Submit your paper : editorIJETjournal@gmail.com

Paper Title : CORRIDOR NETWORK ANALYSIS USING MESOSCOPIC SIMULTION SOFTWARE

ISSN : 2395-1303
Year of Publication : 2021
10.29126/23951303/IJET-V7I3P9

Authors: Pawanjay Jain, Shubhankar Tiwari, H.S. Goliya

         


Abstract
- This research paper seeks to contribute in improving the performance of selected traffic network corridor, comprising of a section of network which includes exclusive bus movement (BRTS) lanes in middle, along with normal traffic movement on either side in opposite directions. In order to improve the performance attributes, we use the mesoscopic simulation tool and signal timing design (FIXED+TSP) is done with the help of Webster’s method. BRTS has been given the priority at intersection We have compared the simulation results between existing traffic signal and calculated one. Videography traffic survey has been carried out traffic volume data has been obtained manually. Origin and Destination details are obtained with the help of INRO EMME software. With the help of EMME matrix input in mesoscopic simulation tool INRO DYNAMEQ, modelled counts are generated, which is then calibrated and validated. Efforts are made to reduce the travel time, vehicle hour delay, increase network average speed of PCU’S, BRTS bus. The corridor section constitutes of seven major intersections with a BRTS specific lane, at each intersection signal priority is given with the help of phase insert TSP mode

Reference
1. Webster, F.V. and Cobbe, B.M. (1966). Traffic Signals. Road Research Laboratory, Road Research Technical Paper No. 56, London, UK. 2. Indian Road Congress “IRC -93:1985, “Guidelines on design on installation of road traffic signals.” IRC New Delhi. 3. Indian Road Congress “I.R.C:106-1990, Guidelines for Capacity Of Urban Roads In Plain” 4. Florian, M., M. Mahut, and N. Tremblay. 2001. “A Hybrid Optimization-Mesoscopic Simulation Dynamic Traffic Assignment Model.” In ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585), 118–21. https://doi.org/10.1109/ITSC.2001.948640. 5. Gliebe, J., & Bergman, Å. (2011). “Case Study Evaluation of Dynamic Traffic Assignment Tools”. 6. J. Sloboden, J. Lewis, V. Alexiadis, Yi-Chang Chiu and Eric Nava Traffic Analysis Toolbox Volume XIV: Guidebook on the Utilization of Dynamic Traffic Assignment in Modeling, 2012. PDF. Publication #: FHWA-HOP-13-015. 7. Calvert, Simeon & Kessels, Femke & Hoogendoorn, Serge. (2018). Capacity drop through reaction times in heterogeneous traffic. Journal of Traffic and Transportation Engineering. 5. 10.1016/j.jtte.2017.07.008. 8. Wang, Yimin & He, Zhaocheng. (2019). Mesoscopic modelling and analysis of traffic flow based on stationary observations. Procedia Computer Science. 151. 800-807. 10.1016/j.procs.2019.04.109
Keywords
-