+publisher:"Delft University of Technology" +contributor:("van Lint, Hans")

Delft University of Technology

1. QUE, JIJIA (author). Exploring the Evolution of Passenger Characteristics Based on Smart Card Data: A Case Study of Shenzhen, China.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:635011a3-a659-47ab-ae88-8feecbc38493

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Passenger travel characteristics (PTCs) are characteristics that are sought from the information contained in trips, such as travel frequency, travel mode, departure location, and etc.… (more)

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APA (6^th Edition):

QUE, J. (. (2019). Exploring the Evolution of Passenger Characteristics Based on Smart Card Data: A Case Study of Shenzhen, China. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:635011a3-a659-47ab-ae88-8feecbc38493

Chicago Manual of Style (16^th Edition):

QUE, JIJIA (author). “Exploring the Evolution of Passenger Characteristics Based on Smart Card Data: A Case Study of Shenzhen, China.” 2019. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:635011a3-a659-47ab-ae88-8feecbc38493.

MLA Handbook (7^th Edition):

QUE, JIJIA (author). “Exploring the Evolution of Passenger Characteristics Based on Smart Card Data: A Case Study of Shenzhen, China.” 2019. Web. 17 Apr 2021.

Vancouver:

QUE J(. Exploring the Evolution of Passenger Characteristics Based on Smart Card Data: A Case Study of Shenzhen, China. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:635011a3-a659-47ab-ae88-8feecbc38493.

Council of Science Editors:

QUE J(. Exploring the Evolution of Passenger Characteristics Based on Smart Card Data: A Case Study of Shenzhen, China. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:635011a3-a659-47ab-ae88-8feecbc38493

Delft University of Technology

2. de Böck, Bas (author). Understanding Traffic Events by Enriching Traffic Data with Geosocial Data.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:ec6e8914-2c6c-41d7-89b1-cbd39e7f6867

► Non-recurrent traffic events, consisting of events of an unpredictable nature such as incidents and vehicle breakdowns, can either directly or indirectly influence road traffic. A… (more)

▼ Non-recurrent traffic events, consisting of events of an unpredictable nature such as incidents and vehicle breakdowns, can either directly or indirectly influence road traffic. A better understanding of these events could prove beneficial towards improving a multitude of facets concerning the management of the Dutch road network. Traditional traffic event detection, based on significant changes in traffic flow/speed characteristics, is often limited by sparse road sensor coverage. More importantly, traditional detection methods are unable to categorize and describe traffic events. The aim of this study is to explore to which extent geosocial data (e.g., data from Twitter and Waze) could enrich traditional traffic data (e.g., traffic speed/flow data), in order to improve the detection, categorization, and description of traffic events in the Netherlands. In order to achieve this, a pipeline was designed for extracting knowledge on traffic events from geosocial data sources. We collected geosocial data from Twitter, Waze, and TomTom and used traffic data provided by DiTTLab. We specifically focused on reports by real road users, which we define as natural persons that report on their own account, therefore excluding all legal person entity accounts such as public/private organizations, and bots. A machine learning approach was applied to automatically classify tweets as either traffic event related or not. In order to categorize tweets into a traffic event category, a rule-based traffic domain annotator was created. Additionally, a geocoding method to link tweets to a geographic location was developed. As Waze and TomTom event reports are classified and geocoded by default, we could cluster these reports together with the processed tweets based on their categorical, spatial and temporal extent into a combined traffic event. These combined traffic event reports were then linked to traffic data, based on corresponding spatial and temporal aspects. In order to present the collected data, a web-based interactive map application was built. This methodology was applied to data collected over the period from 05-12-2017 to 17-02-2018. From the set of collected tweets approximately 6.71% proved traffic event related. Based on a linear support vector machine classification model we achieved an average f1-score of 0.95 and an accuracy of 0.954, for detecting traffic event-related tweets. The rule-based traffic domain annotator showed an average f1-score of 0.874, and an accuracy of 0.964. The geocoding method proved able to geocode tweets to a location that covers all place indicators in a tweet in 86% of the evaluated cases. The remaining 14% of the tweets either got geocoded to a part of relevant indicators or to no relevant indicators at all. Our clustering approach is able to cluster 39.61% of the event reports into a traffic event report cluster consisting out of more than one event report, from which 48.66% could be linked to traffic data. All in all, based on the achieved results, this work… Advisors/Committee Members: Bozzon, Alessandro (mentor), Psyllidis, Achilleas (mentor), Houben, Geert-Jan (graduation committee), van Lint, Hans (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Traffic Events; Traffic Congestion; Social Media

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APA (6^th Edition):

de Böck, B. (. (2018). Understanding Traffic Events by Enriching Traffic Data with Geosocial Data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:ec6e8914-2c6c-41d7-89b1-cbd39e7f6867

Chicago Manual of Style (16^th Edition):

de Böck, Bas (author). “Understanding Traffic Events by Enriching Traffic Data with Geosocial Data.” 2018. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:ec6e8914-2c6c-41d7-89b1-cbd39e7f6867.

