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  • 101.
    Nissan, Albania
    et al.
    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).
    Evaluation of dynamic recommended variable speed limits for motorway traffic control (MCS) on E4 in Stockholm using micro-simulation2009Conference paper (Refereed)
    Abstract [en]

    A sophisticated traffic management system (MCS) has been implemented on the E4 motorway through Stockholm. The system generates variable advisory speed messages (VSL) triggered by automatic incident detection (AID) alarms for downstream queues and congestion. The MCS was introduced to deal with special traffic circumstances such as accidents, lane closures, and high congestion. The traffic impacts of the system were quantitatively evaluated through extensive field studies of driver behaviour using video recordings and data collected from the MCS detectors. Further studies have been performed focusing on system impacts on the speed-density relationships, which were statistically analyzed regarding difference between traffic conditions before and after the implementation of VSL. This paper describes use of the micro-simulation model VISSIM for traffic impact evaluation of MCS.

  • 102.
    Nissan, Albania
    et al.
    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.
    Evaluation of the Impact of Advisory Variable Speed Limits on Motorway Capacity and Level of Service2011In: 6TH INTERNATIONAL SYMPOSIUM ON HIGHWAY CAPACITY AND QUALITY OF SERVICE, Elsevier, 2011, p. 100-109Conference paper (Refereed)
    Abstract [en]

    Variable Speed Limits (VSL) have been introduced to improve the operations of freeway facilities under congested conditions. Experience indicates that the impacts of VSL on traffic performance and safety might be higher if the displayed speed limits were mandatory instead of recommended. This paper focuses on the impact of advisory VSL and proposes a statistical methodology for the comparison of traffic conditions before and after the implementation of VSL using the prevailing flow-density relationships. A case study, with data collected from the E4 motorway in Stockholm, is used to illustrate the methodology and evaluate the impact of advisory VSL. The results indicate that the advisory VSL had no significant impact on traffic conditions, both immediately after the implementation and several months later.

  • 103.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Floating Car and Camera Data Fusion for Non-Parametric Route Travel Time Estimation2014Conference paper (Refereed)
    Abstract [en]

    The paper proposes a non-parametric route travel time estimation method based on fusion of floating car data (FCD) and automated number plate recognition (ANPR) data. Today’s traffic management utilizes heterogeneous data collection systems which can be stationary or mobile. Each data collection system has its own advantages and disadvantages. Stationary sensors usually have less measurement noise than mobile sensors but their network coverage is limited. On the other hand, mobile sensors, commonly installed in fleet vehicles, cover relatively wider areas of the network but they suffer from low penetration rate and low sampling frequency. Traffic state estimations can benefit from fusion of data collected by various sources as they complement each other. The proposed estimation method is implemented using FCD from taxis and the ANPR data from Stockholm, Sweden. The results suggest that the fusion increases the robustness of the estimation, meaning that the fused estimates are always better than the worst of the two (FCD or ANPR), and it sometimes outperforms the two single sources.

  • 104.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. Northeastern University, United States.
    Non-parametric estimation of route travel time distributions from low-frequency floating car data2015In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 58B, p. 343-362Article in journal (Refereed)
    Abstract [en]

    The paper develops a non-parametric method for route travel time distribution estimation using low-frequency floating car data (FCD). While most previous work has focused on link travel time estimation, the method uses FCD observations for estimating the travel time distribution on a route. Potential biases associated with the use of sparse FCD are identified. The method involves a number of steps to reduce the impact of these biases. For evaluation purposes, a case study is used to estimate route travel times from taxi FCD in Stockholm, Sweden. Estimates are compared to observed travel times for routes equipped with Automatic Number Plate Recognition (ANPR) cameras with promising results. As vehicles collecting FCD (in this case, taxis) may not be a representative sample of the overall vehicle fleet and driver population, the ANPR data along several routes are also used to assess and correct for this bias. The method is computationally efficient, scalable, and supports real time applications with large data sets through a proposed distributed implementation.

