01628878

Component

With growing demand for travel, most Indian cities face problems of congestion, acute delay and pollution. There are different approaches adopted by transportation engineers and planners to address such problems. One approach is to efficiently co-ordinate the signals in a traffic network using automated methods. Such automated methods make use of knowledge of traffic's progression from an upstream signal to a downstream signal. The signal directs the movement of vehicles in groups during the release of traffic at green light that are called vehicle platoons. A very simple and accepted notion for signal coordination is that the green light should start when the platoon from the previous signal reaches the signal so that average delay is minimized. For efficient signal coordination, the effect of platoon dispersion should be taken into consideration. Among the different platoon dispersion models, the Robertson's model is widely used in automated signal co-ordination. In this paper, Robertson's model was modified to account for the heterogeneity observed in Indian traffic conditions, and an optimization approach was taken to estimate model parameters in a methodical and time-efficient way. The results from the proposed models were compared with the traditional Robertson's model that was calibrated for Indian conditions. The results showed that the performance of proposed models was almost on par with the calibrated Robertson's model. Also, the proposed models would be more apt for real time application given the traditional trial and error method of estimating the parameters that is more time consuming.

This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.

01618707

17-03975

English

15p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References; Tables

Arterial highways; Dispersion (Statistics); Programming (Mathematics); Traffic platooning; Traffic signal control systems; Vehicle mix

Chennai (India); India

Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2017 Paper #17-03975

TRIS, TRB, ATRI

Dec 8 2016 11:31AM