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  • 1. Allström, Andreas
    et al.
    Rahmani, Mahmood
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Gundlegård, David
    Archer, Jeffery
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Mobile Millennium Stockholm2011In: Proceedings of the 2nd International Conference on Models and Technologies for ITS, 2011Conference paper (Refereed)
  • 2. Amekudzi, A.
    et al.
    McNeil, S.
    Koutsopoulos, Harilaos
    Assessing extrajurisdictional and areawide impacts of clustered brownfield developments2003In: Journal of urban planning and development, ISSN 0733-9488, E-ISSN 1943-5444, Vol. 129, no 1, p. 27-44Article in journal (Refereed)
    Abstract [en]

    Brownfields are vacant, underutilized, or abandoned industrial and commercial sites where real or perceived environmental contamination is an obstacle to development. Federal initiatives in the 1990s reduced legal liabilities associated with brownfields and provided financial incentives for development initiatives. As brownfields are often located in infill areas, they have advantages over greenfields developments in that much of the supporting infrastructure already exists and they are centrally located. However, the existing infrastructure may be deteriorated and obsolete, and brownfield developments in infill areas may require local as well as areawide transportation improvements. This paper uses a modified impact analysis approach, synthesized from regional transportation modeling and site impact analysis tools, to assess the extrajurisdictional and areawide impacts of clustered brownfield developments. The writers apply this approach to clustered brownfield developments in the City of Pittsburgh. The study results show that the synergistic effects and areawide impacts of clustered brownfield developments may not be adequately captured by traditional site impact studies. This paper is potentially useful for municipal agencies involved in assessing and planning for the transportation improvement needs of clustered brownfield developments.

  • 3. Antoniou, C
    et al.
    Balakrishna, R
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    A synthesis of emerging data collection technologies and their impact on traffic management applications2011In: European Transport Research Review, ISSN 1867-0717, Vol. 3, no 3, p. 139-148Article in journal (Refereed)
    Abstract [en]

    act

    Purpose: The objective of this research is to provide an overview of emerging datacollection technologies and their impact on traffic management applications. Methods: Several existing and emerging surveillance technologies are being used for traffic datacollection. Each of these technologies has different technical characteristics and operating principles, which determine the types of data collected, accuracy of the measurements, levels of maturity, feasibility and cost, and network coverage. This paper reviews the different sources of traffic surveillance data currently employed, and the types of traffic management applications they may support. Results: Automated Vehicle Identification data have several applications in traffic management and many more are certain to emerge as these data become more widely available, reliable, and accessible. Representative examples in this field are presented. Furthermore, the fusion of condition information with traffic data can result in better and more responsive dynamic trafficmanagement applications with a richer data background. Conclusions: The current state-of-the-art of traffic modeling is discussed, in the context of using emerging data sources for better planning, operations and dynamic management of road networks. 

  • 4. Antoniou, C
    et al.
    Balakrishna, R
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Emerging Data Collection Technologies and their Impact on Traffic Management Applications2008Conference paper (Refereed)
  • 5. Antoniou, C.
    et al.
    Balakrishna, R.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Exploiting emerging data collection technologies for dynamic traffic management applications2010In: Proceedings of World Conference on Transport Research (WCTR), 2010Conference paper (Refereed)
    Abstract [en]

    Several existing and emerging surveillance technologies are being used for traffic datacollection. Each of these technologies has different technical characteristics and operatingprinciples, which determine the types of data collected, accuracy of the measurements,levels of maturity, feasibility and cost, and network coverage. This paper reviews the differentsources of traffic surveillance data currently employed, and the types of traffic managementapplications they may support. The current state-of-the-art of traffic modeling is alsodiscussed, in the context of using emerging data sources for better planning, operations anddynamic management of road networks.

  • 6. Antoniou, C
    et al.
    Balakrishna, R
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Ben-Akiva, Moshe
    Calibration Methods for Simulation-Based Dynamic Traffic Assignment Systems2011In: International Journal of Modelling and Simulation, ISSN 0228-6203, Vol. 31, no 3, p. 227-233Article in journal (Refereed)
    Abstract [en]

    Dynamic Traffic Assignment (DTA) integrates complex transportation demand and network supply simulation models to estimate prevailing traffic conditions, predict future network performance and generate consistent, anticipatory route guidance. Prior to deployment, the DTA's parameters and inputs must be calibrated to accurately reflect travel behaviour and traffic dynamics. This paper presents a unified framework for off-line and on-line DTA calibration. Off-line calibration simultaneously estimates demand and supply model parameters. On-line calibration jointly updates - in real-time - the off-line estimates in order to more accurately capture current conditions. The developed methodsare flexible and can be applied to any simulation model and may utilize any availabletraffic surveillance information (including Automated Vehicle Identification systems, probe vehicles and other emerging data sources). The off-line and on-line components complement each other to efficiently combine historical and real-time information. Thecalibration approaches are demonstrated with DynaMIT (Dynamic network assignmentfor the Management of Information to Travelers), using time-varying count, speed and density data from conventional traffic sensors.