  • 105.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Route travel time estimation using low-frequency floating car data2013Conference paper (Refereed)
  • 106.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Route travel time estimation using low-frequency floating car data2013In: 2013 16th International IEEE Conference on Intelligent Transportation Systems - (ITSC): Intelligent Transportation Systems for All Modes, IEEE conference proceedings, 2013, p. 2292-2297Conference paper (Refereed)
    Abstract [en]

    The paper develops a non-parametric method for route travel time estimation using low-frequency floating car data (FCD). While most previous work has focused on link travel time estimation, the method uses FCD observations directly for estimating the travel time distribution on a defined route. A list of potential biases associated with FCD is presented and discussed. For each source of bias, a correction method for the observations is proposed. The estimation method is implemented using FCD data from taxis in Stockholm, Sweden. Estimates are compared to observed travel times for two routes equipped with automatic number plate recognition (ANPR) cameras. The mean travel time estimates incorporating all bias corrections perform equally well or better than the link-based approach in terms of RMSE, and estimated percentiles show a good match to ANPR.

  • 107.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Koutsopoulos, Hans N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Path inference from sparse floating car data for urban networks2013In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 30, p. 41-54Article in journal (Refereed)
    Abstract [en]

    The use of probe vehicles in traffic management is growing rapidly. The reason is that the required data collection infrastructure is increasingly in place in urban areas with a significant number of mobile sensors constantly moving and covering expansive areas of the road network. In many cases, the data is sparse in time and location and includes only geo-location and timestamp. Extracting paths taken by the vehicles from such sparse data is an important step towards travel time estimation and is referred to as the map-matching and path inference problem. This paper introduces a path inference method for low-frequency floating car data, assesses its performance, and compares it to recent methods using a set of ground truth data.

  • 108.
    Rahmani, Mahmood
    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).
    Ranganathan, Anand
    IBM.
    Requirements and Potential of GPS-based Floating Car Data for Traffic Management: Stockholm Case Study2010In: 2010 13th International IEEE Conference on Intelligent Transportation Systems, 2010, p. 730-735Conference paper (Refereed)
    Abstract [en]

    The application of GPS probes in traffic management is growing rapidly as the required data collection infrastructure is increasingly in place in urban areas with significant number of mobile sensors moving around covering expansive areas of the road network. The paper presents the development of a laboratory designed to explore GPS and other emerging traffic and traffic-related data for traffic monitoring and control. It also presents results to illustrate the scope of traffic information that can be provided by GPS-based data, using the city of Stockholm as a case study. The preliminary analysis shows that network coverage, especially during peak weekday hours, is adequate. Further investigation is needed to validate the data, and increase its value through fusion with complementary data from other sources.

  • 109.
    Rahmani, Mahmood
    et al.
    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.
    Path inference of low-frequency GPS probes for urban networks2012In: Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on, IEEE , 2012, p. 1698-1701Conference paper (Refereed)
    Abstract [en]

    The use of probe vehicles in traffic management is growing rapidly. The reason is that the required data collection infrastructure is increasingly in place in urban areas with significant number of mobile sensors moving around covering expansive areas of the road network. The data is usually sparse in time and location. It usually includes only geo-location and timestamp. Extracting the paths taken by the vehicles is an important step in using this data. Such methods are referred to as map-matching or path inference. This paper introduces a path inference method for low-frequency probes and evaluates its accuracy in comparison to a recent method.

  • 110.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Jenelius, Erik
    Travel Time Estimation from Sparse Floating Car Data with Consistent Path Inference: A Fixed Point ApproachManuscript (preprint) (Other academic)
    Abstract [en]

    An important application of sparse floating car data (FCD) is the estimation of network link travel times, which requires pre-processing by map-matching and path inference filters. Path inference, in general, requires some a priori assumption about link travel times to infer paths that are reasonable and temporally consistent with observations. Path inference and travel time estimation is thus a joint problem. This paper proposes a fixed point approach to the travel time estimation problem with consistent path inference.The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. In this case study, existing methods for path inference and travel time estimation, without any particular assumptions about path choice models or travel time distributions, are used. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times and data sizes. Using historical initial travel times reduces bias. The results highlight the value of the fixed point estimation process, in particular for accurate path finding and route optimization.

  • 111.
    Rahmani, Mahmood
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. Northeastern University, United States.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach2017In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 85, p. 628-643Article in journal (Refereed)
    Abstract [en]

    Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.

