Bus Rapid Transit: A Handbook for Partners, MTI Report 06-02

In April 2005, the Caltrans Division of Research and Innovation (DRI) asked MTI to assist with the research for and publication of a guidebook for use by Caltrans employees who work with local transit agencies and jurisdictions in planning, designing, and operating Bus Rapid Transit (BRT) systems that involve state facilities. The guidebook was also to assist to transit operators, local governments, community residents, and other stakeholders dealing with the development of BRT systems. Several areas in the state have experienced such projects ( San Diego , Los Angeles , San Francisco , and Alameda County ) and DRI wished to use that experience to guide future efforts and identify needed changes in statutes, policies, and other state concerns. Caltrans convened a Task Team from the Divisions of Research and Innovation, Mass Transportation, and Operations, together with stakeholders representing many of those involved with the BRT activities around the state. Prior to MTI’s involvement, this group produced a white paper on the topic, a series of questions, and an outline of the guidebook that MTI was to write. The MTI team conducted case studies of the major efforts in California, along with less developed studies of some of the other BRT programs under development or in early implementation phases around the state. The purpose was to clarify those issues that need to be addressed in the guidebook, as well as to compile information that would identify items needing legislative or regulatory action and items that Caltrans will need to address through district directives or other internal measures. A literature scan was used to develop a bibliography for future reference. The MTI team also developed a draft Caltrans director’s policy document, which provides the basis for Caltrans’ actions. This ultimately developed to be a project within a project. MTI submitted a draft document to Caltrans as a final product from the Institute. Task team members and Caltrans staff and leadership provided extensive review of the draft Bus Rapid Transit: A Handbook for Partners. Caltrans adopted a new Director’s Policy and published the document, BRT Caltrans. The MTI “wraparound” report presented below discusses in more detail the process that was followed to produce the draft report. The process was in many ways as much a project as the report itself

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Economic Impacts of Bus Rapid Transit in Southeast Michigan

In recent years, Bus Rapid Transit (BRT) has generated great interest across the United States. There are more than 20 BRT systems in existence, and more are in the planning stage (including in Detroit). Within the next few years, BRT will be planned and implemented phase by phase in various parts of Southeast Michigan. The purpose of this study is to develop a framework to identify probable economic impacts of BRT in Southeast Michigan. Taxable real estate values, injury and fatal crash data, and selected demographics of BRT users, including employment sector, age group, median income, and daily vehicle miles traveled were reviewed to identify Southeast Michigan’s current and future trends. The project team also performed shift-share analysis using Cleveland and Kansas City data to determine the BRT-advantaged age group. The authors recommended a number of action items to attract choice riders and gratify riders who must rely on BRT, such as tax incentives, branding, guaranteed levels of service, etc. Based on the literature review and analysis of existing BRT-related data by the project team, BRT-advantaged job sectors and age groups within the Southeast Michigan region were identified. BRT will be implemented in phases. This will affect the amount, type, and timing of investments in BRT. Considering this uncertainty, the potential economic impacts as a function of type and amount of investment were discussed. It is to be noted that in order to achieve the projected results, the BRT system must be planned, designed, and implemented based on the unique attributes of the Southeast Michigan region rather than by copying a system that has achieved success in another region

Estimating commuter rail demand to Kendall Square along the Grand Junction Corridor

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 113-114).Since acquiring the Grand Junction Railroad in June 2010 from CSX, the Massachusetts Bay Transit Authority (MBTA) has explored the possibility of using the line for commuter rail service. In addition the Grand Junction right-of-way has been the subject of other proposals, including a multi-use path by the City of Cambridge and a Bus Rapid Transit (BRT) line as part of the MBTA's Urban Ring study. In September of 2010, our team was asked to examine the possibility of adding passenger service along the Grand Junction Railroad in Cambridge, MA. This new service would allow the current Worcester/Framingham commuter rail line to serve both North and South stations. In response, we performed an analysis based on the existing conditions of the railroad and projected future growth of the Kendall Square business area. To perform this analysis a demand model was developed using the 2010 MIT Transportation Survey and 2000 Census Bureau Journey to Work data. The demand model was used to forecast ridership on the Grand Junction Railroad, for multiple alternatives which included the addition of a commuter rail station at Kendall Square, use of diesel multiple units to improve frequency, and a short high frequency route starting at Auburndale. The results of the analysis demonstrate that a high frequency service from Worcester along the Grand Junction Corridor attracts the most riders, approximately 1,800 peak morning commuters. With the Auburndale service and lower frequency Worcester trains having moderate ridership estimates. This forecast combined four types of riders: new inbound riders to Kendall Square, redirected inbound riders to Kendall Square, new inbound riders to Boston, and redirected reverse riders from North Station. In addition to demonstrating how the demand model and the rider survey dataset were developed this report provides a framework for a more detailed study into potential uses for passenger service along the Grand Junction Railroad.by Adam Bockelie and James Dohm.M.Eng