MLA Handbook (7^th Edition):

de Böck, Bas (author). “Understanding Traffic Events by Enriching Traffic Data with Geosocial Data.” 2018. Web. 17 Apr 2021.

Vancouver:

de Böck B(. Understanding Traffic Events by Enriching Traffic Data with Geosocial Data. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:ec6e8914-2c6c-41d7-89b1-cbd39e7f6867.

Council of Science Editors:

de Böck B(. Understanding Traffic Events by Enriching Traffic Data with Geosocial Data. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:ec6e8914-2c6c-41d7-89b1-cbd39e7f6867

Delft University of Technology

3. Sloot, Mark (author). Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc

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The aim of this master thesis is to develop a dynamic zone-based traffic model for large areas, using the concept of the Network Fundamental Diagram… (more)

Subjects/Keywords: Network Fundamental Diagram

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APA (6^th Edition):

Sloot, M. (. (2019). Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc

Chicago Manual of Style (16^th Edition):

Sloot, Mark (author). “Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram.” 2019. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc.

MLA Handbook (7^th Edition):

Sloot, Mark (author). “Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram.” 2019. Web. 17 Apr 2021.

Vancouver:

Sloot M(. Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc.

Council of Science Editors:

Sloot M(. Modelling traffic in the Randstad using a dynamic zone model based on the Network Fundamental Diagram. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:9020551a-9658-45bf-be80-e6ba736b55bc

Delft University of Technology

4. An, Qi (author). Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow: Development and A Case Study for the Amsterdam Region.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:5671fce6-194a-4487-a0a0-7a43ecb63bed

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Dynamic traffic management (DTM) plays an important role from Dutch policy perspective to prevent road congestion and has been developed from control strategies to services.… (more)

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Dynamic traffic management (DTM) plays an important role from Dutch policy perspective to prevent road congestion and has been developed from control strategies to services. Five traffic control centers, 22 different DTM systems with 35 functions and over 50,000 DTM components make up the national traffic management network in the Netherlands. The malfunctioning of the DTM systems is expected to create negative impacts to the traffic, proper maintenance planning is necessary to ensure their availabilities. However, there is less knowledge about the DTM malfunctions, which makes it difficult to monetize the malfunction effects and therefore to optimally deploy the maintenance budget. In this research, a macroscopic dynamic traffic assignment model “MARPLE” is used to evaluate the social costs of the DTM malfunctions according to the failure function, failure duration, and failure location. The motorway network around Amsterdam is chosen as the study area in this research, and four DTM systems and measures were evaluated, including the rush hour lane (RHL), the motorway traffic management (MTM) system, the dynamic route information panels (DRIPs) and the ramp metering (RM) system. By conversing the DTM malfunctions into the motorway network, the introduced impacts to the traffic both in local and network levels are identified. This research made the first attempt to modify DTM malfunctions in a macroscopic dynamic traffic assignment model, and a methodology was developed to calculate the malfunction costs both in traffic flow and safety aspects. The outcome of this research answered what-if questions with regarding to DTM malfunctions, it also proved the feasibility of the ambition to translate the DTM malfunction impacts at a network level into its social costs, according to which the maintenance strategy for the DTM systems can be better deployed. Overall, the initial goal of calculating the malfunction costs of the DTM systems with a newly developed methodology is met. Through the identified limitations and improvement strategies, the framework developed in this study could offer the possibility to refine the analysis, and/or easily be applied to other DTM systems and road parts.

Civil Engineering | Transport and Planning

Advisors/Committee Members: van Lint, Hans (mentor), Hoogendoorn, Serge (mentor), Taale, Henk (graduation committee), Calvert, Simeon (graduation committee), van den Boomen, Martine (graduation committee), Muhurdarevic, Zlatan (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Risk-based Maintenance; DTM Systems; MARPLE; Function Failure; Social Costs

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

An, Q. (. (2020). Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow: Development and A Case Study for the Amsterdam Region. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5671fce6-194a-4487-a0a0-7a43ecb63bed

Chicago Manual of Style (16^th Edition):

An, Qi (author). “Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow: Development and A Case Study for the Amsterdam Region.” 2020. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:5671fce6-194a-4487-a0a0-7a43ecb63bed.

MLA Handbook (7^th Edition):

An, Qi (author). “Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow: Development and A Case Study for the Amsterdam Region.” 2020. Web. 17 Apr 2021.