  • 112.
    Silvano, Ary
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Farah, Haneen
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Koutsopoulos, Harilaos N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Simulation-based evaluation of theimpact of I2V systems on traffic performanceManuscript (preprint) (Other academic)
  • 113.
    Silvano, Ary
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Farah, Haneen
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Koutsopoulos, Harilaos N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    The free-flow speed distributionon urban roads: A probabilistic approach to model time headway thresholdsManuscript (preprint) (Other academic)
  • 114.
    Silvano, Ary
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. Northeastern University, United States.
    Ma, Xiaoliang
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Analysis of vehicle-bicycle interactions at unsignalized crossings: A probabilistic approach and application2016In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 97, p. 38-48Article in journal (Refereed)
    Abstract [en]

    In the last decades, bicycle usage has been increasing in many countries due to the potential environmental and health benefits. Therefore, there is a need to better understand cyclists’ interactions with vehicles, and to build models and tools for evaluating multimodal transportation infrastructure with respect to cycling safety, accessibility, and other planning aspects. This paper presents a modeling framework to describe driver-cyclist interactions when they are approaching a conflicting zone. In particular, the car driver yielding behavior is modeled as a function of a number of explanatory variables. A two-level hierarchical, probabilistic framework (based on discrete choice theory) is proposed to capture the driver’s yielding decision process when interacting with a cyclist. The first level models the probability of the car driver perceiving a situation with a bicycle as a potential conflict whereas the second models the probability of yielding given that a conflict has been perceived by the driver. The framework also incorporates the randomness of the location of the drivers’ decision point. The methodology is applied in a case study using observations at a typical Swedish roundabout. The results show that the conflict probability is affected differently depending on the user (cyclist or driver) who arrives at the interaction zone first. The yielding probability depends on the speed of the vehicle and the proximity of the cyclist.

  • 115.
    Silvano, Ary P.
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Ma, Xiaoliang
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    When do drivers yield to cyclists at unsignalized roundabouts?: Empirical evidence and behavioral analysis2015In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2520, p. 25-31Article in journal (Refereed)
    Abstract [en]

    Cycling popularity has shown an increasing trend during the last decades in many cities of Europe and USA because of its environmental and health benefits. However, cyclists are frequently involved in traffic accidents, especially, when they interact with vehicles at unsignalized intersections. There is still lack of evidence and analysis on how such interaction is performed. This paper explores empirical evidence of the vehicle-bicycle interaction on a typical Swedish roundabout, and provides insights into factors influencing car drivers’ yielding decisions when they interact with cyclists. The vehicle-bicycle interaction was divided into category groups (Non-Conflict, Conflict, Yield, and Non-Yield) and their speed differences were analyzed by group. Furthermore, a discrete choice model was developed to estimate behavioral aspects of such interactions. The observed data showed a higher and significant speed variation among vehicles, whereas bicycles exhibited lower variation across the groups. The modelling results revealed that the yielding probability decreased when the speed of the vehicle was higher. On the other hand, the bicycle speed had little impact on drivers’ decision to yield. More importantly, the yielding probability increased significantly by the proximity of the cyclist to the conflicting zone. The yielding rate of drivers can be improved by keeping vehicles’ speed under 20 km/h, as drivers have the capacity to detect and yield to cyclists.  

  • 116.
    Silvano, Ary Pezo
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Farah, H.
    Koutsopoulos, HarilaosN.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Simulation-based evaluation of I2V systems' impact on traffic performance: Case study - COOPERS2014In: WIT Transactions on the Built Environment, 2014, p. 429-446Conference paper (Refereed)
    Abstract [en]

    In-vehicle technologies and cooperative services are attracting a lot of attention for their potential to deal with congestion problems and improve traffic safety. This paper aims to investigate the impact of infrastructure-to-vehicle cooperative systems, case of COOPERS, at the aggregate level, on traffic performance. A factorial experiment is designed with two factors: traffic demand and penetration of the system with three levels each. In total, nine scenarios are investigated. To replicate driving behavior with and without the system, speed distributions from a simulator experiment are used. A motorway section of 4 km is built in VISSIM simulation software. Indicators such as speed, density, delays and travel times are chosen to evaluate and compare the motorway performance with and without the system. The results show that drivers driving with the system activated are more aware and alert to near future traffic conditions compared to driving without the system. Driving with the system activated is characterized by smoother and longer speed decelerations when approaching critical incident/accident events. The results show as well that the factors investigated significantly impact the motorway performance. Congestion reduces the impact of the system whereas higher penetration levels improve traffic operation on the motorway. Future research directions can include (1) investigating the impact of the system at the micro level such as lane changing or car-following behaviors; (2) levels of compliance with the system, which is an important aspect as well.

