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Development of a model for the determination of optimal bus garage site selection
Bibliographic Section work. Viewed another way, this same percentage of those who now drive alone and park fre& ‘wouldjoin carpoolsor beginusingpublic transit for travel to work if required to pay for the parking they now receive at no charge. These estimates reflect the results of a variety of previously estimated models of travel mode choice, as well as comparisons of the behavior of similar commuters who park free and who pay for parking, and the results of imposing charges for parking formerly provided free. The major incentive for employers to provide free parkingto their employees appears to be the fact that as a fringe benefit not paid in cash, free parking escapes personal income taxation. Enforcing the reporting and taxation of its cash value, however, is a difficult and predictably unpopular approach. Instead, this research recommends several policies intended to extend the subsidy for work travel now enjoyed only by drivers, in the form of free parking,to travel by other modes.These policies promise to sign&antly increase carpool participationand publictransit use amongwork commutersat very low or no public expense.
Developmentof a Model for the Determinatbn of Optimal Bus Garage Site !3&etbn, Thomas Harold Maze, Wayne State University, Detroit, MI48202(Dissertation in the Department of Civil Engineering,MichiganState University, East Lansing,MI 48823,1982). A model is developed and demonstratedfor determining both the optimal bus garage locations and optimal assignmentof buses to those garages.The model uses a list of candidategarage sites, the transit system’sservice and operational characteristicsand the characteristicsof the regional highway system as input. As output it produces the optimal number, sixes and locations of bus garageadditionsor changes.The model considers garage operating and garage construction costs and thy costs of deadheadingand driver relief under separate operating schedulesfor morning,all-day, and evening assignments on weekdays, Sundays and Saturdays. The model developed is computationallyfeasible. Initially the problem is formulated as a discrete solutionspace fixed-charge facility location probkm. The fixed charge problem is formulated as a mixed integer program. However, because of the difliculty involved in solving a large-scale problem with a general purpose mixed-integerprogram,the problemis solved by a special purpose branch-and-boundprocess. This process utiliis an efficientsequence of classicaltransportationproblems plus a numberof easy-to-useside calculationswhich rule out a wide variety of potential computations. Consequently the model may be applied to a relatively complex system at the cost of a relatively modest amount of computer use. The model is demonstratedin the context of a Detroit metropolitan area case study. The manner in which the model may be used to include judgemental inputs and perform sensitivity analyses is also described.
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‘he h-9 ,misnand useof Olr-Boud Tra&t Surveysfor OpemtionalT&R Plan&g, Marketbg md Research,Robert Gregory Sbawcroft, 1979,UMI8013594 (Dissertation at the University of Washington,Seattle, WA98105). The central problem of this research is that of determininghow reliable and useful data from on-board transit surveys has been and may prove to be with respect to operational transit planning and analysis. Although interest and involvement in on-board surveys has been developing in the United States since the late 1960’s, as yet there has been no philosophical or scientificframework for their design,administration,use and evaluation. State-of-the-art survey practices are described and critiqued on the basis of the primary components of the survey process; (1) questionnairedesign; (2) survey administration;(3) data codii and processing;and (4) data analysis. State-of-the art practices are determined from information compiled from over 30 surveys conducted recently in cities across the country. The practices within each component of the survey process are evaluated relative to a framework of relevant criteria developed from the stated and impliedobjectives of transit surveys as well as general principles regarding the design of survey questionnaires, sampling and statistical theory, and information system concepts. A typical on-board survey consists of about 20 data items from which thousands of diierent analysis products containingmillionsof diierent classificationsof transit patrons and their trips can be produced. The utility of these products is limited by: (1) the statistical reliabilityof the data use, and (2) the ability of interested parties to obtain speci5cally desired pieces of information. While the statistical reliability of data for the system as a whole can be quite high-better than f 1.0% at a 95% confidence level-the reliability of data at the route level is often worse than f 10.0%. particularly when cluster samplingis employed. Most of the studies reviewed did not include precise purpose statements nor did they define which of the several possible survey populationswas of specificinterest prior to the design of the survey. On-b&d surveys can be the source of a great deal of information useful in operational transit planning. The statistical reliability of the data must be addressed, especially for small groups of patrons or trips, so data users can determine if it is accurate enough for the intended purposes of the investigation.The steps which a transit property can take to improve upon the reliability of the data and its use include: (1) developing a standardiid questionnaireform which adheres to the guidelines presented in the literature on survey design; (2) conducting individualsurveys on only a limited portion of a transit system-such as a set of geographically grouped routes-to make it easier to control the survey and achieve higher sampling rates; (3) establishingan on-going series of surveys directly related to service review activities to ensure the data’s timeliness;(4) providing users of the data with instruction on the survey