  • 7. Antoniou, C
    et al.
    Balakrishna, R
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Ben-Akiva, Moshe
    Off-Line and On-Line Calibration of Dynamic Traffic Assignment Systems2009In: IFAC Proceedings Volumes, 2009, p. 104-111Conference paper (Refereed)
    Abstract [en]

    Dynamic traffic assignment (DTA) systems integrate complex transportation demand and network supply simulation models to estimate current traffic conditions, predictfuture network performance and generate consistent, anticipatory route guidance. Before they are applied, DTA system parameters and inputs must be calibrated to accurately reect travel behavior and traffic dynamics. This paper presents a systematic approach that unifies the offline and on-line calibration of DTA systems through a common framework.Off-line calibration simultaneously estimates demand and supply model parameters. The on-line calibration jointly updates in real-time the demand and supply parameter values estimated during the of-line step to better reect prevailing conditions. The methods are general and can utilize any available traffic surveillance information (including emerging data sources, such as Automated Vehicle Identification systems or probe vehicles). The two components complement each other so that the calibration of the DTAsystem parameters efficiently utilizes both historical as well as real-time information. Thecalibration approaches are demonstrated with DynaMIT (Dynamic network assignmentfor the Management of Information to Travelers), using time-varying count, speed and density data obtained from standard loop detectors.

  • 8.
    Antoniou, C
    et al.
    MIT.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    Northeastern University, 437 Snell Engineering Center.
    Incorporating Automated Vehicle Identification Data into Origin-Destination Estimation2004In: TRANSPORTATION NETWORK MODELING 2004, Istanbul, Turkey, 2004, p. 37-44Conference paper (Refereed)
    Abstract [en]

    A methodology for the incorporation of automated vehicle identification (AVI) data into origin-destination (O-D) estimation and prediction is presented. AVI technologies facilitate the collection of useful data, such as point-to-point travel times and subpath flows. A framework for the incorporation of AVI data into the well-established O-D estimation and prediction process is presented. Improvements are proposed for both the formulation and the inputs to the O-D estimation and prediction model. Furthermore, as the O-D estimation and prediction process is often used in the traffic estimation and prediction context, approaches to the incorporation of AVI data into other areas of the dynamic traffic assignment framework are outlined. Performance and computational issues are also considered, and the results of a case study are presented to demonstrate the approach.

  • 9. Antoniou, C
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    Department of Civil Engineering, North-eastern University.
    Non-Linear Kalman Filtering Algorithms for On-Line Calibration of Dynamic Traffic Assignment Models2006In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, Toronto, Canada, 2006, p. 833-838Conference paper (Refereed)
    Abstract [en]

    The problem of on-line calibration of Dynamic Traffic Assignment (DTA) models is receiving increasing attention from researchers and practitioners. The problem can be formulated as a non-linear state-space model. Because of its nonlinear nature, the resulting model cannot be solved by the Kalman Filter and therefore non-linearextensions need to be considered. In this paper, three extensions to the Kalman Filteralgorithm are presented: Extended Kalman Filter (EKF), Limiting EKF (LimEKF), and Unscented Kalman Filter (UKF). The solution algorithms are applied to the calibration of the state-of-the-art DynaMIT-R DTA model and their use is demonstrated in a freeway network in Southampton, U.K. The LimEKF shows accuracy comparable to that of the bestalgorithm, but vastly superior computational performance. 

  • 10. Antoniou, C
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    Northeastern University, 437 Snell Engineering Center.
    Online Calibration of Dynamic Traffic Models2004In: Proceedings of the 2nd International Congress in Transport Research, 2004, p. 37-44Conference paper (Refereed)
  • 11.
    Antoniou, C
    et al.
    MIT.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    On-line Calibration of Traffic Prediction Models2004In: Intelligent Transportation Systems, 2004. Proceedings. The 7th International IEEE Conference on, Washington, D.C., 2004, p. 82-87Conference paper (Refereed)
    Abstract [en]

    A methodology for the on-line calibration of the speed-density relationship is formulated as a flexible state-space model. Applicable solution approaches are discussed and three of them (extended Kalman filter (EKF), iterated EKF, and unscented Kalman filter (UKF) are selected and presented in detail. An application of the methodology with freeway sensor data from two networks in Europe and the U.S. is presented. The improvement in the estimation and prediction of speeds due to on-line calibration (compared with the speeds obtained from the off-line calibrated relationship) is demonstrated. The EKF provides the most straightforward solution to this problem, and indeed achieves considerable improvements in estimation and prediction accuracy. The benefits obtained from the -more computationally expensive-iterated EKF algorithm are shown. An innovative solution technique (the UKF) is also presented. The UKF has a number of unique qualities and advantages over the EKF, including no assumption of analytical representation of the model and no need for explicit computation of derivatives. Empirical results suggest that the UKF outperforms the other two solution techniques in prediction accuracy.

  • 12. Antoniou, C
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Practical considerations for on-line calibration of traffic simulation models2011In: Proceedings of ITS2011: Intelligent Transportation Systems, 2011Conference paper (Refereed)
  • 13. Antoniou, C.
    et al.
    Koutsopoulos, Harilaos N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Yannis, G.
    Dynamic data-driven local traffic state estimation and prediction2013In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 34, p. 89-107Article in journal (Refereed)
    Abstract [en]

    Traffic state prediction is a key problem with considerable implications in modern traffic management. Traffic flow theory has provided significant resources, including models based on traffic flow fundamentals that reflect the underlying phenomena, as well as promote their understanding. They also provide the basis for many traffic simulation models. Speed-density relationships, for example, are routinely used in mesoscopic models. In this paper, an approach for local traffic state estimation and prediction is presented, which exploits available (traffic and other) information and uses data-driven computational approaches. An advantage of the method is its flexibility in incorporating additional explanatory variables. It is also believed that the method is more appropriate for use in the context of mesoscopic traffic simulation models, in place of the traditional speed-density relationships. While these general methods and tools are pre-existing, their application into the specific problem and their integration into the proposed framework for the prediction of traffic state is new. The methodology is illustrated using two freeway data sets from Irvine, CA, and Tel Aviv, Israel. As the proposed models are shown to outperform current state-of-the-art models, they could be valuable when integrated into existing traffic estimation and prediction models.