  • 117.
    Silvano, Ary Pezo
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Farah, H.
    The free-flow speed estimation: a probabilistic approach Impact of speed limit changes, road characteristics and probability to be constrainedManuscript (preprint) (Other academic)
  • 118.
    Sochor, Jana
    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).
    Dziekan, Katrin
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301).
    Urban Mobility and Safety: ITS Technologies and Ethical Issues2008In: 15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008, 2008Conference paper (Refereed)
  • 119.
    Sochor, Jana
    et al.
    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).
    Understanding and enhancing mobility through IT: opportunities and challenges2009Conference paper (Refereed)
    Abstract [en]

    Advancements in positioning and mobile systems allow for increasingly precise and continual measurements of the locations and movements of individuals and objects. These tracking and monitoring capabilities facilitate the collection of activity data and subsequently the study and support of human mobility via all modes, including walking, as well as enable the development of services and devices to support individuals’ mobility needs, and in particular for groups of special interest such as the elderly. However, the collection and use of such data also poses ethical challenges and may negatively impact privacy. This paper addresses the opportunities and discusses the challenges surrounding mobility data on both individual and organizational levels, and introduces a study being undertaken within this context.

  • 120. Sundaram, Srinivasan
    et al.
    Koutsopoulos, Harilaos
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Ben-Akiva, Moshe
    Antoniou, Constantinos
    Balakrishna, Ramachandran
    Simulation-based dynamic traffic assignment for short-term planning applications2011In: Simulation (San Diego, Calif.), ISSN 1569-190X, E-ISSN 1878-1462, Vol. 19, no 1, p. 450-462Article in journal (Refereed)
    Abstract [en]

    Evaluation of Intelligent Transportation Systems (ITS) at the planning level requires the use of appropriate tools that can capture the dynamic and stochastic interactions between demand and supply. The objective of this paper is to present a methodological simulation-based framework for such applications and implement it in the context of dynamic traffic assignment. The framework consists of a mesoscopic supply simulator and a demand simulator that combines OD estimation capabilities with discrete travel behavior models. Simulation-based DTA systems are particularly suited to evaluate a wide range of Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS). The simulation model performance is illustrated through two large-scale case studies in Irvine, California, and Lower Westchester County, NY.

  • 121. Toledo, Tomer
    et al.
    Ben-Akiva, Moshe
    Darda, Deepak
    Jha, Mithilesh
    Koutsopoulos, Haris
    Department of Civil Engineering, Northeastern University.
    Calibration of Microscopic Traffic Simulation Models with Aggregate Data2004In: CALIBRATION AND VALIDATION OF SIMULATION MODELS 2004, 2004, no 1876, p. 10-19Conference paper (Refereed)
    Abstract [en]

    A framework for the calibration of microscopic traffic simulation models using aggregate data is presented. The framework takes into account the interactions between the various inputs and parameters of the simulator by estimating origin-destination (O-D) flows jointly with the behavioral parameters. An optimization-based approach is used for the joint calibration. Since the calibration of the parameters depends on the estimated O-D flows and vice versa, the proposed framework is iterative. O-D estimation is based on the well-known generalized least squares estimator. A systematic search approach based on the complex algorithm is adopted for calibration of the behavioral parameters. This algorithm is particularly useful for the problem at hand since it does not require calculations of derivatives of the objective function. The applicability of the approach is demonstrated through its application to case studies using MITSIMLab, a microscopic traffic simulation model.

  • 122. Toledo, Tomer
    et al.
    Cats, Oded
    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 and Economics.
    Koutsopoulos, Harilaos
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics, Traffic and Logistics.
    Mesoscopic simulation for transit operations2010In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 18, no 6, p. 896-908Article in journal (Refereed)
    Abstract [en]

    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 (APTS). Examples of potential applications include frequency determination, evaluation of real-time control strategies for schedule maintenance and assessing the effects of vehicle scheduling on the level of service. Unlike most previous efforts in this area, the simulation model is built on a platform of a mesoscopic traffic simulation model, which allows modeling of the operation dynamics of large-scale transit systems taking into account the stochasticity due to interactions with road traffic. 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 the Tel-Aviv metropolitan area under various scenarios. The headway distributions at two stops are compared with field observations and show good consistency between simulated and observed data.

