Mixed traffic driver behavioral modeling at urban merge section: an experimental study

ABSTRACT

In this study, the relation between macroscopic parameters (speed, flow, density, occupancy) and microscopic parameters (lateral clearance, average gap, space headway, lateral movement duration, overtaking time, overtaking distance, relative speed) is evaluated by considering vehicle-type-dependent factor using the trajectory data collected at a five-lane urban merge and non-merge sections in Malaysia. Traffic data extractor software is utilized to extract the flow, speed, and trajectory data of the vehicles at both the merge and non-merge sections of urban highway. Both SPSS software and MATLAB software were used to conduct statistical and numerical modeling of the extracted field data. The results show a significant variation in vehicle-type dependant driving behaviors at merge and non-merge section. These parameters are useful in the development of simulation models for the merging part on a multi-lane urban highway. The findings are also useful for estimating the potential collisions under mixed traffic conditions in road safety management.

KEYWORDS:

• Mixed traffic
• vehicle-type
• driving behavior
• dynamic parameters
• merge sections
• lateral movement
• overtaking behavior

Acknowledgments

This work was partially sponsored by Taylor’s University Flagship Research Grant TUFR/2017/001/05. The author is thankful to the Taylor’s University for funding scholarship during this research work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was sponsored by Taylor’s University Post-Graduate Research Scholarship;Taylor’s University Flagship Research Grant [TUFR/2017/001/05];