Transit Planners Research Articles

Modeling a rail transit alignment considering different objectives

An optimization model for station locations for an on-ground rail transit line is developed using different objective functions of demand and cost as both influence the planning of a rail transit alignment. A microscopic analysis is performed to develop a rail transit alignment in a given corridor considering a many-to-one travel demand pattern. A variable demand case is considered as it replicates a realistic scenario for planning a rail transit line. A Genetic Algorithm (GA) based on a Geographical Information System (GIS) database is developed to optimize the station locations for a rail transit alignment. The first objective is to minimize the total system cost per person, which is a function of user cost, operator cost, and location cost. The second objective is to maximize the ridership or the service coverage of the rail transit alignment. The user cost per person is minimized separately as the third objective because the user cost is one of the most important decision-making factors for planning a transit system from the users’ perspective. A transit planner can make an informed decision between various alternatives based on the results obtained using different objective functions. The model is applied in a case study in the Washington, DC area. The optimal locations and sequence of stations obtained using the three objective functions are presented and a comparative study between the results obtained is shown in the paper. In future works we will develop a combinatorial optimization problem using the aforementioned objectives for the rail transit alignment planning and design problem.

Constructing Transit Origin–Destination Tables from Fragmented Data

This study proposes an approach that constructs the origin–destination table (O-D table) for urban bus or light rail lines from fragmented data about the number of boarding and alighting passengers at stops (B-A data) and the analyst's spot knowledge about the trip pattern for selected O-D pairs. The B-A data of transit lines in the city center are often incomplete, yet they may be the only data available to characterize the passenger travel pattern. The proposed approach constructs the O-D table by using data that contain different levels of uncertainties and incompleteness. The model is based on two basic principles, maximum uncertainty and minimum uncertainty. The former is implemented by maximizing the entropy of the O-D table to derive the least-biased values. The latter refers to the maximum consistency with the available data including language-based knowledge about some of the O-D table elements. These principles are implemented by the multiobjective optimization structure. The model is found to be robust if it can incorporate various types of available data as well as the analyst's knowledge. It was tested by using O-D data and B-A data from an actual transit operation. The quality of the derived O-D table is clearly related to the availability and the quality of the data; however, it can be improved significantly with the analyst's spot knowledge about the values of selected O-D pairs. This method will open the way for transit planners to quickly develop a reasonable O-D table from the available incomplete data.

Maturity of Key Technologies Provides More Options for Transit and Paratransit Planners

Travel needs and patterns within metropolitan regions are becoming increasingly more complex. Community pressure to use limited operations budgets in the most effective and efficient manner is also increasing, even though these requirements often conflict. Ideally, in response, service planners should be able to explore a wide range of service design options, unencumbered by technological constraints. A service planning concept based on a spectrum of possible service designs ranging from pure fixed route to pure demand responsive, with many intermediate options, is described. Intelligent transportation system technologies and scheduling software have matured to the point that this concept is now realistic. How these technologies enable a highly integrated system in which numerous service designs can be operated simultaneously is explained. Likely benefits are presented from several perspectives: planning latitude given by time of day, by change of season, and for efficient vehicle use and adaptation to changes in service area character over the years. Some requirements for reorganization by typical transit agencies are discussed. Potential benefits from better coordination or the merger with outside agencies are outlined. Vendors have been cautious to date and are unlikely to complete the technological integration needed without firm commitments. Thus, a funded research project at an appropriate volunteer site would be required.

Sketch Transit Modeling Based on 2000 Census Data

Transit planners need cost-effective ways to evaluate a wide range of alternatives relatively quickly to identify potential transit systems that are likely to offer the greatest benefits for a given cost. A sketch transit planning model is described for the Washington, D.C., region that is based on the metropolitan planning organization's travel demand model structure and model networks but is estimated from more recent 2000 census data, better matches suburban transit ridership, is sensitive to land use effects, and is less costly to use. Similar transit sketch models could be developed and applied in other regions.

Sketch Transit Modeling Based on 2000 Census Data

Transit planners need cost-effective ways to evaluate a wide range of alternatives relatively quickly to identify potential transit systems that are likely to offer the greatest benefits for a given cost. A sketch transit planning model is described for the Washington, D.C., region that is based on the metropolitan planning organization's travel demand model structure and model networks but is estimated from more recent 2000 census data, better matches suburban transit ridership, is sensitive to land use effects, and is less costly to use. Similar transit sketch models could be developed and applied in other regions.