  • 14. Antoniou, C
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    A Comparison of Machine Learning Models for Speed Estimation2006In: IFAC Proceedings Volumes, Delft, The Netherlands, 2006, p. 55-60Conference paper (Refereed)
    Abstract [en]

    Speed-density relationships are a classic way of modeling stationary traffic relationships. Besides offering valuable insight in traffic stream flows, such relationships are widely used in simulation-based Dynamic Traffic Assignment (DTA) systems. In this paper, alternative approaches for modeling traffic dynamics, appropriate for traffic simulation, are proposed. Their basic premise is the wide availability of sensor data. The approaches are based on machine learning methods such as locally weighted regression and support vector regression. Neural networks are also considered, as they are a well-established approach, successful in many applications. While such models may not provide as much insight into traffic flow theory, they allow for easy incorporation of additional information tospeed estimation, and hence, may be more appropriate for use in DTA models, especially simulation based. In particular, in this paper, it is demonstrated (using data from a network in Irvine, CA) that the use of such machine learning methods can improve the accuracy of speed estimation. 

  • 15. Antoniou, C
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    Comparison of Parametric and Non-parametric Regression Models for Speed Estimation2006Conference paper (Refereed)
  • 16. Antoniou, C.
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    Simulation-based, Real-time Traffic Flow Prediction for Congestion Pricing2007Conference paper (Refereed)
    Abstract [en]

    Traffic congestion is one of the major problems plaguing modern cities, resulting in huge productivity losses, psychological disturbance for the citizens, and adverse direct and indirect impacts to the environment. Congestion pricing is one approach that has been long considered as a promising tool for managing congestion. As the thought matures, more advanced alternatives emerge, e.g. spot pricing or dynamic congestion pricing. However, the complexity of such congestion management methods requires the ability to dynamically predict short-term traffic flows, both without any intervention but –perhaps more importantly– resulting from alternative considered congestion pricing schemes. Simulation-based, real-time traffic flow and prediction systems are appropriate for such uses, as they provide the ability to perform short-term traffic flow predictions in real-time, while explicitly modeling the response of the drivers to the proposed congestion management schemes. This paper outlines the use of traffic flow prediction systems for the development and evaluation of congestion pricing schemes.

  • 17. Antoniou, C
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    Yannis, George
    An Efficient Non-linear Kalman Filtering Algorithm Using Simultaneous Perturbation and Applications in Traffic Estimation and Prediction2007In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2007, p. 217-222Conference paper (Refereed)
    Abstract [en]

    The Extended Kalman Filter, a well-established and straightforward extension of theKalman filter, requires a computationally intensive linearization step. In this paper, the use of the simultaneous perturbation is proposed for the computation of the gradient in a far more efficient way than the usual numerical derivatives. The resulting algorithm is applied to the problem of on-line calibration of traffic dynamics models and empirical results are presented. The use of the simultaneous perturbation gradient approximation provides significant improvement over the base case, and comparable results to those obtained by the more computationally intensive finite difference gradient approximation. 

  • 18. Antoniou, C
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    Yannis, George
    Traffic State Prediction Using Markov Chain Models2007In: Proceedings of the European Control Conference 2007, 2007, p. 2428-2435Conference paper (Refereed)
    Abstract [en]

    Motorway traffic management and control relieson models that estimate and predict traffic conditions. In thispaper, a methodology for the identification and short-termprediction of the traffic state is presented. The methodologycombines model-based clustering, variable-length Markovchains and nearest neighbor classification. An application ofthe methodology for short-term speed prediction in a freewaynetwork in Irvine, CA, shows encouraging results.

  • 19. Antoniou, Constantinos
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris N.
    Dynamic Traffic Demand Prediction Using Conventional and Emerging Data Sources2006In: IEE Proceedings Intelligent Transport Systems, ISSN 1748-0248, Vol. 153, no 1, p. 97-104Article in journal (Refereed)
    Abstract [en]

    Origin-destination (OD) flow estimation and prediction is an important problem with applications in Dynamic Traffic Management, and traffic estimation and prediction systems. Recent developments in traffic data collection technologies provide data that have not yet been used in OD estimation and prediction. In this paper, a new, flexible, and general methodology for OD estimation and prediction is presented. The methodology can incorporate any available information from conventional and emerging traffic data collection technologies (such as automatic vehicle identification systems and probe vehicles). The application of the methodology is presented through a case study. The results support the importance of incorporating additional data in the OD estimation problem. An overall improvement for estimation and one-step prediction exceeds 45 when point-to-point information is added to the model (over the base case when only point link flows are available), while an improvement of more than 35 is maintained even for four-step prediction (i.e. 1 h into the future).

