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Understanding intra-urban human mobility patterns and their potential driving forces are vital to city planning and commercial site selection. In this paper, we first investigate the functions of urban regions and how different region types dynamically influence people’s trip decisions. Furthermore, we characterize urban circadian rhythms by time-vary inter-regional transition probabilities between these regions with different functions, and integrate them into intervening opportunity model to predict human mobility. Public transportation card data in Shanghai are used to demonstrate the effectiveness of the model in terms of station passenger flows, travel time and trip flux. By taking regional function into consideration, the proposed model significantly improved the prediction accuracy. Quantitative analysis ulteriorly indicates that trip intentions and regional features are critical elements in trip flux prediction, especially in the afternoon and evening when people have an abundance of opportunities to travel by their own volition. When the function of a certain region changes, our model is able to make reasonable predictions accordingly. The results indicate the importance of considering individual travel motivation and regional function in modeling human mobility. The proposed model could serve as a guide for popularity and trip flux prediction in urban planning and reconstruction. [ABSTRACT FROM AUTHOR]

High-precision road detection from very high resolution (VHR) remote sensing images has broad application value. However, the most advanced deep learning based methods often fail to identify roads when there is a distribution discrepancy between the training samples and test samples, due to their limited generalization ability. In this paper, to address this problem, an open-source data-driven domain-specific representation (OSM-DOER) framework is proposed for cross-domain road detection. On the one hand, as the spatial structure information of the source and target domains is similar, but the texture information is different, the domain-specific representation (DOER) framework is proposed, which not only aligns the distributions of the spatial structure information, but also learns the domain-specific texture information. Furthermore, in order to enhance the representation of the target domain data distribution, open-source and freely available OpenStreetMap (OSM) road centerline data are utilized to generate target domain samples, which are then used in the network training as the supervised information for the target domain. Finally, to verify the superiority of the proposed OSM-DOER framework, we conducted extensive experiments with the public SpaceNet and DeepGlobe road datasets, and large-scale road datasets from Birmingham in the UK and Shanghai in China. The experimental results demonstrate that the proposed OSM-DOER framework shows obvious advantages over the mainstream road detection methods, and the use of OSM road centerline data has great potential for the road detection task. [ABSTRACT FROM AUTHOR]

Inevitable irregularities excite a traveling maglev train along a journey by disturbing air gaps and thus modifying levitation forces. For a half bogie which is a rigid coupled structure with a separate levitation unit at each endpoint, the effects of track irregularities hamper the synchronization of the two units. Motivated by the aforementioned, this paper establishes a newly nonlinear model for the half bogie considering irregularities, internal and external disturbances. Based on this model, a prescribed-time synchronization controller (PTSC) considering input constraints is designed while two adaptive disturbance observers (ADOs) are combined to address track irregularities and disturbances. To reduce the actuating times caused by synchronization, a lazy cooperation mode is adopted by independently introducing an event-triggered mechanism for each levitation unit. Theoretical analysis establishes the stability of the whole control scheme and demonstrates that the tracking errors and estimate errors can be arbitrarily small within a prescribed time, which can be determined by users through a parameter, and the synchronization is achieved. Numerical simulations compared with other two control schemes verify the effectiveness of the proposed control scheme, where both the ideal irregularity model and the field data measured from the Shanghai commercial line are tested. [ABSTRACT FROM AUTHOR]