ORCID Profile
0000-0002-1579-1939
Current Organisations
Monash University
,
Southeast University
,
Technische Universiteit Delft
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Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2338-07
Abstract: This paper develops a simple, robust framework for the problem of finding the route with the least expected travel time from any node to any given destination in a stochastic and time-dependent network. Spatial and temporal link travel time correlations are both considered in the proposed solution, which is based on a dynamic programming approach. In particular, the spatial correlation is represented by a Markovian property of the link states, in which each link is assumed to experience congested or uncongested conditions. The temporal correlation is manifested through the time-dependent expected link travel time given the condition of the link traversed. The framework enables the use of a route guidance system, in which at any decision node within a network, a decision can be made on the basis of current traffic information about which node to take next to achieve the shortest expected travel time to the destination. Numerical ex les are presented to illustrate the computational steps involved in the framework to make route choices and to demonstrate the effectiveness of the proposed solution.
Publisher: IEEE
Date: 06-2008
Publisher: IEEE
Date: 10-2011
Publisher: Elsevier BV
Date: 12-2013
Publisher: IEEE
Date: 04-2018
Publisher: SAGE Publications
Date: 16-03-2022
DOI: 10.1177/03611981221078845
Abstract: Traffic jams are caused by a traffic demand that exceeds road capacity. Road capacity, therefore, is an important road feature. This capacity might change as function of time, even for the same road stretch, owing to changing driving behaviors or vehicle characteristics. In this study, we empirically analyzed the changes in road capacity over a 5- to 10-year period. The study differentiated between free flow capacity and queue discharge rate. We used three road stretches that remained unchanged to study free flow capacity. For 143 other locations that experienced changing properties over time, we analyzed queue discharge rates and corrected for external changes. We found that free flow capacity decreased, and queue discharge rates (slightly) increased over time. It is remarkable that one decreased, whereas the other increased. These results could be used in policies for road planning and design. Moreover, they provide an interesting background for further studies analyzing the effects of particular behavioral changes or driver assistance systems.
Publisher: Informa UK Limited
Date: 13-07-2022
Publisher: IEEE
Date: 10-2008
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2321-07
Abstract: Application of dynamic maximum speed limits may lead to positive effects for the environment, safety, and traffic flows. However, the efficacy of this dynamic traffic management measure depends largely on the behavior of drivers (i.e., compliance). In this paper, it is conjectured that compliance does not depend solely on attitudes of drivers but also depends on drivers’ perceptions of the dynamic maximum speed limit signs and mental workload. It is assumed that characteristics of the dynamic maximum speed limit signs influence the perceptions of drivers as well as their mental workload. It is, however, not yet clear to what extent characteristics of the signs influence perception, mental workload, and compliance of drivers. Therefore, two driving simulator experiments were performed to investigate the influence of four factors on drivers’ perception, mental workload, and compliance. The factors studied were the signs’ content, implementation, location, and frequency. From the results, it followed that different effects of these factors could be observed. For ex le, it was observed that the frequency with which dynamic maximum speed limit signs were provided to the drivers had a significant influence on perception and compliance, although a significant effect on mental workload could not be established. The paper concludes with a discussion of results and recommendations for future research.
Publisher: Elsevier BV
Date: 03-2013
Publisher: Elsevier BV
Date: 06-2012
Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 12-2013
Publisher: Elsevier BV
Date: 11-2013
Publisher: Elsevier BV
Date: 10-2018
Publisher: Hindawi Limited
Date: 24-06-2018
DOI: 10.1155/2018/9236028
Abstract: Freeways form an important part of the road network. Yet, driving behavior on freeways, in particular lane changes and the relation with the choice of speed, is not well understood. To overcome this, an online survey has been carried out. Drivers were shown video clips, and after each clip they had to indicate what they would do after the moment the video stopped. A total of 1258 Dutch respondents completed the survey. The results show that most people have a strategy to choose a speed first and stick to that, which is the first strategy. A second, less often chosen, strategy is to choose a desired lane and adapt the speed based on the chosen lane. A third strategy, slightly less frequently chosen, is that drivers have a desired speed, but contrary to the first strategy, they increase this speed when they are in a different lane overtaking another driver. A small fraction have neither a desired speed nor a desired lane. Of the respondents 80% use the right lane if possible, and 80% avoid overtaking at the right. Also 80% give way to merging traffic. The survey was validated by 25 survey respondents also driving an instrumented vehicle. The strategies in this drive were similar to those in the survey. The findings of this work can be implemented in traffic simulation models, e.g., to determine road capacity and constraints in geometric design.
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2278-13
Abstract: The realization of traffic management on a network level is not only theoretically complex, but also practically challenging because the traffic management policy of the road authorities must be taken into account. In the Netherlands, this policy harmonizes the interests of involved stakeholders by means of a common vision on the functioning of the network, expressed in road priorities and the corresponding target service levels. As a result, network states that reflect the policy's objectives in a systematic and comprehensible way must be realized. This paper presents a predictive route guidance approach that is able to operationalize the formulated policy. This approach degrades and restores target service levels of routes according to their difference in priority, with respect to the network performance. The control approach consists of a finite state machine that determines target service levels according to predicted traffic conditions. These target service levels are used as setpoints in a feedback controller, and the result is a corresponding output signal of a variable message sign. By means of a test case, the finite state machine is compared with a model predictive route guidance controller (that realizes system optimal conditions) and with a user equilibrium feedback controller (that realizes user optimal conditions). Results showed that the finite state machine was able to prevent or limit the effects of phenomena that caused decreased network performance in a comprehensible and efficient way while also accounting for the interests of the road users.
Publisher: IEEE
Date: 09-2010
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2330-09
Abstract: Because vessel traffic in ports and waterways is growing quickly, much attention has been given to maritime traffic safety and port capacity. Many simulation models have been used for predicting traffic safety and port capacity in ports and waterways. However, maritime traffic models have considered only a few aspects the influence on safety of human behavior and external factors has not been included. An analysis based on data from an automatic identification system was performed under various external conditions in an investigation of vessel behavior and external influencing factors. The study area included a junction and a slight bend with high maritime traffic density within the port of Rotterdam, Netherlands. Vessels were classified according to type and gross tonnage. Equidistant cross sections approximately perpendicular to the navigation direction were used for investigation of vessel behavior, including speed, course, and path for each vessel category. The influence of external factors (wind and visibility) on vessel behavior was identified through a comparison with the behavior of unhindered vessels. In the analysis, specific thresholds were set for selecting external conditions and eliminating the influence of encounters. The analysis of unhindered vessels for each vessel category provided insight into vessel behavior. The results revealed that wind had an influence on vessel speed and that visibility affected vessel speed, course, and path. Analysis results can be used as input for the development of a new maritime traffic model, as well as for its verification and validation.
Publisher: Elsevier BV
Date: 02-2000
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/5730648
Abstract: Traffic state estimation is a crucial element in traffic management systems and in providing traffic information to road users. In this article, we evaluate traffic sensing data-based estimation error characteristics in macroscopic traffic state estimation. We consider two types of sensing data, that is, loop-detector data and probe speed data. These data are used to estimate the mean speed in a discrete space-time mesh. We assume that there are no errors in the sensing data. This allows us to study the errors resulting from the differences in characteristics between the sensing data and desired estimate together with the incomplete description of the relation between the two. The aim of the study is to evaluate the dependency of this estimation error on the traffic conditions and sensing data characteristics. For this purpose, we use microscopic traffic simulation, where we compare the estimates with the ground truth using Edie’s definitions. The study exposes a relation between the error distribution characteristics and traffic conditions. Furthermore, we find that it is important to account for the correlation between in idual probe data-based estimation errors. Knowledge related to these estimation errors contributes to making better use of the available sensing data in traffic state estimation.