  • 20. Antoniou, Constantinos
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Non–linear Kalman Filtering Algorithms for On–line Calibration of Dynamic Traffic Assignment Models2007In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 8, no 4, p. 661-670Article in journal (Refereed)
    Abstract [en]

    An online calibration approach that jointly estimates demand and supply parameters of dynamic traffic assignment (DTA) systems is presented and empirically validated through an extensive application. The problem can be formulated as a nonlinear state-space model. Because of its nonlinear nature, the resulting model cannot be solved by the Kalman filter, and therefore, nonlinear extensions need to be considered. The following three extensions to the Kalman filtering algorithm are presented: 1) the extended Kalman filter (EKF); 2) the limiting EKF (LimEKF); and 3) the unscented Kalman filter. The solution algorithms are applied to the on-line calibration of the state-of-the-art DynaMIT DTA model, and their use is demonstrated in a freeway network in Southampton, U.K. The LimEKF shows accuracy that is comparable to that of the best algorithm but with vastly superior computational performance. The robustness of the approach to varying weather conditions is demonstrated, and practical aspects are discussed.

  • 21. Antoniou, Constantinos
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    On-line Calibration of Traffic Prediction Models2005In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, Vol. 1934, p. 235-245Article in journal (Refereed)
    Abstract [en]

    A methodology for the on-line calibration of the speed-density relationship is formulated as a flexible state-space model. Applicable solution approaches are discussed and three of them (extended Kalman filter (EKF), iterated EKF, and unscented Kalman filter (UKF) are selected and presented in detail. An application of the methodology with freeway sensor data from two networks in Europe and the U.S. is presented. The improvement in the estimation and prediction of speeds due to on-line calibration (compared with the speeds obtained from the off-line calibrated relationship) is demonstrated. The EKF provides the most straightforward solution to this problem, and indeed achieves considerable improvements in estimation and prediction accuracy. The benefits obtained from the -more computationally expensive-iterated EKF algorithm are shown. An innovative solution technique (the UKF) is also presented. The UKF has a number of unique qualities and advantages over the EKF, including no assumption of analytical representation of the model and no need for explicit computation of derivatives. Empirical results suggest that the UKF outperforms the other two solution techniques in prediction accuracy.

  • 22. Antoniou, Constantinos
    et al.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Estimation of Traffic Dynamics Models with Machine Learning Methods2006In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, Vol. 1965, p. 103-111Article in journal (Refereed)
    Abstract [en]

    Speed-density relationships are a classic way of modeling stationary traffic relationships. Besides offering valuable insight into traffic stream flows, such relationships are widely used in dynamic traffic assignment (DTA) systems. In this research, an alternative paradigm for traffic dynamics models, appropriate for traffic simulation models and based on machine-learning approaches such as k-means clustering, k-nearest-neighborhood classification, and locally weighted regression is proposed. Although these models may not provide as much insight into traffic flow theory as speed-density relationships do, they allow for easy incorporation of additional information to speed estimation and hence may be more appropriate for use in DTA models, especially simulation-based models. This paper (with data from a network in Irvine, California) demonstrates that such machine-learning methods can considerably improve the accuracy of speed estimation.

  • 23. Antoniou, Constantinos
    et al.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Ben-Akiva, Moshe
    Chauhan, Akhilendra S.
    Evaluation of diversion strategies using dynamic traffic assignment2011In: Transportation planning and technology (Print), ISSN 0308-1060, E-ISSN 1029-0354, Vol. 34, no 3, p. 199-216Article in journal (Refereed)
    Abstract [en]

    A framework for the evaluation of the effectiveness of traffic diversion strategies for non-recurrent congestion, based on predictive guidance and using dynamic traffic assignment, is presented. Predictive guidance is based on a short-term prediction of traffic conditions, incorporating user reaction to information and guidance. A case study of the Lower Westchester County network in New York State, using DynaMIT-P, is presented to illustrate the application of the framework. DynaMIT-P is capable of evaluating diversion strategies based on predicted conditions, which take into account drivers' response to traffic information. The case study simulates the operations of predictive variable message signs positioned in strategic locations. DynaMIT-P is calibrated for the study network and used to establish base conditions for two incident scenarios in the absence of advanced traveller information systems. The effectiveness of predictive diversion strategies is evaluated (using rigorous statistical tests) by comparing traffic conditions with and without diversion strategies. The empirical findings suggest that incident diversion strategies based on predictive guidance result in travel time savings and increased travel time reliability.

  • 24.
    Balakrishna, R.
    et al.
    Caliper Corporation.
    Antoniou, C.
    Department of Transportation Planning and Engineering, National Technical University of Athens.
    Ben-Akiva, M.
    Massachusetts Institute of Technology.
    Koutsopoulos, Haris N.
    Northeastern University, Boston.
    Wen, Yang
    Massachusetts Institute of Technology.
    Calibration of Microscopic Traffic Simulation Models: Methods and Application2007In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 1999, p. 198-207Article in journal (Refereed)
    Abstract [en]

    A mathematical framework and a solution approach are presented for the simultaneous calibration of the demand and supply parameters and inputs to microscopic traffic simulation models as well as a large-scale application emphasizing practical issues. Microscopic traffic simulation models provide detailed estimates of evolving network conditions by modeling time-varying demand patterns and individual drivers' detailed behavioral decisions. Such models are composed of elements that simulate different demand and supply processes and their complex interactions. Several model inputs (such as origin-destination flows) and parameters (car-following and lane-changing coefficients) must be specified before these simulation tools can be applied, and their values must be determined so that the simulation output accurately replicates the reality reflected in traffic measurements. A methodology is presented here for simultaneously estimating all microscopic simulation model parameters by using general traffic measurements. A large-scale case study for the calibration of the MITSimLab microscopic traffic simulation model by using the network of Lower Westchester County, New York, is employed to demonstrate the feasibility, application, and benefits of the proposed methodology.

