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This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitude of expected errors. Probe data are essential to reduce the error but accurate density estimation requires high penetration rates, which is hardly true in practice. We enhance the fishing rate method, i.e. using the ratio of probes detected at the loop locations over the loop flow, to estimate density. Accurate density estimation at the link level can only be obtained when probes and loop data are available in real-time. At the network level, accurate density estimations can be obtained when combining loop and probe observations, even if few links capture both data sources. It requires applying the proper analytical formulation to aggregate the local observations, i.e. carefully defining fishing rates at this scale.

IEEE ITSC 2020, 23rd IEEE International Conference on Intelligent Transportation Systems, Rhodes, GRECE, 20-/09/2020 - 23/09/2020; In order to provide a satisfying quality of service to passengers, companies operating suburban trains seek to implement timetables that perform well despite the occurrence of random disturbances. However, due to some specificities of Mass Transit, the standard approaches for robust train timetabling do not apply in that context. In this paper, we present a data-based stochastic simulation method for assessing the efficiency of train timetables for dense traffic areas. We describe models for the random variabilities that occur daily on such networks, and use them in a stochastic simulation algorithm. Results are presented on a saturated line of Paris suburban network.

hEART 2019, 8th Symposium of the European Association for Research in Transportation, Budapest, HONGRIE, 04-/09/2019 - 06/09/2019; Traffic state prediction models based on 3D or bi-modal Macroscopic Fundamental Diagram (MFD) is discussed in this work. The well known MFD-based models namely, accumulationbased and trip-based models are extended to the case of multimodal traffic. In addition, accumulation-based with outflow delay, which is studied in the context of link level traffic flow dynamics is investigated. The results from MFD-based models is verified with the solution of continuum space-time model, which is based on hyperbolic conservation equations. It is concluded that accumulation-based model with outflow delay address the limitations of conventional accumulation-based model and trip-based solution is most accurate among all the considered MFD-based models.

WCTS 2019, 1st IFAC Workshop on Control of Transportation Systems , Haifa, ISRAEL, 30-/06/2019 - 01/07/2019; In this paper, we propose a model-based perimeter gating control approach to improve network-wide emissions in an urban traffic network. An accumulation-based Macroscopic Fundamental Diagram (MFD) model of a single reservoir city is developed to describe the evaluation of traffic flows in a network. Moreover, a path flow distribution scheme using Dynamic User Equilibrium (DUE) discipline is designed to reproduce driver's adaptation to controlled flow. Perimeter gating control scheme using the Nonlinear Model Predictive Controller (NMPC) is developed to track the optimal green routing coefficient which will indirectly track the network-wide emission levels by manipulating the traffic flows into a reservoir. Simulation results show the effectiveness of the proposed scheme in improving the traffic emissions inside and outside the perimeter. Comparative analysis of nocontrol and NMPC shows that the proposed NMPC-based network-wide emission control strategy outperforms.

Disruptive events occur on road networks on a daily basis and affect traffic flow. Resilience analysis aims to assess the consequences of such disruptions by quantifying the ability of a network to absorb and react to adverse events. In this paper, we advance a methodological approach based on resilience stress testing and a dynamic mesoscopic simulator. We aim to identify and rank the links most critical to the overall performance of the road network, taking into account the dynamic properties of road traffic and focusing on day-to-day disruptions. As a metric to quantify road network performance in the presence of such disruptions, we use the increase in overall travel cost. We then compare our approach with purely topological approaches. We discuss the advantages and drawbacks of the different analyzed metrics. We prove that link ranking varies greatly depending on the metric. Specifically, the proposed stress testing methodology can produce very accurate results by taking into account demand and congestion, but requires computationally intensive simulations, being therefore prohibitive even on medium-sized networks. Conversely, purely static topological metrics can be inaccurate if they do not take into account traffic demand and network dynamics. Our study highlights the need for joining traditional traffic-agnostic topological resilience analysis with demand-aware dynamic stress testing techniques.

