999 resultados para Transit signal priority


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An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.

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Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^

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This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

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Vehicle speed is an important attribute for the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to the traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus; in-service bus during peak; and in-service bus during off peak periods with average car are proposed. The models are cross-validated and the interrelationships are significant

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Although transit travel time variability is essential for understanding the deterioration of reliability, optimising transit schedule and route choice; it has not attracted enough attention from the literature. This paper proposes public transport-oriented definitions of travel time variability and explores the distributions of public transport travel time using the Transit Signal Priority data. First, definitions of public transport travel time variability are established by extending the common definitions of variability in the literature and by using route and services data of public transport vehicles. Second, the paper explores the distribution of public transport travel time. A new approach for analysing the distributions involving all transit vehicles as well as vehicles from a specific route is proposed. The Lognormal distribution is revealed as the descriptors for public transport travel time from the same route and service. The methods described in this study could be of interest for both traffic managers and transit operators for planning and managing the transit systems.

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Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.

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Public Transport Travel Time Variability (PTTV) is essential for understanding the deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes the key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyzes the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach, using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and analyzing the transit systems.

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Vehicle speed is an important attribute for analysing the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus, in-service bus during peak periods, and in-service bus during off-peak periods with average car speed are proposed. The models are cross-validated and the interrelationships are significant.

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Most of our knowledge of extrasolar planets rests on precise radial-velocity measurements, either for direct detection or for confirmation of the planetary origin of photometric transit signals. This has limited our exploration of the parameter space of exoplanet hosts to solar- and later-type, sharp-lined stars. Here we extend the realm of stars with known planetary companions to include hot, fast-rotating stars. Planet-like transits have previously been reported in the light curve obtained by the SuperWASP survey of the A5 star HD15082 (WASP-33 V = 8.3, v sini = 86 km s-1). Here we report further photometry and time-series spectroscopy through three separate transits, which we use to confirm the existence of a gas-giant planet with an orbital period of 1.22d in orbit around HD15082. From the photometry and the properties of the planet signal travelling through the spectral line profiles during the transit, we directly derive the size of the planet, the inclination and obliquity of its orbital plane and its retrograde orbital motion relative to the spin of the star. This kind of analysis opens the way to studying the formation of planets around a whole new class of young, early-type stars, hence under different physical conditions and generally in an earlier stage of formation than in sharp-lined late-type stars. The reflex orbital motion of the star caused by the transiting planet is small, yielding an upper mass limit of 4.1MJupiter on the planet. We also find evidence of a third body of substellar mass in the system, which may explain the unusual orbit of the transiting planet. In HD 15082, the stellar line profiles also show evidence of non-radial pulsations, clearly distinct from the planetary transit signal. This raises the intriguing possibility that tides raised by the close-in planet may excite or amplify the pulsations in such stars.

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Context. Observations of transiting extrasolar planets are of key importance to our understanding of planets because their mass, radius, and mass density can be determined. These measurements indicate that planets of similar mass can have very different radii. For low-density planets, it is generally assumed that they are inflated owing to their proximity to the host-star. To determine the causes of this inflation, it is necessary to obtain a statistically significant sample of planets with precisely measured masses and radii. Aims. The CoRoT space mission allows us to achieve a very high photometric accuracy. By combining CoRoT data with high-precision radial velocity measurements, we derive precise planetary radii and masses. We report the discovery of CoRoT-19b, a gas-giant planet transiting an old, inactive F9V-type star with a period of four days. Methods. After excluding alternative physical configurations mimicking a planetary transit signal, we determine the radius and mass of the planet by combining CoRoT photometry with high-resolution spectroscopy obtained with the echelle spectrographs SOPHIE, HARPS, FIES, and SANDIFORD. To improve the precision of its ephemeris and the epoch, we observed additional transits with the TRAPPIST and Euler telescopes. Using HARPS spectra obtained during the transit, we then determine the projected angle between the spin of the star and the orbit of the planet. Results. We find that the host star of CoRoT-19b is an inactive F9V-type star close to the end of its main-sequence life. The host star has a mass M-* = 1.21 +/- 0.05 M-circle dot and radius R-* = 1.65 +/- 0.04 R-circle dot. The planet has a mass of M-P = 1.11 +/- 0.06 M-Jup and radius of R-P = 1.29 +/- 0.03 R-Jup. The resulting bulk density is only rho = 0.71 +/- 0.06 g cm (3), which is much lower than that for Jupiter. Conclusions. The exoplanet CoRoT-19b is an example of a giant planet of almost the same mass as Jupiter but a approximate to 30% larger radius.

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Accurate measurement of transit time for acoustic wave between two sensors installed on two sides of a furnace is a key to implementing the temperature field measurement technique based on acoustical method. A new method for measuring transit time of acoustic wave based on active acoustic source signal is proposed in this paper, which includes the followings: the time when the acoustic source signal arrives at the two sensors is measured first; then, the difference of two arriving time arguments is computed, thereby we get the transit time of the acoustic wave between two sensors installed on the two sides of the furnace. Avoiding the restriction on acoustic source signal and background noise, the new method can get the transit time of acoustic wave with higher precision and stronger ability of resisting noise interference.

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The accuracy of ranging measurements depends critically on the knowledge of time delays undergone by signals when retransmitted by a remote transponder and due to propagation effects. A new method determines these delays for every single pulsed signal transmission. It utilizes four ground-based reference stations, synchronized in time and installed at well-known geodesic coordinates and a repeater in space, carried by a satellite, balloon, aircraft, and so forth. Signal transmitted by one of the reference bases is retransmitted by the transponder, received back by the four bases, producing four ranging measurements which are processed to determine uniquely the time delays undergone in every retransmission process. A minimization function is derived comparing repeater's positions referred to at least two groups of three reference bases, providing the signal transit time at the repeater and propagation delays, providing the correct repeater position. The method is applicable to the transponder platform positioning and navigation, time synchronization of remote clocks, and location of targets. The algorithm has been demonstrated by simulations adopting a practical example with the transponder carried by an aircraft moving over bases on the ground.