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2249-04
Abstract: Adverse weather conditions have a substantial effect on traffic flow. However, the adaptation effects in longitudinal driving behavior that underlie this impact are unclear, as are the determinants. A driving simulator experiment was performed with a repeated-measures design and 25 participants. The adaptation effects in actual longitudinal driving behavior and the physiological indicators of mental workload (i.e., heart rate and heart rate variability) were measured under two conditions: normal visibility and fog. Significant adaptation effects in longitudinal driving behavior and a significant increase in mental workload were observed. A new estimation method was used to investigate the extent to which fog influenced the position of so-called action points in the (Δv, s) plane of a psycho-spacing model, where Δv was relative speed and s was spacing. In addition, multivariate regression analysis was applied to investigate the extent to which an influence could be observed on acceleration and on jumps in acceleration at the action points. Large differences in the positions of action points in the (Δv, s) plane, acceleration, and jumps in acceleration were observed between conditions therefore, car-following patterns closely resemble those predicted by psycho-spacing theory. However, a large degree of inter- and intradriver heterogeneity was observed, possibly caused by differences in mental workload within and between drivers. This heterogeneity indicates that the assumption of deterministic perceptual thresholds is unrealistic and necessitates the development of a data-driven stochastic model based on the principles of psycho-spacing models.
Publisher: Elsevier BV
Date: 08-2004
Publisher: Hindawi Limited
Date: 2018
DOI: 10.1155/2018/7328074
Abstract: Crowd monitoring systems are more and more used to support crowd management organizations. Currently, counting systems are often used to provide quantitative insights into the pedestrian traffic state, since they are fairly easy to install and the accuracy is reasonably good under normal conditions. However, there are no sensor systems that are 100% accurate. Detection errors might have severe consequences for the density state estimation at large squares. The consequences of these errors for pedestrian state estimation have not yet been determined. This paper studies the impact of one specific type of detection error on the functionality of counting camera systems for density state estimation, namely, a randomly occurring “false negative” detection error. The impact is determined via two tracks, a theoretical track and a simulation track. The latter track studies the distribution of the cumulative number of pedestrians after 24 hours for three stylized cases by means of Monte Carlo simulations. This paper finds that counting camera systems, which have a detection error that is not correlated with the flow rate, provide a reasonably good estimation of the density within an area. At the same time, if the detection error is correlated with the flow rate, counting camera systems should only be used in the situation where symmetric demand patterns are expected.
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 05-2005
Abstract: Traffic operations in public walking spaces are to a large extent determined by differences in pedestrian traffic demand and infrastructure supply. Congestion occurs when pedestrian traffic demand exceeds the capacity. In turn, the latter is determined by a number of factors, such as the width of the bottleneck and the wall surface, as well as the interaction behavior of the pedestrians passing the bottleneck. This article discusses experimental findings of microscopic pedestrian behavior in case of bottlenecks. Results for both a narrow bottleneck and a wide bottleneck are discussed and compared to the results of an experiment without a bottleneck. It is shown how pedestrians inside bottlenecks effectively form layers or trails, the distance between which is approximately 45 cm. This is less than the effective width of a single pedestrian, which is around 55 cm. The layers are thus overlapping, a phenomenon which is referred to as the “zipper” effect. The pedestrians within these layers follow each other at 1.3 seconds, irrespective of the considered experiment. For the narrow bottleneck case (width of one meter) two layers are formed for the wide bottleneck case (width of two meters), four or five layers are formed, although the life span of these layers is rather small. The zipper effect causes the capacity of the bottleneck to increase in a stepwise fashion with the width of the bottleneck, at least for bottlenecks of moderate width (less than 3 m). This has substantial implications for the design of walking facilities.
Publisher: Informa UK Limited
Date: 05-2013
Publisher: Elsevier BV
Date: 2009
Publisher: Springer Science and Business Media LLC
Date: 28-01-2012
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2326-07
Abstract: This paper presents an innovative way to model the decision-making process of the bridge team of a ship. The model aims to provide methods to include human decision making in comprehensive simulation models that can describe the movement of vessels, including hydrodynamic effects external effects due to wind, current, and waves waterway geometry and the interaction with other vessels. The paper uses a simple model to describe a vessel's dynamics and the impact of the control decisions on these dynamics, although generalization to more comprehensive maneuver models is straightforward. The mathematical modeling framework is presented on the basis of a set of behavioral assumptions. The model is described as a differential game in which the bridge team is assumed to react on the expected behavior of other vessels. Different behavioral strategies (risk prone, average risk, and neutral risk) lead to the different models described in the paper. The dynamics of the model are illustrated by simple ex les. The results are plausible and clearly show the potential of the approach. The paper offers some direction for future development.
Publisher: Elsevier BV
Date: 06-2007
Publisher: Elsevier BV
Date: 11-2013
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2230-03
Abstract: Various decision theories have been used to explain travelers' behavior. This paper presents a comparative analysis from the points of view of theory and application of the expected utility theory, prospect theory, and regret theory. The application was based on an empirical data set on route choice behavior with and without information provision. Results show that despite the widespread use of expected utility theory to model travelers' behavior, the use of prospect theory is quite appropriate and promising, especially when information is provided. The reference point plays an important role in the prediction ability of prospect theory. The greatest prediction ability occurs when the reference point is aligned with the observed behavior and thus reinforces the necessity of establishing appropriate and meaningful values. This study empirically shows the potential of alternatives to expected utility theory to capture travelers' behavior better, as in the case of prospect theory under the proposed model specification, but this is not necessarily true, as demonstrated by the results obtained by use of regret theory.
Publisher: WIT Press
Date: 27-06-2006
DOI: 10.2495/CR060011
Publisher: Wiley
Date: 21-08-2009
Publisher: Informa UK Limited
Date: 21-09-2018
Publisher: IEEE
Date: 06-2009
Publisher: IEEE
Date: 06-2012
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2129-07
Abstract: Video data are being used more often to study traffic operations. However, extracting vehicle trajectories from video by current methods is a difficult process, typically resulting in many errors. The process requires extensive labor to correct the trajectories manually. This paper proposes a method to process video data from traffic operations. Instead of detecting a vehicle in each picture of the video separately, the video data are transformed so that the trajectories of the vehicles (their position over time) become visible in a single image. In this single image, the trajectories can be found by detecting lines. The difference from other methods is that trajectories rather than vehicles are detected. Trajectory (line) detection is more robust than vehicle (rectangle) detection with this method, about 95% of the trajectories are detected correctly and, more important, the segments of each trajectory are much longer compared with results from other methods in the literature. Also, the detection is a quick process because only a single image is required to be analyzed. For a data set 5 min long, transforming costs several minutes, and automatically detecting and tracking costs 40 to 50 min per lane. Manual correction is then necessary, which costs about 10 min per lane. In contrast, with a different method the total processing time for analyzing traffic operations costs about 1 week for all lanes together.
Publisher: Elsevier BV
Date: 11-2019
Publisher: IEEE
Date: 09-2012
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2308-13
Abstract: Lane utilization on the highway is affected subtly by dynamic traffic management systems such as speed controls and lane management. To optimize the operation of dynamic traffic management, a better understanding of lane utilization is required, in particular, of how the flows of different vehicle classes (e.g., passenger cars, lorries) vary across the carriageway. Most loop detector systems do not collect this multilane, multiclass count data. This study developed a procedure for estimating multilane, multiclass counts from a variety of standard aggregate loop data formats from around the world. The estimation procedure involved the inference of multilinear regression laws that relate multilane, multiclass data to standard aggregate formats. The regression laws were then trained with small s les of in idual vehicle data on a site-by-site basis. Preliminary results showed that the estimation procedure worked rather well, even when the input data were minimal—the extreme case being that of (U.S.-style) single-loop data, for which only flow and occupancy were available on a by lane basis. An error analysis indicated that small amounts of in idual vehicle data were sufficient to train the estimator, provided they contained a representative mix of the flow behaviors at the site in question. Further work is required for the practical development of the tool, but it appears to have a wide range of potential uses for both researchers and practitioners.
