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Many cities in Iran, including the metropolis of Shiraz, are increasingly car-oriented, resulting in traffic congestion and related issues. Considering the current conditions of Iran, an automated transit network (ATN) can be one of the available solutions to this problem. ATN is an advanced type of public transit consisting of automated vehicles moving passengers on a network of dedicated guideways. As a combination of public, personal, and private transport, ATNs may decrease the use of cars and address related problems. In order to design effective policies aimed at achieving the benefits of ATN, it is necessary to have a better understanding of how people accept an ATN system, especially car users. This research aims at advancing future research on the effects of ATNs on travel behavior through identifying the characteristics of users who are likely to accept ATN services, by examining the heterogeneity in the preferences of these people. To achieve this goal, a stated choice survey was conducted and analyzed using multinomial logit (MNL) and mixed logit (ML) models. The results showed that the parameters of trip purpose, owning a hybrid car, and the level of education affect the preferences toward the ATN system. Additionally, from the comparison of the results of the MNL and ML models, it was found that despite the greater ability of the ML model in estimating possible heterogeneities, likely the MNL model can also help to record some heterogeneities more realistically. In the end, the methodological limitations of the study were also acknowledged. Despite the potential hypothesis bias and the status quo bias, the results captured the directionality and relative importance of the attributes of interest., QC 20230803

This study investigates empty vehicle redistribution algorithms for personal rapid transit and autonomous taxi services. The focus is on passenger service and operator cost. A new redistribution algorithm is presented in this study: index-based redistribution (IBR). IBR is a proactive method, meaning it takes into account both current demand and anticipated future demand, in contrast to reactive methods, which act based on current demand only. From information on currently waiting for passengers, predicted near-future demand and projected arrival of vehicles, IBR calculates an index for each vehicle station, and redistribution is done based on this index. Seven different algorithm combinations are evaluated using a test case in Paris Saclay, France (20 stations and 100 vehicles). A combination of simple nearest neighbours and IBR is shown to be promising. Its results outperform the other methods tested in peak and off-peak demand, in terms of average and maximum passenger waiting times as well as station queue length. The effect of vehicle fleet size on generalised cost is analysed. Waiting times, mileage and fleet size are taken into account while assessing this generalised cost., QC 20190423

Detta dokument innehåller utvärderingen av Centre for Traffic Research (CTR) för perioden 2013-2017. Dokumentet har sammanställts av föreståndaren Wilco Burghout i samarbete med ledningsgruppen Andreas Tapani (för VTI), Jan Lundgren (för Linköpings Universitet). CTR:s övriga styrelsemedlemmar har bidragit med svar på en frågelista och kommentarer.Syftet med utvärderingen är att redovisa och utvärdera CTR:s forskning ochadministration samt samarbetet inom CTR och med andra partners. Dokumentet har följande utvärderingsmoment: •Ekonomi och forskningsprojekt 2013-2017•Vetenskapliga resultat i form av publikationer, färdiga doktorer och licentiater, seminarier och konferenser, samt implementering av resultat.•Samarbete inom CTR och med andra partners•RekommendationerUtvärderingen är baserad på CTR:s strategi & inriktningsdokument 2013-2017, ekonomiska redovisningar, publikationer och rapporter, samt svar från partners och styrelsemedlemmar på ett antal intervjufrågor. Dessutom redovisas slutsatser från diskussionerna kring CTR:s nuvarande och framtida forskningsinriktning på CTR dagen 2017-06-01.Analys av resultaten visar att:-sammanfattning resultat EkonomiInom ramenavtalet med Trafikverket för 2013-2017 har projekt finansierats för 34,5 MSEK, jämfört med garantivolym på 25 MSEK, vilket tyder på stort förtroende från Trafikverket och en ständigt ökande forskningsverksamhet. - sammanfattning resultat forskningCTR:s forskningsprojekt svarar väl mot forskningsinriktningen som beskrivs i CTR:s Strategi & Inriktningsdokument 2013-2017. Projekten som har genomförts och startats under perioden spänner över en rad områden, från modellering av gångtrafikantsystem och bytespunkter till smartare prediktiva trafikstyrning på motorvägar och bättre samverkan mellan olika trafikslag. CTR:s forskningsprojekt kommer till användning i Trafikverkets verksamhet genom bland annat förbättrade verktyg för incidenthantering, bättre utformning av bytespunkter som tar bättre hänsyn till passage, CTR - Kansli stöd

