This paper is to investigate lane-wise flow-density (or equivalently speed-density) relationship which is generally called Fundamental Diagram (FD) over a stretch of homogeneous freeway section using the microscopic NGSIM data (Alexiadis, 2004). Particularly, it investigates how a homogenous traffic breakdown through data analysis and modeling. The breakdown of a homogenous traffic is understoo...

Traffic control requires looking at traffic models of all types in finer details. This paper is to investigate lane-wise flow-density (or equivalently speed-density) relationship which is traditionally called Fundamental Diagram (FD) over a stretch of homogeneous freeway section using the microscopic NGSIM data. Particularly, it investigates how a homogenous traffic further drop (breakdown) thr...

The NGSIM trajectory data sets provide longitudinal and lateral positional information for all vehicles in certain spatiotemporal regions. Velocity and acceleration information cannot be extracted directly since the noise in the NGSIM positional information is greatly increased by the necessary numerical differentiations. We propose a smoothing algorithm for positions, velocities and accelerati...

As a popular research field, autonomous driving may offer great benefits for human society. To achieve that, current studies often applied machine learning methods like reinforcement to enable an agent interact and learn in stimulating environment. However, most simulators lack realistic traffic which cause deficiency interaction. The present study adopted the SMARTS platform create simulator t...

The present work introduced a framework of developing comprehensive extended vehicular trajectory data under heterogeneous non-lane-based traffic conditions like the NGSIM datasets in United States. Due to absence automation and instrumentation, even lack sensor deployment on roads economies India, it is more challenging study driver behavior. A new stitching-based algorithm was used for databa...