Developmentof a Model for the Determinatbn of Optimal Bus Garage Site !3&etbn, Thomas Harold Maze, Wayne State University, Detroit, MI48202(Dissertation in the Department of Civil Engineering,MichiganState University, East Lansing,MI 48823,1982). A model is developed and demonstratedfor determining both the optimal bus garage locations and optimal assignmentof buses to those garages.The model uses a list of candidategarage sites, the transit system’sservice and operational characteristicsand the characteristicsof the regional highway system as input. As output it produces the optimal number, sixes and locations of bus garageadditionsor changes.The model considers garage operating and garage construction costs and thy costs of deadheadingand driver relief under separate operating schedulesfor morning,all-day, and evening assignments on weekdays, Sundays and Saturdays. The model developed is computationallyfeasible. Initially the problem is formulated as a discrete solutionspace fixed-charge facility location probkm. The fixed charge problem is formulated as a mixed integer program. However, because of the difliculty involved in solving a large-scale problem with a general purpose mixed-integerprogram,the problemis solved by a special purpose branch-and-boundprocess. This process utiliis an efficientsequence of classicaltransportationproblems plus a numberof easy-to-useside calculationswhich rule out a wide variety of potential computations. Consequently the model may be applied to a relatively complex system at the cost of a relatively modest amount of computer use. The model is demonstratedin the context of a Detroit metropolitan area case study. The manner in which the model may be used to include judgemental inputs and perform sensitivity analyses is also described.
81
‘he h-9 ,misnand useof Olr-Boud Tra&t Surveysfor OpemtionalT&R Plan&g, Marketbg md Research,Robert Gregory Sbawcroft, 1979,UMI8013594 (Dissertation at the University of Washington,Seattle, WA98105). The central problem of this research is that of determininghow reliable and useful data from on-board transit surveys has been and may prove to be with respect to operational transit planning and analysis. Although interest and involvement in on-board surveys has been developing in the United States since the late 1960’s, as yet there has been no philosophical or scientificframework for their design,administration,use and evaluation. State-of-the-art survey practices are described and critiqued on the basis of the primary components of the survey process; (1) questionnairedesign; (2) survey administration;(3) data codii and processing;and (4) data analysis. State-of-the art practices are determined from information compiled from over 30 surveys conducted recently in cities across the country. The practices within each component of the survey process are evaluated relative to a framework of relevant criteria developed from the stated and impliedobjectives of transit surveys as well as general principles regarding the design of survey questionnaires, sampling and statistical theory, and information system concepts. A typical on-board survey consists of about 20 data items from which thousands of diierent analysis products containingmillionsof diierent classificationsof transit patrons and their trips can be produced. The utility of these products is limited by: (1) the statistical reliabilityof the data use, and (2) the ability of interested parties to obtain speci5cally desired pieces of information. While the statistical reliability of data for the system as a whole can be quite high-better than f 1.0% at a 95% confidence level-the reliability of data at the route level is often worse than f 10.0%. particularly when cluster samplingis employed. Most of the studies reviewed did not include precise purpose statements nor did they define which of the several possible survey populationswas of specificinterest prior to the design of the survey. On-b&d surveys can be the source of a great deal of information useful in operational transit planning. The statistical reliability of the data must be addressed, especially for small groups of patrons or trips, so data users can determine if it is accurate enough for the intended purposes of the investigation.The steps which a transit property can take to improve upon the reliability of the data and its use include: (1) developing a standardiid questionnaireform which adheres to the guidelines presented in the literature on survey design; (2) conducting individualsurveys on only a limited portion of a transit system-such as a set of geographically grouped routes-to make it easier to control the survey and achieve higher sampling rates; (3) establishingan on-going series of surveys directly related to service review activities to ensure the data’s timeliness;(4) providing users of the data with instruction on the survey