  • 25. Balakrishna, R
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    Northeastern University, Boston.
    Off-line Calibration of Dynamic Traffic Assignment: Simultaneous Demand-Supply Estimation2007Conference paper (Refereed)
  • 26. Balakrishna, R
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Simulation-Based Evaluation of DynaMIT's Route Guidance and its Impact on Network Travel Times2004Conference paper (Refereed)
  • 27. Balakrishna, R
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    Northeastern University.
    Simultaneous Off-Line Demand-Supply Calibration for Simulation-Based Dynamic Traffic Assignment Models2007In: 11th World Conference on Transport Research, 2007Conference paper (Refereed)
    Abstract [en]

    Simulation-based Dynamic Traffic Assignment (DTA) systems are widely used in many Intelligent Transportation Systems (ITS), to generate time-varying network performance measures such as travel times, delays, queue lengths and spillbacks. Such DTA systems are comprised of detailed demand and supply model components whose outputs depend on a large number of inputs and parameters that must be calibrated to match real-world traffic data. Owing to the complexity of the calibration process, most studies rely on component-wise estimation that uses parts of the available data to estimate subsets of parameters. Such an approach is potentially inefficient and biased, and typically relies on approximations (such as an assignment matrix) to simplify the relationships between the parameters and the data. In this paper, we apply a methodology for simultaneously calibrating all DTA model parameters (on both demand and supply sides) without using approximations, and incorporating any general traffic data that may be collected. A large-scale optimization problem is formulated, and a scalable solution approach is outlined. The feasibility of the method is demonstrated by calibrating a simulation-based DTA model (DynaMIT) for a real network and dataset from Los Angeles. The benefits of the proposed approach are further validated through the evaluation of the real-time estimation and prediction accuracy of the calibrated model. Numerical results indicate that the new approach significantly outperforms the current state-of-the-art in replicating traffic data that was not used to calibrate the system.

  • 28. Balakrishna, R.
    et al.
    Ben-Akiva, Moshe
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Time-Dependent Origin-Destination Estimation Without Assignment Matrices2008In: Traffic Simulation, EPFL Press , 2008Conference paper (Refereed)
    Abstract [en]

    Time-dependent origin-destination (OD) flows are crucial inputs to dynamic traffic assignment (DTA) models. However, they are often unobserved, and must be estimated from indirect traffic measurements collected from the study network. Approaches to estimate OD flows from link counts traditionally rely on assignment matrices that map the OD flow variables onto the counts. However, this method (a) approximates the complex relationship between OD flows and counts with a linear function, (b) is restricted to the use of only counts, and cannot exploit richer data such as speeds, densities or travel times, and (c) cannot estimate route choice and supply parameters that critically impact the OD estimates. We present a dynamic OD estimation method that is accurate, flexible in the use of general traffic data, simultaneously estimates all parameters that impact OD estimation, and can be applied to any traffic assignment model.

  • 29. Balakrishna, R
    et al.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Incorporating Within-Day Transitions in Simultaneous Estimation of Dynamic Origin-Destination Flows Without Assignment Matrices2008Conference paper (Refereed)
  • 30. Balakrishna, R
    et al.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Simultaneous Calibration of Dynamic Origin-Destination Matrices with Structural Relationships2008Conference paper (Refereed)
  • 31. Balakrishna, R
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    Ben-Akiva, Moshe
    Calibration and Validation of Dynamic Traffic Assignment Systems2005In: Transportation and traffic theory: flow, dynamics and human interaction : proceedings of the 16th International Symposium on Transportation and Traffic Theory, University of Maryland, College Park, Maryland, 19-21 July 2005 / [ed] Hani S. Mahmassani, Elsevier Science , 2005, p. 407-426Conference paper (Refereed)
  • 32. Balakrishna, R
    et al.
    Koutsopoulos, Haris
    Northeastern University.
    Ben-Akiva, Moshe
    Simultaneous Off-Line Demand and Supply Calibration of Dynamic Traffic Assignment Systems2006In: Proceedings of Transportation Research Board Annual Meeting 2006, 2006Conference paper (Refereed)
  • 33.
    Balakrishna, Ramachandran
    et al.
    Caliper Corp.
    Ben-Akiva, Moshe
    MIT, Cambridge.
    Koutsopoulos, Haris N.
    Northeastern Univ, Boston.
    Offline calibration of dynamic traffic assignment: Simultaneous Demand-and-Supply Estimation2007In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2003, p. 50-58Article in journal (Refereed)
    Abstract [en]

    Advances in intelligent transportation systems have resulted in deployment of surveillance systems that automatically collect and store extensive networkwide traffic data. Dynamic traffic assignment (DTA) models have been developed for a variety of dynamic traffic management applications. They are designed to estimate and predict the evolution of congestion with detailed models and algorithms that capture travel demand and network supply and their complex interactions. The availability of rich time-varying traffic data spanning multiple days provides the opportunity to calibrate a DTA model’s inputs and parameters offline so that its outputs reflect field conditions in future offline and online real-time applications. The state of the art of DTA model calibration is a sequential approach, with supply model calibration (assuming known demand inputs) followed by demand calibration with fixed supply parameters. An offline DTA model calibration methodology is presented for simultaneous estimation of all demand-and-supply inputs and parameters, with sensor data. A minimization formulation that can use any general traffic data and present scalable solution approaches for the complex, nonlinear, stochastic optimization problem is adopted. A case study with DynaMIT, a DTA model with traffic estimation and prediction capabilities, is used to demonstrate and validate the methodology. Archived sensor data and a network from Los Angeles, California, are used to demonstrate scalability. Results indicate that the simultaneous approach significantly outperforms the sequential state of the art in terms of modeling accuracy and computational efficiency.

