91 resultados para Public Transportation Systems.


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Urban transit system performance may be quantified and assessed using transit capacity and productive capacity for planning, design and operational management. Bunker (4) defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures transit task performed over distance. Transit productiveness (p-km/h) captures transit work performed over time. This paper applies productive performance with risk assessment to quantify transit system reliability. Theory is developed to monetize transit segment reliability risk on the basis of demonstration Annual Reliability Event rates by transit facility type, segment productiveness, and unit-event severity. A comparative example of peak hour performance of a transit sub-system containing bus-on-street, busway, and rail components in Brisbane, Australia demonstrates through practical application the importance of valuing reliability. Comparison reveals the highest risk segments to be long, highly productive on street bus segments followed by busway (BRT) segments and then rail segments. A transit reliability risk reduction treatment example demonstrates that benefits can be significant and should be incorporated into project evaluation in addition to those of regular travel time savings, reduced emissions and safety improvements. Reliability can be used to identify high risk components of the transit system and draw comparisons between modes both in planning and operations settings, and value improvement scenarios in a project evaluation setting. The methodology can also be applied to inform daily transit system operational management.

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Dedicated Short Range Communication (DSRC) is the emerging key technology supporting cooperative road safety systems within Intelligent Transportation Systems (ITS). The DSRC protocol stack includes a variety of standards such as IEEE 802.11p and SAE J2735. The effectiveness of the DSRC technology depends on not only the interoperable cooperation of these standards, but also on the interoperability of DSRC devices manufactured by various manufacturers. To address the second constraint, the SAE defines a message set dictionary under the J2735 standard for construction of device independent messages. This paper focuses on the deficiencies of the SAE J2735 standard being developed for deployment in Vehicular Ad-hoc Networks (VANET). In this regard, the paper discusses the way how a Basic Safety Message (BSM) as the fundamental message type defined in SAE J2735 is constructed, sent and received by safety communication platforms to provide a comprehensive device independent solution for Cooperative ITS (C-ITS). This provides some insight into the technical knowledge behind the construction and exchange of BSMs within VANET. A series of real-world DSRC data collection experiments was conducted. The results demonstrate that the reliability and throughput of DSRC highly depend on the applications utilizing the medium. Therefore, an active application-dependent medium control measure, using a novel message-dissemination frequency controller, is introduced. This application level message handler improves the reliability of both BSM transmissions/receptions and the Application layer error handling which is extremely vital to decentralized congestion control (DCC) mechanisms.

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Dwell time at the busway station has a significant effect on bus capacity and delay. Dwell time has conventionally been estimated using models developed on the basis of field survey data. However field survey is resource and cost intensive, so dwell time estimation based on limited observations can be somewhat inaccurate. Most public transport systems are now equipped with Automatic Passenger Count (APC) and/or Automatic Fare Collection (AFC) systems. AFC in particular reduces on-board ticketing time, driver’s work load and ultimately reduces bus dwell time. AFC systems can record all passenger transactions providing transit agencies with access to vast quantities of data. AFC data provides transaction timestamps, however this information differs from dwell time because passengers may tag on or tag off at times other than when doors open and close. This research effort contended that models could be developed to reliably estimate dwell time distributions when measured distributions of transaction times are known. Development of the models required calibration and validation using field survey data of actual dwell times, and an appreciation of another component of transaction time being bus time in queue. This research develops models for a peak period and off peak period at a busway station on the South East Busway (SEB) in Brisbane, Australia.

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This paper assesses Intelligent Transportation Systems (ITS) to identify safety systems that are most likely to reduce driver errors at railway crossings. ITS technologies have been integrated in order to develop improved evaluation tools to reduce crashes at railway crossings. Although emerging technologies, knowledge, innovative interventions have been introduced to change driver behaviour, there is a lack of research on the impact of integrating ITS technologies and transportation simulation on drivers. The outcomes of ITS technologies for complementing traditional signage were compared with those of current safety systems (passive and active) at railway crossings. Three ITS technologies are compared with current treatments, in terms of compliance rate and vehicle speed profiles. It is found that ITS technologies improve compliance rate by 17~30% and also encourage drivers to slow down earlier compared to current passive and active crossings when there is a train approaching the railway crossings.

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Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

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Increasing the modal share of public transit systems has become paramount in aiding the reduction on the excessive reliance of personal motor vehicles. More so the need to increase the share of active modes of transport such as the use of bicycles, therefore there is an ever increasing need to use bicycles both on shared pedestrian paths and on-road cycling. The risk to cyclist, or consequently the perception of the risk from both cyclists and motorists alike, is an important factor to increase the use of this transport mode. This paper investigates perception of bicycle safety by conducting a survey and analysing the survey data to understand how participants with different backgrounds perceive the risks of cycling for transport. Contributing factors to people’s perception of bicycle safety were identified and compared across different road user groups, based upon which recommendations were made on how to improve bicycle safety.

