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...

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...

A key qualitative requirement for highway traffic models is the ability to replicate a type of traffic jam popularly referred to as a phantom jam, shock wave or stop-and-go wave. Despite over 50 years of modelling, the precise mechanisms for the generation and propagation of stop-and-go waves and the associated spatio-temporal patterns are in dispute. However, the increasing availability of emp...

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...

Stop and go traffic that leads to oscillate traffic flow frequently is observed on congestion flow. Unexpected reasons such as lane – changing maneuvers, lower speeds of leader vehicle and moving bottleneck cause stop and go traffic and amplifying delay and environment impacts. Stop and go traffic exactly can’t be modeled by traffic models, and also car following models based on kinematic flow ...

Connected and Automated Vehicles (CAV) have been rapidly developed, which, inevitably, renders that human-driven autonomous vehicles share the road. Thus, trajectory prediction is an important research topic, which helps each CAV to efficiently follow a Human-Driven Vehicle (HV). In wider scope, prediction, also, improve throughput of traffic flow enhance its stability. To realize Vehicles, car...

1 In natural traffic flow, the information from preceding vehicles determines driver behavior predominantly. 2 With the availability of connected vehicle technologies (CVT), drivers can receive information from both 3 preceding and following vehicles. This creates new opportunities for vehicle coordination and control at 4 the microscopic level based on bi-directional information. Although the ...