Vancouver:

An Q(. Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow: Development and A Case Study for the Amsterdam Region. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:5671fce6-194a-4487-a0a0-7a43ecb63bed.

Council of Science Editors:

An Q(. Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow: Development and A Case Study for the Amsterdam Region. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:5671fce6-194a-4487-a0a0-7a43ecb63bed

Delft University of Technology

5. Arendsen, Koen (author). Shared mobility for the first and last mile: Exploring the willingness to share.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:9976ea22-07be-4674-b984-1a8f6563f0ee

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<p class="MsoNormal">Over the past decade, the development of ICT and online platforms has provided the infrastructure for new ways of sharing on a scale never… (more)

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<p class="MsoNormal">Over the past decade, the development of ICT and online platforms has provided the infrastructure for new ways of sharing on a scale never seen before which are causing a shift from ownership to access-based- consumption. This trend offers promising prospects for the case of mobility but the true magnitude of impact that the increasing popularity of shared mobility services will have on the total transportation system remains uncertain. For NS, as largest railway operator in the Netherlands, it is therefore relevant to investigate how these new services can contribute to better first and last mile transportation within the multimodal train trip, as most of these types of shared mobility operate on an urban scale. Accordingly, this study aims to explore and measure the factors that affect people’s willingness to use shared mobility services as access or egress transport in multimodal train trips. A series of stated choice experiments was developed in which respondents were asked to choose their preferred mode from a set of alternatives for a given access- or egress trip. Next to conventional modes, included shared modes were bike, (standing) e-scooter, and car. By applying discrete choice modelling, separate mixed logit models were estimated for the home-based side trip (origin to railway station) and the activity based side trip (railway station to final destination) in order to assess the impact of choice factors related to characteristics of the available modes, trip, and traveler. Results show that the willingness to use shared modes is in the first place strongly affected by familiarity with these modes. As the overall observed familiarity and in particular experience with shared modes was low, intrinsic (negative) mode preferences were found to be the dominating choice factors. This was especially the cases for shared e-scooter and to a lesser extent also for the shared car. Traveler characteristics were found affect the magnitude of the fixed mode preference in a sense that young and higher educated travelers significantly appeared to be more open to try shared modes. Contrary to the e-scooter and car, the shared bike exemplifies a more familiar option which was found to results in a different hierarchy of mode related factors: the general fixed mode preference becomes less dominant and usage costs gains more importance.

Transport, Infrastructure and Logistics

Advisors/Committee Members: van Lint, Hans (mentor), van Oort, Niels (mentor), Veeneman, Wijnand (mentor), Alonso González, María (mentor), de Bruyn, M. (mentor), van Hagen, M. (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: shared mobility; bike-sharing; e-scooter; shared car; door-to-door trip; stated preference; discrete choice modelling; public transport

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Arendsen, K. (. (2019). Shared mobility for the first and last mile: Exploring the willingness to share. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9976ea22-07be-4674-b984-1a8f6563f0ee

Chicago Manual of Style (16^th Edition):

Arendsen, Koen (author). “Shared mobility for the first and last mile: Exploring the willingness to share.” 2019. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:9976ea22-07be-4674-b984-1a8f6563f0ee.

MLA Handbook (7^th Edition):

Arendsen, Koen (author). “Shared mobility for the first and last mile: Exploring the willingness to share.” 2019. Web. 17 Apr 2021.

Vancouver:

Arendsen K(. Shared mobility for the first and last mile: Exploring the willingness to share. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:9976ea22-07be-4674-b984-1a8f6563f0ee.

Council of Science Editors:

Arendsen K(. Shared mobility for the first and last mile: Exploring the willingness to share. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:9976ea22-07be-4674-b984-1a8f6563f0ee

Delft University of Technology

6. Zhou, Moyu (author). Analysis of current Dutch traffic management effectiveness with automated vehicles: a ramp-metering case study: Simulation Study.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:ecb3796f-ff68-400f-bf2d-a1ad3b340154

► Automated vehicles are conventional vehicles equipped with advanced sensors, controller and actuators. They achieve intelligent information exchange with the environment through the onboard sensing and… (more)