TRB'18, 97th Annual Meeting of the Transportation Research Board, Washington, Etats-Unis, 06-/01/2018 - 11/01/2018; In this paper, we propose a thorough analysis of the way congestion is usually handled in the accumulation-based framework. This serves as a basis to implement a proper congestion propagation model in the trip-based approach. Theoretical and simulation studies show that in case of several trip lengths in a zone, there exists only one form of inflow limitation at the reservoir entry that complies with the global constraints on flow and production.

In this paper, we propose the Proactive-optimal-path Selection with Coordinator Agents Assisted Routing (PSCAR) protocol for Vehicular Ad hoc NETworks (VANETs) in an urban environment. The main idea of PSCAR is to contribute static nodes as coordinator agents placed at each intersection, in order to improve the routing performance and to deal with radio obstacles (buildings, trees...) and voids as encountered in urban environments. Since the coordinator agents are static nodes, each one knows all the paths to any other coordinator agent in the network. Thus, instead of searching an optimal path toward the destination node, PSCAR will determine an optimal path to the nearest coordinator agent to the destination node so as to better anticipate any change of the destinations position. The optimal path is selected according to two criteria: the total physical distance and the vehicle density on the path. The vehicle density is estimated based on a fundamental diagram of the traffic that allows estimating the vehicular traffic density on each road segment. To evaluate the performance of PSCAR we used the Network Simulator 2 (ns-2) and the mobility simulator SUMO. We compare our scheme with some existing solutions with the aim of showing its effectiveness, in terms of packet delivery ratio, end-to-end delay, and network overhead.

hEART 2018, 7th Symposium of the European Association for Research in Transportation, Athènes, GRECE, 05-/09/2018 - 07/09/2018; In the recent past, Macroscopic Fundamental Diagram (MFD) proved to be an attractive alternative to describe the traffic states at the network level. Several works (Knoop and Hoogendoorn, 2014, Yildirimoglu and Geroliminis, 2014, Kouvelas et al., 2017) employed MFD-based approaches in variety of applications like perimeter control, modeling large-scale cities, etc. Even though Geroliminis and Daganzo (2008) verified the existence of MFD, the stability of its shape faces certain challenges like hysteresis phenomenon (Gayah and Daganzo, 2011), heterogeneity of the traffic in urban networks (Geroliminis and Sun, 2011). Ji and Geroliminis (2012) has shown that partitioning of heterogeneous networks into homogeneous regions can be a solution to obtain a well defined MFD. However, this approach might not be robust as hysteresis may be driven by other factors rather than the network attributes.

The goal of this study is to highlight the effects of adverse weather conditions on traffic demand. The literature review underlines that some events, especially rain and snow, induce significant changes on both travel demand and traffic operations. These changes have several origins (modal shift, time departure postponement, travel cancellation. . .) and depend on many factors, such as time of day (day/night), week (weekdays/weekend), environment (urban/interurban area), trip purpose (discretionary/nondiscretionary). . . The literature review is therefore divided in two parts: a study of surveys that reveals the impact of weather on travel choices, and then statistical analysis conducted on traffic data collected from loop detectors. This preliminary work is completed by statistical analysis and modeling on operational interurban data (a section of the A43 French Highway) and urban data (route næ 3, Tokyo).; L'objectif de cet article est de mettre en évidence les effets de la météorologie sur la demande de trafic. Une étude approfondie de la littérature est d'abord réalisée : d'une part une analyse des conséquences sur la demande de déplacement au sens large à travers le prisme du modèle à quatre étapes (à partir d'enquêtes principalement) et d'autre part un focus sur la demande de trafic, en synthétisant les analyses réalisées à partir des données boucles. L'analyse montre ainsi que certains événements météorologiques, comme la pluie et surtout la neige, conduisent à des modifications dans les comportements (transfert modal, annulation du déplacement. . .) et à une baisse de la demande de trafic. La nature et l'amplitude des changements opérés dépendent de nombreux facteurs, comme la période du jour (journée/nuit), de la semaine (semaine/week-end), du milieu (urbain/interurbain), du motif du déplacement (contraint/non contraint). . . Cette bibliographie est ensuite complétée par des analyses statistiques et des modélisations sur des données opérationnelles recueillies en milieu interurbain (section Lyon-Chambéry de l'A43) et sur la route n 3 des autoroutes urbaines de Tokyo.

