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Verma, Ashish
- Design and Administration of Activity-travel Diaries: A Case Study from Bengaluru City in India
Abstract Views :247 |
PDF Views:112
Authors
M. Manoj
1,
Ashish Verma
2
Affiliations
1 Department of Civil Engineering, Indian Institute of Science, Sustainable Transportation and Urban Planning (CiSTUP), Bengaluru 560 012, IN
2 Centre for Infrastructure, Sustainable Transportation and Urban Planning (CiSTUP), Indian Institute of Science, Bengaluru 560 012, IN
1 Department of Civil Engineering, Indian Institute of Science, Sustainable Transportation and Urban Planning (CiSTUP), Bengaluru 560 012, IN
2 Centre for Infrastructure, Sustainable Transportation and Urban Planning (CiSTUP), Indian Institute of Science, Bengaluru 560 012, IN
Source
Current Science, Vol 109, No 7 (2015), Pagination: 1264-1272Abstract
Studies on travel survey instrument design and administration in the context of Indian cities are limited despite the fact that these aspects of travel survey face unique challenges here when compared to the cities in the developed world. Here we report results of a pilot survey conducted for evaluating the performances, alternative diary formats and survey administration techniques in Bengaluru city, India. The study proposes two diary formats. 'Diary-1' is in day-planner format and is a variant of the one reported earlier in the literature. 'Diary-2' is derived as a combination of 'Diary-1' and the trip-based dairies widely applied in Indian cities. 'Face-to-face', and 'drop-off and pick-up' methods of survey administration are considered for retrieving the activitytravel information of individuals. Evidence appears to be strong that diary-2 is preferable to diary-1 for collecting the travel details of individuals. The comparison of the retrieval methods suggests that the face-toface method of instrument administration is superior to the drop-off and pick-up method in terms of higher response rates and minimum recording errors.Keywords
Activity-Travel Survey, Combined Diary Format, Design and Administration, Transportation Systems.Full Text
- Assessment of Driver Vision Functions in Relation to their Crash Involvement in India
Abstract Views :542 |
PDF Views:113
Authors
Ashish Verma
1,
Neelima Chakrabarty
2,
S. Velmurugan
2,
B. Prithvi Bhat
3,
H. D. Dinesh Kumar
1,
B. Nishanthi
4
Affiliations
1 Department of Civil Engineering, Sustainable Transportation and Urban Planning, Indian Institute of Science, Bengaluru 560 012, IN
2 Traffic Engineering and Safety Division, Central Road Research Institute, Mathura Road, New Delhi 110 025, IN
3 Central Institute of Road Transport, Pune 411 026, IN
4 Department of Civil Engineering, National Institute of Technology, Tiruchirappalli 620 015, IN
1 Department of Civil Engineering, Sustainable Transportation and Urban Planning, Indian Institute of Science, Bengaluru 560 012, IN
2 Traffic Engineering and Safety Division, Central Road Research Institute, Mathura Road, New Delhi 110 025, IN
3 Central Institute of Road Transport, Pune 411 026, IN
4 Department of Civil Engineering, National Institute of Technology, Tiruchirappalli 620 015, IN
Source
Current Science, Vol 110, No 6 (2016), Pagination: 1063-1072Abstract
Among the human factors that influence safe driving, visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the effect of visual functions of drivers in India on their road crash involvement. Experiments were conducted to assess vision functions of Indian licensed drivers belonging to various organizations, age groups and driving experience. The test results were further related to the crash involvement histories of drivers through statistical tools. A generalized linear model was developed to ascertain the influence of these traits on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision, depth perception, contrast sensitivity, acuity and phoria were found to influence their crash involvement rates. In India, there are no efficient standards and testing methods to assess the visual capabilities of drivers during their licensing process and this study highlights the need for the same.Keywords
Crash Involvement, Driver Licensing, Generalized Linear Modelling, Visual Functions.Full Text
References
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- Imputation of trip data for a docked bike-sharing system
Abstract Views :171 |
PDF Views:82
Authors
Affiliations
1 Department of Civil Engineering, Rajiv Gandhi Institute of Technology, Kottayam 686 501, IN
2 Department of Civil Engineering, Indian Institute of Science, Bengaluru 560 012, IN
3 Department of Civil Engineering, Transport Division, Universidad de Chile, CL
1 Department of Civil Engineering, Rajiv Gandhi Institute of Technology, Kottayam 686 501, IN
2 Department of Civil Engineering, Indian Institute of Science, Bengaluru 560 012, IN
3 Department of Civil Engineering, Transport Division, Universidad de Chile, CL
Source
Current Science, Vol 122, No 3 (2022), Pagination: 310-318Abstract
Mobile application-based transportation services are reshaping the urban transportation industries of both the developed and developing worlds. They generate massive amounts of data, which have the potential to provide deeper insights into urban travel activity than ever before. The bike-sharing service (BSS) market is growing at a breakneck pace with new service providers entering the arena. However, we have seen the failure of several BSS start-ups in India in recent years. All these cases have one aspect in common: user dissatisfaction because of insufficient/ineffective rebalancing approaches. The BSS operators rely on data insights to drive their policies and strategies. However, the data generated by these services are found to have several incomplete records as a result of various technical errors, like missing origin/destination. As most BSS modelling focuses on trip origin and destination, completely ignoring (or listwise deleting) trips with missing information results in the loss of valuable data that are still present in other observed variables, which include trip duration, date and time of the trip, and so on. This study proposes two methods for imputing missing data: (i) a probabilistic approach based on Bayes’ theorem, and (ii) a machine learning approach based on the k-nearest neighbor algorithm. The methodologies for their analyses are presented in detail. Data from a BSS that operated in the Indian Institute of Science campus, Bengaluru, India, are used to illustrate the proposed approaches. This is followed by a brief discussion of the results and a comparison of the performanceKeywords
Bike-sharing system, imputation, incomplete records, origin and destination, probabilistic and machine learning approaches, trip data.Full Text
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