"uuid","repository link","title","author","contributor","publication year","abstract","subject topic","language","publication type","publisher","isbn","issn","patent","patent status","bibliographic note","access restriction","embargo date","faculty","department","research group","programme","project","coordinates"
"uuid:5da5eb89-ae79-42a7-bbdd-f3db02efae79","http://resolver.tudelft.nl/uuid:5da5eb89-ae79-42a7-bbdd-f3db02efae79","Advanced Traffic Data for Dynamic Origin-Destination Demand Estimation: State of the Art and Benchmark Study","Djukic, T.; Barcelo, J.; Bullejos, M.; Montero, L.; Cipriani, E.; Van Lint, J.W.C.; Hoogendoorn, S.P.","","2015","In this paper, the use of advanced traffic data is discussed to contribute to the ongoing debate about their applications in dynamic origin-destination (OD) estimation. This is done by discussing the advantages and disadvantages of traffic data with support of the findings of a benchmark study. The benchmark framework is designed to assess the performance of the dynamic OD estimation methods using different traffic data. Results show that despite the use of traffic condition data to identify traffic regime, the use of unreliable prior OD demand has a strong influence on estimation ability. The greatest estimation occurs when the prior OD demand information is aligned with the real traffic state or omitted and using information from automatic vehicle identification (AVI) measurements to establish accurate and meaningful values of OD demand. A common feature observed by methods in this paper indicates that advanced traffic data require more research attention and new techniques to turn them into usable information.","","en","conference paper","TRB","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:cc21a345-100d-4a1c-950e-002139d7a620","http://resolver.tudelft.nl/uuid:cc21a345-100d-4a1c-950e-002139d7a620","Methodology for efficient real time OD demand estimation on large scale networks","Djukic, T.; Van Lint, J.W.C.; Hoogendoorn, S.P.","","2014","In previous work, we have explored the idea of dimensionality reduction and approximation of OD demand based on principal component analysis (PCA). In particular, we have shown how we can apply PCA to linearly transform the high dimensional OD matrices into the lower dimensional space without significant loss of accuracy. Next, we have defined a new transformed set of variables (demand principal components) that is used to represent the OD demand in lower dimensional space. These new variables are defined as state variable in a novel reduced state space model for real time estimation of OD demand. In this paper, we review previous work and continue this line of research. Based on the previous results, we demonstrate the quality improvement of OD estimates using this new formulation and a so-called, ’colored’ Kalman filter approach for OD estimation, in which correlated observation noise is accounted. Moreover, we provide a thorough analysis of the model performance and computational efficiency using real data from a large network, and method for obtaining a reduced set of state variables.","","en","conference paper","Transportation Reseach Board","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:133eab8d-58e9-41d5-8efb-5a54ab0f90df","http://resolver.tudelft.nl/uuid:133eab8d-58e9-41d5-8efb-5a54ab0f90df","Routing strategies based on the macroscopic fundamental diagram","Knoop, V.L.; Hoogendoorn, S.P.; Van Lint, J.W.C.","","2012","An excess number of vehicles in a traffic network will reduce traffic performance. This reduction can be avoided by traffic management. In particular, traffic can be routed such that the bottlenecks are not oversaturated. The macroscopic fundamental diagram provides the relation between the number of vehicles and the network performance. One can apply traffic control on this level, in order to overcome computational complexity of network-wide control using traditional control levels of links or vehicles. Main questions in the paper are: (1) how effective is traffic control using aggregate variables compared to using full information and (2) does the shape of the macroscopic fundamental diagram change under traffic control. A grid network with periodic boundary conditions is used as example, and is split up into several subnetworks. The following routing strategies are compared: (1) the shortest path in distance, (2) the path shortest in time (dynamic due to congestion), (3) an approximation of the path shortest in time, but calculated using only variables aggregated for over a subnetwork, (4) an approximation of the path shortest in time, but calculated using only subnetwork accumulation. For routing strategy 3 and 4 only information aggregated over the subnetwork is used. The results show improved traffic flow using detailed information. Effective control is also possible using aggregated information, but only with the right