Modelling of vehicle interaction behavior during discretionary lane-changing preparation process on freeway

In order to increase the accuracy of microscopic traffic flow simulation,two acceleration models are presented to simulate car-following behaviors of the lane-changing vehicle and following putative vehicle during the discretionary lanechanging preparation( DLCP) process, respectively. The proposed acceleration models can reflect vehicle interaction characteristics. Samples used for describing the starting point and the ending point of DLCP are extracted from a real NGSIM vehicle trajectory data set. The acceleration model for a lanechanging vehicle is supposed to be a linear acceleration model.The acceleration model for the following putative vehicle is constructed by referring to the optimal velocity model,in which optimal velocity is defined as a linear function of the velocity of putative leading vehicle. Similar calibration,a hypothesis test and parameter sensitivity analysis were conducted on the acceleration model of the lane-changing vehicle and following putative vehicle,respectively. The validation results of the two proposed models suggest that the training and testing errors are acceptable compared with similar works on calibrations for car following models. The parameter sensitivity analysis shows that the subtle observed error does not lead to severe variations of car-following behaviors of the lane-changing vehicle and following putative vehicle.

Evaluation of High-Speed Track Quality Using Dynamic Simulation of Vehicle-Track Interaction

Track quality is a determinant factor for evaluating the overall performance of vehicle track interaction with respect to safety, ride quality and maintenance. Important parameters specifying the general quality of the track include track geometry (undamped) and track stiffness (damped), which can be evaluated by measurements taken along with track sections. A new co-simulation model based on Finite Element Method (FEM) and Multi Body Simulation (MBS) is built for the detailed description of track quality and its contribution to vehicle track interaction without simplifying the track structure as interconnected single elements. The simulation models and tools have been validated with the help of measured track geometry, track stiffness and dynamic wheel rail forces along the track sections of high speed lines. A comparative study between high speed lines using conventional ballasted track and ballastless track showed a significantly better quality in ballastless track sections. The dynamic forces which were determined by simulations and verified by measurements along the ballastless track section were comparatively less than the specified limits by German regulations for ballastless track design. Lower levels of dynamic forces can be utilized for optimization of track design and installation procedures with respect to lower initial costs.

Smartphone-based bridge frequency identification using vehicle contact-point response

Bridge frequency(BF)identification using the vehicle scanning method has attracted considerable attention during the last two decades.However,most previous studies have adopted unrealistic vehicle models,thus finding limited practical applications.This study proposes a smartphone-based BF identification method that uses the contact-point acceleration response of a four degree-of-freedom vehicle model.The said response can be inferred from the vehicle body response measured by a smartphone.For realizing practical applications,this method is incorporated into a self-developed smartphone app to obtain data smoothly and identify BFs in a timely manner.Numerical and experimental investigations are performed to verify the effectiveness of the proposed method.In particular,the robustness of this method is investigated numerically against various factors,including the vehicle speed,bridge span,road roughness,and bridge type.Furthermore,laboratory calibration tests are performed to investigate the accuracy of the smartphone gyroscope in measuring the angular velocity,where anomalous data are detected and eliminated.Laboratory experiment results for a simply supported bridge indicate that the proposed method can be used to identify the first two BFs with acceptable accuracy.

Feature mapping and state estimation for highly automated vehicles

The past decade has witnessed an acceleration of autonomous vehicle research and development,with technological advances contributed by academia,government,and the industrial and consumer sectors.These advancements hold the potential to improve society by enhancing transportation safety and throughput,where decreased congestion saves time and reduces vehicle emissions.Two of the key technologies to enable vehicle infrastructure interaction,advanced traffic management,and automated vehicles are automated roadway mapping and reliable vehicle state estimation.In this paper,we present an overview and new methods for the problems automated roadway mapping plus a discussion of the extension of these methods to the problem of vehicle state estimation.Results from the application of these methods to feature mapping and state estimation are presented.

Application of the Point-Descriptor-Precedence representation for micro-scale traffic analysis at a non-signalized T-junction

An intersection of two or more roads poses a risk for potential conflicts among vehicles.Often the reasons triggering such conflicts are not clear,as they might be too subtle for the human eye.The environment also plays a part in understanding where,when,and why a particular vehicle interaction has occurred in a certain way.Therefore,it is of paramount importance to dive deeper into the vehicle interaction at a micro-scale within the embedded geographical environment,particularly at the intersections.This would in turn assist in evaluating the association of vehicle interactions with conflict risks and near-miss accidents.Moreover,detection of such micro traffic interactions could also be used to improvise the complexity of the already established transport infrastructure.Conversely,traffic at intersections has been explored mainly for flow estimation,capacity and width measurements,and traffic congestion,etc.,whereas the detection of micro-scale traffic interactions at intersections remains relatively under-explored.In this paper,we present a novel approach to retrieve and represent micro-scale traffic movement interactions at a non-signalized T-junction by extending a recently introduced qualitative spatiotemporal Point-Descriptor-Precedence(PDP)representation.We study how the PDP representation offers a fine solution to study the interaction of traffic flows at intersections.This permits tracking the micro-movement of vehicles in much finer detail,which is used later to retrieve movement patterns from a motion dataset.Unlike conventional approaches,we start our approach with the actual movements before modeling the static intersection environment.Additionally,with the aid of illustrative examples,we discuss how the length,width,and speed of the vehicles can be exploited in our approach to detect specific patterns more accurately.Additionally,we address the potential benefits of our approach for traffic safety assessment and how it can be extended to a network of intersections using different transport modes.