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2359-05
Abstract: This paper presents a quick-scan approach to assess the cost-effectiveness of smaller and poorly demarcated transportation measures the approach can be used as an initial scan while packages are established to solve specific transportation problems. This paper adds to the available evaluation literature and relies on a combination of expert opinions and simple models rather than on data-intensive, four-stage transportation models. The approach consists of five steps and yields an assessment of the cost-effectiveness of the measure that is being evaluated. As an illustration of this approach, the cost-effectiveness of a pricing measure within a large Dutch travel demand management program was determined to illustrate the approach itself and the plausibility of its results. It was concluded that the proposed method was suitable for an initial quick-scan assessment. This assessment would be valuable in the first selection of packages of measures and could support policy makers who must decide in which measures to invest, even when those measures have not yet been described or designed at a highly detailed level.
Publisher: Wiley
Date: 20-02-2012
DOI: 10.1002/ATR.210
Publisher: Informa UK Limited
Date: 13-04-2023
Publisher: Informa UK Limited
Date: 04-01-2020
Publisher: Springer Science and Business Media LLC
Date: 16-12-2010
Publisher: Elsevier BV
Date: 2009
Publisher: Informa UK Limited
Date: 28-01-2021
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2234-10
Abstract: Estimation of the time needed to evacuate a population from a threatened area in case of a disaster is one of the main issues in the design of an evacuation plan. The challenge is to develop a strategy that optimally uses the network capacity to minimize the total evacuation time. In this paper, the impacts of various departure time spans on evacuation time and network performance are investigated with a microscopic traffic simulation model. The network performance has been analyzed with the use of the macroscopic fundamental diagram (MFD). Although the MFD usually shows a decrease in travel production after a peak is reached, this is not the case in the simulation of evacuation scenarios. The outflow of the network remains constant because it depends on the capacity of local bottlenecks upstream of the limited number of destinations, but the number of vehicles in the network increases because of an increase in congestion. Although the overall network performance is insensitive to the evacuation time spans, it is observed that for shorter evacuation time spans, internal gridlock effects cause lengthy delays for specific groups of drivers, who, it turns out, are unable to leave the network in time. The use of a simulation study in combination with an MFD can therefore identify the routes used and the bottlenecks on these routes leading to the destinations, while the maximum production level (defined as the number of arrivals, determined in the MFD) indicates the optimal level of demand.
Publisher: Elsevier BV
Date: 04-2011
Publisher: Elsevier BV
Date: 08-2019
Publisher: IEEE
Date: 10-2011
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2124-04
Abstract: Parameter values obtained by calibrating a car-following model using trajectory observations can provide important new insights into longitudinal driving behavior that cannot be derived from double loop detector data. However, that holds only if these behavioral parameters can be reliably estimated. This important aspect of calibration has been generally neglected in scientific research. In this contribution, therefore, calibrations are done to analyze several aspects influencing the degree to which behavioral parameters can be reliably estimated. In these calibrations trajectory data created by the authors with known characteristics as well as empirical trajectories are used. It is shown that traffic conditions during observation determine which model parameters can be reliably estimated. That measurement errors do negatively influence the reliability of parameter estimates is also demonstrated. The same negative effect appears to occur when a car-following model not fully able to capture the dynamics of the observed driver is calibrated. Finally, it is found that the extent to which a specific parameter can be reliably estimated is dependent on the degree to which it affects model predictions and thereby the value of the calibration objective. From this contribution it is concluded that to answer a specific research question on longitudinal driving behavior, it is essential to collect trajectories during appropriate traffic conditions. The results furthermore stress that even when trajectories contain enough information to calibrate the behavioral parameters of interest, whether it is reliable enough to draw inferences on car-following behavior needs to be determined for every parameter value separately.
Publisher: Springer Science and Business Media LLC
Date: 06-2005
Publisher: Informa UK Limited
Date: 16-08-2019
Publisher: Informa UK Limited
Date: 2020
Publisher: Elsevier BV
Date: 12-2009
Publisher: IEEE
Date: 10-2008
Publisher: Elsevier BV
Date: 2010
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 2010
Publisher: Elsevier BV
Date: 2010
Publisher: SAGE Publications
Date: 2007
DOI: 10.3141/2039-07
Abstract: To support traffic operators in regional traffic management centers with their network control tasks, the Traffic Research Center of the Dutch Ministry of Transportation has proposed a two-step scenario-based approach. In the first step, traffic engineers prepare candidate traffic control scenarios that are likely to resolve problems that occur in real-world network traffic operations. In the second step, network operators can try out a limited number of control scenarios with an online prediction system to see which of these best resolves the problems at hand. To prepare the scenarios, a scenario assessment system is used that predicts the impacts of a specific control scenario by using a dynamic network traffic flow model (MetaNet). The development of a fully automated calibration approach for the input and parameters of this macroscopic network simulation model is described. The approach presented consisted of four steps—preparing inflows and turning proportions, establishing lane-specific traffic flow parameters, estimating the global simulation parameters, and determining unresolved model inputs—eventually leading to input data and a set of parameters that yield the best prediction of networkwide traffic conditions. Furthermore, the approach checks the available input data for inconsistencies in terms of network configuration and measurement errors. On the basis of the application ex les tested, the approach is well suited for the calibration task at hand, yielding a remarkable improvement in the prediction error. Furthermore, the computation time for a realistic network is sufficient for most practical applications.
Publisher: Elsevier BV
Date: 2009
Publisher: Elsevier BV
Date: 2009
Publisher: Springer Science and Business Media LLC
Date: 30-03-2011
Publisher: Springer Science and Business Media LLC
Date: 14-05-2020
DOI: 10.1007/S11116-020-10110-2
Abstract: Simulation studies suggest that pooled on-demand services (also referred to as Demand Responsive Transport, ridesharing, shared ride-hailing or shared ridesourcing services) have the potential to bring large benefits to urban areas while inducing limited time losses for their users. However, in reality, the large majority of users request in idual rides (and not pooled rides) in existing on-demand services, leading to increases in motorised vehicle miles travelled. In this study, we investigate to what extent fare discounts, additional travel time, and the (un)willingness to share the ride with (different numbers of) other passengers play a role in the decision of in iduals to share rides. To this end, we design a stated preference study targeting Dutch urban in iduals. In our research, we (1) disentangle the sharing aspect from related time–cost trade-offs (e.g. detours), (2) investigate preference heterogeneity regarding the studied attributes and identify distinct market segments, and (3) simulate scenarios to understand the impact of the obtained parameters in the breakdown between in idual and pooled services. We find that less than one third of respondents have strong preferences against sharing their rides. Also, we find that different market segments vary not only in their values of the willingness to share, but also in how they perceive this willingness to share (per-ride or proportional to the in-vehicle time). Further, the scenario analysis demonstrates that the share of in iduals who are willing to share rides depends primarily on the time–cost trade-offs, rather than on the disutility stemming from pooling rides per se.