The concept of a dynamic and flexible Intelligent Subscription Bus Service (I-Service) was developed, and two integrated questionnaires were conducted among the commuters of a large university campus. To determine travel times to the campus by I-Service, a digital urban road network map with travel time databases was produced, and software was developed to calculate optimum routes using these databases. Travel times for each participant were determined by the shortest travel time principle. The proposed hypothetical service was introduced to participants, and anticipated advantages for each participant were reported back to them by means of a second questionnaire to determine if they would prefer using I-Service. As a result, a 49% modal shift potential from all other modes in general and a 52% modal shift potential from private car to I-Service were found., QC 20161118

As a result of the continuously increasing numbers of motor vehicles in metropolitan areas worldwide, road traffic emission levels have been recognized as a challenge during the planning and management of transportation. Experiments were conducted to collect on-road emission data using portable emission measurement systems in two Chinese cities in order to estimate real traffic emissions and energy consumption levels and to build computational models for operational transport environment projects. In total, dynamic pollutant emissions and fuel consumption levels from dozens of light duty vehicles, primarily from four different vehicle classes, were measured at a second-by-second level. Using the collected data, several microscopic emission models including CMEM, VT-Micro, EMIT, and POLY were evaluated and compared through calibration and validation procedures. Non-linear optimization methods are applied for the calibration of the CMEM and EMIT models. Numerical results show that the models can realize performance levels close to the CMEM model in most cases. The VT-Micro model shows advantages in its unanimous performance and ability to describe low emission profiles while the EMIT model has a clear physics basis and a simple model structure. Both of them can be applied when extensive emission computation is required in estimating environmental impacts resulting from dynamic road traffic., QC 20120806

Efficient feeder distributor systems around train stations are important in attracting train passengers. Such systems would be a suitable application for personal rapid transit (PRT). This paper suggests layouts and operations strategies for transfer stations between PRT and heavy rail. Ticket handling can be avoided by having the train fare include PRT trips. Ridesharing can be encouraged by destination signs. The catchment area that can be efficiently served is related to the interval between trains. The capacity of the station and guideway can be improved by coupling PRT vehicles in the station and decoupling them as necessary en route. Applications in Sweden are illustrated with the PRTsim software. In one case, outgoing PRT vehicles were loaded to 78%., QC 20121123

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., QC 20110111

Cost issues have been an important concern in the development of Personal Rapid Transit (PRT) since the concept was developed several decades ago. The lightweight, computer-guided electric vehicles operating the PRT system are generally a major part of the capital cost of the system, especially in larger network with high demand. A sufficient number of empty vehicles are needed to be moved to the stations where passengers are waiting or demand is expected. Generally a larger fleet size leads to a reduction in waiting time of passengers and thus a higher level of service given a specific demand, but an increased investment cost including capital cost per vehicle and additional operation and maintenance. So it requires a compromise between user cost (in terms of passenger waiting times) and operator cost (in terms of fleet sizedependent capital cost and operating/maintenance costs). There should be an optimal fleet size so that the sum of these two costs can be minimized while an expected level of service is achieved. This paper presents first the way to obtain the PRT demand, and then a prescription to determine the optimal fleet size using a cost-effectiveness analysis with traffic simulation. This prescription identifies the set of activities that are necessary to perform the optimization task. Each activity is regarded as a component in our general framework and this framework is illustrated by a case study in the Waal/ Eemshaven harbor area in the Port of Rotterdam, The Netherlands., QC 20140901