choice of a subnetwork macroscopic fundamental diagram. Furthermore, when optimizing with detailed information – an hence in a subnetwork – the macroscopic fundamental diagram changes.","","en","conference paper","Transportation Research Board","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:08b4ae06-b920-4bb7-94c3-9184d13eaaf1","http://resolver.tudelft.nl/uuid:08b4ae06-b920-4bb7-94c3-9184d13eaaf1","Emergency evacuation of Tehran city: Simulation results","Joueiai, M.; Van Lint, J.W.C.; Hoogendoorn, S.P.; Pouya, N.","","2014","Tehran is capital of Iran in wide metropolitan area. Large-scale disasters such as earthquakes in such a city cause many casualties and economical damage. One of the most effective risk mitigation actions in such disasters is emergency evacuation. This paper evaluates the dynamics of the vehicular traffic of Tehran under an evacuation condition. The main arterials of the city of Tehran are simulated by a macroscopic traffic flow simulation model (FastLane). The dynamics of traffic in the network are assessed by means of the Network Fundamental Diagram under different loading durations. Simulation results confirm the effect of loading duration and spatial spread of density on network performance. As was previously suggested in the literature, increasing loading duration leads to higher average network flow in the recovery phase compared to maximum network flow in the loading phase. Furthermore, simulation results demonstrate a clear decrease of average velocity by increasing the spatial spread of the densities in the network. These results can be used when making decisions regarding emergency evacuation plans for the city of Tehran.","","en","conference paper","Trail","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:260c7445-ef07-41da-8135-c43819b942e6","http://resolver.tudelft.nl/uuid:260c7445-ef07-41da-8135-c43819b942e6","Data fusion solutions to compute performance measures for urban arterials","Van Lint, J.W.C.; Bertini, R.L.; Hoogendoorn, S.P.","","2014","","","en","conference paper","Transportation Research Board","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:97e02faf-0057-42c9-b875-037e387f614f","http://resolver.tudelft.nl/uuid:97e02faf-0057-42c9-b875-037e387f614f","The impact of traffic dynamics on macroscopic fundamental diagram (poster)","Knoop, V.L.; Hoogendoorn, S.P.; Van Lint, J.W.C.","","2013","","","en","conference paper","","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:27b3bf4f-af1c-4003-9a34-a020edbb1ab0","http://resolver.tudelft.nl/uuid:27b3bf4f-af1c-4003-9a34-a020edbb1ab0","A new generic multi-class kinematic wave traffic flow model: Model development and analysis of its properties","Van Wageningen-Kessels, F.L.M.; Van Lint, J.W.C.; Hoogendoorn, S.P.; Vuik, C.","","2014","We propose and analyze a generic multi-class kinematic wave traffic flow model: Fastlane. The model takes into account heterogeneity among driver-vehicle units with respect to speed and space occupancy: long vehicles with large headways (e.g. trucks) take more space than short vehicles with short headways (e.g. passenger cars). Moreover, and this is what makes the model unique, this effect is larger when the traffic volume is higher. This state dependent space occupancy is reflected in dynamic passenger car equivalent values. The resulting model is shown to satisfy important requirements such as providing a unique solution and being anisotropic. Simulations are applied to compare Fastlane to other multi-class models. Furthermore, we show that the characteristic velocity depends on the truck share, which is one of the main consequences of our modeling approach.","","en","conference paper","TRB","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:74bf5f04-7ad9-42f4-9b35-27b13b258d85","http://resolver.tudelft.nl/uuid:74bf5f04-7ad9-42f4-9b35-27b13b258d85","Data collection by serious gaming","Van den Berg, M.; Doirado, E.; Van Nes, R.; Van Lint, J.W.C.; Prendinger, H.; Hoogendoorn, S.P.","","2012","","","en","conference paper","Trail Research School","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:6f54b309-51d1-453d-ab38-65f927722ed5","http://resolver.tudelft.nl/uuid:6f54b309-51d1-453d-ab38-65f927722ed5","Assessment of multi class kinematic wave models","Van Wageningen-Kessels, F.L.M.; Van Lint, J.W.C.; Vuik, C.; Hoogendoorn, S.P.","","2012","In the last decade many multi class kinematic wave (MCKW) traffic ow models have been proposed. MCKW models introduce heterogeneity among vehicles and drivers. For example, they take into account differences in (maximum) velocities and driving style. Nevertheless, the models are macroscopic and the ow is modeled as a continuum flow, without tracing individual vehicles. The first MCKW models were simple extensions of the mixed class kinematic wave model [1, 2]. For example, Wong and Wong introduced a kinematic wave model with unequal velocities for all classes [3]. More recent MCKW models take into account that some vehicle classes use more road space per vehicle than others and that this space occupancy may change if the velocity changes [4, 5, 6, 7]. Recently, frameworks were proposed to assess fundamental relations [8] and to assess car following traffic ow models [9, 10]. Some important properties of MCKW models have been analyzed before [3, 4, 5, 11, 12, 13], but no consistent assessment framework has been developed yet. Our main contribution is the introduction of a framework for the assessment of MCKW models. It is applied to analyze whether MCKW models have certain important properties. The framework consists of a set of requirements (see Section 2) and a generalized MCKW model (see Section 3). In the full paper we show that all MCKW models known from literature fit in the generalized model. In Section 4 we apply the framework and assess all MCKW models. We conclude that only few models have all desirable properties. Finally, in Section 5 we give an outlook for the full paper.","","en","conference paper","EPFL","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:062de501-08d9-416b-a3df-a7b878c9ccff","http://resolver.tudelft.nl/uuid:062de501-08d9-416b-a3df-a7b878c9ccff","Traffic flow modeling: A genealogy","Van Wageningen-Kessels, F.L.M.; Hoogendoorn, S.P.; Vuik, C.; Van Lint, J.W.C.","","2014","","","en","conference paper","TRB","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:be528909-afaf-4164-abf3-a8610661b329","http://resolver.tudelft.nl/uuid:be528909-afaf-4164-abf3-a8610661b329","Fastlane: Traffic flow modeling and multi-class dynamic traffic management","Schreiter, T.; Van Wageningen-Kessels, F.L.M.; Yuan, Y.; Van Lint, J.W.C.; Hoogendoorn, S.P.","","2012","Dynamic Traffic Management (DTM) aims to improve traffic conditions. DTM usually consists of two steps: first the current traffic is estimated, then appropriate control actions are determined based on that estimate. In order to estimate and control the traffic, a suitable traffic flow model that reproduces the properties of traffic well must be used. One of the most important properties is that traffic is composed of multiple vehicle classes. While many traffic flow models have been proposed and applied in DTM, most of them do not capture the dynamics of multiple vehicle classes. In this paper, we propose a multi-class traffic flow model, Fastlane, that reproduces the dynamics and interactions of different vehicle classes. It is especially well-suited for short term multi-class traffic control on freeways. We show three applications of Fastlane: traffic state estimation, traffic state prediction and pro-active control.","traffic flow; multi-class; traffic management; state estimation; model-predictive control","en","conference paper","TRAIL Research School","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:a0bc67d6-d519-443b-8272-a5664317db27","http://resolver.tudelft.nl/uuid:a0bc67d6-d519-443b-8272-a5664317db27","Vehicle-class Specific Route-guidance of Freeway Traffic by Model-predictive Control","Schreiter, T.; Landman, R.L.; Van Lint, J.W.C.; Hegyi, A.; Hoogendoorn, S.P.","","2012","Few Active Traffic Management measures proposed in the past consider the distinction of different vehicle classes. Examples of vehicle-class specific measures are truck lanes and high-occupancy/toll (HOT) lanes. We propose that the distinction of different vehicle classes, with different flow characteristics and societal and economic function, can contribute to the effectiveness of traffic management measures. In this paper, we develop a multi-class controller that reroutes the traffic class-specifically dependent on the vehicle class. The vehicle-class specific properties such as vehicle length and value of time are used in a model-predictive control approach to optimize the total time spent and the economic costs. Experiments in a simple network with synthetic data show that a multi-class controller outperforms a single-class controller. We further show that the value of time and the incident strength have an influence on which vehicle class is rerouted by the multi-class controller.","","en","conference paper","Transportation Research Board","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:1d036d94-d090-4487-be74-ec1bcdd5271a","http://resolver.tudelft.nl/uuid:1d036d94-d090-4487-be74-ec1bcdd5271a","Data requirements for traffic control on a macroscopic level","Knoop, V.L.; Van Lint, J.W.C.; Hoogendoorn, S.P.","","2011","With current techniques, traffic monitoring and control is a data intensive process. Network control on a higher level, using high level variables, can make this process less data demanding. The macroscopic fundamental diagram relates accumulation, i.e. the number of vehicles in an area, to the network performance, but only holds for situations with homogeneous congestion. This paper shows that subnetwork accumulation and the variation thereof are also good precursors of the network performance. With this result, traffic control can be performed with less data, namely only the accumulation of the subnetworks rather than all speeds and densities for the whole network.","macroscopic fundamental diagram; subnetworks; inhomogeneous congestion","en","conference paper","","","","","","","","","Civil Engineering and Geosciences","","","","",""
