace most car travel to work (68.5% to 97.1%) and car travel to education (71.9% to 96.9%), with AERs increasing from 40 km to 100 km, assuming car drivers are willing to use an EV. It is estimated that the average operating cost savings per person would be up to AUD 3.12 and AUD 2.79 each day, regarding travel to work and education, respectively. Considering both travel to work and education, EVs could replace up to 33.8 million kilometres of car travel, consuming around 7.6 GWh and resulting in a reduction in carbon dioxide (CO2) emissions of about 610 tons each day.

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    Future Transportation
    Other literature type . Article . 2021 . Peer-reviewed
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    Future Transportation
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      Future Transportation
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      Future Transportation
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    Authors: Arias Molinares, Daniela; Julio, Raky; García Palomares, Juan Carlos; Gutiérrez Puebla, Javier;

    As shared mobility burst in different cities as one of the most innovative transport solutions, few efforts are found related to the exploration of dockless services and more specifically, to analysing opinions from those users that are subscribed to both, docked and dockless services simultaneously. Therefore, our study explores station-based bike-sharing users’ preferences for other dockless services. To that end, we firstly divide the sample into two groups: Group 1 being users that only use Bicimad (Madrid's station-based bike-sharing) and Group 2 being Bicimad users that are also subscribed to other dockless services. Results show that both groups have similar users’ profiles according to their socio-demographic characteristics (male, 35–49 years old, well-educated, medium income and employee), although Group 2 shows a slightly higher rate of under-26-year-olds, which could be supporting the idea that these services are more attractive for the youngest. Moreover, our findings show that approximately 12% of station-based bike-sharing users are also subscribed to dockless services. At a higher rate, those subscribed to dockless services live outside the city centre, where the bike-sharing system is not available, showing that the two models may essentially have a complemental relationship, especially in the peripheries. Finally, results point at the importance of bike-sharing systems having a positive impact on its users, as they are keener to try new dockless options and a reduced willingness to use private cars. Insights may help to better inform public policy and promote the use of shared micromobility.

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    Journal of Urban Mobility
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      Journal of Urban Mobility
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    Authors: Liu, Yang; Lyu, Cheng; Zhang, Yuan; Liu, Zhiyuan; +2 Authors

    Real-time traffic state (e.g., speed) prediction is an essential component for traffic control and management in an urban road network. How to build an effective large-scale traffic state prediction system is a challenging but highly valuable problem. This study focuses on the construction of an effective solution designed for spatio-temporal data to predict the traffic state of large-scale traffic systems. In this study, we first summarize the three challenges faced by large-scale traffic state prediction, i.e., scale, granularity, and sparsity. Based on the domain knowledge of traffic engineering, the propagation of traffic states along the road network is theoretically analyzed, which are elaborated in aspects of the temporal and spatial propagation of traffic state, traffic state experience replay, and multi-source data fusion. A deep learning architecture, termed as Deep Traffic State Prediction (DeepTSP), is therefore proposed to address the current challenges in traffic state prediction. Experiments demonstrate that the proposed DeepTSP model can effectively predict large-scale traffic states.

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    Communications in Transportation Research
    Other literature type . Article . 2021 . Peer-reviewed
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      Communications in Transportation Research
      Other literature type . Article . 2021 . Peer-reviewed
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    Authors: Abedi, Mohammadmahdi; Correia, A. Gomes; Fangueiro, Raúl;

    In this study, the geotechnical and piezoresistivity properties of a sustainable self-sensing cementitious stabilised sand reinforced with recycled fibres (self-sensing cementitious geocomposite, SCG) were extensively investigated. In this route, different concentrations of recycled glass, polypropylene, and ultra-high-molecular-weight polyethylene (GF, PP, and UHMWPE) fibres were incorporated into the conductive stabilised sand with 10% cement composed of 0.17% hybrid (1:1) carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs). The specimens were fabricated using the standard Proctor compaction method at optimum water content, and their mechanical, hydraulic, microstructural, durability, and piezoresistivity properties were investigated after 28 days of hydration using different laboratory test methods. The test results indicate that the maximum dry densities of all SCGs were obtained with a degree of saturation of approximately 85%. For these moisture conditions, there are well-defined relationships between the maximum dry density and strength, permeability, and ultrasonic pulse velocity for SCGs. The GF and UHMWPE fibres exhibited the best performances in terms of strength, durability in climatic cycles, as well as a reduction in permeability. A unique relationship between the ratio of tangent modulus and strength with the strain was defined for all the SCGs that can be of practical use in geocomposite. Furthermore, the piezoresistivity and sensitivity of the SCGs were also increased by reinforcing the geocomposites with fibres, due to increasing their ductility. In summary, we believe that this novel approach contributes to a new era of smart geocomposite materials in sustainable intelligent transport infrastructures. This work was supported by the European Commission-Shiff2Rail Program under the project “IN2TRACK2–826255-H2020-S2RJU-2018/ H2020-S2RJU CFM-2018′′. It was also partly financed by FCT/MCTES through National Funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Engineering Structures (ISISE) under reference UIDB/04029/2020, and under the R&D Unit Centre for Textile Science and Technology (2C2T).

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    Transportation Engineering
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      Transportation Engineering
      Other literature type . Article . 2021 . Peer-reviewed
      License: Elsevier TDM
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      Universidade do Minho: RepositoriUM
      Other literature type . 2021
      License: CC BY NC ND
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      This Research product is the result of merged Research products in OpenAIRE.

      You have already added works in your ORCID record related to the merged Research product.