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2260-17
Abstract: A new data-driven stochastic car-following model based on the principles of psychospacing or action-point modeling is presented. It uses empirical or experimental trajectory data and mimics the main microscopic behavioral characteristics present in the data. In the action-point model, regions are defined in the relative speed–distance headway plane, in which the follower is likely to perform an action (increase or decrease acceleration) or not. These regions can be established empirically from vehicle trajectory data and thereby yield a joint cumulative probability distribution function of the action points. Furthermore, the conditional distribution of the actions (the size of the acceleration or deceleration given the current distance headway and relative speed or given the acceleration before the action) can be determined from these data as well. To assess the data correctly, a new filtering technique is proposed. The main hypothesis behind this idea is that the speed profile is a continuous piecewise linear function: accelerations are piecewise constant changing values at nonequidistant discrete time instants. The durations of these constant acceleration periods are not fixed but depend on the state of the follower in relation to its leader. The data analysis illustrates that driving behavior shows nonequidistant constant acceleration periods. The distributions of the action points and the conditional accelerations form the core of the presented data-driven stochastic model. The mathematical formalization that describes how these distributions can be used to simulate car-following behavior is presented. Empirical data collected on a Dutch motorway are used to illustrate the workings of the approach and the simulation results.
Publisher: Informa UK Limited
Date: 28-12-2017
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2260-14
Abstract: With increasing public concern about the environment, livability and sustainability have become important issues in dynamic traffic management (DTM). Microscopic fuel consumption and emission models use vehicle speed and acceleration as inputs and are suitable for investigating the environmental effects of DTM measures at the link level. However, the lack of microscopic traffic data limits the application of these models. A method is provided for acquiring microscopic information from macroscopic traffic data. The main approach is to reconstruct the traffic state and vehicle group trajectories with an adaptive smoothing method, derive acceleration from the reconstructed vehicle trajectories, and calculate fuel consumption and emissions with filtered speed and estimated acceleration as inputs. The derived acceleration is compared with vehicle trajectories from simulation. Validation of the method shows that the estimated acceleration reflects the congestion characteristics. A case study investigating the environmental benefits of a freeway control algorithm on a Dutch freeway was conducted to illustrate the application potential of the method.
Publisher: Elsevier BV
Date: 2010
Publisher: SAGE Publications
Date: 2007
DOI: 10.3141/2014-01
Abstract: Performing the same trip many times, travelers can learn about available routes from their experiences. Two types of learning found in psychological learning theory appear to play a role in day-to-day route choice: implicit (reinforcement-based) and explicit (belief-based). Memory decay also plays a major role. Although much progress had been made in modeling learning in route choice, a model that captures both learning types and for which the parameters are empirically underpinned was not found. Such a model thus is developed, and a large data set from experimental research is used to validate it and to estimate its parameters. The developed model uses a Markov formulation for the day-to-day updating of a person's belief about travel time (i.e., perceived travel time) on a route. Reinforcement (and inertia) is modeled by including the latest 10 route choices in the model. Results indicate that 20% of perceived travel time is from the most recent experience therefore, formulations that use either the mathematical mean of all past experienced travel times or only the most recent travel times are not accurate. Furthermore, the reinforcement–inertia part of the model can make up a significant part of the route utility and therefore should be a standard component in route choice models. In sum, the results validate the theoretical and mathematical model.
Publisher: IEEE
Date: 09-2010
Publisher: Elsevier BV
Date: 10-2018
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2161-05
Abstract: Macroscopic fundamental diagrams (MFDs) exist in large urban networks in which traffic conditions are homogenous. They can be used for estimation of the level of service on road networks, perimeter control, and macroscopic traffic modeling. However, before the MFD concept can be applied, the factors that influence the MFD shape should be identified and their effects investigated. A microscopic simulation model is used to change conditions, that is, to derive MFDs under different conditions and for different types of networks. Results indicate that a relationship indeed exists between production and accumulation for the whole network as well as for parts of the network focused on freeway or urban links. MFD shape is a property not only of the network itself but also of the applied traffic control measures. At the same time, congestion onset and resolution lead to heterogeneous traffic conditions with congestion at specific locations in the network, resulting in loops in congested parts of the MFD. Investigation of the effect of traffic demand on MFD also indicates that rapidly changing traffic demands drastically affect MFD shape.
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2124-14
Abstract: This investigation focuses on how the heterogeneity of pedestrian characteristics influences the buildup of congestion and affects the efficiency of pedestrian flows. Three commonly used parameters in pedestrian models–-desired speed, body size, and reaction time–-were varied in the population. Real pedestrian flows are heterogeneous regarding pedestrian characteristics. However, not much is known about the way that affects the qualities of the flow and how important it is to the outcomes of microsimulation models. The NOMAD model developed by Delft University of Technology is used to perform simulations in which the aforementioned heterogeneity is introduced. The investigation was carried out by creating bidirectional flows with fixed demands. The flows were analyzed by observing the development of breakdowns, average speeds, and average densities for different demands. It is shown that the influence of heterogeneity on breakdown probabilities and flow efficiency is considerable. To investigate this further, the dynamic lane formation process is investigated in detail. In addition to further insights into the causes for breakdown, it is found that the number of lanes increases with the decrease in heterogeneity in desired speed and in body size. However the opposite happens for heterogeneity in reaction time. Results indicate that heterogeneity in the population has a large impact on the flow quality and should be included in models explicitly to improve prediction performance.
Publisher: IEEE
Date: 09-2010
Publisher: Wiley
Date: 2003
DOI: 10.1002/OCA.727
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2009
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2291-06
Abstract: For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia the National Institute of Informatics, Tokyo and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academics from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2012
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2188-12
Abstract: The ability of microscopic (simulation) models to represent lane-changing behavior according to reality has recently been questioned. In this paper the merging maneuver (a specific type of lane changing) is analyzed with empirical data. First, a conceptual model is composed it includes the factors influencing merging behavior, namely the merge location and its relation to prevailing driving conditions, gap acceptance, and the relaxation phenomenon. The empirical data set consists of 35 min of vehicle maneuvers on 400 m of freeway, collected by a camera mounted underneath a helicopter. This process results in a data set of 3,459 vehicle trajectories, from which 704 trajectories describe merging vehicles. It is found that different merge locations are used under congested and freeflow traffic conditions. During free-flow, most vehicles merge at the first half of the acceleration lane. Under congested traffic conditions, relatively more merges are registered at the end of the acceleration lane. The smallest accepted gap observed in the data set lies between 0.75 and 1.0 s. Net headways between the merging vehicle and the new leader and new follower of less than 0.25 s are recorded. These short accepted gaps are growing over time and indicate relaxation behavior. From the data analysis it can be concluded that gap acceptance theories, as they are used in current models and theories to model merge behavior, are not able to model the observed behavior accurately.
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2302-10
Abstract: With the reliability of travel time high on the political agenda, tools are needed to predict these indicators for the reliability of travel time in ex ante evaluations. In this paper such a framework is developed for assessing traffic measures and policies under a range of scenarios, with a particular focus on the resulting travel time distribution. The framework uses Monte Carlo s ling to generate stochastic realizations of demand and supply characteristics. The former characteristics relate to variations in travel patterns, the latter to variations in drive behavior (capacities, speeds). An extensive effort is made to account for variability in demand and supply resulting from weather, road work, special events, and so forth. The overall conclusion is that incorporating the variability of demand and supply characteristics has a large effect on the results of evaluation studies. This effect is demonstrated in an ex le case on a real Dutch traffic network, in which a typical dynamic measure, the opening of a peak hour lane, is evaluated with the framework. In this case, the average demand and supply conditions used for the one-shot evaluation lead to an underestimation of spillback effects, which are captured when evaluating over a wide range of demand and supply characteristics. As a result, the gains in average travel time are significantly underestimated in the one-shot procedure (6% instead of 26%). Further research should focus on improving speed and validity over a wider range of circumstances of the developed framework.
