Passenger transmission and productiveness of transit lines with high loads

Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements

Development and Evaluation of Bus Operation Control System Based on Cooperative Speed Guidance

Buses often have strong bunching or large interval tendency when traveling further along the route. To restrain this further deterioration of operation service, this paper developed a bus operation control system to dynamically adjust bus speed, bus dwell time, and traffic signal timings along the running path. In addition, a simulation platform was developed to evaluate the proposed control system with the actual data collected from bus route number 210 in Shanghai. The simulation results show that the proposed control system can mitigate the amplification trend of the headway deviation along the route to produce headways within a given tolerance

Reliability Analysis of Public Transit Systems Using Stochastic Simulation

Unreliable public transport systems cause excessive waiting times, late or early arrivals at destinations and missed connections for passengers. Also, unreliability results in economic losses to transit operators through under utilization of vehicles, equipment and work force. The reliability analysis of bus transit, covered in this paper, is based on numerical estimation of headway variations at different bus stops along the route. A number of simulations are conducted to determine the variation of performance of bus operation due to the variability of departure headways. The average waiting time of passengers is used as an indicator of operational performance. Simulation results show that the spread of passenger waiting times widens as the headway variation increases. Impact of size of vehicle on waiting time distributions is also investigated. Irregular headways lead to uneven passenger loads on buses. Such variation in passenger counts result in some buses becoming full and being unable to serve certain stops. Thus, average waiting time increases with smaller bus size. Simulation also reveals that the average waiting time increases for passengers waiting further along the route

Evaluating Inter-Agency Vehicle Headway Adherence Using AVL Data

A frequent source of frustration for riders of public transit is irregularity in arrival times of the transport vehicles. The use of GPS-based automatic vehicle locator (AVL) services in conjunction with web devices and smart signage can mitigate some of the uncertainty involved in waiting for the transit vehicles and can be used to minimize wait times at the stop; however, regularly unreliable vehicle arrivals can over time impede the use of public transit as a viable alternative to other forms of transportation. A number of factors, including land use, traffic patterns, policy, rolling stock and loading rates influence the tendency of buses to experience headway irregularity. We seek to identify factors associated with the gapping and bunching of buses—identified through gathered AVL data—at a number of cities in the US. By comparing these factors between different transit agencies, I hope to determine if the rates of gapping and bunching are more closely associated with local factors (e.g., land use or ridership) or by latent, agency-wide factors.Master of City and Regional Plannin

Development and application of dynamic models for predicting transit arrival times

Stochastic variations in traffic conditions and ridership often have a negative impact in transit operations resulting in the deterioration of schedule/headway adherence and lengthening of passenger wait times. Providing accurate information on transit vehicle arrival times is critical to reduce the negative impacts on transit users. In this study, models for dynamically predicting transit arrival times in urban settings are developed, including a basic model, a Kalman filtering model, link-based and stop-based artificial neural networks (ANNs) and Neural/Dynamic (ND) models. The reliability of these models is assessed by enhancing the microscopic simulation program CORSIM which can calculate bus dwell and passenger wait times based on time-dependent passenger demands and vehicle inter-departure times (headways) at stops. The proposed prediction models are integrated with the enhanced CORSIM individually to predict bus arrival times while simulating the operations of a bus transit route in New Jersey. The reliability analysis of prediction results demonstrates that ANNs are superior to the basic and Kalman filtering models. The stop-based ANN generally predicts more accurately than the link-based ANN. By integrating an ANN (either link-based or stop-based) with the Kalman filtering algorithm, two ND models (NDL and NDS) are developed to decrease prediction error. The results show that the performance of the ND models is fairly close. The NDS model performs better than the NDL model when stop-spacing is relatively long and the number of intersections between a pair of stops is relatively large. In the study, an application of the proposed prediction models to a real-time headway control model is also explored and experimented through simulating a high frequency light rail transit route. The results show that with the accurate prediction of vehicle arrival information from the proposed models, the regularity of headways between any pair of consecutive operating vehicles is improved, while the average passenger wait times at stops are reduced significantly

Schedule Synchronisation in public Transport by Tabu Search and Genetic Method

This paper concerns schedule synchronization problems in public transit networks. In particular, it consists of three main parts. In the first the subject area is introduced, the terms are defined and framework for optimal synchronization in the form of problem representation and formulation is proposed. The second part is devoted to transfer synchronization problem when passengers changing transit lines at transfer points. The intergrated Tabu Search and Genetic solution method is developed with respect to this specific problem. The third part deals with headways harmonization problem i.e. synchronization of different transit lines schedules on a common segments of routes. For the solution of this problem a new bilevel optimization method is proposed with zones harmonization at the bottom level and co-ordination of zones, by time buffers assigned to timing points, at the upper level. Finally, the synchronization problems are numerically illustrated by real-life examples of the public transport lines in Cracow

A transit route simulator for the evaluation of control strategies using automatically collected data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005.Includes bibliographical references (leaves 133-135).This thesis develops and tests an extensible simulation model that uses automatically collected transit data to simulate transit route operations, demand, and control mechanisms. This model is motivated by the increasing availability of automatically collected transit data, which enables more detailed simulation and validation and also allows for advanced control strategies that can be evaluated using simulation. A framework is presented for using simulation to evaluate the improvement in service quality enabled by data. Most previous transit route simulation models included an explicit representation of traffic flow, which requires extra input data and introduces extra complexity. A detailed simulator design is presented that uses only transit-derived data to simulate vehicle and passenger movements and outputs a detailed log for flexibility of performance measurement. A case study of operations on the CTA's Route 9 Ashland was used to demonstrate and test the simulator. The simulator could be used to test alternative operator and supervisor behavior strategies and supervisor deployment schemes, as well as potential technological advances involving real-time data. Schedule, vehicle movement, terminal departure punctuality, passenger demand, and dwell time inputs for the simulator were derived from Route 9's schedule, AVL data, and APC data. The case study simulation was subjected to validation tests that compare simulated and real headway regularity, trip travel time, and maximum load statistics. Significant differences were found in all three tests. Adjustments were employed in attempt to make the simulation match reality.(cont.) The results of adjustments to input parameters show that dwell times are an important source of headway variability. The results of adjustments to operator and passenger behavior and of controls indicate that effects that apply only to bunched vehicles have limited impact on service. After each of these adjustments, the simulation still did not pass validation tests. A prime cause for this result may be the intelligent behavior of transit agency personnel, particularly operators, a potentially fruitful area for future research.by Isaac E. Moses.S.M

Why Does Public Transport Not Arrive on Time? The Pervasiveness of Equal Headway Instability

BACKGROUND: The equal headway instability phenomenon is pervasive in public transport systems. This instability is characterized by an aggregation of vehicles that causes inefficient service. While equal headway instability is common, it has not been studied independently of a particular scenario. However, the phenomenon is apparent in many transport systems and can be modeled and rectified in abstraction. METHODOLOGY: We present a multi-agent simulation where a default method with no restrictions always leads to unstable headways. We discuss two methods that attempt to achieve equal headways, called minimum and maximum. Since one parameter of the methods depends on the passenger density, adaptive versions--where the relevant parameter is adjusted automatically--are also put forward. Our results show that the adaptive maximum method improves significantly over the default method. The model and simulation give insights of the interplay between transport design and passenger behavior. Finally, we provide technological and social suggestions for engineers and passengers to help achieve equal headways and thus reduce delays. CONCLUSIONS: The equal headway instability phenomenon can be avoided with the suggested technological and social measures