  • 123. Toledo, Tomer
    et al.
    Koutsopoulos, Haris
    Department of Civil Engineering, Northeastern University.
    Statistical Validation of Traffic Simulation Models2004In: CALIBRATION AND VALIDATION OF SIMULATION MODELS 2004, 2004, no 1876, p. 142-150Conference paper (Refereed)
    Abstract [en]

    Traffic simulation models support detailed analysis of the dynamics of traffic phenomena and are important tools for analysis of transportation systems. In order to evaluate correctly the impact of different traffic management schemes, simulation models must be able to replicate reality adequately. Model validation (i.e., the process of checking to what extent the model replicates reality) is discussed. The role of validation is defined within the scope of model development and calibration, and the framework for performing the validation is discussed. A hierarchy of statistical methods to validate different types of simulation outputs against observed data is examined. Also, a validation method is proposed on the basis of statistical tests on metamodels fitted to the observed and simulated data. A case study illustrates the applicability of the various methods.

  • 124. Toledo, Tomer
    et al.
    Koutsopoulos, Haris
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Ben-Akiva, Moshe
    Estimation of an Integrated Driving Behavior Mode2009In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 17, no 4Article in journal (Refereed)
  • 125. Toledo, Tomer
    et al.
    Koutsopoulos, Haris
    Ben-Akiva, Moshe
    Methodology for the Calibration of Microscopic Traffic Simulation Models with Aggregate Data2004Conference paper (Refereed)
  • 126. Toledo, Tomer
    et al.
    Koutsopoulos, Haris N.
    Ahmed, Kazi Iftekhar
    Estimation of Vehicle Trajectories with Locally Weighted Regression2007In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 1999, p. 161-169Article in journal (Refereed)
    Abstract [en]

    Vehicle trajectory data are important for calibrating driver behavior models (e.g., car following, acceleration, lane changing, and gap acceptance). The data are usually collected through imaging technologies, such as video. Processing these data may require substantial effort, and the resulting trajectories usually contain measurement and processing errors while also missing data points. An approach is presented to the processing of position data to develop vehicle trajectories and consequently speed and acceleration profiles. The approach uses local regression, a method well suited for mapping highly nonlinear functions. The proposed methodology is applied to a set of position data. The results demonstrate the value of the method to development of vehicle trajectories and speed and acceleration profiles. The conducted sensitivity analysis also shows that the method is rather robust regarding measurement errors and missing values.

  • 127. Toledo, Tomer
    et al.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Traffic and Logistics (closed 20110301).
    Ben-Akiva, Moshe
    Estimation of an integrated driving behavior model2009In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 17, no 4, p. 365-380Article in journal (Refereed)
    Abstract [en]

    This paper presents the methodology and results of estimation of an integrated driving behavior model that attempts to integrate various driving decisions. The model explains lane changing and acceleration decisions jointly and so, captures inter-dependencies between these behaviors and represents drivers' planning capabilities. It introduces new models that capture drivers' choice of a target gap that they intend to use in order to change lanes, and acceleration models that capture drivers' behavior to facilitate the completion of a desired lane change using the target gap. The parameters of all components of the model are estimated simultaneously with the maximum likelihood method and using detailed vehicle trajectory data collected in a freeway section in Arlington, Virginia. The estimation results are presented and discussed in detail.

  • 128. Toledo, Tomer
    et al.
    Koutsopoulos, Haris N.
    Ben-Akiva, Moshe
    Integrated driving behavior modeling2007In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 15, no 2, p. 96-112Article in journal (Refereed)
    Abstract [en]

    This paper develops, implements and tests a framework for driving behavior modeling that integrates the various decisions, such as acceleration, lane changing and gap acceptance. Furthermore, the proposed framework is based on the concepts of short-term goal and short-term plan. Drivers are assumed to conceive and perform short-term plans in order to accomplish short-term goals. This behavioral framework supports a more realistic representation of the driving task, since it captures drivers’ planning capabilities and allows decisions to be based on anticipated future conditions.

