| 1. |
- Ben-Akiva, Moshe, et al.
(author)
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Traffic Simulation with MITSIMLab
- 2010
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In: Fundamentals of Traffic Simulation. - New York, NY : Springer. - 1441961429 ; , s. 233-268
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Book chapter (peer-reviewed)abstract
- 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.
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| 2. |
- Burghout, Wilco, et al.
(author)
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DYMOBUS: dynamic mesoscopic modelling of bus public transport
- 2009
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In: Conference proceedings to ITS 2009 conference.
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Conference paper (peer-reviewed)abstract
- 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.
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| 3. |
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| 4. |
- Cats, Oded, 1983-
(author)
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Dynamic Modelling of Transit Operations and Passenger Decisions
- 2011
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Doctoral thesis (other academic/artistic)abstract
- Efficient and reliable public transport systems are fundamental in promoting green growth developments in metropolitan areas. A large range of Advanced Public Transport Systems (APTS) facilitates the design of real-time operations and demand management. The analysis of transit performance requires a dynamic tool that will enable to emulate the dynamic loading of travelers and their interaction with the transit system. BusMezzo, a dynamic transit operations and assignment model was developed to enable the analysis and evaluation of transit performance and level of service under various system conditions and APTS. The model represents the interactions between traffic dynamics, transit operations and traveler decisions. The model was implemented within a mesoscopic traffic simulation model. The different sources of transit operations uncertainty including traffic conditions, vehicle capacities, dwell times, vehicle schedules and service disruptions are modeled explicitly. The dynamic path choice model in BusMezzo considers each traveler as an adaptive decision maker. Travelers’ progress in the transit system consists of successive decisions that are defined by the need to choose the next path element. The evaluations are based on the respective path alternatives and their anticipated downstream attributes. Travel decisions are modeled within the framework of discrete random utility models. A non-compensatory choice-set generation model and the path utility function were estimated based on a web-based survey. BusMezzo enables the analysis and evaluation of proactive control strategies and the impacts of real-time information provision. Several experiments were conducted to analyze transit performance from travelers, operator and drivers perspectives under various holding strategies. This analysis has facilitated the design of a field trial of the most promising strategy. Furthermore, a case study on real-time traveler information systems regarding the next vehicle arrival time investigated the impacts of various levels of coverage and comprehensiveness. As passengers are more informed, passenger loads are subject to more fluctuation due to the traveler adaptations.
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| 5. |
- Cats, Oded, et al.
(author)
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Effect of real-time transit information on dynamic passenger path choice.
- 2011
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In: Transportation Research Record. - : SAGE Publications. - 0361-1981. ; 2217, s. 46-54
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Journal article (peer-reviewed)abstract
- 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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| 6. |
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| 7. |
- Cats, Oded, et al.
(author)
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Evaluation of real-time holding strategies for improved bus service reliability
- 2010
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In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. - Madeira, Portugal. - 9781424476572 ; , s. 718-723
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Conference paper (peer-reviewed)abstract
- Service reliability is one of the main measures of performance determining transit system level of service. Holding control strategies are a common transit operations practice aimed to reduce transit service unreliability by setting criteria for departure fromtime point stops. In order to adequately analyze the sources of uncertainty involved with transit performance, it is essential to model dynamically the interactions between traffic conditions, passenger demand and transit operations. BusMezzo, a transit simulation model has been developed on a platform of a mesoscopic traffic simulation model, which enables the representation of large-scale transit systems. The model implements severalreal-time holding strategies. It is used to evaluate the application of these strategies in areal-world high-demand bus line in the Tel Aviv metropolitan area, under various scenarios. An analysis of the results suggests that a holding strategy based on the mean headway from the preceding bus and the next bus, restricted by a maximum allowableholding time, is especially efficient.
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| 8. |
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| 9. |
- Cats, Oded, et al.
(author)
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Mesoscopic Modeling of Bus Public Transportation
- 2010
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In: Transportation Research Record. - : SAGE Publications. - 0361-1981 .- 2169-4052. ; :2188, s. 9-18
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Journal article (peer-reviewed)abstract
- 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.
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