This article analyzes the scheduling protocol for basic safety messages standardized in the SAE J2945/1 and presents large-scale scalability results obtained from a high-fidelity simulation platform. The presented results demonstrate the protocol’s efficacy to address the scalability issues in vehicle-to-vehicle communication. By employing a distributed opportunistic approach, the SAE J2945/1 congestion control algorithm keeps the overall offered channel load within an optimal operating range, while meeting the minimum tracking requirements set forth by upper-layer applications. The scheduling protocol allows transmission of event-triggered and vehicle-dynamics driven messages that further the situational awareness in cooperative vehicle-to-vehicle communications. The validation results are evaluated using position tracking error as the main performance measure, with age of communicated information as the supporting evaluation measure of the congestion control algorithm. In addition, we examine the optimality of the default settings of the SAE J2915/1 congestion control algorithm parameters. Comprehensive analysis and trade-off study of the control parameters reveal some areas of improvement to further the algorithm’s efficacy.

Modern vehicles are equipped with more and more sophisticated computer modules, which need to periodically download files from the cloud, such as security certificates, digital maps, system firmwares, etc. Collaborative content distribution utilizes V2V communication to distribute large files across the vehicular networks. It has the potential to significantly reduce the cost of cellular-based communication such as 4G LTE. In this report, we have conducted a simulation study to verify the feasibility of a hybrid cellular and V2V collaborative content distribution network. In our simulation, a small portion of the simulated vehicles download the file directly from the cloud via cellular communication, while other vehicles receive the file via collaborative V2V communications. Our simulation results show that, with only 1% of vehicles enabled with cellular communication, it takes less than 24 hours to distribute a file to 90% of the vehicles in a metropolitan area, and around 48 to 72 hours to distribute to 99%. The results are very promising for many delay-tolerant content distribution applications in vehicular networks.

Cooperative vehicle safety (CVS) systems operate based on broadcast of vehicle position and safety information to neighboring cars. The communication medium of CVS is a vehicular ad-hoc network. One of the main challenges in large scale deployment of CVS systems is the issue of scalability. To address the scalability problem, several congestion control methods have been proposed and are currently under field study. These algorithms adapt transmission rate and power based on network measures such as channel busy ratio. We examine two such algorithms and study their dynamic behavior in time and space to evaluate stability (in time) and fairness (in space) properties of these algorithms. We present stability conditions and evaluate stability and fairness of the algorithms through simulation experiments. Results show that there is a trade-off between fast convergence, temporal stability and spatial fairness. The proper ranges of parameters for achieving stability are presented for the discussed algorithms. Stability is verified for all typical highway density cases for static traffic as well as real scenarios. Fairness is shown to be naturally achieved for some algorithms and its analysis is under study in another work of us. Under the same conditions other algorithms may have problem to maintain fairness in space. We have shown that this can be resolved by a distributed measurement of CBR and is verified.

Scalability is one of the main challenges of cooperative vehicle safety (CVS) systems. In this paper, we describe a demonstration of the scalability solution that we have developed for CVS. The solution is an adaptive communication scheme for safety messages. The demo comprises of a demonstration of the rate control algorithm using recorded vehicle trajectories, and a live demonstration of the power control scheme using emulated interference. We show that the proposed algorithms are able to deliver considerably better performance than the baseline solution for CVS. The demonstration will use several DSRC units as well as visualization and simulation software for visualizing the network dynamics.

We propose an intervehicle communication framework for the cooperative active safety system (CASS) whose operation is based on the dissemination of each vehicle's state information through a wireless network. Such a CASS requires each subject vehicle to be aware of its surroundings, particularly of the motion and position of other vehicles in its proximity. In this paper, we assume that all vehicles are equipped with onboard communication devices. In such situations, the wireless channel is simultaneously shared by a large number of vehicles, and one of the most difficult challenges in designing CASS is to maintain real-time tracking accuracy of neighboring vehicles while avoiding network congestion and failure. To address this issue, we analyze the problem that multiple scalar linear time-invariant dynamical systems track each other over a multiaccess channel, and then, we propose a rate adaptation algorithm to distributively control the self-information broadcast behavior of each vehicle. The proposed algorithm uses a closed-loop control concept and accounts for the lossy channel. Simulation results show that, if the message generation rate is dynamically adjusted in an on-demand fashion, more accurate and robust tracking performance can be achieved under various traffic conditions.