    An integrated driving behavior model, which utilizes these concepts, is developed. The model captures both lane changing and acceleration behaviors. The driver’s short-term goal is defined by the target lane. Drivers who wish to change lanes but cannot change lanes immediately, select a short-term plan to perform the desired lane change. Short-term plans are defined by the various gaps in traffic in the target lane. Drivers adapt their acceleration behavior to facilitate the lane change using the target gap. Hence, inter-dependencies between lane changing and acceleration behaviors are captured.

  • 129.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Koutsopoulos, Hans N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, United States .
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    c-SPSA: Cluster-wise simultaneous perturbation stochastic approximation algorithm and its application to dynamic origin-destination matrix estimation2015In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 55, p. 231-245Article in journal (Refereed)
    Abstract [en]

    The simultaneous perturbation stochastic approximation (SPSA) algorithm has been used in the literature for the solution of the dynamic origin-destination (OD) estimation problem. Its main advantage is that it allows quite general formulations of the problem that can include a wide range of sensor measurements. While SPSA is relatively simple to implement, its performance depends on a set of parameters that need to be properly determined. As a result, especially in cases where the gradient of the objective function changes quickly, SPSA may not be as stable and even diverge. A modification of the SPSA algorithm, referred to as c-SPSA, is proposed which applies the simultaneous perturbation approximation of the gradient within a small number of carefully constructed "homogeneous" clusters one at a time, as opposed to all elements at once. The paper establishes the theoretical properties of the new algorithm with an upper bound for the bias of the gradient estimate and shows that it is lower than the corresponding SPSA bias. It also proposes a systematic approach, based on the k-means algorithm, to identify appropriate clusters. The performance of c-SPSA, with alternative implementation strategies, is evaluated in the context of estimating OD flows in an actual urban network. The results demonstrate the efficiency of the proposed c-SPSA algorithm in finding better OD estimates and achieve faster convergence and more robust performance compared to SPSA with fewer overall number of function evaluations.

  • 130.
    Tympakianaki, Athina
    et al.
    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.
    Burghout, Wilco
    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.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    A Comparative Evaluation of Gradient-based and Stochastic Approximation Algorithms for Estimation of Dynamic Origin-Destination Matrices2013Conference paper (Refereed)
  • 131.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, United States.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Anatomy of tunnel congestion: causes and implications for tunnel traffic management2017Manuscript (preprint) (Other academic)
    Abstract [en]

    Tunnel congestion is an important safety problem and is often dealt with using disruptive traffic management strategies, such as closures. The paper proposes an approach to identify the underlying causes of recurrent congestion in tunnels and tests the hypothesis that the cause may vary from day to day. It also suggests that the appropriate tunnel management strategy to deploy depends on the cause. Utilizing traffic sensor data the approach consists of: (i) cluster analysis of historical traffic data to identify distinct congestion patterns; (ii) in-depth analysis of the underlying demand patterns and associated bottlenecks; (iii) simulation to evaluate alternative strategies for each demand pattern; (iv) on-line classification analysis which is able to identify, in real time, the emerging congestion pattern, and inform the type of mitigation strategy to be implemented. The methodology is demonstrated for a congested tunnel in Stockholm, Sweden revealing two different spatiotemporal congestion patterns. The results show that, if the current strategy of closures is to be used, the timing should depend on the congestion pattern. However, metering is the most promising strategy. The on-line classification of the emerging congestion pattern is effective and can inform appropriate strategy proactively. The analysis emphasizes that the effectiveness of tunnel traffic management can be increased by identifying the causes of congestion on a given day. 

  • 132.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, United States.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Anatomy of tunnel congestion: causes and implications for tunnel traffic managementManuscript (preprint) (Other academic)
    Abstract [en]

    Tunnel congestion is an important safety problem and is often dealt with using disruptive traffic management strategies, such as closures. The paper proposes an approach to identify the underlying causes of recurrent congestion in tunnels and tests the hypothesis that the cause may vary from day to day. It also suggests that the appropriate tunnel management strategy to deploy depends on the cause. Utilizing traffic sensor data the approach consists of: (i) cluster analysis of historical traffic data to identify distinct congestion patterns; (ii) in-depth analysis of the underlying demand patterns and associated bottlenecks; (iii) simulation to evaluate alternative strategies for each demand pattern; (iv) on-line classification analysis which is able to identify, in real time, the emerging congestion pattern, and inform the type of mitigation strategy to be implemented. The methodology is demonstrated for a congested tunnel in Stockholm, Sweden revealing two different spatiotemporal congestion patterns. The results show that, if the current strategy of closures is to be used, the timing should depend on the congestion pattern. However, metering is the most promising strategy. The on-line classification of the emerging congestion pattern is effective and can inform appropriate strategy proactively. The analysis emphasizes that the effectiveness of tunnel traffic management can be increased by identifying the causes of congestion on a given day. 

