1,720,955 research outputs found
Matrix estimation for static traffic assignment models with queuing
No full textA matrix estimation method using the semi dynamic assignment model STAQ is developed exploiting its methodological advantages over full DTA models. The matrix estimation problem is formulated as a bi-level problem and is solved on the node level taking flow metering into account. In the lower level the method uses marginal simulation of the node model within the assignment model to approximate the response function. The implicit relations between turn demand and link flows as defined by the directional capacity proportional node model are analyzed and made explicit. In the upper level an objective function minimizing differences between estimated and observed link flows and differences between prior and posterior ODmatrices is used, both components using a MSE distance function. The two components in the objective function are weighted and normalized. A method to prevent overshooting due to approximation errors is proposed as well as a method to correct the prior ODmatrix in case of insensitivity of the link flow due to supply constraints inconsistent with observed link flows. Test runs are conducted showing that the method finds (non-unique) solutions to the matrix estimation problem when only differences in link flows are taken into account, but may fail to converge when also differences between prior and estimated ODmatrix are taken into account. Further investigation suggests that secondary interaction effects should be included in the response function to solve the problem in these cases
Travel demand matrix estimation methods integrating the full richness of observed traffic flow data from congested networks
No full textIn strategic transport models, road travel demand matrices are usually estimated using estimation methods that fuse prior or synthetic travel demand matrices with flow data observed on individual roads (‘links’) in the network. On the one hand, ever more data on flows, speeds and/or densities on link level is available, driven by technological advances (e.g. PnD’s, smartphones, IoT), trends in transport policy towards smarter usage instead of expansion of the network and the smart mobility concepts arising from them. On the other hand, the urgency of robust and sound estimation procedures is triggered by rising congestion levels on these networks that are at an all-time high.In this paper we address the known difficulties when estimating travel demand using link flows observed on a network with high levels of congestion. Such a network incorporates at least several active bottlenecks, which influence flow values both upstream (queues will form) and downstream (flow is metered). This implies that, on such a network, observed link flow values may represent either 1) the unconstrained travel demand for that link, 2) a proportion of the capacity of a set of upstream links, 3) the capacity of the normative (in terms of capacity deficit) downstream link or 4) a combination of these quantities. Which quantity each observed link flow represents depends on the specific traffic conditions in the network. Note that in practice a very large portion of observed flows is affected by flow metering (2) whereas only a small portion is unaffected (1) or affected by queues (3 or 4).Demand matrix estimation methods use a traffic assignment model to assess the relationship between travel demand and link flow in intercept information. If the assignment model that provides the intercept information does not strictly adhere to link capacity constraints, as with static traffic assignment models, flow metering effects of bottlenecks (2) are not taken into account and all traffic is considered unaffected (1), thereby forcing incorrect assumptions upon the estimation. Therefore, matrix estimation methods using these models should only be applied on observed flows values that are unaffected (1), rendering them mostly useless on networks with high congestion levels. Note that by nature these assignment models should actually not be applied on study areas with congestion altogether.Current practice to use observed flows affected by congestion (2, 3 or 4) is to derive unconstrained link demand values from the observed flow values, for example using the ‘Tonenmethodiek’ (used in the Dutch LMS/NRM models), or similar techniques that shift observed flows to upstream unconstrained links. Then, instead of the actual observed flows, these post-processed link demand values are used during matrix estimation. As such, these methods exhibit poor tractability and robustness and do not integrate any information from the assignment model about the composition of routes on the observed links.This paper describes and compares three novel demand matrix estimation methods for large scale strategic congested transport models that use assignment models that strictly adhere to link capacity constraints, allowing them to explicitly consider the conditions under which link flows are observed. It compares these methods to the current practice and gives practical insights from applications, thereby demonstrating that these methods allow for usage of (big) data sources such as floating car data, congestion patterns and (route) travel time observations. Using these novel approaches, the need to post-process synthetic link demands is taken away, thereby increasing tractability and robustness of the matrix estimation methods and allowing for use of observed congestion patterns as additional input. Furthermore, these methods more efficiently reveal inconsistencies between model link capacities and observed congestion patterns and inconsistencies between count values, allowing the modeler to correct the model network and other matrix estimation input.Authors continue research on the topic, the next goal being to extent the methods to support estimation of OD demand covering multiple time period(s), which should eventually lead to a method that supports 24 hour estimation.Transport and Plannin
Testing of a demand matrix estimation method incorporating observed speeds and congestion patterns on the Dutch strategic model system using an assignment model with hard capacity constraints
