In this paper, a fuzzy-innovation based adaptive extended Kalman filter (FI-AKF)is proposed to improve the performance of the GNSS/INS fusion system, which is degradeddue to satellite signal cutoff and attenuation and inaccurate modeling in dense urbanenvironments. The information used for sensor fusion is obtained from real-time kinematic (RTK),micro-electro-mechanical system based inertial measumrement unit (MEMS-IMU), and on-boarddiagnostics (OBD). The fuzzy logic system is proposed to adaptively update the measurementcovariance matrix of the RTK according to the position dilution of precision (PDOP), the numberof receivable satellites, and the innovation of the extended Kalman filter (EKF). In addition, thedriving state of the vehicle is defined as stop, straight run, left/right turn, and the like. To reduce theheading estimation error of the Kalman filter, the estimated heading is corrected according to thedriving state. Also, the measurement covariance matrices of IMU and OBD are applied adaptivelyconsidering the characteristics of each sensor according to the driving state. In order to analyze theperformance of the proposed FI-AKF positioning system in a dense urban environment, a computersimulation is performed. The proposed FI-AKF is compared to the performance of the existingextended Kalman filter and the innovation-based adaptive extended Kalman filter. In addition, weconduct a performance comparison experiment with a commercial positioning system in the field test.Through each experiment, it is confirmed that the proposed FI-AKF system has higher positioningperformance than the comparison positioning systems in a dense urban environment.
Transportation safety is one of the most important applications of vehicular ad hoc networks which is based on IEEE 802.11p. When a vehicle is in an emergency situation, a safety-related message is transmitted to the neighboring vehicles and infrastructures. Vehicles and infrastructures exchange periodic messages on vehicle position, traffic information, and so forth to provide various services. When the traffic load is very high, the emergency message cannot be delivered immediately. To overcome this situation, a prioritybased transmission scheme is considered to guarantee the transmission of the emergency message. In this paper, the performance of vehicular communication networks is analyzed in two perspectives. Firstly, an analytical Markov chain model for vehicle-to-vehicle (V2V) ad hoc communication networks is proposed for broadcasting messages with priority based on the IEEE 802.11p wireless access for vehicular environments (WAVE) standard. Secondly, an analytic queuing model for vehicular communication networks is proposed to evaluate the network performance to deal with safety and nonsafety messages.
The robust reception of network parameters is a very important issue for the successful deployment of mobile infotainment services, particularly in fast-moving environments. An infrastructure broadcasts service access-related messages to consumer devices. These access messages critically affect the connectivity between the consumer devices and service providers. This paper proposes an algorithm to increase the connectivity by collaborating consumer devices to share access information messages. The consumer device that receives the access message retransmits the message by attached it to its beacon message. This is performed only when there are neighboring consumer devices that did not receive the message. This paper also proposes an extended beacon message for this purpose. The proposed algorithm was evaluated with computer simulations 1 .
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