  • 34. Balakrishna, Ramachandran
    et al.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Incorporating Within-Day Transitions in Simultaneous Offline Estimation of Dynamic Origin-Destination Flows Without Assignment Matrices2008In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2085, p. 31-38Article in journal (Refereed)
    Abstract [en]

    An offline methodology is presented: it simultaneously estimates dynamic origin-destination (O-D) matrices, without using assignment matrices that incorporate within-day transition equations. The proposed formulation and solution approach extends a calibration method recently developed that directly uses the output of any network loading model (such as a dynamic traffic assignment or simulation model) so that the complex relationships between O-D flows and model outputs are accurately captured (as opposed to the more common method of approximate linear relationships based oil file assignment matrix). The study extends the original formulation by incorporating spatial and temporal relationships among various O-D flows (transition equations). These transition equations link O-D flow variables across time intervals in such it way that known structural demand patterns can be preserved in the new estimates. Such transition equations, although common in the context of real-time O-D flows, complicate the offline simultaneous estimation of O-D flows and have not been used to their full potential in the past. The approach is demonstrated through a case study.

  • 35.
    Balakrishna, Ramachandran
    et al.
    Department of Civil and Environmental Engineering, Massachusetts Institute of Technology.
    Koutsopoulos, Haris N.
    Department of Civil and Environmental Engineering, Northeastern University, Boston.
    Ben-Akiva, Moshe
    Department of Civil and Environmental Engineering, Northeastern University, Boston.
    Fernandez Ruiz, Bruno M.
    Massachusetts Institute of Technology.
    Mehta, Manish
    Lehman Brothers Inc..
    A Simulation-based Evaluation of Advanced Traveler Information Systems2005In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, Vol. 1910, p. 90-98Article in journal (Refereed)
    Abstract [en]

    Traveler information has the potential to reduce travel times and improve their reliability. Studies have verified that driver overreaction from the dissemination of information can be eliminated through prediction-based route guidance that uses short-term forecasts of network state. Critical off-line tests of advanced dynamic traffic assignment-based prediction systems have been limited, since the system being evaluated has also been used as the test bed. This paper outlines a detailed simulation-based laboratory for the objective and independent evaluation of advanced traveler information systems, a laboratory with the flexibility to analyze the impacts of various design parameters and modeling errors on the quality of the generated guidance. MITSIMLab, a system for the evaluation of advanced traffic management systems, is integrated with Dynamic Network Assignment for the Management of Information to Travelers (DynaMIT), a simulation-based decision support system designed to generate prediction-based route guidance. Evaluation criteria and requirements for the closed-loop integration of MITSIMLab and DynaMIT are discussed. Detailed case studies demonstrating the evaluation methodology and sensitivity of DynaMIT's guidance are presented.

  • 36.
    Ben-Akiva, M.
    et al.
    Massachusetts Institute of Technology.
    Bottom, J.
    CRA International.
    Gao, S.
    Caliper Corporation.
    Koutsopoulos, Haris N.
    Northeastern University, Boston.
    Wen, Y.
    Massachusetts Institute of Technology.
    Towards Disaggregate Dynamic Travel Forecasting Models2007In: Tsinghua Science and Technology, ISSN 1007-0214, Vol. 12, no 2, p. 115-130Article in journal (Refereed)
    Abstract [en]

    The authors argue that travel forecasting models should be dynamic and disaggregate in their representation of demand, supply, and supply-demand interactions, and propose a framework for such models. The proposed framework consists of disaggregate activity-based representation of travel choices of individual motorists on the demand side integrated with disaggregate dynamic modeling of network performance, through vehicle-based traffic simulation models on the supply side. The demand model generates individual members of the population and assigns to them socioeconomic characteristics. The generated motorists maintain these characteristics when they are loaded on the network by the supply model. In an equilibrium setting, the framework lends itself to a fixed-point formulation to represent and resolve demand-supply interactions. The paper discusses some of the remaining development challenges and presents an example of an existing travel forecasting model system that incorporates many of the proposed elements.

  • 37. Ben-Akiva, Moshe
    et al.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Antoniou, C
    Balakrishna, R
    Traffic Simulation with DynaMIT2010In: Fundamentals of Traffic Simulation, Springer, 2010, p. 363-398Chapter in book (Refereed)
    Abstract [en]

    DynaMIT (Dynamic Network Assignment for the Management of Information to Travelers) is a dynamic traffic assignment model system that estimates and predicts traffic. DynaMIT is also a real-time system for decision support at traffic management centers for generation of predictive traffic information. A planning version also exists. DynaMIT captures the dynamic performance of the network (e.g., lane-based queuing and spillback effects), travel behavior, its sensitivity to traffic conditions and available traffic information, and consistency between demand and supply. DynaMIT consists of a demand simulator, a supply simulator, and algorithms that capture demand and supply interactions. Methodologies for the online and offline estimation of OD flows and the offline and online calibration of various inputs and parameters (such as network performance parameters) have been developed as well. Several case studies from the United States, Europe, and Asia are discussed, and a distributed version of DynaMIT is also presented.

