Data Fusion-Based Traffic Density Estimation and Prediction

Ramkumar, Anand; Ramadurai, Gitakrishnan; Vanajakshi, Lelitha

doi:10.1080/15472450.2013.806844

Cited by 72 publications

(26 citation statements)

References 14 publications

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“…However, once Assumptions 1 and 2 are satisfied by DTA problems with physical queues, the proposed algorithm can be used to obtain their solutions. For future studies, we will develop more efficient solution algorithms, and apply the DTA model to evaluate the effect of various traffic management and transport planning measures such as road pricing (Lo and Szeto 2005), network design (Szeto, Jaber, and O'Mahony 2010;Szeto et al 2014;Miandoabchi, Farahani, and Szeto 2012a;Miandoabchi et al 2012b), staggered work hours (Yushimito, Ban, and Holguín-Veras 2014), incident detection (Ghosh and Smith 2014), and traffic flow/density forecasting (Szeto et al 2009;Ye, Szeto, and Wong 2012;Anand, Ramadurai, and Vanajakshi 2014;Chiou, Lan, and Tseng 2014).…”

Section: Resultsmentioning

confidence: 99%

A nonlinear equation system approach to the dynamic stochastic user equilibrium simultaneous route and departure time choice problem

Long

Szeto

Shi

et al. 2015

Transportmetrica A: Transport Science

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In dynamic stochastic user equilibrium simultaneous route and departure time choice (DSUE-SRDTC) problems, route travel costs can be non-monotone even if route travel times are monotone with respect to route flows. As a result, the mapping function of the variational inequality (VI) problems for the DSUE-SRDTC problems can be non-monotone, and many existing solution algorithms developed for the DSUE-SRDTC problems do not guarantee convergence under this non-monotone condition. This paper formulates the DSUE-SRDTC problem with fixed demand as a system of nonlinear equations. The mapping function of the proposed system of nonlinear equations is defined by a dynamic route choice problem, which can also be formulated as a VI problem with a strictly monotone mapping function under some assumptions. This property enables that the solution algorithm for the DSUE-SRDTC problem can avoid the requirement of the monotonicity of the route travel cost functions for the convergence of the solution procedure. A backtracking inexact Broyden-Fletcher-GoldfarbShanno (BFGS) method is adopted to solve the system of nonlinear equations, and iterative methods are developed to generate an initial solution for the BFGS method and solve the dynamic route choice problem. Finally, numerical examples are set up to show that the proposed method outperforms many existing algorithms for solving the DSUE-SRDTC problem in terms of guaranteeing solution convergence.

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Section: Resultsmentioning

confidence: 99%

A nonlinear equation system approach to the dynamic stochastic user equilibrium simultaneous route and departure time choice problem

Long

Szeto

Shi

et al. 2015

Transportmetrica A: Transport Science

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“…In future research, we will be interested in extending the proposed approach to develop probit-based or the nested logit SDUO models to overcome the shortcomings. In addition, we also plan to use the proposed models for the offline transport planning and policy evaluation, such as advanced traveler information services, network design (e.g., Szeto et al, 2010Szeto et al, , 2014Miandoabchi et al, 2012a,b), signal control, intersection improvement, staggered work hours (e.g., Yushimito et al, 2014), incident detection (e.g., Ghosh and Smith, 2014), traffic flow/density forecasting (e.g., Szeto et al, 2009;Ye et al, 2012;Anand et al, 2014;Chiou et al, 2014), and so on. Furthermore, our current formulation and analysis is based on a discrete-time setting.…”

Section: Resultsmentioning

confidence: 99%

An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance

Long

Szeto

Huang

et al. 2015

Transportation Research Part B: Methodological

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a b s t r a c tDifferent from traditional methods, this paper formulates the logit-based stochastic dynamic user optimal (SDUO) route choice problem as a fixed point (FP) problem in terms of intersection movement choice probabilities, which contain travelers' route information so that the realistic effects of physical queues can be captured in the formulation when a physical-queue traffic flow model is adopted, and that route enumeration and column generation heuristics can be avoided in the solution procedure when efficient path sets are used. The choice probability can be either destination specific or origin-destination specific, resulting into two formulations. To capture the effect of physical queues in these FP formulations, the link transmission model is modified for the network loading and travel time determination. The self-regulated averaging method (SRAM) was adopted to solve the FP formulations. Numerical examples were developed to illustrate the properties of the problem and the effectiveness of the solution method. The proposed models were further used to evaluate the effect of information quality and road network improvement on the network performance in terms of total system travel time (TSTT) and the cost of total vehicle emissions (CTVE). Numerical results show that providing better information quality, enhancing link outflow capacity, or constructing a new road can lead to poor network performance.

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“…The time factor (TF) is the ratio between the target duration of the highway traffic and the actual duration of the simulation (10). It expresses the speed of the simulation.…”

Section: E Simulation Speedmentioning

confidence: 99%

“…To overcome this weakness, various research projects [10]- [14] address the use of other less costly data sources, such as the mobile phone or GPS (Global Positioning System) to estimate road traffic variables.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Distributed Traffic Events Generator for Smart Highways

Daaif¹,

Bouattane²,

Youssfi³

et al. 2017

ijacsa

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Abstract-This paper deals with a spatiotemporal traffic events generator for real highway networks. The goal is to use the event generator to test real-time and batch traffic analysis applications. In this context, we represent a highway network as an oriented graph based on the geographic data of the different sensors locations. The traffic is generated based on a sociocultural calendar using a virtual clock to speed up the simulation process. In order to enable our generator to support the global worldwide highway networks, we propose a dynamic sized distributed architecture based on multi-agent systems. In this platform, we distinguish the physical model based on sensors from the logical model based on an oriented graph. The architecture of the simulator and the results of some of its implementations applied to the Moroccan highway network are presented.

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Data Fusion-Based Traffic Density Estimation and Prediction

Cited by 72 publications

References 14 publications

A nonlinear equation system approach to the dynamic stochastic user equilibrium simultaneous route and departure time choice problem

A nonlinear equation system approach to the dynamic stochastic user equilibrium simultaneous route and departure time choice problem

An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance

An Efficient Distributed Traffic Events Generator for Smart Highways

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