959 resultados para Demand-Responsive Transportation Systems.


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This dissertation aims to improve the performance of existing assignment-based dynamic origin-destination (O-D) matrix estimation models to successfully apply Intelligent Transportation Systems (ITS) strategies for the purposes of traffic congestion relief and dynamic traffic assignment (DTA) in transportation network modeling. The methodology framework has two advantages over the existing assignment-based dynamic O-D matrix estimation models. First, it combines an initial O-D estimation model into the estimation process to provide a high confidence level of initial input for the dynamic O-D estimation model, which has the potential to improve the final estimation results and reduce the associated computation time. Second, the proposed methodology framework can automatically convert traffic volume deviation to traffic density deviation in the objective function under congested traffic conditions. Traffic density is a better indicator for traffic demand than traffic volume under congested traffic condition, thus the conversion can contribute to improving the estimation performance. The proposed method indicates a better performance than a typical assignment-based estimation model (Zhou et al., 2003) in several case studies. In the case study for I-95 in Miami-Dade County, Florida, the proposed method produces a good result in seven iterations, with a root mean square percentage error (RMSPE) of 0.010 for traffic volume and a RMSPE of 0.283 for speed. In contrast, Zhou's model requires 50 iterations to obtain a RMSPE of 0.023 for volume and a RMSPE of 0.285 for speed. In the case study for Jacksonville, Florida, the proposed method reaches a convergent solution in 16 iterations with a RMSPE of 0.045 for volume and a RMSPE of 0.110 for speed, while Zhou's model needs 10 iterations to obtain the best solution, with a RMSPE of 0.168 for volume and a RMSPE of 0.179 for speed. The successful application of the proposed methodology framework to real road networks demonstrates its ability to provide results both with satisfactory accuracy and within a reasonable time, thus establishing its potential usefulness to support dynamic traffic assignment modeling, ITS systems, and other strategies.

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Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

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The TRB-sponsored International Paratransit Conference, “Shaping the New Future of Paratransit”, held in Monterey, CA in the United States (US) in October 2014 represented the first coming together of the international paratransit community in conference format since 1997. The conference itself drew a worldwide attendance from a cross-section of operators, technology providers, policymakers and researchers. The presentations from the conference were organised around a number of themes which, when brought together, represented a substantial manifesto for the flexible and demand responsive transport community. This paper looks at a number of these themes with an analysis to highlight the key points and common strands of worldwide experience.

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El vertiginoso crecimiento de los centros urbanos, las tecnologías emergentes y la demanda de nuevos servicios por parte de la población plantea encaminar esfuerzos hacia el desarrollo de las ciudades inteligentes. Éste concepto ha tomado fuerza entre los sectores político, económico, social, académico, ambiental y civil; de forma paralela, se han generado iniciativas que conducen hacia la integración de la infraestructura, la tecnología y los servicios para los ciudadanos. En éste contexto, una de las problemáticas con mayor impacto en la sociedad es la seguridad vial. Es necesario contar con mecanismos que disminuyan la accidentalidad, mejoren la atención a incidentes, optimicen la movilidad urbana y planeación municipal, ayuden a reducir el consumo de combustible y la emisión de gases de efecto de invernadero, así como ofrecer información dinámica y efectiva a los viajeros. En este artículo se describen dos (2) enfoques que contribuyen de manera eficiente dicho problema: los videojuegos como juegos serios y los sistemas de transporte inteligente. Ambos enfoques están encaminados a evitar colisiones y su diseño e implementación requieren componentes altamente tecnológicos (e.g. sistemas telemáticos e informáticos, inteligencia artificial, procesamiento de imágenes y modelado 3D).

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The early stages of the building design process are when the most far reaching decisions are made regarding the configuration of the proposed project. This paper examines methods of providing decision support to building designers across multiple disciplines during the early stage of design. The level of detail supported is at the massing study stage where the basic envelope of the project is being defined. The block outlines on the building envelope are sliced into floors. Within a floor the only spatial divisions supported are the “user” space and the building core. The building core includes vertical transportation systems, emergency egress and vertical duct runs. The current focus of the project described in the paper is multi-storey mixed use office/residential buildings with car parking. This is a common type of building in redevelopment projects within and adjacent to the central business districts of major Australian cities. The key design parameters for system selection across the major systems in multi-storey building projects - architectural, structural, HVAC, vertical transportation, electrical distribution, fire protection, hydraulics and cost – are examined. These have been identified through literature research and discussions with building designers from various disciplines. This information is being encoded in decision support tools. The decision support tools communicate through a shared database to ensure that the relevant information is shared across all of the disciplines. An internal data model has been developed to support the very early design phase and the high level system descriptions required. A mapping to IFC 2x2 has also been defined to ensure that this early information is available at later stages of the design process.