  • 133.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
    Anatomy of tunnel congestion: Causes and implications for tunnel traffic management2019In: Tunnelling and Underground Space Technology, ISSN 0886-7798, E-ISSN 1878-4364, Vol. 83, p. 498-508Article in journal (Refereed)
    Abstract [en]

    Tunnel congestion is an important safety problem and is often dealt with using disruptive traffic management strategies, such as closures. The paper proposes an approach to identify the underlying causes of recurrent congestion in tunnels and tests the hypothesis that the cause may vary from day to day. It also suggests that the appropriate tunnel management strategy to deploy depends on the cause. Utilizing traffic sensor data the approach consists of: (i) cluster analysis of historical traffic data to identify distinct congestion patterns; (ii) in-depth analysis of the underlying demand patterns and associated bottlenecks; (iii) simulation to evaluate alternative strategies for each demand pattern; (iv) on-line classification analysis which is able to identify, in real time, the emerging congestion pattern, and inform the type of mitigation strategy to be implemented. The methodology is demonstrated for a congested tunnel in Stockholm, Sweden revealing two different spatio-temporal congestion patterns. The results show that, if the current strategy of closures is to be used, the timing should depend on the congestion pattern. However, metering is the most promising strategy. The on-line classification of the emerging congestion pattern is effective and can inform appropriate strategy proactively. The analysis emphasizes that the effectiveness of tunnel traffic management can be increased by identifying the causes of congestion on a given day.

  • 134.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, United States.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Impact analysis of transport network disruptions using multimodal data: A case study for tunnel closures in Stockholm.Manuscript (preprint) (Other academic)
    Abstract [en]

    The paper explores the utilization of heterogeneous data sources to analyze the multimodal impacts of transport network disruptions. A systematic data-driven approach is proposed for the analysis of impacts with respect to two aspects: (a) spatiotemporal network changes, and (b) multimodal effects. The feasibility and benefits of combining various data sources are demonstrated through a case study for a tunnel in Stockholm, Sweden which is often prone to closures. Several questions are addressed including the identification of impacted areas, and the evaluation of impacts on network performance, demand patterns and performance of the public transport system. The results indicate significant impact of tunnel closures on the network traffic conditions due to the redistribution of vehicles on alternative paths. Effects are also found on the performance of public transport. Analysis of the demand reveals redistribution of traffic during the tunnel closures, consistent with the observed impacts on network performance. Evidence for redistribution of travelers to public transport is observed as a potential effect of the closures. Better understanding of multimodal impacts of a disruption can assist authorities in their decision-making process to apply adequate traffic management policies.

  • 135.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering. Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, United States.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Robust SPSA algorithms for dynamic OD matrix estimation2018In: The 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018) / The 8th International Conference on Sustainable Energy Information Technology (SEIT-2018) / Affiliated WorkshopsThe 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018) / The 8th International Conference on Sustainable Energy Information Technology (SEIT-2018) / Affiliated Workshops, Elsevier, 2018, Vol. 130, p. 57-64Conference paper (Refereed)
    Abstract [en]

    The Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm has been used for solving the off-line dynamic origin-destination (OD) estimation problem. While the algorithm can be used with very general formulations of the problem, it can also be unstable. The paper proposes methods and evaluates their effectiveness in improving the SPSA performance at two levels: a) scaling the step size and using a hybrid gradient estimation; and b) proposing alternative clustering strategies to be used with the c-SPSA version of the algorithm, where OD flows are estimated in clusters. The proposed enhancements are evaluated through simulation experiments on a real network.