IEEE 802.11p-based Dedicated Short Range Communications (DSRC) is considered a promising wireless technology for enhancing transportation safety and improving highway efficiency. Here, using a large set of empirical measurement data taken in a rich variety of realistic driving environments, we attempt to characterize communication properties of DSRC as well as to analyze the causes of communication loss. Specifically, from a perspective of vehicular network engineers, the fundamental characteristic of DSRC communications is Packet Delivery Ratio (PDR). We investigate the impact of both uncontrollable environmental factors and controllable radio parameters on DSRC characteristics. Moreover, we also examine temporal correlation, spatial correlation and symmetric correlation of DSRC characteristics under realistic vehicular environments.

Cooperative vehicle safety (CVS) systems rely on vehicular ad-hoc networks operating in broadcast mode to deliver vehicle tracking and safety information to neighboring cars. This information is used to enable collision avoidance and warning systems. One of the main challenges of the eventual large scale deployment of such systems is network congestion, which could critically degrade the quality of a CVS system. In this paper, we present a method for congestion monitoring and control based on limited feedback from the network. We study the relationship between channel occupancy, as a readily available feedback measure, controllable network parameters, and network performance. We describe a performance measure relevant to CVS systems and present a congestion control method, based on channel occupancy measurements, that robustly maintains the system performance near optimal operation points. We examine the convergence properties of the congestion control algorithm and provide guidelines for the design of such systems based on network and traffic density conditions. Through simulation experiments we show significant gains in performance when closed loop congestion control methods are applied.

Vehicular ad-hoc networks (VANETs) play a critical role in enabling highway active safety applications such as collision warning and vehicle tracking. The most pressing challenge in enabling such applications is to maximize the amount of disseminated vehicle state information while avoiding network congestion. In this paper, we explore the structure of VANET tracking problem and propose an adaptive rate control algorithm based on network condition and tracking error. Proposed algorithm uses a closed-loop control concept and accounts for the lossy channel. This algorithm is shown to achieve better tracking performance than existing solutions. We first analyze the algorithm behavior in small scale Matlab simulations with bounded dynamical systems and then evaluate its performance using OPNET simulations with realistic vehicle trajectories from a microscopic traffic simulator (SHIFT).

The success of VANET safety mechanisms, e.g. pre-crash warning and collaborative collision avoidance, relies on good proximity-awareness of each subject vehicle. Prior analysis shows that a self-information dissemination control on each car, which adapts communication rate based on estimation error and channel congestion, can achieve higher tracking accuracy than others in a multi-access channel. In this paper, we extensively evaluate the robustness of three communication policies under different highway traffics. The worst case scenario, in terms of tracking accuracy, is identified to be a bidirectional highway with one direction congested and another direction being free flowing. Our proposed algorithms are shown to be robust and achieve much better tracking performance than 100-ms beaconing suggested by.

The dedicated short range communication (DSRC) standard (also known as IEEE 802.11p) can be used to enable a number of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless radio communication based active safety and telematics applications. In this paper, we briefly document various experimental measurement scenarios and characterize performance of the DSRC standard based radio modules in ldr Additive White Gaussian Noise (AWGN) wireless channel ldr Line-of-sight, no-vehicle-traffic, street road environment ldr Line-of-sight, parking lot environment with moderate-to- dense (surrounding) vehicle density ldr Line-of-sight, freeway environment with low-to-moderate (surrounding) vehicle density The wireless channel models, derived from performance statistics for above mentioned experimental measurement environments, have been incorporated into a DSRC wireless network simulator, and are being used to quantitatively characterize the large-scale network performances (and functional feasibilities) of several V2V, DSRC wireless communication standard based active safety and telematics applications.