Use of Automatic Vehicle Location and Passenger Count Data to Evaluate Bus Operations

New technologies such as automatic vehicle location (AVL) and automatic passenger counters (APC) make tremendous amounts of data available to transit planners and operators. Transit agencies would like to use these data to inform service planning and management and ultimately to provide more reliable service. This requires data processing in such a way as to provide pertinent information to transit planners. The research presented considers a sample of data collected from Chicago Transit Authority buses during the initial stage of AVL and APC implementation in Chicago, Illinois. Methods were developed for extracting information from these data that could be used to compute service reliability indicators. This research also discusses some of the challenges encountered in the data collection process. At the time of the data collection, the home garage for the bus route under consideration was not fully stocked with AVL-equipped buses. Other challenges included the misplacement of some time points and underc...

Use of Automatic Vehicle Location and Passenger Count Data to Evaluate Bus Operations

New technologies such as automatic vehicle location (AVL) and automatic passenger counters (APC) make tremendous amounts of data available to transit planners and operators. Transit agencies would like to use these data to inform service planning and management and ultimately to provide more reliable service. This requires data processing in such a way as to provide pertinent information to transit planners. The research presented considers a sample of data collected from Chicago Transit Authority buses during the initial stage of AVL and APC implementation in Chicago, Illinois. Methods were developed for extracting information from these data that could be used to compute service reliability indicators. This research also discusses some of the challenges encountered in the data collection process. At the time of the data collection, the home garage for the bus route under consideration was not fully stocked with AVL-equipped buses. Other challenges included the misplacement of some time points and undercounting by the APC system. The data proved useful even with these challenges, and valuable information, such as bus travel patterns, schedule adherence, and headway regularity, was gained from this study. By recognizing some of the challenges faced in the data collection process, this research provided insights that can be used to inform future larger-scale studies of transit operations using AVL and APC data.

Confronting the Challenges in This Information Age: Towards a New Transit Modeling Approach

Information is affecting our life in significant ways. Transit planners have a dream that one day they can fully utilise all available information as the model input, and the planning tool is also able to provide valuable information for policy making. Transit operators also want to realise their dream such that in one day they can quickly decide the incident management strategy by providing passengers with the time-dependent route guidance information. Passengers also imagine that one day they are able to plot their route and print their itinerary with detailed in-vehicle/waiting/walking/transferring time before they leave their home or office. All is dream in the past in view of the lack of information (such as the detailed time-dependent origin-destination (O-D) demand information), as well as the limitation of computation power. As such, the conventional transit models often simplify the real situation or ignore some of the system/passenger behavior. With the advent of the information age, the introdu...

Estimation of Statewide Urban Public Transit Benefits in Tennessee

A comprehensive transit benefits assessment procedure is described as applied to each of the 12 urban public transit operating districts in the state of Tennessee. A multiple-branch benefits assessment tree is developed around transit use benefits and transit supply benefits, the former emphasizing the costs of lost mobility in the absence of current transit services and the latter reflecting the economic benefits resulting from federal and state support for public transit in each district. Empirical results are presented at the statewide level and in dollar terms. With a generally conservative approach to benefits estimation, it is found that urban transit benefits—mainly from fixed-route bus service—exceed costs by 2 to 2.5 times, with higher ratios possible in the larger metropolitan areas. Sensitivity to forgone travel benefits, however, suggests the need for further data refinements. On the basis of past literature, the study develops a comprehensive set of wide-ranging benefits computations that have been applied consistently across each of the state's 12 urban transit districts and uses data sources that can be cost-effectively updated by transit planners.

Model for Determining Optimum Bus-Stop Spacingin Urban Areas

This paper proposes a model that can be used to determine effectively a sub-optimal policy for bus-stop spacing in urban areas. Transit users are usually interested in minimizing their out-of-vehicle travel time. Conversely, transit operators are interested in minimizing their fixed operating cost. Often, transit operators are required to make transit highly accessible to their patrons, because they operate under stringent budgets. This paper demonstrates, from a sensitivity analysis, that proper spacing of stops can significantly improve the quality of transit service, and decrease travel time, headway, and fleet size (i.e., number of buses). The Highway Capacity Manual, which contains a library of formulas for analyzing various transit performance measures, does not adequately address transit-stop spacing as a primary operational parameter. It is postulated in this report that optimal spacing of bus stops can reduce operating costs by minimizing the required number of buses in service. The proposed model is derived from the fundamental relationships that exist among velocity, uniform acceleration/deceleration, and displacement, and among the average bus operating speed, headway, required fleet size, and potential system capacity. The model can serve as a valuable decision support tool for transit planners in determining suitable spacing of bus stops for prevailing network and traffic conditions.