An elastic demand schedule-based multimodal assignment model for the simulation of high speed rail (HSR) systems

HSR represents the future of medium-haul intercity transport. In fact, a number of HSR projects are being developed all over the world despite the financial and economic crisis. Such large investments require reliable demand forecasting models to develop solid business plans aiming at optimizing the fares structure and the timetables (operational level) and, on the other hand, at exploring opportunities for new businesses in the long period (strategic level). In this paper we present a model system developed to forecast the national passenger demand for different macroeconomic, transport supply, and HSR market scenarios. The core of the model is based on the simulation of the competition between transportation modes (i.e. air, auto, rail), railways services (intercity vs. High Speed Rail) and HSR operators using an explicit representation of the timetables of all competing modes\services (schedule-based assignment). This requires, in turn, a diachronic network representation of the transport supply for scheduled services and a nested logit model of mode, service, operator, and run choice. To authors’ knowledge this represents the first case of elastic demand, schedule-based assignment model at national scale to forecast HSR demand. The overall modeling framework has been calibrated based on extensive traffic counts and mixed RP-SP interviews gathered between 2009 and 2011, on the Italian multimodal transportation system. The results of the models estimation are presented, and, some applications to test HSR service options (i.e. fares and timetable) of a new operator entering the HSR market and competing with the national incumbent are discussed

Passenger Demand Forecasting for New Rail Services – Manual of Advice

This Seminar reports on a research grant undertaken for the Economic and Social Research Council that commenced in January 1989 and is due to be completed in December 1991. The aims of the project are: 1. To develop forecasting approaches that are suitable for predicting the demand of new rail services. 2. To assess the accuracy of these approaches in terms of their predictions of current and future patronage. 3. By comparing the relative costs and accuracy of a range of forecasting approaches, the most appropriate methods for different levels of investment will be determined 4. To produce a manual of advice

Full Issue 14(4)

il saggio esamina compiutamente la disciplina dell'art. 19 d.lgs. n. 5/200

OPTIMIZATION OF STATION LOCATIONS AND TRACK ALIGNMENTS FOR RAIL TRANSIT LINES

Designing urban rail transit systems is a complex problem, which involves the determination of station locations, track geometry, right-of-way type, and various other system characteristics. The existing studies overlook the complex interactions between railway alignments and station locations in a practical design process. This study proposes a comprehensive methodology that helps transit planners to concurrently optimize station locations and track alignments for an urban rail transit line. The modeling framework resolves the essential trade-off between an economically efficient system with low initial and operation cost and an effective system that provides convenient service for the public. The proposed method accounts for various geometric requirements and real-world design constraints for track alignment and stations plans. This method integrates a genetic algorithm (GA) for optimization with comprehensive evaluation of various important measures of effectiveness based on processing Geographical Information System (GIS) data. The base model designs the track alignment through a sequence of preset stations. Detailed assumptions and formulations are presented for geometric requirements, design constraints, and evaluation criteria. Three extensions of the base model are proposed. The first extension explicitly incorporates vehicle dynamics in the design of track alignments, with the objective of better balancing the initial construction cost with the operation and user costs recurring throughout the system's life cycle. In the second extension, an integrated optimization model of rail transit station locations and track alignment is formulated for situations in which the locations of major stations are not preset. The concurrent optimization model searches through additional decision variables for station locations and station types, estimate rail transit demand, and incorporates demand and station cost in the evaluation framework. The third extension considers the existing road network when selecting sections of the alignment. Special algorithms are developed to allow the optimized alignment to take advantage of links in an existing network for construction cost reduction, and to account for disturbances of roadway traffic at highway/rail crossings. Numerical results show that these extensions have significantly enhanced the applicability of the proposed optimization methodology in concurrently selecting rail transit station locations and generating track alignment