Modeling Generalized Cost of Travel for Rural Bus Users: A Case Study

Kumar, Chanakya; Basu, Debasis; Maitra, Bhargab

doi:10.5038/2375-0901.7.2.4

Cited by 42 publications

(33 citation statements)

References 13 publications

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“…7 This corresponds to 3 INR up to a distance of 4 km, and an additional 0.31 INR per additional km. These fares were charged in Patna around 2004 (Kumar et al, 2004).…”

Section: Utility Functionmentioning

confidence: 99%

Bicycle superhighway: An environmentally sustainable policy for urban transport

Agarwal

Ziemke

Nagel

2020

Transportation Research Part A: Policy and Practice

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Bicycle is a sustainable low-carbon transport mode. However, insufficient or unplanned infrastructure leads to decrease in the share of bicycle in many cities of developing nations. In order to increase the bicycle share and to provide safer, faster and more direct routes, a bicycle superhighway is proposed for urban areas. This study identifies the potential of increase in the bicycle share. For maximum utilization of the new infrastructure, an algorithm is presented to identify the optimum number and locations of the connectors between proposed new infrastructure and existing network. Household income levels are incorporated into the decision making process of individual travellers for a better understanding of the modal shift. A real-world case study of Patna, India is chosen to show the application of the proposed superhighway. It is shown that for Patna, the bicycle share can escalate as high as 48% up from 32% by providing this kind of infrastructure. However, together with bicycles, allowing motorbikes on the superhighway limits the bicycle share to 44%. The increase in bicycle share is mainly a result of people switching from motorbike, public transport and walk to the bicycle. Further, to evaluate the benefits of the bicycle superhighway, this study first extends an emission modelling tool to estimate the time-dependent, vehicle-specific emissions under mixed traffic conditions. Allowing only bicyclists on the superhighway improves congested urban areas, reduces emissions, and increases accessibility. However, allowing motorbikes on the superhighway increases emissions significantly in the central part of the urban area and reduces accessibilities by bicycle mode to education facilities which are undesirable. This study elicits that a physically segregated high-quality bicycle superhighway will not only attract current noncyclist travellers and increase the share of the bicycle mode, but will also reduce negative transport externalities significantly.

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“…7 This corresponds to 3 INR up to a distance of 4 km, and an additional 0.31 INR per additional km. These fares were charged in Patna around 2004 (Kumar et al, 2004).…”

Section: Utility Functionmentioning

confidence: 99%

Bicycle superhighway: An environmentally sustainable policy for urban transport

Agarwal

Ziemke

Nagel

2020

Transportation Research Part A: Policy and Practice

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“…Aljarad [19] developed intercity mode choice using disaggregate transport mode choice models and found that the travel cost was high significant and had negative coefficients. Kumar, et al [20] have examined rural intercity bus services in India, to determine users' behaviours towards various features of service. As anticipated, the travel time and travel cost adversely impacted on paratransit utility.…”

Section: Model Estimation and Resultsmentioning

confidence: 99%

Forecasting Paratransit Utility by Using Multinomial Logit Model: A Case Study

Victory¹,

Ahmed²

2016

IJET

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Paratransit plays an important role in the urban passenger transportation system in the developing countries. Three cities viz. Imphal East, Imphal West and Silchar in India have been undertaken for the study. Household survey and traffic survey have been employed to collect data for the paratransit users. Modelling techniques and tools also have been used to forecast the utility of paratransit in the region. For this purpose, a Multinomial Logit Model (MNL) had been used. A total of seven variables were considered in the model estimation of which three are quantitative i.e. trip length (km), travel cost (rupees) and travel time (minutes) and four are qualitative variables i.e. reliability, comfort, road condition and convenience.

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“…They included dynamic variables (such as motions), ambient variables (such as temperature, pressure, air quality, ventilation and noise), spatial variables (such as workspace, legroom, seat shape) as well as human factors (like age and gender). Other studies have also shown that bus-operating factors such as in-vehicle time [Vovsha (2014)], passenger load [Kumar, Basu and Maitra (2004)], effects of road infrastructure [Bodini (2013)] have significant impacts on the levels of comfort experienced. Smartphones have been employed to measure dynamic factors that affect comfort in public transportation [Castellanos, Susin and Fruett (2011)].…”

Section: Related Workmentioning

confidence: 99%

Analysis of Bus Ride Comfort Using Smartphone Sensor Data

Chin¹,

Pang²,

Wang³

2019

Computers, Materials &Amp; Continua

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Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger's choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle's motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point scale and recorded at 5-second intervals. The kinematic motion characteristics obtained includes tri-axial linear accelerations, tri-axial rotational velocities, tri-axial inclinations and the latitude and longitude position of the vehicle and the updated speed. The data acquired were statistically analyzed using the Classification & Regression Tree method to correlate ride comfort with the best set of kinematic data. The results indicated that these kinematic changes captured in the smartphone can reflect the passenger ride comfort with an accuracy of about 90%. The work demonstrates that it is possible to make use of larger and readily available kinematic data to assess passenger comfort. This understanding also suggests the possibility of measuring driver behavior and performance.

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Modeling Generalized Cost of Travel for Rural Bus Users: A Case Study

Cited by 42 publications

References 13 publications

Bicycle superhighway: An environmentally sustainable policy for urban transport

Bicycle superhighway: An environmentally sustainable policy for urban transport

Forecasting Paratransit Utility by Using Multinomial Logit Model: A Case Study

Analysis of Bus Ride Comfort Using Smartphone Sensor Data

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