  • 38. Ben-Akiva, Moshe
    et al.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Toledo, Tomer
    Yang, Qi
    Choundhury, Charisma
    Antoniou, Constantinos
    Balakrishna, Ramachandran
    Traffic Simulation with MITSIMLab2010In: Fundamentals of Traffic Simulation, Springer, 2010, p. 233-268Chapter in book (Refereed)
    Abstract [en]

    MITSIMLab (MIcroscopic Traffic SIMulation Laboratory) is a microscopic traffic simulation model that evaluates the impacts of alternative traffic management system designs at the operational level and assists in their subsequent refinement. MITSIMLab models the travel and driving behavior of individual vehicles, the detailed movement of transit vehicles, and the various control and information provision strategies through a generic controller. A calibration methodology for important parameters and inputs was also developed. The model has been extended to address the special driving behavior evidenced in urban networks and has been used as a test bed for the evaluation of advanced traveler information systems (ATIS). Calibration and validation results from networks in the United States and Europe are discussed.

  • 39. Biem, Alain
    et al.
    Bouillet, Eric
    Feng, Hanhua
    Ranganathan, Anand
    Riabov, Anton
    Verscheure, Olivier
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Moran Toledo, Carlos
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    IBM InfoSphere Streams for Scalable, Real-Time, Intelligent Transportation Services2010In: 2010 International Conference on Management of Data, SIGMOD '10, 2010, p. 1093-1103Conference paper (Refereed)
    Abstract [en]

    With the widespread adoption of location tracking technologies like GPS, the domain of intelligent transportation services has seen growing interest in the last few years. Services in this domain make use of real-time location-based data from a variety of sources, combine this data with static location-based data such as maps and points of interest databases, and provide useful information to end-users. Some of the major challenges in this domain include i) scalability, in terms of processing large volumes of real-time and static data; ii) extensibility, in terms of being able to add new kinds of analyses on the data rapidly, and iii) user interaction, in terms of being able to support different kinds of one-time and continuous queries from the end-user. In this paper, we demonstrate the use of IBM InfoSphere Streams, a scalable stream processing platform, for tackling these challenges. We describe a prototype system that generates dynamic, multi-faceted views of transportation information for the city of Stockholm, using real vehicle GPS and road-network data. The system also continuously derives current traffic statistics, and provides useful value-added information such as shortest-time routes from real-time observed and inferred traffic conditions. Our performance experiments illustrate the scalability of the system. For instance, our system can process over 120000 incoming GPS points per second, combine it with a map containing over 600,000 links, continuously generate different kinds of traffic statistics and answer user queries.

  • 40. Biem, Alain
    et al.
    Bouillet, Eric
    Ranganathan, Anand
    Rahmani, Mahmood
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Real-Time Traffic Information Management using Stream Computing2010Report (Other academic)
  • 41.
    Burghout, Wilco
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR.
    Cats, Oded
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Toledo, Tomer
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    DYMOBUS: dynamic mesoscopic modelling of bus public transport2009In: Conference proceedings to ITS 2009 conference, 2009Conference paper (Refereed)
    Abstract [en]

    In today’s public bus transport punctuality is one of the main problems to deal with for traffic planners and operators, especially in large cities such as Stockholm. The current static models do not handle congestion delays and the interaction between bus and car traffic, leading to overly optimistic timetables and hard to manage delays. In the DYMOBUS project (Funded by VINNOVA and City of Stockholm) a dynamic modelling tool was developed in order to study these interactions. This paper discusses a mesoscopic, mixed-traffic, a transit simulation model designed to support evaluation of operations planning and control, especially in the context of Advanced Public Transportation Systems (APTS). Examples of applications include frequency determination, evaluation of real time control strategies for schedule maintenance and restoration from major disruptions. The transit simulation component is designed to represent realistically the uncertainty in operations, in order to assess service reliability. The simulation models all sources of uncertainty: chaining of trips, travel time variability, behavior at stops and a detailed representation of passenger demand at the various stops. Unlike most previous efforts in this area, the simulation model is built on the platform of a mesoscopic traffic simulation model, which allows modeling of the operations of large-scale transit systems. A Tel-Aviv case study demonstrates the transit simulation capabilities of the model.

  • 42.
    Burghout, Wilco
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Koutsopoulos, Harilaos
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Hybrid Traffic Simulation Models: Vehicle loading at meso-micro boundaries2008In: Transport Simulation, Lausanne: EPFL Press , 2008, 1Chapter in book (Other academic)
  • 43.
    Burghout, Wilco
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Andreasson, Ingmar
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    A Discrete-Event Mesoscopic Traffic Simulation Model for Hybrid Traffic Simulation2006In: IEEE Intelligent Transportation Systems Conference, 2006. ITSC'06, IEEE , 2006, p. 1102-1107Conference paper (Refereed)
    Abstract [en]

    The paper presents a mesoscopic traffic simulation model, particularly suited for the development of integrated meso-micro traffic simulation models. The model combines a number of the recent advances in simulation modeling, such as discrete-event time resolution and combined queue-server and speed-density modeling, with a number of new features such as the ability to integrate with microscopic models to create hybrid traffic simulation. The ability to integrate with microscopic models extends the area of use to include evaluation of ITS systems, which often require the detailed modeling of vehicles in areas of interest, combined with a more general modeling of large surrounding areas to capture network effects of local phenomena. The paper discusses the structure of the model, presents a framework for integration with micro models, and illustrates its validity through a case study with a congested network north of Stockholm. It also compares its performance with a hybrid model applied to the same network.

