A Hybrid Submicroscopic-Microscopic Traffic Flow Simulation Framework

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Freddy Antony Mullakkal-Babu - (Author)
  • Meng Wang - , Delft University of Technology (Author)
  • Bart van Arem - (Author)
  • Barys Shyrokau - (Author)
  • Riender Happee - (Author)

Abstract

Current lane-based microscopic traffic simulators combine car-following and lane changing logic to describe the (often discrete) lateral vehicle motion on multi-lane road segments. However, the simulated lateral trajectories are physically unplausible and inside-lane behavior such as lane-keeping and curve negotiation cannot be modelled. In this work, we integrate lateral vehicle dynamics and yaw motion into a traffic simulation framework, aiming to describe lateral motion and vehicle interactions with more precision. The resulting framework consists of two coupled layers, an upper tactical level that plans maneuvers such as lane-changing; and a lower operational layer with a control module (steering and acceleration control) that operates in a closed loop with the bicycle model of vehicle dynamics. The feedback mechanism between the layers allows for dynamic trajectory re-planning. Unlike the microscopic traffic models, the proposed framework accounts for lateral vehicle dynamics and yaw motion; provides additional variables such as vehicle heading and front wheel steering angle; and is hence termed as submicroscopic. Case study results demonstrate the power of the framework to include lateral maneuvers such as curve negotiation, corrective steering, lane change abortion and fragmented lane changing. The framework was operationalized to model multi-lane traffic flow consisting of human-driven vehicles. At the macroscopic level, the traffic flow simulation can reproduce phenomena such as capacity drop. Thus the framework preserves the properties of the component models and at the same time describe the continuous 2-D planar movement of vehicles.

Details

Original languageEnglish
Article number9088249
Pages (from-to)3430-3443
Number of pages14
JournalIEEE Transactions on Intelligent Transportation Systems
Volume22
Issue number6
Publication statusPublished - Jun 2021
Peer-reviewedYes
Externally publishedYes

External IDs

Scopus 85107421742
Mendeley c8987efe-19a5-38ed-83e8-ffece719f57f

Keywords