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Arkatkar, Shriniwas S.
- A Comparative Study on Application of Time Series Analysis for Traffic Forecasting in India: Prospects and Limitations
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PDF Views:144
Authors
Affiliations
1 Zachry Department of Civil Engineering, Texas A&M University, College Station 77840, TX, US
2 Department of Agricultural Economics, Texas A&M University, College Station 77843, TX, US
3 Department of Civil Engineering, National Institute of Technology, Surat 395 007, IN
4 Department of Civil Engineering, Birla Institute of Technology and Science, Pilani 333 031, IN
1 Zachry Department of Civil Engineering, Texas A&M University, College Station 77840, TX, US
2 Department of Agricultural Economics, Texas A&M University, College Station 77843, TX, US
3 Department of Civil Engineering, National Institute of Technology, Surat 395 007, IN
4 Department of Civil Engineering, Birla Institute of Technology and Science, Pilani 333 031, IN
Source
Current Science, Vol 110, No 3 (2016), Pagination: 373-385Abstract
Modelling of growth trend and improvement in forecasting techniques for vehicular population has always been and will continue to be of paramount importance for any major infrastructure development initiatives in the transportation engineering sector. Although many traditional as well as some advanced methods are in vogue for this process of estimation, there has been a continuous quest for improving on the accuracy of different methods. Time-series (TS) analysis technique has been in use for short-term forecasting in the fields of finance and economics, and has been investigated here for its prospective use in traffic engineering. Towards this end, results obtained from two other traditional approaches, namely trend line analysis and econometric analysis, have also been collated, underlining the better results obtained from TS analysis. A regression model has been developed for predicting fatality rate and its results have been compared with those from TS analysis. Based on the incentive provided by reduced errors obtained from using increasing number of data points for model-building, forecasting has been done for the year 2021 using time-series modelling. With most of the datasets used and locations analysed for forecasting, the TS analysis technique has been found to be a useful tool for prediction, resulting in lower estimation errors for almost all the cases considered. It has also been inferred that the proximity of the forecasting window to the sample dataset has a noticeable effect on the accuracy of time-series forecasting, in addition to the amount of data used for analysis.Keywords
Regression Model, Time-Series Analysis, Traffic Forecasting, Transportation Engineering.Full Text
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- Analysis of the Determinants of Service Headway Variability at Tollbooths Under Mixed Traffic Scenario in Emerging Countries
Abstract Views :177 |
PDF Views:86
Authors
Yogeshwar V. Navandar
1,
Chintaman Santosh Bari
2,
Ashish Dhamaniya
2,
Shriniwas S. Arkatkar
2,
D. A. Patel
2
Affiliations
1 Department of Civil Engineering, NIT Campus P. O., Kozhikode 673 601, IN
2 Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat 395 007, IN
1 Department of Civil Engineering, NIT Campus P. O., Kozhikode 673 601, IN
2 Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat 395 007, IN
Source
Current Science, Vol 121, No 1 (2021), Pagination: 148-160Abstract
This study makes an effort to model service-headway distribution at manually operated toll plazas (MTC) under mixed traffic conditions. To identify the most suitable probability distribution among the selected candidate distributions, Kolmogorov–Smirnov, Ander-son–Darling, and chi-squared tests were performed. It was found that the generalized extreme value (GEV) was the most suited distribution for modelling service-headway distribution at tollbooths. The results show that GEV distribution parameters can capture possi-ble variations in service headway at tollbooths under MTC reasonably well. The study results can also be used for capacity and level-of-service estimation and the development of warrants for converting MTC to electronic lanes.Keywords
Generalized Extreme Value, Mixed Traffic Conditions, Probability Distribution, Service Headway, Shape Factor, Tollbooth.Full Text
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