▼ Automated vehicles are conventional vehicles equipped with advanced sensors, controller and actuators. They achieve intelligent information exchange with the environment through the onboard sensing and cooperative system. vehicles are possible to have situation awareness and automatically analyze the safety and dangerous state of journeys. Finally vehicles can reach destinations following drivers' willing. The ongoing research on intelligent vehicles is mainly about improving the safety, comfort, efficiency and provide an excellent human-car interface. As a self-organizing system, the traffic system is quite complicated. There are many disturbance factors to lead to various traffic problems. One of the daily occurring problems is congestion on the motorway. In order to reduce congestion, Rijkswaterstaat applies various dynamic traffic management (DTM) measures to guide the traffic. It works well nowadays in conventional traffic. However, automated vehicles entered the market recently and will start to play an essential role in future traffic. The automated vehicles' reaction to DTM measures may be different from conventional vehicles while the traffic problems still exist. Therefore, it is necessary to research the effectiveness of current Dutch traffic management in automated vehicles. This thesis aims to investigate the effectiveness of current Dutch DTM measures with driver assistant and partially automated vehicles. Due to the time limitation, only the ramp metering measure will be researched through a simulation study. Therefore the main research question is 'How partial automated driving influences the performance of current Dutch dynamic traffic management system and how can this be evaluated via simulation?'. Three methods are applied, including literature review, simulation and statistical analysis. The literature part reviews levels of automation, various longitudinal and lateral vehicle motion models, which are chosen and modified in the simulation. Many ramp metering algorithms are also introduced in the literature review. The ramp metering controller in the simulation follows RWS algorithm. Besides, the motorway demand and the penetration rate of level 1 and 2 vehicles are two input of the simulation. From the simulation results, it is concluded that the level 2 automation consisting of Adaptive Cruise Control (ACC) and Lane Change Assistance (LCA) system brings a negative impact on the motorway capacity. The ramp metering measure remains efficient if the penetration rate of level 2 vehicles is low. However, when the capacity reduces to the critical flow set up in the ramp metering controller, Ramp metering loses its efficiency. The parameters in the ramp metering controller therefore, require an update. For further research, it is recommended to simulate the same scenarios with different ramp metering algorithms. Since the functions of the algorithms are different, there might be other robust control algorithms for automated vehicles. Besides, another limitation of this thesis is that the automation… Advisors/Committee Members: van Lint, Hans (graduation committee), Calvert, Simeon (mentor), Taale, Henk (mentor), Schakel, Wouter (mentor), Pan, Wei (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Dynamic Traffic Management; Ramp Metering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zhou, M. (. (2019). Analysis of current Dutch traffic management effectiveness with automated vehicles: a ramp-metering case study: Simulation Study. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:ecb3796f-ff68-400f-bf2d-a1ad3b340154

Chicago Manual of Style (16^th Edition):

Zhou, Moyu (author). “Analysis of current Dutch traffic management effectiveness with automated vehicles: a ramp-metering case study: Simulation Study.” 2019. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:ecb3796f-ff68-400f-bf2d-a1ad3b340154.

MLA Handbook (7^th Edition):

Zhou, Moyu (author). “Analysis of current Dutch traffic management effectiveness with automated vehicles: a ramp-metering case study: Simulation Study.” 2019. Web. 17 Apr 2021.

Vancouver:

Zhou M(. Analysis of current Dutch traffic management effectiveness with automated vehicles: a ramp-metering case study: Simulation Study. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:ecb3796f-ff68-400f-bf2d-a1ad3b340154.

Council of Science Editors:

Zhou M(. Analysis of current Dutch traffic management effectiveness with automated vehicles: a ramp-metering case study: Simulation Study. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:ecb3796f-ff68-400f-bf2d-a1ad3b340154

Delft University of Technology

7. van Vianen, Karen (author). Automatic Incident Detection with Floating Car Data.

Degree: 2017, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:b4a254a3-0785-4267-97ed-626d162c4244

► Based on incident characteristics and quality of loop data and floating car data, a new incident detection algorithm is designed based on floating car data.… (more)

Subjects/Keywords: Incident detection; Algorithm; Floating Car Data

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APA (6^th Edition):

van Vianen, K. (. (2017). Automatic Incident Detection with Floating Car Data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b4a254a3-0785-4267-97ed-626d162c4244

Chicago Manual of Style (16^th Edition):

van Vianen, Karen (author). “Automatic Incident Detection with Floating Car Data.” 2017. Masters Thesis, Delft University of Technology. Accessed April 17, 2021. http://resolver.tudelft.nl/uuid:b4a254a3-0785-4267-97ed-626d162c4244.

MLA Handbook (7^th Edition):

van Vianen, Karen (author). “Automatic Incident Detection with Floating Car Data.” 2017. Web. 17 Apr 2021.

Vancouver:

van Vianen K(. Automatic Incident Detection with Floating Car Data. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 17]. Available from: http://resolver.tudelft.nl/uuid:b4a254a3-0785-4267-97ed-626d162c4244.

Council of Science Editors:

van Vianen K(. Automatic Incident Detection with Floating Car Data. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:b4a254a3-0785-4267-97ed-626d162c4244

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Open Access Theses and Dissertations