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The unmanned aerial vehicle(UAV) used in agricultural fields usually has a load, which affects stability of flight trajectory. This problem is a great technical challenge and critical issue which has fascinated many researchers in this area. This research paper presents a flight dynamics model for agricultural UAV under load condition. The robust T-S fuzzy control method is applied in the attitude angle control part, and the traditional PID controller is used in the position loop control part. Results of simulation depict that the flight trajectory of agricultural UAV can reach certain stability when the load is relatively small.

Blind search for available parking space is accountable for most traffic congestion, accident, and pollution in cities, which severely impact people's life. Parking management based on an online smart parking system is practical to alleviate parking problems in which parking allocation is the core. However, existing researches are weak at satisfying allocation effect and speed simultaneously when solving large-scale dynamic parking allocation problem. To address this problem, we firstly construct an online “Collection-Allocation-Response” smart parking system (CARSP) to offer parking services to users and rent parking spaces from owners so as to obtain revenue for system managers. We then propose a novel Doubly Periodic Rolling Horizon allocation approach (DPRH) that circularly conduct allocation within a short period and reallocation within a long period. We formulate a narrow allocation model (without reallocation) and broad allocation model (with reallocation), both of which are binary integer programming models with the objective of maximizing system integrated benefit. We design seven performance metrics to evaluate the overall allocation effect and speed of CARSP based on DPRH. According to the three-day district-level instance in Beijing, CARSP based on DPRH performs excellently in balancing allocation effect and speed. This study is meaningful for constructing and optimizing an online smart parking system., Author(s): Shangbin Ning [1,2]; Zhenyu Han [1]; Yang Yang [3,4]; Zhenzhou Yuan (corresponding author) [1,2]; Xianyu Wu [1,2] 1. Introduction With the swift development in urbanization and the great growth [...]

In this paper, a self-adaptive, two-stage fuzzy controller is established to realize the real-time online optimization of traffic signal timing plan, which takes multimodels of transportation as the research object to analyze the reliability of the control system at the isolated urban intersection. In this system, the first stage calculates traffic urgency degree for all red phases and selects the red phase with maximum traffic urgency degree as the next green phase. The second stage determines whether to extend or terminate the current signal phase. Aiming at the problems of the parameters of membership functions empirical settings and insufficient response to the real-time fluctuation in traffic flow, the controller introduces an improved hybrid genetic algorithm to solve it and enable the controller to self-learn. Finally, a microsimulation platform is constructed based on the VISSIM and Python language to evaluate the efficiency and reliability of the controller under complex actual traffic conditions. Results showed that the average delay time per vehicle is reduced by 14.59%, while the average number of stops per vehicle is reduced by 0.71% compared with the traditional control method. Results indicate that the traffic signal timing plan generated by the controller can efficiently improve the intersection traffic capacity and has good efficiency and reliability under the condition of medium saturation and unsteady flow., Author(s): Mingzhi Wang [1]; Xianyu Wu (corresponding author) [2]; He Tian [1]; Jie Lin [2]; Meimei He [2]; Liuqing Ding [2] 1. Introduction At present, with the development of shared [...]