MATEC Web Conf.
Volume 124, 20172017 6th International Conference on Transportation and Traffic Engineering (ICTTE 2017)
|Number of page(s)||5|
|Section||Modeling and Analysis of Traffic System|
|Published online||29 September 2017|
Platoon Dispersion Analysis Based on Diffusion Theory
1 Project Officer, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India
2 Former Graduate Student, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India
3 Associate Professor, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India
4 Associate Professor, Department of Civil, Construction, and Environmental Engineering, Iowa State University, Iowa, USA
Urbanization and gro wing demand for travel, causes the traffic system to work ineffectively in most urban areas leadin g to traffic congestion. Many approaches have been adopted to address this problem, one among them being the signal co-ordination. This can be achieved if the platoon of vehicles that gets discharged at one signal gets green at consecutive signals with minimal delay. However, platoons tend to get dispersed as they travel and this dispersion phenomenon should be taken into account for effective signal coordination. Reported studies in this area are from the homogeneous and lane disciplined traffic conditions. This paper analyse the platoon dispersion characteristics under heterogeneous and lane-less traffic conditions. Out of the various modeling techniques reported, the approach based on diffusion theory is used in this study. The diffusion theory based models so far assumed thedata to follow normal distribution. However, in the present study, the data was found to follow lognormal distribution and hence the implementation was carried out using lognormal distribution. The parameters of lognormal distribution were calibrated for the study condition. For comparison purpose, normal distribution was also calibrated and the results were evaluated. It was foun d that model with log normal distribution performed better in all cases than the o ne with normal distribution.
© The Authors, published by EDP Sciences, 2017
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