Operations analysis of gravity assisted rapid transit

Gravity assisted rapid transit (GART) with 6 percent grades before and after each station are compared with conventional systems in terms of energy consumption, run time, line capacity and schedule stability under abnormal circumstances. Parametric analyses of run times and energy consumption include the impact of alternate accelerating and braking levels. The capcity analysis uses a network simulation program to determine the location and severity of all signal delays. Based on results of initial simulations, the block design was revised to eliminate bottlenecks in normal operations. The systems are then compared at headways of 80 to 180 seconds. One month of incidence reports of a modern operating transit system are reviewed to determine the failures to be simulated. The impact of failures resulting in station delays (30 to 360 seconds), speed limit reduction (20 mph and 30 mph to one or more trains), vehicle performance (75 percent acceleration) are compared at scheduled headway of 90 to 180 seconds

A new schedule-based transit assignment model with travel strategies and supply uncertainties

This paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space–time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers.postprin

The posssibilities of railway transport utilizing as a backbone network of integrated passenger transport systems

The aspects of utilizing of railway transport as a backbone network of integrated passenger transport systems are solved in the contribution. The basic requirements on this railway transport service are specified in the contribution. The main attention is focused on creating of line structure of the integrated transport systems. The location of interchange points is also accented in the contribution. The theoretical presumptions are also illustrated in the way of convenient practical examples

Short-Term prediction of vehicle occupancy in Advanced Public Transportation Information Systems (APTIS)

Most ITS applications to transit systems are oriented to the efficient management of Public Transportation (PT) operator’s resources, that is crew and fleet of vehicles. However, the potential of ITS application to transit system goes further than the efficient management of the fleet of vehicles. In fact, information on the real-time actual network state, if communicated to travelers, may be an effective tool for improving quality and effectiveness of services and, hence, for diverting people to PT modes. In this paper, we focus on Advanced Public Transportation Information System (APTIS) deploying shared en-route descriptive information. The case study of the city of Naples (Italy) is analyzed. Here PT travelers have reacted positively to being provided information on waiting time at stops and have expressed great interest in receiving additional information such as passenger occupancy of future vehicles. The latter information can be efficiently obtained by means of a modeling framework simulating travelers path choice and the way in which they propagate over the network, as well as Origin-Destination (OD) travel demand pattern. Such a modeling framework is described in this paper. This is based on the schedule based approach and simulates within-day dynamics in transit networks, on both the demand and supply side. Preliminary applications to a small-scale example network are also presented in the paper

17-11 Evaluation of Transit Priority Treatments in Tennessee

Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition

Transportation network companies as cost reduction strategies for paratransit

Paratransit service is an auxiliary type of public transportation provided for people with disabilities and older adults. Federal ADA regulations require all transit agencies receiving federal funding to provide paratransit service, but the per trip cost to transit operators is extremely expensive. Many transit agencies are looking for ways to reduce costs without limiting services. For many agencies, this results in providing the minimum services as required by ADA regulations. However, Boston’s Massachusetts Bay Transit Authority (MBTA) has taken a different approach to cost reduction by entering into one of the first partnerships with transportation network companies. In September 2016, MBTA’s paratransit service, The Ride, began a partnership with both Uber and Lyft as a cost reduction strategy for paratransit provision. Since the beginning of the partnership, MBTA has been able to reduce costs of providing paratransit while maintaining the same level of service. This report will examine the benefits and limitations of such partnerships between transit agencies and transportation network companies, using MBTA’s The Ride partnership as an example for potentially successful partnerships throughout the United States.Community and Regional Plannin

Agent-based modelling of air transport demand

Constraints such as opening hours or passenger capacities influence travel options that can be offered by an airport and by the connecting airlines. If infrastructure, policy or technological measures modify transport options, then the benefits do not only depend on the technology, but also on possibly heterogeneous user preferences such as desired arrival times or on the availability of alternative travel modes. This paper proposes an agent-based, iterative assignment procedure to model European air traffic and German passenger demand on a microscopic level, capturing individual passenger preferences. Air transport technology is simulated microscopically, i.e. each aircraft is represented as single unit with attached attributes such as departure time, flight duration or seat availability. Trip-chaining and delay propagation can be added. Microsimulation is used to verify and assess passengers’ choices of travel alternatives, where those choices improve over iterations until an agent-based stochastic user equilibrium is reached. This requires fast simulation models, thus, similar to other approaches in air traffic modelling a queue model is used. In contrast to those approaches, the queue model in this work is solved algorithmically. Overall, the approach is suited to analyze, forecast and evaluate the consequences of mid-distance transport measures

Mixed Data and Classification of Transit Stops

An analysis of the characteristics and behavior of individual bus stops can reveal clusters of similar stops, which can be of use in making routing and scheduling decisions, as well as determining what facilities to provide at each stop. This paper provides an exploratory analysis, including several possible clustering results, of a dataset provided by the Regional Transit Service of Rochester, NY. The dataset describes ridership on public buses, recording the time, location, and number of entering and exiting passengers each time a bus stops. A description of the overall behavior of bus ridership is followed by a stop-level analysis. We compare multiple measures of stop similarity, based on location, route information, and ridership volume over time

Railway traffic disturbance management by means of control strategies applied to operations in the transit system

Railway systems in metropolitan areas support a high density of daily traffic that is exposed to different types of disturbances in the service. An interesting topic in the literature is to obtain action protocols in the presence of contingencies which can affect the system operation, avoiding the propagation of perturbation and minimizing its negative consequences. Assume that, with a small margin of time (e.g. one day), the decision-maker of the transportation network is knowing that a part of the train fleet will become inoperative temporarily along a specific transit line and none additional vehicle will be able to restore the affected services. The decision to be taken in consequence will require to reschedule the existing services by possibly reducing the number of expeditions (line runs). This will affect travellers who regularly use the transit system to get around. Consider that the decision-maker aims to lose the least number of passengers as a consequence of having introduced changes into the transit line. A strategy that could be applied in this context is to remove those line runs which are historically less used by travellers without affecting the remaining services. Another alternative strategy might be to reschedule the timetables of the available units, taking into account the pattern of arrivals of users to the boarding stations and the user behavior during waiting times (announced in situ). The aim of this work consists of assessing the strategy of train rescheduling along the current transportation line when the supply must be reduced in order to reinforce the service of another line, exploited by the same public operator, which has suffered an incidence or emergency.Ministerio de Economía y CompetitividadFondo Europeo de Desarrollo Regiona