"uuid:c12376f2-a34b-468c-8075-0bc9e46d9b3d","http://resolver.tudelft.nl/uuid:c12376f2-a34b-468c-8075-0bc9e46d9b3d","Everscape: The Making of a Disaster Evacuation Experience","Doirado, E.; Van den Berg, M.; Van Lint, J.W.C.; Hoogendoorn, S.P.; Prendinger, H.","","2012","Disaster evacuation studies are important but difficult or impossible to conduct in the real world. Evacuation simulation in a virtual world can be an important tool to obtain data on the escape and choice behavior of people. However, to obtain accurate “realistic” data, the engagement of participants is a key challenge. Therefore, we describe the making of an engaging evacuation scenario called “Everscape”, and highlight the collaborative effort of researchers from the informatics and transportation fields. Further, we describe encouraging results from a pilot study, which investigates the level of engagement of participants of the Everscape experience.","participatory simulation; user experience; collaboration; design; human factors; experimentation","en","conference paper","ACM","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:4342a18a-6175-43ad-9cd0-4d7c5b7aa458","http://resolver.tudelft.nl/uuid:4342a18a-6175-43ad-9cd0-4d7c5b7aa458","The impact of traffic dynamics on macroscopic fundamental diagram","Knoop, V.L.; Hoogendoorn, S.P.; Van Lint, J.W.C.","","2013","Literature shows that – under specific conditions – the macroscopic fundamental diagram (MFD) describes a crisp relationship between the average flow (production) and the average density in an entire network. The limiting condition is that traffic conditions must be homogeneous over the whole network. Recent works describe hysteresis effects: systematic deviations from the MFD as result of loading and unloading. This article proposes a two dimensional generalization of the MFD, the so-called Generalized Macroscopic Fundamental Diagram (GMFD), which relates the average flow to both the average density and the (spatial) inhomogeneity of density. The most important contribution is that we show this is a continuous function. Using this function, we can describe the mentioned hysteresis patterns. The underlying traffic phenomenon explaining the two dimensional surface described by the GMFD is that congestion concentrates (and subsequently spreads out) around the bottlenecks that oversaturate first. We call this the nucleation effect. Due to this effect, the network flow is not constant for a fixed number of vehicles as predicted by the MFD, but decreases due to local queuing and spill back processes around the congestion ”nuclei”. During this build up of congestion, the production hence decreases, which gives the hysteresis effects.","","en","conference paper","Transportation Research Board","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:991b4e50-6720-433c-869c-b0dbb50791a1","http://resolver.tudelft.nl/uuid:991b4e50-6720-433c-869c-b0dbb50791a1","Multi-scale traffic flow theory and modelling","Joueiai, M.; Van Lint, J.W.C.; Hoogendoorn, S.P.","","2012","","","en","conference paper","Trail Research School","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:6c0d4f56-9ac4-4ce8-9d17-fc4f6a3342d3","http://resolver.tudelft.nl/uuid:6c0d4f56-9ac4-4ce8-9d17-fc4f6a3342d3","Bayesian calibration of car-following models","Van Hinsbergen, C.P.IJ.; Van Lint, H.W.C.; Hoogendoorn, S.P.; Van Zuylen, H.J.","","2010","Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model parameter are converted to posterior distributions. The priors and posteriors are then used to calculate the so-called ‘evidence’, which can be used to quantitatively assess how well different models explain one driver’s car-following behavior. When considered over multiple drivers, the evidence represents probabilities for different models as a whole. These model probabilities can be used in a micro simulation, where for each driver first a model is drawn according to these probabilities, after which parameters are drawn from the posterior distribution for each parameter of that model that were obtained when calibrating the model. In a test case on actual data the Bayesian evidence indeed reveals inter-driver differences and it is shown how these differences can quantitatively be assessed","Calibration, car-following model; longitudinal driver behavior; Bayesian evidence; interdriver differences","en","conference paper","IFAC","","","","","","","","Civil Engineering and Geosciences","","","","",""
