Utility-Based Kalman Filtering for real-time estimation of daily demand flows

Scientific Conference (2018)

Time-dependent Origin-Destination (OD) demand flows are fundamental inputs for Dynamic Traffic Assignment (DTA) systems and real-time traffic management. This work introduces a novel state-space framework ... [more ▼]

Time-dependent Origin-Destination (OD) demand flows are fundamental inputs for Dynamic Traffic Assignment (DTA) systems and real-time traffic management. This work introduces a novel state-space framework to estimate these demand flows in an online context. Specifically, we propose to explicitly include trip-chaining behavior within the state-space formulation, which is solved using the well-established Kalman Filtering technique. While existing works already consider structural information and recursive behavior within the online demand estimation problem, this information has been always considered at the OD level. In this study, we introduce this structural information by explicitly representing trip-chaining within the estimation framework. The advantage is twofold. First, all trips belonging to the same tour can be jointly calibrated. Second, given the estimation during a certain time interval, a prediction of the structural deviation over the whole day can be obtained without the need to run additional simulations. The effectiveness of the proposed methodology is demonstrated first on a toy network and then on a large real-world network. Results show that the model improves the prediction performance with respect to a conventional Kalman Filtering approach. We also show that, on the basis of the estimation of the morning commute, the model can be used to predict the evening commute without need of running additional simulations. [less ▲]

A global optimization heuristic for the decomposed static anticipatory network traffic control problem anticipatory network traffic control problem

in Transportation Research Procedia (2017)

Developing traffic control strategies taking explicitly into account the route choice behavior of users has been widely recognized irregularities in the solution space shape, such as non-convexity and non ... [more ▼]

Developing traffic control strategies taking explicitly into account the route choice behavior of users has been widely recognized irregularities in the solution space shape, such as non-convexity and non-smoothness. In this work, we propose an extended as a very challenging problem. Furthermore, the inclusion of user behavior in optimization based control schemes introduces strong decomposition scheme for the anticipatory traffic control problem, based upon our previous contributions, which aims at i) reducing irregularities in the solution space shape, such as non-convexity and non-smoothness. In this work, we propose an extended the computational complexity of the problem by approaching it in a controller-by-controller fashion, and ii) internalizing specific decomposition scheme for the anticipatory traffic control problem, based upon our previous contributions, which aims at i) reducing constraints in the objective function, guiding the optimization process away from non-significant minima, such as flat regions. the computational complexity of the problem by approaching it in a controller-by-controller fashion, and ii) internalizing specific Through two small scale test networks and different, randomly chosen initial points, we compare how the proposed extension constraints in the objective function, guiding the optimization process away from non-significant minima, such as flat regions. influences optimization results with respect to our previously developed decomposed approach, as well as centralized schemes. Through two small scale test networks and different, randomly chosen initial points, we compare how the proposed extension influences optimization results with respect to our previously developed decomposed approach, as well as centralized schemes. [less ▲]

Estimating Urban Road Traffic States Using Mobile Network Signaling Data

in Abstract book of the 20th International Conference on Intelligent Transportation Systems (2017, October)

It is intuitive that there is a causal relationship between human mobility and signaling events in mobile phone networks. Among these events, not only the initiation of calls and data sessions can be used ... [more ▼]

It is intuitive that there is a causal relationship between human mobility and signaling events in mobile phone networks. Among these events, not only the initiation of calls and data sessions can be used in analyses, but also handovers between different locations that reflect mobility. In this work, we investigate if handovers can be used as a proxy metric for flows in the underlying road network, especially in urban environments. More precisely, we show that characteristic profiles of handovers within and between clusters of mobile network cells exist. We base these profiles on models from road traffic flow theory, and show that they can be used for traffic state estimation using floating-car data as ground truth. The presented model can be beneficial in areas with good mobile network coverage but low road traffic counting infrastructure, e.g. in developing countries, but also serve as an additional predictor for existing traffic state monitoring systems. [less ▲]

Effectiveness of the Two-Step Dynamic Demand Estimation model on large networks

in Proceedings of 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) (2017, June 28)

In this paper, the authors present a Two-Step approach that sequentially adjusts generation and distribution values of the (dynamic) OD matrix. While the proposed methodology already provided excellent ... [more ▼]

