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Abstract
This paper presents design of a vehicle stop-and-go cruise control strategy based on analyzed results of the manual driving data. Human drivers driving characteristics have been investigated using vehicle driving data obtained from 100 participants on low speed urban traffic ways. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would feel comfortable to the human driver under low speed stop-and-go driving conditions. Vehicle following characteristics of the cruise controlled vehicle have been investigated using a validated vehicle simulator and real driving radar sensor data.
This paper describes the speed control of a remotely operated multi-wheel motor-driven electric vehicle that can be effectively utilized not only on paved roads but also on unpaved roads or obstacles. The proposed speed control algorithm consists of an upper-level control module and two lower-level control modules. The upper-level module generates acceleration commands and the weighting factor, allowing the tractive and braking forces to intersect smoothly. Two lower-level modules generate motor torque and hydraulic brake commands, respectively. This speed controller tracks the speed commands of each axle to reduce wheel slip on unpaved roads. In addition, it uses the pitch angle of the vehicle body for mobility on slopes or obstacles. The disturbance observer is also applied to the lower-level control modules for robustness against modeling errors and frequently changing road conditions. Finally, the proposed speed control algorithm is applied to a simulation model and a six-wheel motor-driven prototype vehicle used for military purposes. Its effectiveness is verified through various scenarios, including unpaved roads and obstacles.
The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.
This paper proposes an improved virtual flexible bar algorithm for improving the trajectory tracking accuracy of the automatic vehicle following system. To achieve successful vehicle following, the algorithm mainly consists of two parts: construct the flexible bar which can fit the lead vehicle's trajectory and calculate the internal force of the flexible bar which pulls the trailing vehicle to track the trajectory. The cubic spline interpolation was applied in order to smooth the flexible bar, thus making it fit the lead vehicle's trajectory better. What's more, an adaptive trajectory tracking control was also implemented to maintain the smooth motion of the follower vehicle and make sure that the follower vehicle could carry out the commands transmitted from the controller accurately. The simulation results validate that the follower vehicle is able to trail the trajectories of the lead vehicle and maintain a safe following distance. The proposed model improves the accuracy of vehicle following because it avoids the accumulated error, as compared to the other models.
An improved virtual flexible bar algorithm which aims at improving the trajectory tracking accuracy of automatic vehicle following system is proposed in this paper. To achieve successful vehicle following, the algorithm mainly consists two parts: the flexible bar which can fit the leader vehicle's trajectory and the force acting in the flexible bar which pull the follower vehicle to track the leader's trajectory besides adjusting the velocity and acceleration of the follower according to the motion state of the leader. In order to maintain the smooth motion of the follower and make sure that the follower could carry out the commands transmitted from the controller accurately, an adaptive trajectory tracking control is also implemented. The simulated experimental results validate that the follower is able to trail the trajectories of the leader vehicle keep the error within an satisfied limits meanwhile maintaining a safe following distance.
Korea is currently experiencing a rapidly increasing distribution rate of in-vehicle display devices, such as navigation or DMB displays, owing to remarkable advances in IT. At the same time, the number of traffic accidents and traffic violations is increasing due to the distraction of drivers’ attention by such devices. In particular, in-vehicle display devices such as navigation systems temporarily distract drivers’ visual or cognitive attention when they perform a unit task. Accordingly, it is necessary to prepare adequate standards to regulate in-vehicle display devices, especially in Korea. There are few empirical studies that have employed experiments to support such regulation. In this study, an experiment was conducted using a driving simulator to establish the proper standards regarding the maximum distraction time per unit task that can be allowed without causing any disturbance in safe driving. A total of 25 participants participated in the experiment. The distraction time was controlled by asking participants to perform the two tasks at once: while participants were driving as a primary task, they performed secondary task that count the number of intersections between the start point and the arrival point displayed on the screen. The results showed that the 2.0 second condition differed from the controlled condition in the deviation in the distance from the preceding vehicle, speed, and steering wheel movement, whereas there were no differences between the controlled condition and the 1.0 or 1.5 second condition. Finally, the limitations of the study and the implications of the findings with regard to future studies and application of the Korean version of guidelines for in-vehicle display devices are discussed.
In this paper, we have investigated the effects of adaptive cruise control (ACC) vehicles in a mixture with manually-controlled (manual) vehicles. The manual vehicles are simulated by using the modified comfortable driving model, which can describe synchronized traffic flow. The phase transition probabilities from free flow to synchronized flow and from synchronized flow to jams are studied. The impact of ACC vehicles on the flow rates in free flow and synchronized flow and on the propagation velocity of the downstream front of jams are investigated. The dependence of microscopic properties of traffic flow, including the spatiotemporal patterns and the velocity distribution, is explored. Our results are expected to be useful for developing ACC systems. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007
A virtual flexible curved bar coupled with force delay algorithm is proposed for automatic vehicle following, aiming at improving the accuracy of vehicle trajectory tracking, especially when leader vehicle is accelerating or making turns. A virtual flexible curved bar with force delay has been modeled that connects the leader to the follower. The length of this virtual bar is a function of the turning radiuses of the leader vehicle. Through this model, the follower vehicle is in effect being virtually dragged by the leader through the virtual flexible curved bar. It is the virtual dragging force that makes the follower accelerate/decelerate so as to adjust its speed to match that of the leader. Finally, simulations were carried out in MATLAB. The results showed that the proposed algorithm has improved the trajectory tracking error greatly, compared to the virtual rigid straight link approach.
Entrainment and vehicle following controllers are proposed for autonomous intelligent vehicles in both non-tight and tight vehicle following maneuvers. A nonlinear vehicle model is used for designing the controllers. The proposed vehicle following controller is designed based on a constant time headway policy; whereas, the proposed entrainment controller is designed based on a k-factor headway policy. The proposed vehicle following controller not only provides local individual vehicle stability but also guarantees asymptotic platoon stability without the availability of feedforward information. Furthermore, the achieved asymptotic platoon stability is shown to be theoretically robust with respect to sensor delays. Computer simulations demonstrate the performance of the proposed controllers.
Implementation and vehicle tests of a vehicle longitudinal control algorithm for stop-and-go cruise control have been performed. The vehicle longitudinal control scheme consists of a set-speed control algorithm, a speed control algorithm, and a distance control algorithm. A desired acceleration for the vehicle for the control of vehicle-to-vehicle relative speed and clearance has been designed using linear quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. Vehicle tests have been conducted using two test vehicles. A 2000 cm3 passenger car equipped with a radar distance sensor, throttle/brake actuators and a controller has been used as a subject vehicle in the vehicle tests. A millimetre wave radar sensor has been used for distance measurement. A step motor and an electronic vacuum booster have been used for throttle/brake actuators. It has been shown that the implemented vehicle longitudinal control system can provide satisfactory performance in vehicle set-speed control and vehicle clearance control at lower speeds.
This paper demonstrates, via analysis and simulation, the feasibility of a vehicle-follower control system which maintains intervehicular spacings of 30-60 cm within platoons of automated guideway transit (AGT) vehicles. Asymptotic stability of the platoon is shown to be achievable when each vehicle references its speed to that of the platoon leader. Jerk limiting, which is regarded as essential for all AGT longitudinal controllers, is shown to be potentially destabilizing. The nonlinear effects produced by the jerk limiter are analyzed by use of describing functions, and it is demonstrated how the undesirable effects can be avoided.