Skip to the main content

Original scientific paper

https://doi.org/10.7307/ptt.v38i6.3163

Traffic Flow Research – Application of the Roundabout Investigation Model (MIKR)

Mustafa Mehanović ; Department of Road Traffic, Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina
Ajdin Džananović orcid id orcid.org/0000-0002-3283-5008 ; Department of Road Traffic, Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina
Mirza Berković orcid id orcid.org/0009-0007-3348-029X ; Department of Road Traffic, Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina


Full text: english pdf 1.501 Kb

page 1303-1319

downloads: 0

cite


Abstract

Monitoring vehicle movements at roundabouts and determining their operational throughput traditionally relies on tracking individual turning movements, a process that is technically demanding, labour-intensive and often impractical for complex multi-leg roundabouts. This study proposes a simplified approach to data collection and the determination of roundabout flow parameters. Two data collection techniques were examined: simplified manual counting of vehicles at entry legs and automated licence plate recognition. For roundabout flow parameters, determining the key methodological contribution is applying the roundabout investigation model (MIKR). Model MIKR enables capacity and turning-movement estimation using only entry and exit counts, thereby substantially reducing the scope of required field observations compared with conventional trajectory-based methods. The results show that licence plate recognition can determine turning flows with an accuracy of approximately 90%. The MIKR model reliably estimates roundabout capacity without requiring vehicle trajectory tracking. These findings confirm the practical value of the MIKR approach and highlight its potential for more efficient and cost-effective traffic-flow analysis at roundabouts.

Keywords

capacity analysis; turning movement counts; data collection methods

Hrčak ID:

348579

URI

https://hrcak.srce.hr/348579

Publication date:

29.6.2026.

Visits: 0 *