No full textTo prepare the Dutch regional and national strategic transport models (LMS/NRM) for policy questions of the future, Rijkswaterstaat – WVL wants to improve the correspondence between link speeds and route travel times estimated by these models in the base year and observed link flows and route travel times. This paper describes a project in which the heavily congested model of NRM-West (the regional model of the Randstad containing Amsterdam, Rotterdam, The Hague and Utrecht) is used as a testcase for modelling improvements to the LMS/NRM to better fit with observed (big) data mentioned before. In this project commissioned by Rijkswaterstaat – WVL, the traffic assignment model of LMS/NRM is replaced by the quasi dynamic traffic assignment model STAQ (first described in Brederode et al., 2010), and the OD matrices are recalibrated taking into account the flow metering effects of active bottlenecks as observed, together with the traditional calibration on observed flows from loop detector data. Because implementation of a different assignment model in the LMS/NRM methodology implies a lot of (potential) side effects to the model system, we restrict ourselves in this project to not make any changes to the software (solve) used for the matrix estimation itself. Instead congestion effects are taken into account while generating assignment matrices (a.k.a. screenline matrices) based on STAQ output. This means that the methods tested within this project can easily be transferred to models using other matrix estimation methods intended to be used with static traffic assignment models. Incorporation of congestion effects into the assignment matrices also allows for direct comparison of flows from the assignment model with observed flows, instead of comparing unconstrained modelled demand with a ‘link demand’ (referred to as ‘wensvraag’ in dutch) estimated from the observed flow, as is currently the case for LMS/NRM. The paper primarily presents (preliminary) results of the project in the form of comparisons of observed congestion patterns, speeds and travel times with assignment results. Furthermore, the paper describes what needed to be done to be able to use STAQ in NRM/LMS, how the flow metering effects on active bottlenecks as calculated by STAQ are used to construct assignment matrices that take flow metering into account, along with pitfalls, limitations and opportunities of the method in practice. Furthermore, the paper provides a perspective on applicability of a matrix estimation method that can include observed travel times (from e.g. floating car data) and distribution patterns (from e.g. GSM data) in its objective function on top of the methodology described above. Depending on progress on this method, which is being undertaken as part of ongoing PhD research of the lead author of this paper, preliminary results on the NRM-West will be included.Transport and Plannin
Adding new modes to existing transport demand gravity models: Methodology for adding disaggregate discrete choice parameters to an aggregate gravity model
No full textThis thesis describes a methodology for adding information about the preferences for new modes from external discrete choice models to exisiting transport demand gravity models. The methodology consists of 4 steps: (i) translation of deterrence functions towards discrete choice utility functions; (ii) linearization of non-linear translated utility functions, (iii) determination of factors to correct the scale of external models and (iv) the specification of the combined model. The thesis provides a case study related to "Urban Mobility as a Service" for the Eindhoven-Veldhoven area to show the practical validity of this methodology.Civil Engineering | Transport and Plannin
Analysing Mobility Hubs using Microsimulation Travel Demand Model: The case of OCTAVIUS
No full textThe traditional transport hubs are shaping into the idea of the mobility hubs with the advent of multiple vehicle-sharing forms, such as bike-sharing and car-sharing. Also, a gradual shift in the culture of consumption towards more usage and less ownership, as well as the shared economy supported by internet platforms and mobile apps, allows easy access to multiple daily mobility choices, especially in urban environments. The Mobility hubs seek to merge conventional public transport with these new shared services which have the potential to serve as a solution to the first/last mile problem within the public transport and will allow operators increase their ridership. Transport demand models are used to forecast future travel demand but consider the same travel behaviour as that of today. Mobility Hubs have the potential to change the travel behaviour of travellers and travel demand models should not only be able to forecast the future travel demand but also take into consideration the potential changes in travel behaviour due to the mobility hubs. This study deals with a microsimulation travel demand model, OCTAVIUS and to identify the extent to which such a microsimulation demand model can capture the travel behaviour associated with the future mobility hubs
Static Traffic Assignment with Queuing: Model properties and applications
No full textThis paper describes the road traffic assignment model Static Traffic Assignment with Queuing (STAQ) that was developed for situations where both static (STA) and dynamic (DTA) traffic assignment models are insufficient: strategic applications on large-scale congested networks. The paper demonstrates how the model overcomes shortcomings in STA and DTA modelling approaches in the strategic context by describing its concept, methodology and solution algorithm as well as by presenting model applications on (small) theoretical and (large) real-life networks. The STAQ model captures flow metering and spillback effects of bottlenecks like in DTA models, while its input and computational requirements are only slightly higher than those of STA models. It does so in a very tractable fashion, and acquires high-precision user equilibria (relative gap < 1E-04) on large-scale networks. In light of its accuracy, robustness and accountability, the STAQ model is discussed as a viable alternative to STA and DTA modelling approaches.Transport and PlanningTransport and Plannin
Extension of a static into a semi-dynamic traffic assignment model with strict capacity constraints
No full textTo improve the accuracy of large-scale strategic transport models in congested conditions, this paper presents a straightforward extension of a static capacity-constrained traffic assignment model into a semi-dynamic version. The semi-dynamic model is more accurate than its static counterpart as it relaxes the empty network assumption, but, unlike its dynamic counterpart, maintains the stability and scalability properties required for application in large-scale strategic transport model systems. Applications show that, contrary to static models, semi-dynamic queue sizes and delays are very similar to dynamic outcomes, whereas only the congestion patterns differ due to the omission of spillback. The static and semi-dynamic models are able to reach user equilibrium conditions, whereas the dynamic model cannot. On a real-world transport model, the static model omits up to 76% of collective losses. It is therefore very likely that the empty network assumption influences (policy) decisions based on static model outcomes.Transport and PlanningTransport and Plannin
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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