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A control approach for automated highway driving is proposed in this study, which can learn from human driving data, and is applied to the longitudinal trajectory of an autonomous car. Naturalistic driving data are used as samples to train the model offline. Then, the model is used online to emulate what a human driver would do by computing acceleration. This reference acceleration is tracked by a...
We consider the problem of system identification of helicopter dynamics. Helicopters are complex systems, coupling rigid body dynamics with aerodynamics, engine dynamics, vibration, and other phenomena. Resultantly, they pose a challenging system identification problem, especially when considering non-stationary flight regimes. We pose the dynamics modeling problem as direct high-dimensional regression,...
Trajectory regression, which aims to predict the travel time of arbitrary trajectories on road networks, attracts significant attention in various applications of traffic systems these years. In this paper, we tackle this problem with a multitask learning (MTL) framework. To take the temporal nature of the problem into consideration, we divide the regression problem into a set of sub-tasks of distinct...
To test the hardware or software of a strap-down inertial navigation system, or conduct a related simulation study, the flight trajectory data and the output parameters of gyroscope and accelerometer should be known in advance. And in practice a set of discrete data is often used to represent flight trajectory information. Therefore this paper proposes a new method that can produce discrete trajectory...
Prior autonomous navigation systems focused on the demonstration of the technological feasibility. But as the technology evolves, improving user experience through learning expert's or individual's driving pattern emerges as a promising research direction. As a first step toward this goal, we investigate methods to learn from human demonstrations in urban scenarios without any environmental disturbances...
This paper calibrates an interrupted traffic flow system model using the trajectory datasets provided by Next Generation SIMulation (NGSIM) program. The realistic lane changing may cut off the traffic flow into discontinuous flow, giving rise to congestion and vehicle delay. The aim of this paper is to study the car-following behaviors of drivers in real traffic scenes in which lane changing happens...
This paper presents a research effort aimed at modeling normal and safety-critical driving behavior in traffic under naturalistic driving data using agent based modeling techniques. Neuro-fuzzy reinforcement learning was used to train the agents. The developed agents were implemented in the VISSIM simulation platform and were evaluated by comparing the behavior of vehicles with and without agent behavior...
This study points out the importance of estimating the traffic service level. For the estimation, a car-following model is proposed based on the assumption that a driver tries to adjust acceleration to maximize utility instantaneously. Two types of data are applied for model verification: data from a probe car that are precise but probably biased, and data from a video camera which are not expected...
Considering basic characteristics of moving objects, like temporal, spatial, multi-dimensional, massive, the paper proposes approach to spatio-temporal data modeling for moving objects data management, which represents in the model abstract data types and processes, dynamic attributes, spatio-temporal topological relationship, and spatio-temporal operations. It also presents how to use the model for...
The use of wireless devices with accelerometers and gyroscopes to measure the movements of humans and objects is a growing area of interest. Applications range from simple activity detection to detailed full-body motion capture using networks of sensors worn on the body. A variety of algorithms have been proposed for these applications, but opportunities for accurate evaluation and comparison have...
Microscopic traffic simulation models coupled with instantaneous emission models have the potential to provide improved assessments of the environmental impact of traffic networks, management strategies and technology implementations. This paper describes a toolbox, which links the microscopic traffic flow simulator VISSIM with the instantaneous emission model PHEM (Passenger car and Heavy-duty Emission...
The control of car following is essential to its safety and its operational efficiency. For this purpose, this paper builds a linear, continuous and time-delay model of car following. And then, presents a controller based on an adaptive network fuzzy inference system (ANFIS) for the car-following collision avoidance system to adaptively control the speed of the vehicle. The relative distance and relative...
In this paper we present a software platform dedicated to the maneuverability assessment of naval units, both on surface and submerged. The suggested platform exhibits such characteristics as real-time processing of ship track and heading data, off-line processing of post-processed DGPS data for increased accuracy and real-time calculation and graphical presentation of maneuvering performance evaluation...
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