"uuid:5bbd9737-59ae-43e2-a69d-549b698a38f0","http://resolver.tudelft.nl/uuid:5bbd9737-59ae-43e2-a69d-549b698a38f0","Data fusion solutions to compute performance measures for urban arterials","Van Lint, J.W.C.; Bertini, R.L.; Hoogendoorn, S.P.","","2014","One of the key problems faced by traffic management operators of large urban traffic networks is the lack of sufficient data to compute performance indicators. These indicators, such as travel time, queue length, loss hours, total time spent, are useful for both offline evaluation purposes, as well as online traffic control applications. In the latter case, such data is particularly of use in coordination algorithms that require information on the number of vehicles present or queuing in certain areas. This information in turn is used for example to assess the amount of buffer space available to temporarily store or reroute vehicles from more densely used parts of the network. Computing the amount of vehicles present or queuing in a certain area requires, of course, counting the number of vehicles that enter or exit that area. In this extended abstract we show how through fusing vehicle counts and travel times (measured by any means available), the well-known drift-error can be reduced to virtually zero. In the complete paper we show how this algorithm fits in a wider suite of data fusion tools to compute urban traffic performance indicators on the basis of multiple sources of data","","en","conference paper","TRB","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""
"uuid:57d0cff6-9a0e-4f32-aa43-1c7a94f0ae40","http://resolver.tudelft.nl/uuid:57d0cff6-9a0e-4f32-aa43-1c7a94f0ae40","Efficient real time OD matrix estimation based on principal component analysis","Djukic, T.; Flötteröd, G.; Van Lint, H.; Hoogendoorn, S.P.","","2012","In this paper we explore the idea of dimensionality reduction and approximation of OD demand based on principal component analysis (PCA). First, we show how we can apply PCA to linearly transform the high dimensional OD matrices into the lower dimensional space without significant loss of accuracy. Next, we define a new transformed set of variables (demand principal components) that is used to represent the OD demand in lower dimensional space. We use these new variables as state variable in a novel reduced state space model for real time estimation of OD demand. Through an example we demonstrate the quality improvement of OD estimates using this new formulation and a so-called ‘colored’ Kalman filter over the standard Kalman filter approach for OD estimation, when correlated measurement noise is accounted due to reduction of variables in state vector.","","en","conference paper","TRAIL research school","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:e9b96b41-5495-40ca-9b24-f73e0a0488f3","http://resolver.tudelft.nl/uuid:e9b96b41-5495-40ca-9b24-f73e0a0488f3","New generic multiclass kinematic wave traffic flow model: Model development and analysis of its properties","Van Wageningen-Kessels, F.L.M.; Van Lint, J.W.C.; Hoogendoorn, S.P.; Vuik, C.","","2014","We propose and analyze a generic multi-class kinematic wave traffic flow model: Fastlane. The model takes into account heterogeneity among driver-vehicle units with respect to speed and space occupancy: long vehicles with large headways (e.g. trucks) take more space than short vehicles with short headways (e.g. passenger cars). Moreover, and this is what makes the model unique, this effect is larger when the traffic volume is higher. This state dependent space occupancy is reflected in dynamic passenger car equivalent values. The resulting model is shown to satisfy important requirements such as providing a unique solution and being anisotropic. Simulations are applied to compare Fastlane to other multiclass models. Furthermore, we show that the characteristic velocity depends on the truck share, which is one of the main consequences of our modeling approach.","","en","journal article","","","","","","","","","Civil Engineering and Geosciences","Transport & Planning","","","",""
"uuid:67c3e294-0bbd-488f-933e-dcd79230e616","http://resolver.tudelft.nl/uuid:67c3e294-0bbd-488f-933e-dcd79230e616","Traffic flow modeling: A Genealogy","Van Wageningen-Kessels, F.L.M.; Hoogendoorn, S.P.; Vuik, C.; Van Lint, J.W.C.","","2014","80 years ago, Bruce Greenshields presented the first traffic flow model at the Annual Meeting of the Highway Research Board. Since then, many models and simulation tools have been developed. We show a model tree with four families of traffic flow models, all descending from Greenshields' model. The tree shows the historical development of traffic flow modeling and the relations between models. Based on the tree we discuss the main trends and future developments in traffic flow modeling and simulation.","","en","lecture notes","","","","","","","","","Civil Engineering and Geosciences","Transport and Planning","","","",""