In this paper, the authors present a Two-Step approach that sequentially adjusts generation and distribution values of the (dynamic) OD matrix. While the proposed methodology already provided excellent results for updating demand flows on a motorway, the aim of this paper is to validate this conclusion on a real network: Luxembourg City. This network represents the typical middle-sized European city in terms of network dimension. Moreover, Luxembourg City has the typical structure of a metropolitan area, composed of a city centre, ring, and suburb areas. An innovative element of this paper is to use mobile network data to create a time-dependent profile of the generated demand inside and outside the ring. To support the claim that the model is ready for practical implementation, it is interfaced with PTV Visum, one of the most widely adopted software tools for traffic analysis. Results of these experiments provide a solid empirical ground in order to further develop this model and to understand if its assumptions hold for urban scenarios. [less ▲]

Lessons learnt from a corporate car-sharing system: the case of the University of Luxembourg

Scientific Conference (2017, May)

Discussion on cross-border integration using non-dominant mobility flows

Scientific Conference (2017, April 12)

On the edge of two different countries, cross-border regions exhibit very peculiar features. While borders can be seen as an interface or a barrier, analyze the interactions between two sovereign spatial ... [more ▼]

On the edge of two different countries, cross-border regions exhibit very peculiar features. While borders can be seen as an interface or a barrier, analyze the interactions between two sovereign spatial entities is extremely important for political reasons, economical development, land use management, etc. Because of data availability issues, spatial cross-border integration is mostly characterized using cross-border workers commuting flow information, or more rarely, by using activities performed by cross-border workers in the country they work. Despite its small size (2586 km2), the Grand-duchy of Luxembourg is a strong economic locomotive. Among the 380 000 available jobs in the country, 42% are occupied by cross border workers from France, Belgium and Germany. While the commuting behavior and the activity chains of the cross border workers have been largely studied this is not the case for the population living in Luxembourg. This study, using two weeks of travel diary data of 35 staff members of the University of Luxembourg living in the Grand-Duchy of Luxembourg, aims at analyzing the relationship that the respondents have with borders. Our hypothesis is that cross-border integration characterization would gain in robustness if non-dominant centripetal flows were taken into account as well. [less ▲]

Usage of Smartphone Data to Derive an Indicator for Collaborative Mobility between Individuals

in ISPRS International Journal of Geo-Information (2017), 6(3), 62

The potential of geospatial big data has been drawing attention for a few years. Despite the larger and larger market penetration of portable technologies (nomadic and wearable devices like smartphones ... [more ▼]

The potential of geospatial big data has been drawing attention for a few years. Despite the larger and larger market penetration of portable technologies (nomadic and wearable devices like smartphones and smartwatches), their opportunities for travel behavior analysis are still relatively unexplored. The main objective of our study is to extract the human mobility patterns from GPS traces in order to derive an indicator for enhancing Collaborative Mobility (CM) between individuals. The first step, extracting activity duration and location, is done using state-of-the-art automated recognition tools. Sensors data are used to reconstruct individual’s activity location and duration across time. For constructing the indicator, in a second step, we defined different variables and methods for specific case studies. Smartphone sensor data are being collected from a limited number of individuals and for one week. These data are used to evaluate the proposed indicator. Based on the value of the indicator, we analyzed the potential for identifying CM among groups of users, such as sharing traveling resources (e.g., carpooling, ridesharing, parking sharing) and time (rescheduling and reordering activities). [less ▲]

Towards Estimating Urban Macroscopic Fundamental Diagrams From Mobile Phone Signaling Data: A Simulation Study

Poster (2017)

On characterizing the relationship between route choice behavior and optimal traffic control solution space

in Transportation Research Procedia (2017), 23

Explicitly including the dynamics of users' route choice behaviour in optimal traffic control applications has been of interest for researchers in the last five decades. This has been recognized as a very ... [more ▼]

Explicitly including the dynamics of users' route choice behaviour in optimal traffic control applications has been of interest for researchers in the last five decades. This has been recognized as a very challenging problem, due to the added layer of complexity and the considerable non-convexity of the resulting problem, even when dealing with simple static assignment and analytical link cost functions. In this work we establish a direct behavioural connection between the different shapes and structures emerging in the solution space of such problems and the underlying route choice behaviour. We specifically investigate how changes in the active equilibrium route set exert direct influence on the solution space's structure and behaviour. Based on this result, we then formulate and validate a constrained version of the original problem, yielding desirable properties in terms of solution space regularity. © 2017 The Authors. [less ▲]

An iterative learning approach for anticipatory traffic signal control on urban networks

in Transportmetrica B: Transport Dynamics (2017), 5(4), 407-430