  • 136.
    Tympakianaki, Athina
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering. Northeastern Univ, Dept Civil & Environm Engn, Boston, MA 02115 USA.
    Jenelius, Erik
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Cebecauer, Matej
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.
    Impact analysis of transport network disruptions using multimodal data: A case study for tunnel closures in Stockholm2018In: Case Studies on Transport Policy, ISSN 2213-624X, E-ISSN 2213-6258, Vol. 6, no 2, p. 179-189Article in journal (Refereed)
    Abstract [en]

    The paper explores the utilization of heterogeneous data sources to analyze the multimodal impacts of transport network disruptions. A systematic data-driven approach is proposed for the analysis of impacts with respect to two aspects: (a) spatiotemporal network changes, and (b) multimodal effects. The feasibility and benefits of combining various data sources are demonstrated through a case study for a tunnel in Stockholm, Sweden which is often prone to closures. Several questions are addressed including the identification of impacted areas, and the evaluation of impacts on network performance, demand patterns and performance of the public transport system. The results indicate significant impact of tunnel closures on the network traffic conditions due to the redistribution of vehicles on alternative paths. Effects are also found on the performance of public transport. Analysis of the demand reveals redistribution of traffic during the tunnel closures, consistent with the observed impacts on network performance. Evidence for redistribution of travelers to public transport is observed as a potential effect of the closures. Better understanding of multimodal impacts of a disruption can assist authorities in their decision-making process to apply adequate traffic management policies.

  • 137. Viggiano, Cecilia
    et al.
    Koutsopoulos, Haris N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport planning, economics and engineering.
    Attanucci, John
    User Behavior in Multiroute Bus Corridors Analysis by a Web-Based Survey2014In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2418, p. 92-99Article in journal (Refereed)
    Abstract [en]

    Multiroute corridors are a common feature of bus networks. In these corridors, passengers select a route from a set of parallel routes that serve the desired destinations. Understanding how passengers make these decisions can help measure passenger experience and inform network and service planning. A web-based survey was used to collect information on users of a multiroute corridor in London that includes both local and limited-stop bus service. The survey was used both as a tool to understand behavior and as a demonstration case for the viability of web-based surveys, a relatively new methodology for data collection on public transport user behavior. The representativeness and the accuracy of the survey responses were analyzed. The results revealed that online surveys could collect detailed information from a large, fairly representative sample of bus passengers. The responses to questions in the survey were used to categorize passenger behavior by route choice strategy. Passengers could either wait for a bus of a specific route or take the first bus to arrive that serves their destination. The survey data showed that passengers' route choice strategies were influenced by several factors, including trip length, trip purpose, passenger income, use of countdown next-bus information, passenger attitudes toward crowding, and levels of risk aversion.

  • 138. Vythoulkas, P. C.
    et al.
    Koutsopoulos, Harilaos
    Modeling discrete choice behavior using concepts from fuzzy set theory, approximate reasoning and neural networks2003In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 11, no 1, p. 51-73Article in journal (Refereed)
    Abstract [en]

    Models of discrete choice analysis are usually based on the random utility framework. They assume that decision makers make decisions that maximize their utility. Alternative formulations of the problem have also been proposed in the literature. These approaches model the decision makers' perceptions of the attributes of the various alternatives using fuzzy sets and linguistic variables, and the decision process itself, using concepts from approximate reasoning and fuzzy control. The underlying assumption is that decision makers use a few simple rules that relate their vague perceptions of the various attributes to their preferences towards the available alternatives. The paper extends this approach by incorporating rule weights, which capture the importance of a particular rule in the decision process. It also presents an approach for calibrating the weights using concepts from neural networks. A case study, involving mode choice, is used to demonstrate the potential of the approach and compare it to alternative formulations and methodologies.

  • 139. Wang, Z.
    et al.
    Koutsopoulos, Harilaos N.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Calibration of urban rail simulation models: A methodology using SPSA algorithm2011Conference paper (Refereed)
    Abstract [en]

    Rail simulation model calibration is a process of adjusting model parameters while comparing model output with observations from the real rail system. There is a lack of systematic methodology for calibrating urban rail simulation models. Based on a simulator developed for urban rail operations and control, the paper demonstrates a methodology of calibrating model parameters, and specifically, fine-tuning some of the simulation inputs. The calibration process is modeled as a multi-variate optimization problem and solved by the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. A case study of the Massachusetts Bay Transportation Authority (MBTA) Red Line shows that the methodology improves the simulation model dramatically in terms of replicating the track block runtimes. At the same time, it upgrades the station specific dwell time parameters and enhances a-priori boarding rates at stations fairly effectively.

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