To support the implementation of a real-time traffic information system in Stockholm using automatic vehicle identification (AVI) data, a travel time analysis platform has been developed. The platform is composed of a client-side travel time data analysis program and a database server where historical travel time data are stored. In the study, several existing freeway travel time estimation algorithms and their modifications were implemented in the travel time analysis program, and evaluated using four months data collected on urban streets and arterials in and near the city of Stockholm. The advantages and disadvantages of those algorithms are analyzed using the highly noisy travel time measurements. The results show that with modifications in the parameter settings and the algorithms themselves, the methods are capable of estimating the travel times from the noise-corrupted urban data. In addition to the travel time estimation, the paper presents a simple data disruption recognition approach on the way toward a more comprehensive disruption and incident warning system., QC 20110218

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Personal Rapid Transit (PRT) offers direct, on-demand travel in automated vehicles seating 3-6 passengers on exclusive right-of-way. Commercially available systems now offer speeds up to 45 kph at headways from 3 seconds. With 3-second headways, a typical load of 1.5 passengers and 30 empty vehicles, the link capacity will be 1200 passengers per hour (one direction). This paper explores ways to extend the capabilities of PRT with respect to capacity and speed. Strategies have been developed and verified with the generic simulation software PRTsim., QC 20141007

This paper first reports a data acquisition method that the authors used in a project on modeling driver behavior for microscopic traffic simulations. An advanced instrumented vehicle was employed to collect driver-behavior data, mainly car-following and lane-changing patterns, on Swedish roads. To eliminate the measurement noise in acquired car-following patterns, the Kalman smoothing algorithm was applied to the state-space model of the physical states (acceleration, speed, and position) of both instrumented and tracked vehicles. The denoised driving patterns were used in the analysis of driver properties in the car-following stage. For further modeling of car-following behavior, we developed and implemented a consolidated fuzzy clustering algorithm to classify different car-following regimes from the preprocessed data. The algorithm considers time continuity of collected driver-behavior patterns and can be more reliably applied in the classification of continuous car-following regimes when the classical fuzzy C-means algorithm gives unclear results., QC 20100602

An instrumented vehicle has been used to study car-following behavior on Swedish motorways. In this study, the previous data collection and pre-processing work were briefly reviewed. To understand the driving behavior in the car-following stage more clearly, the collected time series were classified into a number of regimes using unsupervised fuzzy clustering methods. Then, the statistical relations between the driver acceleration response and the perceptual variables in each regime were analyzed using correlation and regression methods. It was found that regime classification helps discern the behavioral variance between those regime clusters. According to the data analysis, some of the car-following regimes, for example, opening and braking, can be described adequately in the statistical sense by a linear regression model (Helly's model). Therefore, a multiple regime car-following model with simple model forms, for example, linear models, has the potential to robustly represent the general car-following behavior in most regimes., QC 20100602

Driver behavior plays an important role in modeling vehicle dynamics in a traffic simulation environment. To study one element of general driver behavior, that of car following, an advanced-instrumented vehicle has been applied in dynamic data collection in real-traffic flow on Swedish roads. This paper briefly introduces the car-following data collection and smoothing methods. Moreover, spectrum analysis methods based on Fourier analysis of car-following data are introduced to estimate driver reaction times, a crucial parameter of driver behavior. A generalized general motor-type model was calibrated, an extension of the classic nonlinear general motor model, in a stable following regime based on estimated driver reaction times. The calibrated model was then evaluated by closed-loop simulations., QC 20111007

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., TSC import 1988 2012-02-14.QC 20120222

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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., QC 20110218

This paper will introduce a data collection method that we used in a project on modeling driver behavior in microscopic traffic simulation. A modern instrumented vehicle was employed to study a crucial element of driver behavior, that of car following, on Swedish roads. The collected car following data shows noisy patterns. To eliminate the measurement noise, Kalman smoothing algorithm is applied to the state-space formulation of the physical states (acceleration, speed and position) of tracked vehicles. The smoothed data shows clear car following patterns and has been further applied in our car following model calibration and validation study., QC 20111014

TSC import 2017 2012-02-14. NQC