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The older adult population (65 years and over) represents a rapid growing segment of the population in many developed countries. Unlike earlier cohorts of older drivers that included many who were familiar with public transportation, the present cohort of older drivers historically has a greater reliance on the private automobile as their main form of transportation. Recent studies of older adults’ travel patterns reported automobile to be responsible for over 80% of the total number of hours spent on all trips. While older drivers, as a group, does not demonstrate a particular road risk, the evident demographic change and the increased physical fragility and severity of crash-related injuries makes older driver safety a prevalent public health issue. This study systematically reviewed the safety and mobility outcomes of existing strategies used internationally to manage older driver safety, with a specific focus on age-based testing (ABT), license restriction and self-regulation (i.e. voluntary limiting driving in potentially hazardous situations). ABT remains the most commonly adopted strategy by licensing authorities both within Australia and internationally. Heterogeneity in the development of functional declines, and in driving behaviours within the older driver population, makes age an unreliable index of driving capacity. Given the counter-productive safety and mobility outcomes of ABT strategies, their continued popularity within both the legislative and public domains remains problematic. Self-regulation may provide greater potential for reducing older drivers’ crash risk while maintaining their mobility and independence. The current body of literature on older drivers’ self-regulation is systematically reviewed. Despite being promoted by researchers and licensing authorities as a strategy to maintain older driver safety and mobility, the proportion of older drivers who self-regulate, and exactly how they do so, remains unclear. Future research on older drivers’ adoption of self-regulation, particularly the underlying psychological factors that underlies this process, is needed in order to promote its use within the older driver community.

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In this paper, an integrated inter-vehicles wireless communications and positioning system supporting alternate positioning techniques is proposed to meet the requirements of safety applications of Cooperative Intelligent Transportation Systems (C-ITS). Recent advances have repeatedly demonstrated that road safety problems can be to a large extent addressed via a range of technologies including wireless communications and positioning in vehicular environments. The novel communication stack utilizing a dedicated frequency spectrum (e.g. at 5.9 GHz band), known as Dedicated Short-Range Communications (DSRC), has been particularly designed for Wireless Access in Vehicular Environments (WAVE) to support safety applications in highly dynamic environments. Global Navigation Satellite Systems (GNSS) is another essential enabler to support safety on rail and roads. Although current vehicle navigation systems such as single frequency Global Positioning System (GPS) receivers can provide route guidance with 5-10 meters (road-level) position accuracy, positioning systems utilized in C-ITS must provide position solutions with lane-level and even in-lane-level accuracies based on the requirements of safety applications. This article reviews the issues and technical approaches that are involved in designing a vehicular safety communications and positioning architecture; it also provides technological solutions to further improve vehicular safety by integrating the DSRC and GNSS-based positioning technologies.

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One of the concerns about the use of Bluetooth MAC Scanner (BMS) data, especially from urban arterial, is the bias in the travel time estimates from multiple Bluetooth devices being transported by a vehicle. For instance, if a bus is transporting 20 passengers with Bluetooth equipped mobile phones, then the discovery of these mobile phones by BMS will be considered as 20 different vehicles, and the average travel time along the corridor estimated from the BMS data will be biased with the travel time from the bus. This paper integrates Bus Vehicle Identification system with BMS network to empirically evaluate such bias, if any. The paper also reports an interesting finding on the uniqueness of MAC IDs.

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Addressing the Crew Scheduling Problem (CSP) in transportation systems can be too complex to capture all details. The designed models usually ignore or simplify features which are difficult to formulate. This paper proposes an alternative formulation using a Mixed Integer Programming (MIP) approach to the problem. The optimisation model integrates the two phases of pairing generation and pairing optimisation by simultaneously sequencing trips into feasible duties and minimising total elapsed time of any duty. Crew scheduling constraints in which the crew have to return to their home depot at the end of the shift are included in the model. The flexibility of this model comes in the inclusion of the time interval of relief opportunities, allowing the crew to be relieved during a finite time interval. This will enhance the robustness of the schedule and provide a better representation of real-world conditions.

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Traffic accidents often cause lane closure, and diminish stability of travel time as well as the level of road services. On the other hand, research on the implementation of ITS services aiming at the reduction of traffic accidents has made considerable progress lately. However there has been little discussion on the benefits obtained by traffic accident reduction from the view point of travel time reliability. Therefore, in this research, relationships between traffic accidents and travel time reliability are examined, and the benefit of traffic accident reduction is calculated based on the scheduling model under travel time uncertainties. The results show the significance of traffic accident reduction for the improvement of travel time reliability.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

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Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.

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This project is a breakthrough in developing new scientific approaches for the design, development and evaluation of inter-vehicle communications, networking and positioning systems as part of Cooperative Intelligent Transportation Systems ensuring the safety of both roads and rail networks. This research focused on the elicitation, specification, analysis and validation of requirements for Vehicle-to-Vehicle communications and networking, and Vehicle-to-Vehicle positioning, which are accomplished with the research platform developed for this study. A number of mathematical models for communications, networking and positioning were developed from which simulations and field experiments were conducted to evaluate the overall performance of the platform. The outcomes of this research significantly contribute to improving the performance of the communications and positioning components of Cooperative Intelligent Transportation Systems.

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This paper estimates the demand for transportation systems that are used primarily by disabled individuals. These systems are known as paratransit systems and have experienced large increases in number and average size over the past 15 years. We first use a national database and standard time series techniques to model aggregate demand. We then use a unique data set of administrative records from a paratransit system in central Virginia to estimate standard and nonstandard count models of individual demand. We conclude that most of the demand growth is from new passengers, but that predicting the growth of new passengers is very difficult. Our results also highlight the importance of incorporating autocorrelation and possible sample attrition into standard count models.