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As transit service performance should be considered from the transit passengers' perspectives, it is essential to determine passengers' perceptions of service performance and to understand the role of these perceptions in travel decisions. As the bus market share has steadily declined, the aim of this study is to explore the impact of perceptions of bus service performance on mode choice preference to increase bus ridership. To achieve this research objective, an intention survey is conducted to obtain bus passengers' attitudes. Exploratory factor analysis and confirmatory factor analysis are used to measure passengers' perceptions and to extract the main factors from the bus service attributes. Next, structural equation modeling is used to reveal how passengers' perceptions vary by demographics and trip characteristics. Finally, multinomial logit modeling is used to explore the impact of perception factors on mode choice preference. The results of this study show that perceptions of the reliability and comfort of bus services have a more significant impact on passengers' mode choice preference than perceptions of availability and safety do. The implications in terms of improving bus service reliability and comfort can increase bus ridership.

Density control is of great relevance for wireless sensor networks monitoring hazardous applications where sensors are deployed with high density. Due to the multihop relay communication and many-to-one traffic characters in wireless sensor networks, the nodes closer to the sink tend to die faster, causing a bottleneck for improving the network lifetime. In this paper, the theoretical aspects of the network load and the node density are investigated systematically. And then, the accessibility condition to satisfy that all the working sensors exhaust their energy with the same ratio is proved. By introducing the concept of the equivalent sensing radius, a novel algorithm for density control to achieve balanced energy consumption per node is thus proposed. Different from other methods in the literature, a new pixel-based transmission mechanism is adopted, to reduce the duplication of the same messages. Combined with the accessibility condition, nodes on different energy layers are activated with a nonuniform distribution, so as to balance the energy depletion and enhance the survival of the network effectively. Extensive simulation results are presented to demonstrate the effectiveness of our algorithm.

The demand for mobile laser scanning in urban areas has grown in recent years. Mobile-based light detection and ranging (LiDAR) technology can be used to collect high-precision digital information on city roads and building façades. However, due to the small size of curbs, the information that can be used for curb detection is limited. Moreover, occlusion may cause the extraction method unable to correctly capture the curb area. This paper presents the development of an algorithm for extracting street curbs from mobile-based LiDAR point cloud data to support city managers in street deformation monitoring and urban street reconstruction. The proposed method extracts curbs in three complex scenarios: vegetation covering the curbs, curved street curbs, and occlusion curbs by vehicles, pedestrians. This paper combined both spatial information and geometric information, using the spatial attributes of the road boundary. It can adapt to different heights and different road boundary structures. Analyses of real study sites show the rationality and applicability of this method for obtaining accurate results in curb-based street extraction from mobile-based LiDAR data. The overall performance of road curb extraction is fully discussed, and the results are shown to be promising. Both the completeness and correctness of the extracted left and right road edges are greater than 98%.

Visual Simultaneous Localization and Mapping (VSLAM) is a prerequisite for robots to accomplish fully autonomous movement and exploration in unknown environments. At present, many impressive VSLAM systems have emerged, but most of them rely on the static world assumption, which limits their application in real dynamic scenarios. To improve the robustness and efficiency of the system in dynamic environments, this paper proposes a dynamic RGBD SLAM based on a combination of geometric and semantic information (DGS-SLAM). First, a dynamic object detection module based on the multinomial residual model is proposed, which executes the motion segmentation of the scene by combining the motion residual information of adjacent frames and the potential motion information of the semantic segmentation module. Second, a camera pose tracking strategy using feature point classification results is designed to achieve robust system tracking. Finally, according to the results of dynamic segmentation and camera tracking, a semantic segmentation module based on a semantic frame selection strategy is designed for extracting potential moving targets in the scene. Extensive evaluation in public TUM and Bonn datasets demonstrates that DGS-SLAM has higher robustness and speed than state-of-the-art dynamic RGB-D SLAM systems in dynamic scenes.

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Nowadays, global navigation satellite systems (GNSSs) are widely used in location-based services (LBSs) as they can provide high-accuracy position services continuously. However, their performance deteriorates in indoor scenarios, in which GNSS signal reception is limited or completely impossible. In this paper, an enhanced constrained Kalman filter is presented to enhance the indoor positioning performance of a LBS and for use in a WiFi/pedestrian dead reckoning (PDR) integrated navigation algorithm. A robust scheme for computing the gross error in constrained conditions is suggested to make the performance of the constrained condition model in the WiFi/PDR integrated system more robust. The results of simulation analysis indicate that the robustly constrained Kalman filter can reliably determine gross errors in constrained conditions. An indoor field experiment was conducted to test the performance of the proposed filter algorithm, and the results show that the improved filter can eliminate the effect of gross error from constrained conditions in the WiFi/PDR system.