  • 44.
    Burghout, Wilco
    et al.
    KTH, Superseded Departments, Infrastructure.
    Koutsopoulos, Haris
    Andreasson, Ingmar
    KTH, Superseded Departments, Infrastructure.
    Hybrid mesoscopic-microscopic traffic simulation2004Conference paper (Refereed)
  • 45.
    Burghout, Wilco
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Andreasson, Ingmar
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR.
    Incident Management and Traffic Information: Tools and Methods for Simulation-Based Traffic Prediction2010In: TRB 89th Annual Meeting Compendium of Papers,, 2010Conference paper (Refereed)
  • 46.
    Burghout, Wilco
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics.
    Andreasson, Ingmar
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics.
    Hybrid Mesoscopic-Microscopic Traffic Simulation2005In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, Vol. 1934, p. 218-225Article in journal (Refereed)
    Abstract [en]

    Traffic simulation is an important tool for modeling the operations of dynamic traffic systems. Although microscopic simulation models provide a detailed representation of the traffic process, macroscopic and mesoscopic models capture the traffic dynamics of large networks in less detail but without the problems of application and calibration of microscopic models. This paper presents a hybrid mesoscopic-microscopic model that applies microscopic simulation to areas of specific interest while simulating a large surrounding network in less detail with a mesoscopic model. The requirements that are important for a hybrid model to be consistent across the models at different levels of detail are identified. These requirements vary from the network and route choice consistency to the consistency of the traffic dynamics at the boundaries of the microscopic and mesoscopic submodels. An integration framework that satisfies these requirements is proposed. A prototype hybrid model is used to demonstrate the application of the integration framework and the solution of the various integration issues. The hybrid model integrates MlTSIMLab, a microscopic traffic simulation model, and Mezzo, a newly developed mesoscopic model. The hybrid model is applied in two case studies. The results are promising and support both the proposed architecture and the importance of integrating microscopic and mesoscopic models.

  • 47.
    Burghout, Wilco
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics, Traffic and Logistics.
    Andreasson, Ingmar
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics.
    Incident Management and Traffic Information Tools and Methods for Simulation-Based Traffic Prediction2010In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2161, p. 20-28Article in journal (Refereed)
    Abstract [en]

    Incident response and mitigation are among the main tasks of operators at traffic control centers. Simulation models have a good chance of reproducing and predicting the effects of incident response by explicitly modeling driver response to the incident and information provided. In the PREDIKT project sponsored by the Swedish National Road Administration, the state-of-the-art mesoscopic simulation model MEZZO was extended to provide decision support for incident management. Numerous essential modeling components are described and tested, including modeling the incident response logic, a mixed-logit model, and a method for generating alternatives for drivers switching routes. In addition, the results of a fast calibration method based on simultaneous perturbation statistic approximation are presented. The model components are tested in a small case study that investigates the effect of delay in providing information to drivers after incidents. A linearization of speed-density functions also is shown to improve computational performance by 30% and increase calibration speed and stability while preserving simulation accuracy.

  • 48. Cats, O.
    et al.
    Toledo, T.
    Burghout, Wilco
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Koutsopoulos, Harilaos
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Mesoscopic Simulation for Transit2008Conference paper (Refereed)
  • 49.
    Cats, Oded
    et al.
    Faculty of Civil and Environmental Engineering, Technion-Israel Institute of Technology, Haifa.
    Burghout, Wilco
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR.
    Toledo, Tomer
    Koutsopoulos, Harilaos
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Mesoscopic Modeling of Bus Public Transportation2010In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2188, p. 9-18Article in journal (Refereed)
    Abstract [en]

    Analysis of public transport system performance and level of service in urban areas is essential. Dynamic modeling of traffic conditions, passenger demand, and transit operations is important to represent adequately the complexity of and the interactions between these components in modern public transportation systems. This paper presents a transit simulation model designed to support evaluation of operations planning and control, especially in the context of advanced public transportation systems. Unlike most previous efforts in this area, the simulation model is built on a platform of a mesoscopic traffic simulation model, which allows modeling or the operation dynamics of large-scale transit systems, taking into account the main sources of service uncertainty and stochasticity. The capabilities of Mezzo as an evaluation tool of transit operations are demonstrated with an application to a real-world, high-demand bus line in metropolitan Tel Aviv, Israel, under various scenarios. The application shows that important phenomena such as bus bunching are reproduced realistically. A comparison of simulated running times and headway distributions with field data shows the model is capable of replicating observed data.

  • 50.
    Cats, Oded
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Burghout, Wilco
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Toledo, Tomer
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Effect of real-time transit information on dynamic passenger path choice.2011In: Transportation Research Record, ISSN 0361-1981, Vol. 2217, p. 46-54Article in journal (Refereed)
    Abstract [en]

    Real-time information is increasingly being implemented in transit networks worldwide. The evaluation of the effect of real-time information requires dynamic modeling of transit operations and of passenger path choices. This paper presents a dynamic transit analysis and evaluation tool that represents time-tables, operation strategies, real-time information, adaptive passenger choices, and traffic dynamics at the network level. Transit path choices are modeled as a sequence of boarding, walking and alighting decisions that passengers undertake when carrying out their journey. The model is applied to the Metro network of Stockholm, Sweden area under various operating conditions and information provision scenarios, as a proof of concept. An analysis of the results indicates substantial path choice shifts and potential time savings associated with more comprehensive real-time information provision and transfer coordination improvements.

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