Analysis of traffic flow due to lane changes by heavy vehicles

Zuniar Ayu Permata Sari, Nahry, Gari Mauramdha

Research output: Contribution to journalConference articlepeer-review


The transportation of goods via heavy vehicles (HV) plays a crucial role in urban economics. However, the operational and physical characteristics of these vehicles negatively impact traffic flow, leading to reduced speeds and increased congestion. This study examines the influence of HV lane changes on average traffic speed by implementing diverse lane change intensities and alternative strategies that restrict HV to specific lanes, narrowing their lane-changing space. Five HV classes based on axle count were analyzed using Vissim traffic simulation software on a 600 m JORR toll road segment. Three strategies were assessed across various scenarios, with differing HV composition percentages. Results show that HV lane changes, simulated using Vissim, significantly affect average traffic speed. Comparing high and low-intensity lane changes revealed an approximately 12% speed increase. Additionally, every 5% increment in HV composition led to an average 3% traffic speed reduction. In high-density conditions for every 5% increase in the composition of HV from high-intensity compared to medium and low-intensity lane changes, the average speed of traffic flow increases by 4% and 8% in low-density conditions. This research highlights the importance of enforcing designated lane usage for HV on toll roads to enhance traffic flow performance.

Original languageEnglish
Article number012026
JournalIOP Conference Series: Earth and Environmental Science
Issue number1
Publication statusPublished - 2024
Event4th International Symposium on Transportation Studies in Developing Countries, ISTSDC 2023 - Bandung, Indonesia
Duration: 11 Nov 202312 Nov 2023


  • heavy vehicles
  • highways
  • lane changes
  • speed average
  • vissim


Dive into the research topics of 'Analysis of traffic flow due to lane changes by heavy vehicles'. Together they form a unique fingerprint.

Cite this