Publisher: IEEE
Date: 09-2012
Publisher: IEEE
Date: 04-2011
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 06-2018
Abstract: An efficient simulation method for two-dimensional continuum pedestrian flow models is introduced. It is a two-dimensional adaptation of the Godunov scheme for one-dimensional road traffic flow models. It is further extended to include multiple classes, representing groups of pedestrians with different behavior, origin, and destination. The method can be applied to continuum pedestrian flow models in a wide range of applications from the design of train stations and other travel hubs to the study of crowd behavior and safety at sports, religious, and cultural events. The combination of the efficient simulation method with continuum models enables the user to get simulation results much quicker than before. This opens doors to real-time crowd control and to more advanced optimization of planning and control. Test results show the importance of choosing appropriate numerical settings, including grid cell and time step size for realistic simulation results.
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2283-09
Abstract: Prediction of the time evolution of origin–destination (O-D) matrices is important for many applications in the traffic domain. These applications range from ex ante evaluation to real-time prediction and control. Since O-D matrices are high-dimensional multivariate data structures, both the specification and the estimation of O-D prediction models are methodologically and computationally cumbersome. This paper demonstrates that a significant reduction of the dimensionality of the O-D data that preserves structural patterns can dramatically reduce computational costs without a significant loss of accuracy. This paper explores the application of principal component analysis (PCA) for this purpose. PCA shows that the dimensionality of the time series of O-D demand can be reduced significantly. This paper also shows how the results from the PCA method can be used to reveal the structure in the underlying temporal variability patterns in dynamic O-D matrices. The results indicate three main patterns that can be distinguished in dynamic O-D matrices: structural, structural deviation, and stochastic trend patterns. Insight into how these trends contribute to each O-D pair and how this information can be further used to predict dynamic O-D matrices on the basis of a set of dynamic O-D matrices obtained from real data is provided.
Publisher: The Royal Society
Date: 13-10-2010
Abstract: Parameter identification of microscopic driving models is a difficult task. This is caused by the fact that parameters—such as reaction time, sensitivity to stimuli, etc.—are generally not directly observable from common traffic data, but also due to the lack of reliable statistical estimation techniques. This contribution puts forward a new approach to identifying parameters of car-following models. One of the main contributions of this article is that the proposed approach allows for joint estimation of parameters using different data sources, including prior information on parameter values (or the valid range of values). This is achieved by generalizing the maximum-likelihood estimation approach proposed by the authors in previous work. The approach allows for statistical analysis of the parameter estimates, including the standard error of the parameter estimates and the correlation of the estimates. Using the likelihood-ratio test, models of different complexity (defined by the number of model parameters) can be cross-compared. A nice property of this test is that it takes into account the number of parameters of a model as well as the performance. To illustrate the workings, the approach is applied to two car-following models using vehicle trajectories of a Dutch freeway collected from a helicopter, in combination with data collected with a driving simulator.
Publisher: SAGE Publications
Date: 13-05-2023
DOI: 10.1177/03611981231166947
Abstract: When making trips in urban environments, cyclists lose time as they stop and idle at signalized intersections. The main objective of this study was to show how augmenting the situational awareness of traffic signal controllers, using observations from moving sensor platforms, can enable prioritization of cyclists and reduce lost time within the control cycle in an effective way. We investigated the potential of using observations from connected autonomous vehicles (CAVs) as a source of new information, using a revised vehicle-actuated controller. This controller exploits CAV-generated observations of cyclists to optimize the control for cyclists. The results from a simulation study indicated that with a low CAV penetration rate, prioritizing cyclists by tracking reduced cyclist delays and stops, even with a small field of view. As the delay of car directions were not taken into account in this study, the average car delay increased considerably with an increasing number of cyclists. Future work is needed to optimize the control that balances the delays and stops of cyclists and cars.
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2263-05
Abstract: One of the key traffic variables required for the ex post and ex ante evaluation of traffic management and policy measures is origin–destination (O-D) demand matrices. Without ground truth O-D information, however, it is difficult, if not impossible, to assess the quality of an O-D estimation method because so many unknowns are involved. One indicator of the quality of an O-D estimation method is the sensitivity of the method to, and its robustness against, random and structural perturbations of the input from a few typical test networks (e.g., data from sensors, prior O-D matrices). In this paper, an assessment methodology is proposed on the basis of the Latin hypercube method, which is an efficient alternative to Monte Carlo s ling and particularly suited for high-dimensional estimation problems. The methodology is demonstrated on a real urban corridor network for a well-known O-D estimation method (the minimum information estimation method) to illustrate the results that can be obtained and how these results can be used to benchmark different O-D estimation methods.
Publisher: SAGE Publications
Date: 27-07-2021
DOI: 10.1177/03611981211032648
Abstract: Traffic engineers rely on microscopic traffic models to design, plan, and operate a wide range of traffic applications. Recently, large data sets, yet incomplete and from small space regions, are becoming available thanks to technology improvements and governmental efforts. With this study we aim to gain new empirical insights into longitudinal driving behavior and to formulate a model which can benefit from these new challenging data sources. This paper proposes an application of an existing formulation, Gaussian process regression (GPR), to describe in idual longitudinal driving behavior of drivers. The method integrates a parametric and a non-parametric mathematical formulation. The model predicts in idual driver’s acceleration given a set of variables. It uses the GPR to make predictions when there exists correlation between new input and the training data set. The data-driven model benefits from a large training data set to capture all driver longitudinal behavior, which would be difficult to fit in fixed parametric equation(s). The methodology allows us to train models with new variables without the need of altering the model formulation. And importantly, the model also uses existing traditional parametric car-following models to predict acceleration when no similar situations are found in the training data set. A case study using radar data in an urban environment shows that a hybrid model performs better than parametric model alone and suggests that traffic light status over time influences drivers’ acceleration. This methodology can help engineers to use large data sets and to find new variables to describe traffic behavior.
Publisher: Hindawi Limited
Date: 28-08-2020
DOI: 10.1155/2020/9272845
Abstract: An increasing number of people use the bicycle for urban trips resulting in local congestion at intersections, especially during peak hours. Understanding the queue dynamics is key to find the correct measures that can reduce the delays for cyclists without affecting other traffic modes. To this end, the discharge process of bicycle queues is studied, focusing on the impact of jam density on the queue discharge rate and how this process is affected by cyclists that merge into the queue during the discharge phase. The impact of merging cyclists is captured by a newly introduced bicycle equivalent (BE) value. This direction-specific BE value is used to convert a merging cyclist into a cyclist that is waiting in the original queue. Results show that the queue discharge rate increases with increasing density of the queue. Furthermore, cyclists that merge by overtaking contribute to the queue discharge rate, while cyclists who merge from a perpendicular direction hinder the discharge process, thereby decreasing the bicycle flow at the intersection. The insights can be used to develop measures which minimise delay at intersections and to design efficient infrastructure for bicyclists.
Publisher: Informa UK Limited
Date: 07-05-2021
Publisher: Elsevier BV
Date: 2010
Publisher: SAGE Publications
Date: 21-08-2021
DOI: 10.1177/03611981211029919
Abstract: Public transport in rural areas is under pressure because demand is low and dispersed. To reduce costs, flexible and on-demand services are often proposed as alternatives for conventional bus services. Conventional services are generally not suitable for rural areas, because the demand is low and dispersed. In this paper, a stated preference survey is designed to identify the preferences of rural bus users for alternative services. Other than the traditional bus, two other modes are included in this study: a demand responsive transport (DRT) service and an express bus service with bike-sharing services for last mile transport. Given the on-demand nature of these alternatives, flexibility- and reliability-related attributes are included in the stated preference survey. The results from the choice model indicate that the reliability and flexibility aspects do not have a large effect on the preference for the on-demand alternatives. Instead, cost, access and egress times, and in-vehicle time play a bigger role in in iduals’ preferences toward the different alternatives. A sensitivity analysis shows that changes in the operational characteristics can make the on-demand alternatives more attractive. However, many bus users still prefer the conventional bus service over the on-demand alternatives.