The goal of this study is to highlight the effects of adverse weather conditions on traffic demand. The literature review underlines that some events, especially rain and snow, induce significant changes on both travel demand and traffic operations. These changes have several origins (modal shift, time departure postponement, travel cancellation. . .) and depend on many factors, such as time of day (day/night), week (weekdays/weekend), environment (urban/interurban area), trip purpose (discretionary/nondiscretionary). . . The literature review is therefore divided in two parts: a study of surveys that reveals the impact of weather on travel choices, and then statistical analysis conducted on traffic data collected from loop detectors. This preliminary work is completed by statistical analysis and modeling on operational interurban data (a section of the A43 French Highway) and urban data (route næ 3, Tokyo).; L'objectif de cet article est de mettre en évidence les effets de la météorologie sur la demande de trafic. Une étude approfondie de la littérature est d'abord réalisée : d'une part une analyse des conséquences sur la demande de déplacement au sens large à travers le prisme du modèle à quatre étapes (à partir d'enquêtes principalement) et d'autre part un focus sur la demande de trafic, en synthétisant les analyses réalisées à partir des données boucles. L'analyse montre ainsi que certains événements météorologiques, comme la pluie et surtout la neige, conduisent à des modifications dans les comportements (transfert modal, annulation du déplacement. . .) et à une baisse de la demande de trafic. La nature et l'amplitude des changements opérés dépendent de nombreux facteurs, comme la période du jour (journée/nuit), de la semaine (semaine/week-end), du milieu (urbain/interurbain), du motif du déplacement (contraint/non contraint). . . Cette bibliographie est ensuite complétée par des analyses statistiques et des modélisations sur des données opérationnelles recueillies en milieu interurbain (section Lyon-Chambéry de l'A43) et sur la route n 3 des autoroutes urbaines de Tokyo.

Past research has shown that road users accept shorter time gaps when the waiting time/number of vehicles they let pass before attempting to merge into the traffic increases. While elderly pedestrians are known to be an extremely vulnerable group of road users, very few studies dealt with the effect of environmental constraints and crossing complexity on this population’s safety. The present study aimed at determining whether or not street-crossing decisions and behavior of younger and older pedestrians were differently affected by a traffic flow. In an interactive street-crossing task, we assessed whether mean time gap and crossing decisions depended on the position of the gap pedestrians selected into the traffic stream. Results revealed that irrespective of their age pedestrians accepted a smaller time gap when they chose the second interval of the traffic compared to the first one. Contrasting with previous hypotheses, this traffic-related behavior was not accompanied by an increase in the decisions risk. The findings also showed that the transition threshold from rejecting to accepting time gaps was shorter when the second interval was selected compared to the first one. This increment in task constraints might help younger and older pedestrians alike to perceive action possibilities more accurately and to be better attuned to traffic conditions by comparing gaps between each other. This opens an interesting perspective in the understanding and the training of the ability of elderly road users to remain accurate in their judgements.

We study the relation between the average traffic flow and the vehicle density on road networks that we call 2D-traffic fundamental diagram. We show that this diagram presents mainly four phases. We analyze different cases. First, the case of a junction managed with a priority rule is presented, four traffic phases are identified and described, and a good analytic approximation of the fundamental diagram is obtained by computing a generalized eigenvalue of the dynamics of the system. Then, the model is extended to the case of two junctions, and finally to a regular city. The system still presents mainly four phases. The role of a critical circuit of non-priority roads appears clearly in the two junctions case. In Section 4, we use traffic light controls to improve the traffic diagram. We present the improvements obtained by open-loop, local feedback, and global feedback strategies. A comparison based on the response times to reach the stationary regime is also given. Finally, we show the importance of the design of the junction. It appears that if the junction is enough large, the traffic is almost not slowed down by the junction., 37 pages

A scalar Kalman filter is applied to traffic density estimation in a 500-metre section of the Boulevard Peripherique in Paris using presence detector data. After derivation of the model and filter equations, estimates are compared to real traffic density measuremenns extracted from a film. Results indicate accuracy of estimates; excellent tracking capabilities; and low sensitivity with respect to changing application conditions.