Real-time traffic state estimation in urban corridors from heterogeneous data

Nantes, Alfredo; Ngoduy, Dong; Bhaskar, Ashish; Miska, Marc; Chung, Edward

doi:10.1016/j.trc.2015.07.005

Cited by 110 publications

(51 citation statements)

References 38 publications

(16 reference statements)

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“…In this theoretical framework, the use of multiple cameras with dissimilar detection errors to detect the flow at one entrance has not been accounted for. The characteristics of the problem above are similar to the classical traffic management problems of queue length estimation upstream of traffic signals and density estimation on highway links, which traffic engineers have been studying for quite some years (e.g., [13][14][15][16][17][18][19]). Many distinct types of filters, such as Kalman Filters, Particle filters, and Hidden Markov Models, have been proposed to improve the estimation of the number of vehicles in a queue and/or on a link in the highway network.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Monitoring the Number of Pedestrians in an Area: The Applicability of Counting Systems for Density State Estimation

Duives

Daamen

Hoogendoorn

2018

Journal of Advanced Transportation

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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.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Monitoring the Number of Pedestrians in an Area: The Applicability of Counting Systems for Density State Estimation

Duives

Daamen

Hoogendoorn

2018

Journal of Advanced Transportation

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“…Authors in [22] proposed the model of day to day traffic evolution based on strategic thinking and marginal decision rule. The proposed framework enables to capture both benefit and cost associated with route changes.…”

Section: Existing Workmentioning

confidence: 99%

Commuters’ traffic pattern and prediction analysis in a metropolitan area

Chavhan

Venkataram

2017

J Veh Routing Algorithms

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A metropolitan area is an area with dynamic demands and is one of the main indicators of economic growth of nation. It involves the complexity of efficient analysis and prediction of patterns of growth or decline of traffic volume and patterns of resource utilization with respect to time and place. To solve these complexities, we propose agent-based commuters' traffic pattern and prediction analysis model in a metropolitan area. The proposed system model is capable of analyzing and predicting the patterns of commuters' traffic flow volume and resource utilization in each zone and region, using the population density, availability of resources, type of place, time period, and commuters' and vehicles' arrival rates. The proposed model provides qualitative form of traffic; increases the probability of measure of unpredictable information; and aids in emergency traffic planning and route-finding services. The result shows the effectiveness of the model at different time periods in a day for forecasting of the resource utilization and changes in traffic volumes in zones and regions in the metropolitan area.

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“…Besides computational limitations of the ABM, the availability of suitable data has been a bottleneck; both factors might lose their relevance in the near future. The difficulty of incorporating (real-time) data from various sources was demonstrated by Nantes et al [31]. They integrated data from loop detectors and data with a detailed temporal and spatial resolution from GPS and Bluetooth sensors into a real-time traffic prediction model for a very small section of an urban road network.…”

Section: Examples For Geospatial Transport Modeling Approachesmentioning

confidence: 99%

GIS and Transport Modeling—Strengthening the Spatial Perspective

Loidl

Wallentin

Cyganski

et al. 2016

IJGI

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Abstract:The movement and transport of people and goods is spatial by its very nature. Thus, geospatial fundamentals of transport systems need to be adequately considered in transport models. Until recently, this was not always the case. Instead, transport research and geography evolved widely independently in domain silos. However, driven by recent conceptual, methodological and technical developments, the need for an integrated approach is obvious. This paper attempts to outline the potential of Geographical Information Systems (GIS) for transport modeling. We identify three fields of transport modeling where the spatial perspective can significantly contribute to a more efficient modeling process and more reliable model results, namely, geospatial data, disaggregated transport models and the role of geo-visualization. For these three fields, available findings from various domains are compiled, before open aspects are formulated as research directions, with exemplary research questions. The overall aim of this paper is to strengthen the spatial perspective in transport modeling and to call for a further integration of GIS in the domain of transport modeling.

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Real-time traffic state estimation in urban corridors from heterogeneous data

Cited by 110 publications

References 38 publications

Monitoring the Number of Pedestrians in an Area: The Applicability of Counting Systems for Density State Estimation

Monitoring the Number of Pedestrians in an Area: The Applicability of Counting Systems for Density State Estimation

Commuters’ traffic pattern and prediction analysis in a metropolitan area

GIS and Transport Modeling—Strengthening the Spatial Perspective

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