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/8483750
Abstract: This paper describes a study which gives insight into the size of improvement that is possible with in idual in-car routing advice based on the actual traffic situation derived from floating car data (FCD). It also gives an idea about the required penetration rate of floating car data needed to achieve a certain degree of improvement. The study uses real loop detector data from the region of Amsterdam collected for over a year, a route generating algorithm for in-car routing advice, and emulated floating car data to generate the routing advice. The case with in-car routing advice has been compared to the base case, where drivers base their routing decisions on average knowledge of travel times in the network. The improvement in total delay using the in-vehicle system is dependent on penetration rate and accuracy of the floating car data and varies from 2.0% to 3.4% for 10% penetration rate. This leads to yearly savings of about 15 million euros if delay is monetarised using standard prices for value of time (VOT).
Publisher: Elsevier BV
Date: 07-2009
Publisher: IEEE
Date: 09-2010
Publisher: Elsevier
Date: 2007
Publisher: Elsevier BV
Date: 2011
Publisher: Elsevier BV
Date: 10-2005
Publisher: Hindawi Limited
Date: 03-07-2019
DOI: 10.1155/2019/5874085
Abstract: Ideally, a multitude of steps has to be taken before a commercial implementation of a pedestrian model is used in practice. Calibration, the main goal of which is to increase the accuracy of the predictions by determining the set of values for the model parameters that allows for the best replication of reality, has an important role in this process. Yet, up to recently, calibration has received relatively little attention within the field of pedestrian modelling. Most studies focus only on one specific movement base case and/or use a single metric. It is questionable how generally applicable a pedestrian simulation model is that has been calibrated using a limited set of movement base cases and one metric. The objective of this research is twofold, namely, to (1) determine the effect of the choice of movement base cases, metrics, and density levels on the calibration results and (2) to develop a multiple-objective calibration approach to determine the aforementioned effects. In this paper a multiple-objective calibration scheme is presented for pedestrian simulation models, in which multiple normalized metrics (i.e., flow, spatial distribution, effort, and travel time) are combined by means of weighted sum method that accounts for the stochastic nature of the model. Based on the analysis of the calibration results, it can be concluded that (1) it is necessary to use multiple movement base cases when calibrating a model to capture all relevant behaviours, (2) the level of density influences the calibration results, and (3) the choice of metric or combinations of metrics influence the results severely.
Publisher: Elsevier BV
Date: 11-2013
Publisher: Elsevier BV
Date: 09-2013
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2188-05
Abstract: Microscopic simulation models have become widely applied tools in traffic engineering. Nevertheless, parameter identification of these models remains a difficult task. This is partially because parameters are generally not directly observable from common traffic data also there is a lack of reliable statistical estimation techniques. This study puts forward a new general and structured approach to identifying parameters of car-following models. One of the main contributions of this study is joint estimation of parameters for multiple vehicles. Furthermore, prior information on the parameter values (or the valid range of values) can be estimated. The study also deals with serial correlation in the trajectory data. In doing so, the newly developed approach generalizes the maximum likelihood estimation approach proposed by the authors. The approach allows for statistical analysis of the model estimates, including the standard error of the parameter estimates and the correlation of the estimates. With the likelihood ratio test, models of different complexity (defined by the number of model parameters) can be cross-compared. A useful property of this test is that it takes into account the number of parameters of a model as well as the performance. The approach is applied to car-following behavior by using Dutch freeway vehicle trajectories collected from a helicopter.
Publisher: Informa UK Limited
Date: 21-02-2023
Publisher: Hindawi Limited
Date: 29-06-2021
DOI: 10.1155/2021/5594738
Abstract: Commercial areas, especially urban ones with numerous buildings, are becoming increasingly prone to congestion because of their popularity. Visual inspections show that interactions between pedestrians and building entrances affect the distribution of pedestrian trajectories, which influences the utility of pedestrian spaces and the design of urban shopping areas. Herein, we analyse the dynamics of pedestrian deviations around building entrances. We used a video recorded using an unmanned aerial vehicle to determine pedestrian trajectories in a Chinese commercial walking space. First, the candidate variables affecting deviation behaviours were determined via correlation testing. Second, two regression models were developed by considering the deviation behaviours of pedestrians walking past a building entrance. The models suggest that the starting position of a pedestrian’s deviation, the total pedestrian flow at the building entrance, the density in an area in the vicinity of the entrance, and the number of interacting pedestrians impact the total distance traversed during path deviation.
Publisher: Informa UK Limited
Date: 21-10-2021
Publisher: Informa UK Limited
Date: 29-03-2021
Publisher: Elsevier BV
Date: 2009
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2188-04
Abstract: The kinematic wave model is often used in simulation tools to describe dynamic traffic flow and to estimate and predict traffic states. Discretization of the model is generally based on Eulerian coordinates, which are fixed in space. However, the Lagrangian coordinate system, in which the coordinates move with the velocity of the vehicles, results in more accurate solutions. Furthermore, if the model includes multiple user classes, it describes real traffic more accurately. Such a multiclass model, in contrast to a mixed-class model, treats different types of vehicles (e.g., passenger cars and trucks or vehicles with different origins or destinations, or both) differently. The Lagrangian coordinate system is combined with a multiclass model, and a Lagrangian formulation of the kinematic wave model for multiple user classes is proposed. It is shown that the advantages of the Lagrangian formulation also apply for the multiclass model. Simulations based on the Lagrangian formulation result in more accurate solutions than simulations based on the Eulerian formulation.
Publisher: Elsevier BV
Date: 05-2001
Publisher: Informa UK Limited
Date: 04-12-2021
Publisher: Elsevier BV
Date: 09-2005
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2256-10
Abstract: The limited coordination between public and private actors in the fields of traffic information and management has led to reduced efficiency and sometimes undesirable situations. The main objective of the Strategic Council for Traffic Information and Traffic Management installed by the Dutch Ministry of Transportation is to develop a joint strategy for the development and the organization of traffic information and traffic management by public authorities and private parties. This strategy will outline future developments and related actions, as well as the organization and roles of the relevant actors for traffic management and information activities. To satisfy these requirements, a proposed scenario-based approach entails sketching different scenarios to describe the situations in 2015, 2020, and 2028 for public and private stakeholders involved in traffic management and traffic information. The approach to determine these scenarios, the scenarios themselves, and their implications are described. The developed scenarios were built around the dimension of freedom of choice of the traveler. After extreme scenarios were identified, possible scenarios were sketched and were linked to instruments and to multiple objectives. On the basis of the scenarios, no-regret activities (those beneficial regardless of scenario) were identified as part of the robust strategy forming essential elements for all possible scenarios. These no-regret activities reflect an important outcome of the project they entail setting up the value chain of traffic information, setting up a data warehouse to share all relevant data (including the functional and technical standards), and preparing for integrated network management and cooperative systems.