Enhancements of CORSIM Model in Simulating Transit Operations

A CORSIM-based microscopic simulation model is developed, which provides transit planners and operators with the ability to simulate bus operations on transit routes. Several modules in CORSIM for processing bus operations are modified to calculate bus dwell times at stops. The bus dwell time is dynamically determined by the passenger arrival rate, average boarding time, and vehicle interdeparture time (headway). Bunching of buses—due to variations in passenger demand at stops, travel times on streets, and delays at intersections—deteriorates the quality of service and operating efficiency, which can be observed from the simulation results. The input requirements and the modular nature of the proposed model are highlighted. Outputs, including bus arrival and departure times, dwell time, and average passenger waiting time at each stop, are generated for the evaluation of bus operations. The proposed simulation model is calibrated and validated by two sets of data collected from bus route 39 of the New Jersey Transit Corporation.

How Chaos Does Not Destroy Ridership: Operations of an Exclusive Busway Carrying More Than 35,000 Passengers per Hour per Direction

Busways have been reported to carry up to 28,000 passengers per hour per direction (pphpd). However, recent passenger counts indicate that the exclusive busway in Bogotá, Colombia, has a flow of more than 35,000 pphpd. This passenger flow is achieved despite poor operating conditions and a general lack of maintenance without a city busway management and operation authority. Consequently, there is little police control, no systems management, and scarce information for users. These conditions should affect passenger flow negatively, but the Bogotá busway carries more passengers than all busways for which data are available. The analysis suggests that the Bogotá busway is able to move high passenger flows due to three concurrent and interactive sets of factors. First, the high competition among bus operators provides drivers with an incentive to operate more efficiently. Second, the design provides two lanes, allowing for vehicle overtake, as well as stations that enable six or more buses simultaneously to pick up and discharge passengers. Third, the buses move in platoons along the busway. Each platoon consists of 12 to 16 buses with average 96-s headways. Furthermore, time-distance diagrams indicate that the platoons are not stable, because vehicles keep changing from one platoon to another. The analysis underscores the importance for transit planners of trade-offs among passenger flows, level of service, and optimal system operation.

Use of Geographic Information System for Analysis of Transit Pedestrian Access

The development and application of transit accessibility measures by geographic information system technology are described. The approach allows transit planners to focus on access to transit routes and bus stops at the neighborhood level and draws attention to the significance of the walk access mode to transit. Then land use, population, and employment characteristics are incorporated into the evaluation of transit service. A case study example of a “what-if” scenario for evaluation of transit service alternatives is discussed. Conclusions are offered about the use and further development of the approach for transit planners.

Using GIS tools to improve transit ridership on routes serving large employment centers: The Boston South End Medical Area case study

One potential application of Geographic Information System (GIS) in transit management and operation is ridership analysis on transit routes. Large employment centers need to be conveniently served by transit routes in order to reduce traffic congestion and minimize the need for parking spaces. Transit planners, when designing bus mutes, consider demographic factors such as the number of employers, the number of residences, and residents' income levels in order to determine the type and characteristics of the service to be provided. The usual unit of analysis in these studies is fairly aggregate geographically. The advance of computer technologies, and specifically GIS, coupled with rapidly increasing availability of detailed data, provide new tools for designing better transit routes. This paper describes how planning transit routes can be transformed into a more proactive process, and how GIS technologies can be used to reach that goal. Our methodology includes using the address-matching capabilities of GIS to pinpoint the residences of the employees of large employers and to map these locations with respect to existing transit lines and employment sources. A statistical analysis of current accessibility is then completed. This application of GIS technology aids in diagnosing major gaps with existing services to major centers and in proposing improvements to these services. To provide a concrete example, we use data from three large medical institutions in the South End Medical Area of Boston. These employers currently claim to be underserved by public transport. We examine how well the existing lines are serving these institutions.

