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Dottorato di Ricerca in Ingegneria delle Infrastrutture e dei Trasporti XX ciclo Real time control of public transit (La gestione in tempo reale del trasporto collettivo) Real time control of public transit
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The objective of this Thesis is the improvement in speed and regularity of transit systems, using real-time control strategies, in particular, vehicle holding and conditional transit priority. This objective is attained by taking into account the inherent uncertainty of transit operation, due to the random travel times and passenger arrivals at stops. A simulation model of a single transit route is presented, with explicit representation of traffic lights. Priority at intersections is assumed to be given only by green extension actuated by local sensors, with upstream stop location, while the vehicle holding strategies are based also on the availability of real time information at stops, by means of a prevision for the future arrivals. The results are evaluated and compared using suitably defined performance indicators. In a parallel study, some relations between transit assignment and operation models and between transit operation and dwell time models are highlighted by identifying some features of the transit headway distributions and comparing the results obtained, in carrying out a sensitivity analysis of the operation model, if different dwell time models are utilized.
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The City of Portland, in collaboration with TriMet (Portland's regional transit service provider) and the Oregon Department of Transportation, has implemented transit signal priority (TSP) at more than 240 intersections on seven transit routes as a part of the Streamline program. This study focuses on the simulation of one intersection in Portland by using hardware-in-the-loop simulation to examine the effects of TSP signal control strategies on transit performance. More specifically, near- and farside bus stops are studied with hardware-in-the-loop traffic simulation to determine the effect of stop location on the effectiveness of the Portland TSP system. This analysis is verified by using a deterministic spreadsheet model to determine the effectiveness of the system and to address whether a green time extension plan should be used if there is passenger activity at a nearside stop.
In the paper a multilevel control system for public transport is presented. Special attention is given to the bottom DDC level realizing real time dispatching control. It is based on the Automatic Vehicle Monitoring / AVM / system which gives the repetitive feedback. The dispatching control ensures that the system state tracks the given time - table / punctuality control / or regular headway / regularity control /. A discrete control model describing the fundamental phenomena observed during the movement of buses is proposed. Bunching of buses has been analysed in detail because it degrades service and operating efficiency. The DDC level is divided into two layers. The lower one acts as a discrete regulator, optimal in the L-Q or L-Q-G sense. The upper layer realizes repetitive control by selecting or generating actual modification of the schedule which yields the pattern for the discrete regulator. Different kinds of bus dispatching control strategies / holding, priority control at intersections, reserve, overtaking, curtailment / can be realized in the proposed model. It is expected that the implementation of the results of the paper in real-life bus dispatching control based on AVM system will improve its performance.
Schedule disturbances in public transport operations have a tendency to intensify along the line and propagate to successive vehicles due to the uneven accumulation of passengers. This phenomenon, affecting efficiency and reliability of service, occurs frequently with surface services due to street congestion, as well as with rapid transit when It approaches capacity volumes. In recent years, considerable attention has been given to this problem. Newell and Potts [1] (*), using a deterministic model, derived an expression for the behavior of delays both along the line and of subsequent vehicles at individual stations due to passenger accumulation. They gave a theoretical explanation of the phenomenon of pairing of buses, which later Potts and Tamlin tried to verify through observations of bus operations [2]. While they did observe the tendency for pairing of vehicles, their experiment indicated that numerous other factors in street operation (signals, traffic, etc.) make it difficult to distinguish individual causes of delays. Rapid transit is more convenient for these observations since passenger boarding is the dominant variable factor in operation. Tiercin [3] described a new method of schedule control tested by RATP in Paris for one of the principal « Metro » lines, and London Transport, in planning for « Victoria Line», used computer simulation of rapid transit operation at minimum intervals to derive operational measures to increase stability of service. This work was reported by Welding and Day (4) and in an unpublished Research Report [5]. Recently, Lehmann [6] and Sudmeyer [7] gave an Interesting theoretical analysis of propagation of delays along the line; their discussion was followed by a paper by this author [8] which is incorporated and somewhat expanded here. In this paper a theoretical analysis of the behavior of disturbances is extended to include the changes of disturbances with time (for subsequent vehicles at any given station). Practical implications are discussed and measures to minimize this phenomenon in public transport operations are suggested. A diagram for easy evaluation of stability of any service is also given here.
This paper describes simple tests that can be used to identify situations for which control is potentially effective. This analysis provides transit operators with a simple screening model to evaluate potential effectiveness of controls.
This paper presents recent research to model and solve real-time transit operations control problems. Types of control strategies studied include deadheading, expressing, and holding, both single and in combination. We formulated mathematical models for these control problems assuming real-time vehicle location information available. Important properties of the models are proved and illustrated. Efficient algorithms are developed for solving the control models. The advantages, disadvantages, and conditions for each type of control strategy are investigated. We show that while station-skipping strategies such as deadheading and expressing work in a totally different manner from holding, a coordinated combination of them results in the most effective and least disruptive control policies. Using AVI data collected for the MBTA Green Line (Boston, MA), the computational results show the control model are generally quite effective. The algorithms are also tested in situations where there are significant stochastic disturbances. Under stochastic conditions model performance is found to decline only moderately.
Since congestion on roads has deteriorated quality of bus service, attractiveness of bus has been weakened. Bus priority signal is a method to shorten control delay of bus at signalized intersections and to improve its service quality, such as reliability, in-vehicle time and waiting time. It may, however, cause congestion in general traffic. For this reason, this study attempts to develop a signal priority strategy to improve bus service quality while little inducing additional delay in general traffic by restricting target buses for priority. The effectiveness of this strategy is evaluated using microscopic simulation model, PARAMICS. The results show that this selected signal priority strategy reduces bus travel time and improves regularity of bus headway, compared with fixed signal control. Furthermore, it may regulate bus headway more powerfully and induce less delay to general traffic than non- selected signal priority.
16. Abstract Bus priority treatments have been used for decades in various effortsto improve,transit services. To improve bus movements alongtheir routes without incurring delays to other traffic,
Current practical and theoretical approaches to bus route problem are reviewed and a new model for setting frequencies is developed. The model allocates the available buses between time periods and between routes so as to maximize net social benefits subject to constraints on total subsidy, fleet size, and levels of vehicle loading. An algorithm is developed to solve this nonlinear program.
The average passenger boarding and alighting times and bus dwell times at stops are important information for estimating transit service capacities. Bus dwell time directly affects vehicle travel time, and thus the fleet size required to provide service based on scheduled headway is affected. Research focused on estimating bus dwell time and the impact of boarding and alighting passengers on dwell time. In addition, the effect of standees, time of day, and service type on bus dwell time was investigated. The data were recently collected from an archived database, within which automatic passenger counter information was recorded. The dwell times and passenger counts were recorded daily during 2001 and the first 6 months of 2002. The bus dwell time and average passenger boarding and alighting time at stops are explained using descriptive statistics.