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Analysis on Effects of Driving Behavior on Freeway Traffic Flow: A Comparative Evaluation of Two Driver Profiles Using Two Car Following Models

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Date

2022

Author

Goncu, Sadullah
Erdagi, Ismet Goksad
Silgu, Mehmet Ali
Celikoglu, Hilmi Berk

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GONCU, Sadullah, Ismet Goksad ERDAGİ, Mehmet Ali SİLGU & Hilmi Berk CELİKOGLU. "Analysis on Effects of Driving Behavior on Freeway Traffic Flow: A Comparative Evaluation of Two Driver Profiles Using Two Car Following Models" 2022 IEEE Intelligent Vehicles Symposium (IV), (2022).

Abstract

Car-following (CF) behavior is the most abstract form of driving action and, CF behavior modeling has been one of the core aspects of traffic engineering studies for several decades. The literature about CF behavior modeling is vibrant and still evolving. Furthermore, the effect of CF models on the traffic flow performance through case studies on different traffic facilities is still being investigated. To shed light on this matter, this study presents a microsimulation-based case study considering a freeway stretch in Istanbul, Turkey, employing two different CF models, i.e., Intelligent Driver Model (IDM) and Wiedemann 99 through scenarios. Simulation of Urban Mobility (SUMO) is utilized as the microsimulation environment. Both CF models are calibrated according to the measurements. Scenarios for the comparative evaluation are setup based on the questions "What if German drivers used this freeway stretch? How much would the traffic flow performance change?" Using different case studies conducted in German Freeways on the literature, simulation model parameters are obtained for both models and, simulation analyses are performed. Traffic flow performances are evaluated based on the selected performance measures, such as throughput and total travel time. According to the findings, it is seen that results differ significantly between scenarios. We elaborate on the differences obtained and discuss the implications on different scenarios which are handled through different CF models.

Source

2022 IEEE Intelligent Vehicles Symposium (IV)

URI

https://hdl.handle.net/11352/4160

Collections

  • İnşaat Mühendisliği Bölümü [101]
  • Scopus İndeksli Yayınlar / Scopus Indexed Publications [432]
  • WOS İndeksli Yayınlar / WOS Indexed Publications [405]



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