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The paper analyses the expected value of OD volumes from probe with fixed error, error that is proportional to zone size and inversely proportional to zone size. To add realism to the analysis, real trip ODs in the Tokyo Metropolitan Region are synthesised. The results show that for small zone coding with average radius of 1.1km, and fixed measurement error of 100m, an accuracy of 70% can be expected. The equivalent accuracy for medium zone coding with average radius of 5km would translate into a fixed error of approximately 300m. As expected small zone coding is more sensitive than medium zone coding as the chances of the probe error envelope falling into adjacent zones are higher. For the same error radii, error proportional to zone size would deliver higher level of accuracy. As over half (54.8%) of the trip ends start or end at zone with equivalent radius of ≤ 1.2 km and only 13% of trips ends occurred at zones with equivalent radius ≥2.5km, measurement error that is proportional to zone size such as mobile phone would deliver higher level of accuracy. The synthesis of real OD with different probe error characteristics have shown that expected value of >85% is difficult to achieve for small zone coding with average radius of 1.1km. For most transport applications, OD matrix at medium zone coding is sufficient for transport management. From this study it can be drawn that GPS with error range between 2 and 5m, and at medium zone coding (average radius of 5km) would provide OD estimates greater than 90% of the expected value. However, for a typical mobile phone operating error range at medium zone coding the expected value would be lower than 85%. This paper assumes transmission of one origin and one destination positions from the probe. However, if multiple positions within the origin and destination zones are transmitted, map matching to transport network could be performed and it would greatly improve the accuracy of the probe data.

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Vehicle detectors have been installed at approximately every 300 meters on each lane on Tokyo metropolitan expressway. Various traffic data such as traffic volume, average speed and time occupancy are collected by vehicle detectors. We can understand traffic characteristics of every point by comparing traffic data collected at consecutive points. In this study, we focused on average speed, analyzed road potential by operating speed during free-flow conditions, and identified latent bottlenecks. Furthermore, we analyzed effects for road potential by the rainfall level and day of the week. It’s expected that this method of analysis will be utilized for installation of ITS such as drive assist, estimation of parameters for traffic simulation and feedback to road design as congestion measures.

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With growing concern over the use of the car in our urbanized society, there have emerged a number of lobby groups and professional bodies promoting a return to public transport, walking and cycling, with the urban village as the key driving land use, as a means of making our cities’ transportation systems more sustainable. This research has aimed at developing a framework applicable to the Australian setting that can facilitate increased passenger patronage of rail based urban transport systems from adjacent or associated land uses. The framework specifically tested the application of the Park & Ride and Transit Oriented Development (TOD) concepts and their applicability within the cultural, institutional, political and transit operational characteristics of Australian society. The researcher found that, although the application of the TOD concept had been limited to small pockets of town houses and mixed use developments around stations, the development industry and emerging groups within the community are posed to embrace the concept and bring with it increased rail patronage. The lack of a clear commitment to infrastructure and supporting land uses is a major barrier to the implementation of TODs. The research findings demonstrated significant scope for the size of a TOD to expand to a much greater radius of activity from the public transport interchange, than the commonly quoted 400 to 600 meters, thus incorporating many more residents and potential patrons. The provision of Park & Rides, and associated support facilities like Kiss & Rides, have followed worldwide trends of high patronage demands from the middle and outer car dependent suburbs of our cities. The data collection and analysis gathered by the researcher demonstrated that in many cases Park & Rides should form part of a TOD to ensure ease of access to rail stations by all modes and patron types. The question, however, remains how best to plan the incorporation of a Park & Ride within a TOD and still maintain those features that attract and promote TODs as a living entity.

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This paper presents a travel time prediction model and evaluates its performance and transferability. Advanced Travelers Information Systems (ATIS) are gaining more and more importance, increasing the need for accurate, timely and useful information to the travelers. Travel time information quantifies the traffic condition in an easy to understand way for the users. The proposed travel time prediction model is based on an efficient use of nearest neighbor search. The model is calibrated for optimal performance using Genetic Algorithms. Results indicate better performance by using the proposed model than the presently used naïve model.

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In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multi-agent system (MAS) in which the IP and TSP are represented by separate software agents. One task of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between timetables attained from the proposed methods and those derived by the scheduling principles adopted in practice.

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In an open railway access market, the Infrastructure Provider (IP), upon the receipts of service bids from the Train Service Providers (TSPs), assigns track access rights according to its own business objectives and the merits of the bids; and produces the train service timetable through negotiations. In practice, IP chooses to negotiate with the TSPs one by one in such a sequence that IP optimizes its objectives. The TSP bids are usually very complicated, containing a large number of parameters in different natures. It is a difficult task even for an expert to give a priority sequence for negotiations from the contents of the bids. This study proposes the application of fuzzy ranking method to compare and prioritize the TSP bids in order to produce a negotiation sequence. The results of this study allow investigations on the behaviors of the stakeholders in bid preparation and negotiation, as well as evaluation of service quality in the open railway market.

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Robustness of the track allocation problem is rarely addressed in literatures and the obtained track allocation schemes (TAS) embody some bottlenecks. Therefore, an approach to detect bottlenecks is needed to support local optimization. First a TAS is transformed to an executable model by Petri nets. Then disturbances analysis is performed using the model and the indicators of the total trains' departure delays are collected to detect bottlenecks when each train suffers a disturbance. Finally, the results of the tests based on a rail hub linking six lines and a TAS about thirty minutes show that the minimum buffer time is 21 seconds and there are two bottlenecks where the buffer times are 57 and 44 seconds respectively, and it indicates that the bottlenecks do not certainly locate at the area where there is minimum buffer time. The proposed approach can further support selection of multi schemes and robustness optimization.

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Many economic, social and environmental sustainability problems associated with typical urban transportation systems have revealed the importance of three domains of action: vehicle, infrastructure and user. These domains need to be carefully reconsidered in search of a sustainable urban development path. Although intelligent transportation systems have contributed substantially to enhancing efficiency, safety and comfort of travel, questions related to users’ behaviours and preferences, which stimulate considerable environmental effects, still needed to be further examined. In this chapter, options for smart urban transportation infrastructure development and the technological means for achieving broader goals of sustainable communities and urban development are explored.