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2071-03
Abstract: Incidents on freeways cause large delays for road users. These delays depend largely on the capacity at the incident location, which is determined by the drivers’ behavior at the accident location. Few empirical facts are available on traffic operations during an incident. This paper presents high-quality videos of the traffic flow around two accidents recorded from a helicopter. From the collected images, traffic counts have been performed at the exact location of the incident. This has two advantages. First, the capacity at the bottleneck per lane could be estimated. Second, truck counts could be converted to passenger car units at the location of the bottleneck. Counts show that the (outflow) capacity of the remaining lanes is about 50% lower than the (free-flow) capacity of the same number of lanes. This means that the road capacity in the opposite direction is reduced by half by the rubbernecking effect. The capacity of the road in the direction of the accident is reduced by more than half because not all lanes are in use. The images provide information on the causes for the capacity reduction. A leader accelerates and the follower accelerates a short time later. The average time between these two accelerations is estimated at about 3 s, but the video also shows a large spread of these times. The results can be used to assess consequences of incidents, in an analytical way and in macroscopic or microscopic traffic simulators.
Publisher: SAGE Publications
Date: 2007
DOI: 10.3141/1999-11
Abstract: A dedicated trajectory data collection method using a helicopter enabled a range of in-depth empirical studies of car-following behavior. These studies found a high degree of heterogeneity in car-following behavior that is, drivers' driving styles turned out to be highly different because different modeling approaches were needed to model these behaviors satisfactorily. Therefore the impact of heterogeneity in car following on modeling traffic dynamics is examined to gain insight into the effect of incorporating different types and degrees of heterogeneity in car-following behavior on the dynamics of a simulated traffic flow. The microsimulation approach that was adopted focused on two case studies: the first case study focused on heterogeneity in parameter values by comparing stability results for heterogeneous platoons and homogeneous platoons, which could in fact be seen as a solid preparation for the second case study. The second study was a simulation of a fixed stretch of road on which, from a certain point on, a speed limit was imposed for the drivers. In this case study the link between the empirical results and the simulations was strengthened as several types of heterogeneity (e.g., different model specifications for different drivers and different parameter settings and combinations of them) were explored and compared with the empirically estimated parameters. Both analyses show clear differences between simulations with homogeneous drivers and simulations with heterogeneous drivers.
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2049-21
Abstract: Every day, traffic managers and road users use different sources of information on the current state of the road network in their decision process. The efficiency of these decisions strongly depends on how accurate, reliable, and timely the available information is. Moreover, the data collected are typically scattered in space and time large areas are usually unmonitored, and data quality is undependable. Within this view, the distribution of a unique data set that contains sufficient levels of quality over the whole network may improve the way information is provided to the user and improve the effectiveness of management strategies. The need for guaranteed standard levels of data quality for road authorities and service providers motivated the establishment of the National Data Warehouse project to provide traffic information as well as information on the status of the road network system as a whole. This information is extended to a basic network level, which allows road authorities or service providers to combine this information with their own data set and obtain a broader view of the problems that occur on the network they manage or monitor. The requirements that such a data bank should satisfy—namely, the accuracy and reliability of information (which depend on the spatial location and aggregation time)—were investigated. The impact of these elements has been quantified through theoretical and numerical analysis, showing that both elements strongly affect good estimation and prediction of travel times and network states, especially under variable traffic conditions.
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2188-08
Abstract: The values on parameters describing longitudinal driving behavior in car-following models differ substantially between drivers. Different in idual interactions with the environment are assumed to play an important role, which might be explained through mental workload. Therefore a driving simulator experiment with a repeated measures design was performed to investigate to what extent perception of an incident in the other driving lane influences physiological indicators as well as subjective estimates of mental workload and longitudinal driving behavior. As almost none of the current models of car-following behavior incorporate mental workload as a determinant of driving behavior, an investigation was conducted by using a calibration approach for joint estimation to determine whether these models, represented by the intelligent driver model and the Helly model, adequately described longitudinal driving behavior in case of incidents in the other driving lane. The results indicated that perception of an incident in the other driving lane influenced mental workload as measured by physiological indicators and longitudinal driving behavior. In addition, the results indicated that current car-following models did not adequately describe driving behavior in case of incidents in the other driving lane.
Publisher: Elsevier BV
Date: 06-2023
Publisher: Informa UK Limited
Date: 21-09-2020
Publisher: Elsevier BV
Date: 06-2019
Publisher: IEEE
Date: 09-2010
Publisher: Elsevier BV
Date: 12-2006
Publisher: Informa UK Limited
Date: 06-04-2017
Publisher: IEEE
Date: 04-2011
Publisher: Hindawi Limited
Date: 20-12-2012
DOI: 10.1155/2012/807805
Abstract: Technological innovations can be assumed to have made the driving task more complex. It is, however, not yet clear to what extent this complexity leads to changes in longitudinal driving behavior. Furthermore, it remains to be seen how these adaptation effects can best be modeled mathematically. In order to determine the effect of complexity on empirical longitudinal driving behavior we performed a driving simulator experiment with a repeated measures design. Through this experiment we established that complexity of the driving task leads to substantial changes in speed and spacing. In order to provide insight into how complexity is actually related to changes in longitudinal driving behavior we introduce a new theoretical framework based on the Task-Capability-Interface model. Finally in this paper we take some first steps towards modeling of adaptation effects in longitudinal driving behavior in relation to complexity of the driving task through the introduction of a new neurofuzzy car-following model and based on the proposed theoretical framework. In this paper we show that this model yields a relatively good prediction of longitudinal driving behavior in case of driving conditions with differing complexity. The paper finishes with a discussion section and recommendations for future research.
Publisher: IEEE
Date: 09-2012
Publisher: IEEE
Date: 04-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2023
Publisher: IEEE
Date: 10-2011
Publisher: Elsevier BV
Date: 02-2004
Publisher: Elsevier BV
Date: 08-2018
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2049-11
Abstract: Traffic state estimation plays an important role in operational traffic management and is essential for real-time traffic modeling and prediction. As more heterogeneous traffic data [e.g., from loops, probe vehicles, advanced vehicle identification (AVI) systems] become available, data fusion has become one of the main challenges of state estimation. Given the different semantics over space and time (e.g., AVI data and local data from loops), data fusion is a far more complex problem than it appears at first glance. A new algorithm for fusing data from local detectors (loops) with travel times obtained from AVI systems was developed. This simple but mathematically elegant algorithm— called piecewise inverse speed correction—by using in idual travel times (PISCIT) correctly and efficiently combines these data (in essence incompatible) and produces a state estimate (space mean speeds per cell), which is better than one obtained by any of the data sources in idually. Moreover, PISCIT is robust with respect to structural and random errors in the source data. The approach is validated using synthetic data generated by microscopic simulation. The algorithm corrects the traffic state correctly even when nonuniform deviations are up to 70%.
Publisher: Informa UK Limited
Date: 19-12-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2011
Publisher: IEEE
Date: 10-2008
Publisher: IEEE
Date: 09-2010
Publisher: IEEE
Date: 04-2011
Publisher: IEEE
Date: 09-2012
Publisher: Elsevier BV
Date: 2009
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2196-05
Abstract: Traffic simulation models are frequently used to support decisions when an evacuation is planned. These models typically focus on traffic dynamics and the effect of traffic control measures to locate possible bottlenecks and predict evacuation times. However, a clear view of the crucial factors that determine evacuation time and emergent traffic states is lacking. In this paper, a structured and comprehensive sensitivity analysis identifies and quantifies the impact of variations in travel demand and network supply in the case of evacuation. The sensitivity analysis involves applying the macroscopic evacuation traffic simulation model EVAQ, in which aspects such as trip generation, departure rates, route flow rates, road capacities, and maximum speeds are systematically varied. That is accomplished using a case study that describes evacuation of the Rotterdam, Netherlands, metropolitan area. Departure rates and route flow rates are found to have a substantial nonlinear impact on network conditions and arrival pattern, particularly when the network load is relatively high, whereas trip generation and road capacities have a smaller quasilinear impact. Maximum speeds, independent of the effect on road capacities, have no significant impact on evacuation. The results, discussion, and conclusions presented can be used to identify the most important factors in (a) verifying, calibrating, and validating an evacuation model (b) designing a network for evacuation studies and (c) evaluating and testing the robustness of evacuation plans.
