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dc.contributor.advisorVerma, Ashish
dc.contributor.authorRahul, T M
dc.date.accessioned2017-11-16T10:02:35Z
dc.date.accessioned2018-07-31T05:41:04Z
dc.date.available2017-11-16T10:02:35Z
dc.date.available2018-07-31T05:41:04Z
dc.date.issued2017-11-16
dc.date.submitted2015
dc.identifier.urihttps://etd.iisc.ac.in/handle/2005/2767
dc.identifier.abstracthttp://etd.iisc.ac.in/static/etd/abstracts/3613/G26873 -Abs.pdfen_US
dc.description.abstractIndian cities are currently facing various transportation issues like congestion, pollution, urban inequity, high fatality rate due to accidents etc. because of an increase in the ownership of private motor vehicles and their usage. This has prompted many policy makers to search for alternate modal options that are more sustainable than motorized modes. Non Motorized Transport (NMT), which includes mainly walking and cycling in an urban context, do not produce many of the issues associated with motorized modes like congestion, pollution, fatal accidents etc. But, promotion of NMT requires a clear-cut planning strategy, with a lucid understanding of various strategies and their effect on the NMT usage. Present study tries to answer certain pertinent questions, particularly with respect to walking and cycling, which can arise while preparing a plan for promoting NMT in Indian cities. The following are the questions that the author seeks to answer in the present study. 1) Which are the areas inside a city that a planner shall target for promotion of NMT?2) Where shall a planner locate the infrastructures for NMT in these areas?3) What may be the possible impacts of providing these NMT facilities?4) What may be the possible effect of built environment factors on the choice of NMT? Providing NMT infrastructures requires knowledge of location characteristics such as the trip distance of NMT. Present study tries to elicit the existing distance characteristics of walking and cycling in terms of an acceptable trip distance. The household travel data of Bangalore city, for the year 2009, are used in the study. First, a description and a statistical analysis of the walking and cycling trip distances across the subcategories of socio-demographic and regional factors is done. Secondly, the acceptable distance is computed from the cumulative trip length distribution based on the results of the statistical analysis. The socio-demographic and regional factors used in the study include purpose, age, gender, educational level, occupational status, and motor vehicle ownership. The major results include a significant difference between the mean trip distances on foot for the subcategories of variables such as gender (z value, 4.94), whether the respondent owned a private vehicle (z value, -21.2), and whether the trip was made inside the Central Business District (CBD) (z value, -3.93). One of the major implications of this study pertains to requirement of a footpath around main activity centers like bus stations, at least up to a distance of 1385 meters (maximum value for walking as the main mode) and around the bus stops, at least up to a distance of 750 meters (maximum value for walking as the access mode). Next, the present study analyzes the influence of built environment factors –density and diversity -on the mode choice and trip distance of the residents in the Bangalore city. The built environment factors are analyzed, for their marginal effects in the presence of various socio-demographic and alternative attributes, for the two segments -respondents owning at least a personal vehicle and respondents not owning any personal vehicle. The density used is the total density, which was the sum of population density in a zone and employment density in a zone. The diversity index, which was an explainer of the land-use mixture, was set such that, when a zone with small area had employment opportunities comparable with its population, the diversity index would be high. When tested on a holdout sample other than the ones used in the estimation of the mode choice model, for the vehicle-owning group, the model estimated produced a validation accuracy of 93% and 91% respectively for two-wheelers and walking. For the vehicle non-owning group, the prediction success rate was highest for walking (97%), and lowest for public transit (84%). For the vehicle non-owning group, an increase in the density increased the trip distance (parameter values of 0.016 for total density at origin and 0.002 for total density at destination) and decreased the NMT usage (parameter values of -0.036 and 0.038 respectively for cycling and walking for total density at origin, and -0.092 and 0.073 respectively for cycling and walking for total density at destination), but for the vehicle-owning group, the inverse was true. The results for the vehicle non-owning group highlighted the requirement of a policy framework to control the employment and housing location of them in order to reduce their trip distance. In the mode choice model for the personal vehicle-owning group, the similarity between the parameters of the built environment factors across the two-wheeler and NMT reflected the need for adopting policies that would change the attitude of people towards NMT. Also, the trip distance model determined that females preferred a shorter working distance, with a parameter value -0.109 for the vehicle-owning group and -0.04 for the vehicle non-owning group, when compared with males. Lastly, the study develops a methodological framework to determine the sustainability impact on providing NMT infrastructures using a Composite Sustainability Index (CSI). More specifically, the study develops a methodological framework to determine the variation in the CSI on providing NMT -walking and cycling – infrastructure. The methodology establishes a link between the proposed NMT infrastructures and the CSI using two explanatory indicators: 1) number of motorized vehicles and 2) vehicle-kilometers travelled by the motorized modes. The main components of the framework include the estimation of a mode choice model for a study area, calculation of the explanatory indicators for the scenarios before and after providing NMT infrastructures, and determination of the sustainability impact. The proposed framework, along with the acceptable distance determined in the earlier step, is then used to determine the sustainability impact on providing NMT facilities, for a future scenario, inside the CBD of Bangalore and around the bus stops carrying trips to the CBD. Three case studies are presented with the first one considering only intra zonal (CBD) trips, the second one considering only inter zonal trips having CBD as destination, and the third one considering both above mentioned the trips. The results of all the three case studies found an increase in the CSI (0.002 for the first case study, 0.076 for the second case study, and 0.100 for the third case study) for the peak-hour trips inside the CBD, on providing NMT infrastructures. This increase showed an improvement in the sustainability. Further, for the case study 1, which consisted of high percentage of short distance trips, the major beneficiaries of the NMT infrastructures were the low-income group. There was a reduction in public transport trips, of which the main contributors were the low-income group, from 142706.2 to 96410.2.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesG26873en_US
dc.subjectNon Motorized Transportationen_US
dc.subjectUrban Transportationen_US
dc.subjectNon Motorozed Transport Planning-Indiaen_US
dc.subjectWalkingen_US
dc.subjectCyclingen_US
dc.subjectNon Motorized Infrastructure Sustainabilityen_US
dc.subjectPedestrian and Bicycle Planningen_US
dc.subjectNon Motorized Tranportation-Bangaloreen_US
dc.subjectNMT Indiaen_US
dc.subjectNon-motorized Transportationen_US
dc.subjectWalking and Cyclingen_US
dc.subjectPedestrian Travel Behaviouren_US
dc.subjectPedestrian Travel Behavioren_US
dc.subjectNon-Motorized Transporten_US
dc.subjectTransportation Policiesen_US
dc.subjectTransportation Policyen_US
dc.subject.classificationCivil Engineeringen_US
dc.titleNon Motorized Transport Planning for an Indian Cityen_US
dc.typeThesisen_US
dc.degree.namePhDen_US
dc.degree.levelDoctoralen_US
dc.degree.disciplineFaculty of Engineeringen_US


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