Presents a navigation algorithm, which integrates a virtual obstacle concept with a potential-field-based method to manoeuvre cylindrical mobile robots in unknown or unstructured environments. This study focuses on the real-time feature of the navigation algorithm for fast moving mobile robots. We mainly consider the potential-field method in conjunction with virtual obstacle concept as the basis of our navigation algorithm. Simulation and experiments of our algorithm shows good performance and ability to overcome the local minimum problem associated with potential field methods.

A neural network controller for constrained robot manipulators is presented. A feedforward neural network is used to adaptively compensate for the uncertainties in the robot dynamics. Training signals are proposed for the feedforward neural network controller. The neural network weights are tuned online, with no online learning phase required. It is shown that the controller is able to deal with the uncertainties of the robot which include modelled undertainties (dynamic parameter uncertainties, etc.) as well as unmodelled uncertainties (frictions, etc.). The suggested controller is simple in structure and can be implemented easily. The controller has the proportional-integral (PI) type force feedback control structure with a low proportional force feedback gain. Detailed experimental results show the effectiveness of the proposed controller.

Output redefinition is proposed for a flexible-link robot so that the transfer function of the system is minimum phase and this facilitates the design of trajectory tracking controllers. We show that the zero-dynamics is exponentially stable with the newly defined output function. Asymptotic tracking of step, linear and second order polynomial trajectories are achieved using controllers designed based on this new technique and the link vibrations are damped out significantly. The unique feature of the controller design technique is that the poles of the zero-dynamics can be placed at any desired locations in the left half of the s-plane. This enables us to suppress undesirable link vibrations well while the robot tip tracks a prescribed tip-trajectory.

Controller design for multi-link flexible robots taking into consideration control input constraints is presented. The control law is obtained as a solution that minimizes a certain performance index. A result on quadratic programming is used to synthesize the controller and the controller can be implemented online. The feedback controller guarantees that the control input constraints are not violated while joint-angle regulation and vibration damping are achieved. Local asymptotic stability of the closed-loop system is shown. Simulation results of a two-link flexible robot are presented in order to demonstrate the feasibility and good performance of the controller.

Command shaping is an important method to reduce vibration in flexible link robots. This paper presents a very simple rest-to-rest motion control command which eliminates multiple mode residual vibration in a flexible link robot in finite time. The command is constructed by solving linear equations. The finite time duration in which the desired motion of the joint angle is achieved along with elimination of the residual vibration can be arbitrarily specified, which offers the option for trade-offs among various considerations. The necessary conditions for using the command as a reference input for the joint angle in a closed-loop configuration (using a PD controller) are also discussed.

The authors consider the problem of determining the displacement (position and orientation) and the velocity (linear and angular) of a rigid body handled by a three-fingered robot hand with frictional point contact. Direct measurement of configuration and velocity of the grasped object is difficult in practice. It is well known that the displacement of the rigid body is completely specified by the initial and final positions of three noncolinear points fixed on the object. Similarly, the instantaneous velocity of the rigid body can be determined from the linear velocity of three noncolinear points fixed on the body. Previously developed algorithms are computationally involved by the need to compute several trigonometric functions or matrix inverses. The authors present alternate computationally efficient algorithms for determining the displacement and the velocity of an object handled by a three-fingered robot hand.

A feedback control problem for regulation of contact force and position in constrained robot systems is considered. The nonlinear differential-algebraic equations which describe the dynamics of a constrained robot system are linearized about a constrained equilibrium. A method of obtaining an equivalent state realization for the resulting linear differential-algebraic equations is developed. This method is numerically efficient since it is based on a singular value decomposition. A linear quadratic optimal control problem associated with the linearized differential-algebraic equations is solved. The resulting linear feedback control law guarantees good regulation of both contact force and position of the constrained robot. Since the method is based on the linearization of the nonlinear differential-algebraic equations, it is valid only in a neighborhood about the point of linearization. Two robot examples are considered in order to illustrate the proposed method.>