Information fusion method of INS/GPS navigation system based on filtering technology is a research focus at present. In order to improve the precision of navigation information, a navigation technology based on Adaptive Kalman Filter with attenuation factor is proposed to restrain noise in this paper. The algorithm continuously updates the measurement noise variance and processes noise variance of the system by collecting the estimated and measured values, and this method can suppress white noise. Because a measured value closer to the current time would more accurately reflect the characteristics of the noise, an attenuation factor is introduced to increase the weight of the current value, in order to deal with the noise variance caused by environment disturbance. To validate the effectiveness of the proposed algorithm, a series of road tests are carried out in urban environment. The GPS and IMU data of the experiments are collected and processed by dSPACE and MATLAB/Simulink. Based on the test results, the accuracy of the proposed algorithm is 20% higher than that of a traditional adaptive Kalman filter. It also shows that the precision of the integrated navigation can be improved due to the reduction of the influence of environment noise.

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Vehicle driving safety is influenced by many factors, including drivers, vehicles, and road environments. The interactions among them are quite complex. Consequently, existing methods that evaluate driving safety perform inadequately because they only consider limited factors and their interactions. As such, it is difficult for kinematics-based and dynamics-based vehicle driving safety assistant systems to adapt to increasingly complex traffic environments. In this paper, we propose a new concept, i.e., the driving safety field. The concept makes use of field theory to represent risk factors owing to drivers, vehicles, road conditions, and other traffic factors. A unified model of the driving safety field is constructed, which includes the following three parts: 1) a potential field, which is determined by nonmoving objects on the roads, such as a stopped vehicle; 2) a kinetic field, which is determined by the moving objects on roads, such as vehicles and pedestrians; and 3) a behavior field, which is determined by the individual characteristics of drivers. Moreover, the applications of the model are proposed, and its application to a typical carfollowing scenario is illustrated, which evaluates the risks caused by multiple traffic factors. The driving safety field can reveal driver-vehicle-road interactions and their influences on driving safety, as well as predict driving safety trends owing to dynamic changes. In addition, the model can provide a new foundation for establishing driving safety measures and active vehicle control under complex traffic environments.

In this paper, traffic-aware sleeping control (SC) and power matching (PM) of a single base station (BS) in cellular networks are studied. The objective is to find the sleeping control and power matching configurations that achieve the Pareto optimal tradeoff between total power consumption and average delay. Two types of sleeping control schemes are considered: The BS goes to sleep whenever there is no active user, and wakes up when N users are assembled or after a period of multiple or single vacation time. We first discuss when to incorporate sleeping control into power matching energy efficiently. The explicit relationship between total power consumption and average delay with varying service rate is analyzed theoretically, indicating that sacrificing delay cannot always be traded for energy saving, and we also provide conditions under which the energy-optimal rate exists. Moreover, the optimal pair of sleeping parameter and service rate to achieve the optimal energy-delay tradeoff, and the energy consumption lower bound are also derived. Both the analytical and simulation results show that tolerable sacrifice of delay performance can be traded for substantial amount of energy saving given that careful designs were made according to our analysis.

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Abstract-In this paper, we study sleeping control and power matching for a single cell in cellular networks with bursty traffic. The base station (BS) sleeps whenever the system is empty, and wakes up when N users are assembled during the sleep period. The service capacity of the BS in the active mode is controlled through adjusting its transmit power. The total power consumption and average delay are analyzed, based on which the impact of parameter N and transmit power on the energy-delay tradeoff is studied. It is shown that given the average traffic load, the more bursty the traffic is, the less the total power is consumed, while the delay performance of more bursty traffic is better only under certain circumstances. The optimal energy-delay tradeoff is then obtained through joint sleeping control and power matching optimization. The relationship between the optimal control parameters and the asymptotic performance are also provided. Moreover, the influence of the traffic autocorrelation is explored, which shows less impact on the system performance compared with that of the burstiness. Numerical results show the energy saving gain of the joint sleeping control and power matching scheme, as well as the impact of burstiness on the optimal energy-delay tradeoff.

Road curb detection is essential for autonomous vehicles to locate themselves and make a rational decision, especially under road discontinuities, obstacle occlusions, and curved road scenarios. However, an effective and systematic solution to this problem has remained elusive. In this paper, a robust 3D-LiDAR-based method for road curb detection and tracking in a structured environment is proposed. The proposed method consists of four main stages: 1) a multi-feature based method is applied to extract candidate points; 2) a density-based clustering method is proposed for classifying left and right candidate points; 3) a candidate points filter (including distance filter and RANSAC filter) is proposed to remove false points; and 4) a least-square algorithm is used to obtain road curb curve and the amplitude-limiting Kalman filter is deployed to prevent false detection and miss detection. The comprehensive experiment evaluations show that the proposed method can deal with straight and curved road without being influenced by surrounding obstacles.INDEX TERMS Autonomous vehicle, 3D-LiDAR, curb detection, point cloud.

Internet interdomain routing is policy-driven, and thus physical connectivity does not imply reachability. On average, routing on today's Internet works quite well, ensuring reachability for most networks and achieving reasonable performance across most paths. However, there is a serious lack of understanding of Internet routing resilience to significant but realistic failures such as those caused by the 911 event, the 2003 Northeast blackout, and the recent Taiwan earthquake in December 2006. In this paper, we systematically analyze how the current Internet routing system reacts to various types of failures by developing a realistic failure model, and then pinpoint reliability bottlenecks of the Internet. For validity of our simulation results, we generate topology graphs by addressing concerns over the incompleteness of topology and the inaccuracy of inferred AS relationships. By focusing on the impact of structural and policy properties, our analysis provides guidelines for future Internet design. The simulation tool we provide for analyzing routing resilience is also efficient to scale to Internet-size topologies.