Modeling the impact of lane-changing's anticipation on car-following behavior

Lane-changing (LC) in congested traffic has been identified as a trigger for the sudden deceleration behavior of the new follower in the target lane, leading to severe traffic disturbances. Thus, investigating the response of the new follower to an LC maneuver is an important research topic in the literature. To date, numerous efforts have...

Stability Analysis of Mixed Traffic Flow using Car-Following Models on Trajectory Data

There is an increase in the need to understand traffic flow behavior through multiple fronts, especially in developing countries like India, where a high degree of heterogeneity, non-lane-discipline, and non-compliance to traffic rules prevail in the road sections. As a result, it can impact the stability of the traffic stream. Four car...

Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models

The Dutch governmental organisation Rijkswaterstaat contributes to the smooth and safe flow of traffic, as both traffic jams and accidents cost society large amounts of money each day. Roads are designed for the current traffic composition. Due to the promotion of Adaptive Cruise Control (ACC) systems, utilisation of these systems is expected to...

A geometric Brownian motion car-following model: towards a better understanding of capacity drop

Traffic flow downstream of the congestion is generally lower than the pre-queue capacity. This phenomenon is called the capacity drop. Recent empirical observations show a positive relationship between the speed in congestion and the queue discharge rate. Literature indicates that variations in driver behaviors can account for the capacity drop....

Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection

This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine...

Optimization of traffic flow at freeway sags by controlling the acceleration of vehicles equipped with in-car systems

Sags are bottlenecks in freeway networks. According to previous research, the main cause is that most drivers do not accelerate enough at sags. Consequently, they keep longer headways than expected given their speed, which leads to congestion in high demand conditions. Nowadays, there is growing interest in the development of traffic control...

Identification and modeling of behavioral changes in longitudinal driving through vehicle-based signals

Vehicles are an integral part of everyday life. Since drivers depend on these transport means to perform their activities, it is important to investigate how they behave inside the vehicles in order to facilitate their task and avoid any undesired consequences (e.g. congestion, accidents). Different components of the driving environment have an...

Bayesian Data Assimilation for Improved Modeling of Road Traffic

This thesis deals with the optimal use of existing models that predict certain phenomena of the road traffic system. Such models are extensively used in Advanced Traffic Information Systems (ATIS), Dynamic Traffic Management (DTM) or Model Predictive Control (MPC) approaches in order to improve the traffic system. As road traffic is the result...

Bayesian calibration of car-following models

Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model parameter are converted to posterior...