Publisher: Elsevier BV
Date: 2011
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2088-19
Abstract: The heterogeneity of traffic is a significant if not dominant factor in accurately modeling freeway traffic flow operations. For ex le, high truck percentages may induce congestion at much lower volumes, and hence different network traffic conditions may result than with low truck percentages. This implies that traffic models for real-time decision support systems in traffic management centers should provide the means to account for traffic heterogeneity. A new, multiclass, first-order traffic model is presented that provides these means and is implemented in the decision-support system BOSS-Offline, operational in all five highway traffic management centers in the Netherlands. FASTLANE differs from earlier multiclass first-order macroscopic traffic models in that it calculates the dynamics in terms of state-dependent (instead of constant) passenger-car equivalents, which is in line with both theory and empirical microscopic data. The model is numerically solved by an efficient and stable Godunov-based solver while maintaining a dynamic and realistic representation of class-specific flows and densities throughout the network. In two synthetic test cases and one based on real data, the workings of FASTLANE under different truck percentages and different conditions are demonstrated.
Publisher: Informa UK Limited
Date: 21-12-2016
Publisher: IEEE
Date: 09-2010
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2091-11
Abstract: Dynamic traffic assignment (DTA) models typically describe travelers selecting their routes before departure (pretrip) or during the trip (en route). However, in reality, people follow a certain route but have the opportunity to deviate from that route. An analytical hybrid route choice model is proposed that unifies pretrip and en route route choice in a tractable way. It enables modeling intermediate states where travelers make pretrip route choice decisions and may deviate from this route if they receive information about a more attractive route, for instance, because of unforeseen adverse traffic conditions. The hybrid route choice model is widely applicable to various planning and management applications in DTA and makes the DTA model more realistic in cases such as route guidance problems, where the combination of prescribed routes and en route route choice is evident. Furthermore, the proposed route choice model is generic because different dynamic traffic flow models can be used in the model, analytical or simulation-based. Also, two common problems in DTA related to gridlock and time-varying network conditions are solved in the hybrid route choice model.
Publisher: SAGE Publications
Date: 2007
DOI: 10.3141/2018-07
Abstract: This paper describes a driving simulator experiment to test the functioning and acceptance of a standardized overtaking assistant design. On a simulated two-lane road, 24 participants drove 15 min with and without a prototype overtaking assistant. The overtaking assistant calculated the available time to perform an overtaking maneuver, taking the preceding vehicle and opposing traffic into account. When it was safe to overtake, the assistant showed a green sign to participants when it was not safe, a red sign was shown. The number of overtaking maneuvers performed in the base scenario (without assistance) did not vary significantly from that in the assistant scenario. Male participants, however, did overtake significantly more than female participants. The reported activation level of all participants had grown significantly after the run with the overtaking assistant, compared with a similar run without assistance. Participants’ ratings for the usefulness of the assistant and on how satisfying it was were both low some participants thought the assistant was too careful (shows a red sign while it is safe to overtake), and others thought it was not careful enough (shows a green sign while it is not safe to overtake). The overtaking frequency of participants was not significantly related to sensation-seeking scores, which are highly related to risky driving. It was concluded that according to the performance of the overtaking maneuvers, it is possible to design a standardized overtaking assistant. However, it should be possible to improve the system to suit the different drivers’ perceptions better.
Publisher: Informa UK Limited
Date: 20-06-2019
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2088-13
Abstract: Interest in calibration of car-following models by using real-life microscopic trajectory data is increasing. However, more information is needed on the influence of methodological issues on calibration results as well as on the influence of practical issues related to the use of real-life data. In particular, the influence of measurement errors on parameter estimates has not yet been considered in detail. To gain insight into the influence of measurement errors on calibration results, synthetic data were created to which several types of measurement error are introduced. These data are input to a validated calibration procedure, after which it is studied how well the parameters used for creating the data can be identified from the erroneous data. The sensitivity of the objective function to small changes in the optimal parameters also is assessed. The calibrations are repeated by using different variables in the objective. The three main findings are that (a) measurement errors can yield a considerable bias in the estimation results, (b) parameters minimizing the objective function do not necessarily capture following dynamics best, and (c) measurement errors substantially reduce the sensitivity of the objective function and consequently reduce the reliability of estimation results. The extent to which these problems caused by measurement errors can be avoided by smoothing the data carefully before use is assessed and discussed.
Publisher: SAGE Publications
Date: 19-08-2021
DOI: 10.1177/03611981211033861
Abstract: Freeway on-r areas are susceptible to traffic congestion during peak hours. To delay or prevent the onset of congestion, r metering can be applied. A R Metering Installation (RMI) controls the inflow from the on-r to the main line so that the total flow can be kept just below capacity. Current r metering algorithms apply macroscopic traffic characteristics, which do not entirely prevent inefficient merging behavior from occurring. This paper presents a microscopic r metering approach based on gap detection in the right-hand lane of the main line. As preparation for the analyses, trajectory data were collected, by which the mean and standard deviation of driver accelerations were calculated. Simulation, including driver acceleration, is used to test the r metering controller. Overall, it shows travel-time savings compared with no-control and compared with existing macroscopic r metering systems. Especially during periods of very high main line demand, the microscopic control approach is able to achieve additional travel-time savings. This way, the proposed algorithm can contribute to more efficient road usage and shorter travel times.
Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2278-04
Abstract: Lane changes are an important aspect of freeway flow. Most models of lane change are microscopic. Lane change behavior of in idual vehicles or drivers is described, and, therefore, models are calibrated microscopically. Macroscopic validation often is restricted to the distribution of vehicles across lanes. To the best of the authors' knowledge, no systematic analysis has been made of the number of lane changes as a function of the operational characteristics of the origin and target lane. This paper fills the gap in lane change literature with an analysis of the number of lane changes as a function of several incentives. On the basis of data availability, two “simple” sites were selected, that is, as close as possible to a straight continuous freeway. Statistical analysis at the selected sites revealed that drivers changed lanes on average once per 2 km driven. Furthermore, an analysis of the number of lane changes (per kilometer per hour) as a function of the density in the origin lane and in the target lane showed that the number of lane changes increased with the density in the origin lane for a fixed density in the target lane. The number of lane changes also increased with the density in the target lane for a fixed density in the origin lane. The underlying mechanism was therefore different from gap-acceptance theory. The analyses presented in this paper can be used to verify qualitatively (microscopic and macroscopic) lane change models and to propose better ones.
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2088-11
Abstract: Modeling breakdown probabilities or phase-transition probabilities is an important issue when assessing and predicting the reliability of traffic flow operations. Looking at empirical spatiotemporal patterns, these probabilities clearly are a function not only of the local prevailing traffic conditions (density, speed) but also of time and space. For instance, the probability that a start-stop wave occurs generally increases when moving upstream away from the bottleneck location. A simple partial differential equation is presented that can be used to model the dynamics of breakdown probabilities, in conjunction with the well-known kinematic wave model. The main assumption is that the breakdown probability dynamics satisfy the way information propagates in a traffic flow, that is, they move along with the characteristics. The main result is that the main characteristics of the breakdown probabilities can be reproduced. This is illustrated through two ex les: free flow to synchronized flow (F-S transition) and synchronized to jam (S-J transition). It is shown that the probability of an F-S transition increases away from the on r in the direction of the flow the probability of an S-J transition increases as one moves upstream in the synchronized flow area.
No related grants have been discovered for Serge Hoogendoorn.