The capital, energy, and time economics of an automated, on-demand transportation system

Many transit and rail planners believe that the only way to decrease the capital and operating cost of rail and transit systems is to decrease the size and weight of the vehicles. The authors discuss the requirements of such a downsized transportation system and the benefits to be gained by decreasing the size of the operational vehicles. Not only can the capital and operating cost of the system be dramatically decreased, but the operational requirements of a system involving the use of smaller vehicles permits its use as an on-demand system, further increasing system utility to the passenger and system operator. The capital cost, energy economics, and the economics of the CyberTran transportation system are reviewed. >

An AI‐based approach for transit route system planning and design

AbstractWe present an AI‐based solution approach to the transit network design problem (TNDP). Past approaches fall into three categories: optimization formulations of idealized situations, heuristic approaches, or practical guidelines and ad hoc procedures reflecting the professional judgement and practical experience of transit planners. We discuss the sources of complexity of the TNDP as well as the shortcomings of the previous approaches. This discussion motivates the need for AI search techniques that implement the existing designer's knowledge and expertise to achieve better solutions efficiently. Then we propose a hybrid solution approach that incorporates the knowledge and expertise of transit network planners and implements efficient search techniques using AI tools, algorithmic procedures developed by others, and modules for tools implemented in conventional languages. The three major components of the solution approach are presented, namely, the lisp‐implemented route generation design algorithm (RGA), the analysis procedure TRUST (Transit Route Analyst), and the route improvement algorithm (RIA). An example illustration is included.

Planning Development with Transit Projects

One of the principal objectives of a transit project is to stimulate economic development. It is desirable to have early involvement of private sector developers in the transit planning process. However, the private sector seldom becomes involved before a transit project is nearly completed, and transit planners and public officials seldom incorporate developers' decision processes into their planning in order to increase the range of economic development opportunities. This study presents a site‐development model which simulates the long‐ and short‐range decision processes of developers. These decision processes involve four steps: (1) Determination of development demand for route alignment, station location and specific parcels development; (2) analysis of site constraints on development; (3) analysis of various design and marketing options; and (4) the financial analysis of an individual project. Three uses of the model for typical development problems are illustrated using data from the King Street St...

Approximate procedures for planning public transit systems: A review and some examples

AbstractThe approximate analytical models of public transit systems are reviewed. First, the derivation and formation of the standard model form is presented. Once the model is explained in general terms some practical planning applications are considered and evaluated. The model type presents an invaluable tool to the transit planner but a few operational problems need to be considered. Further benefits to the planning professionals would be realized if researchers were to devote more effort to sensitivity analysis as a means of determining which system parameters have the greatest impact upon the operation of the transit system.

The allocation of buses in heavily utilized networks with overlapping routes

Many transit systems outside North America are characterized by networks with extensively overlapping routes and buses frequently operating at, or close to, capacity. This paper addresses the problem of allocating a fleet of buses between routes in this type of system; a problem that must be solved recurrently by transit planners. A formulation of the problem is developed which recognizes passenger route choice behavior, and seeks to minimize a function of passenger wait time and bus crowding subject to constraints on the number of buses available and the provision of enough capacity on each route to carry all passengers who would select it. An algorithm is developed based on the decomposition of the problem into base allocation and surplus allocation components. The base allocation identifies a feasible solution using an (approx.) minimum number of buses. The surplus allocation is illustrated for the simple objective of minimizing the maximum crowding level on any route. The bus allocation procedure developed in this paper has been applied to part of the Cairo bus system in a completely manual procedure, and is proposed to be the central element of a short-range bus service planning process for that city.

RAM: A normative tool for transit route planning : Leonard Goldstein (Dissertation in the Department of Transportation Planning and Engineering, Polytechnic Institute of New York, New York, NY 11201).

This work deals with the development of a Route Allocation Model (RAM), a practical methodology to assist the transit planner in the development of transit needs. RAM is a computerized transit route design tool which will sequentially allocate bus (or other) routes to an area under study. The model is multi-purpose in that it may be utilized for standard transit route planning or for transit route planning under a scenario of special interest. These scenarios may include such items as limited auto-environment planning, school bus planning, standard Transportation Systems Management Element applications, and the updating of currently outdated transit routes to reflect present day transportation needs. This document discusses such items as: the nature of the general transit routing problem; a disutility function; a definition of the network and the RAM approach. There are charts that illustrate the differences between the conventional approach of route planning and the RAM approach to transit route planning. The scope includes a case study application of the RAM methodology in Queens County, New York City. Results obtained for this case study are presented as well as recommendations for further research. The RAM methodology is developed within this text and complemented by the appendices of computer outputs which illustrate components of the methodology. The appendix material is not included herein, but it is available on request from the Transportation Research and Training Center, Polytechnic Institute of New York. /UMTA/