There is a growing demand for detailed and accurate landslide maps and inventories around the globe, but particularly in hazard-prone regions such as the Himalayas. Most standard mapping methods ...require expert knowledge, supervision and fieldwork. In this study, we use optical data from the Rapid Eye satellite and topographic factors to analyze the potential of machine learning methods, i.e., artificial neural network (ANN), support vector machines (SVM) and random forest (RF), and different deep-learning convolution neural networks (CNNs) for landslide detection. We use two training zones and one test zone to independently evaluate the performance of different methods in the highly landslide-prone Rasuwa district in Nepal. Twenty different maps are created using ANN, SVM and RF and different CNN instantiations and are compared against the results of extensive fieldwork through a mean intersection-over-union (mIOU) and other common metrics. This accuracy assessment yields the best result of 78.26% mIOU for a small window size CNN, which uses spectral information only. The additional information from a 5 m digital elevation model helps to discriminate between human settlements and landslides but does not improve the overall classification accuracy. CNNs do not automatically outperform ANN, SVM and RF, although this is sometimes claimed. Rather, the performance of CNNs strongly depends on their design, i.e., layer depth, input window sizes and training strategies. Here, we conclude that the CNN method is still in its infancy as most researchers will either use predefined parameters in solutions like Google TensorFlow or will apply different settings in a trial-and-error manner. Nevertheless, deep-learning can improve landslide mapping in the future if the effects of the different designs are better understood, enough training samples exist, and the effects of augmentation strategies to artificially increase the number of existing samples are better understood.
Four donor–acceptor salicylaldimines with benzoheterocyclic substituents at nitrogen imine were prepared and characterised by means of optical spectroscopy. Their luminescent properties were compared ...with two isoelectronic carbocyclic analogues. In contrast to the typical salicylaldimines, our reported benzoheterocyclic compounds exhibit solely local emissive behaviour in all media whereas for the carbocyclic analogues we expectedly observe dominant ESIPT emission in the majority of instances. Low temperature (5 K - liquid helium) fluorescence measurements revealed the effect of the restriction of the molecular rotation which was manifested by significant increment of the fluorescence intensity. The comprehensive experimental and ab initio study reveal effect of solvent polarity, viscosity and temperature on the complex photophysics of heterocyclic and carbocyclic substituted salicylaldimines with several degrees of freedom for molecular transformations. This work adds considerable insight in emission lifetime data which greatly facilitates understanding of the fluorescence mechanism of the molecules with environmentally dependent restrictions.
Autonomous intersection management (AIM) has been widely researched, but previous studies assume that vehicles will follow assigned trajectories precisely. The purpose of this paper is to investigate ...the safety buffers needed between intersecting vehicles to avoid a collision if a vehicle malfunctions. We optimize vehicle trajectories by deciding the arrival times at each conflict point (point of possible intersection with other vehicles) along each vehicle's trajectory. Because intersecting vehicles rely on the intersection manager (IM) to detect and communicate malfunctions, the reaction time from the IM determines the minimum safety buffer needed. Although a smaller reaction time reduces the safety buffer, it increases the probability that the IM falsely detects a malfunction, instructing vehicles to stop and creating unnecessary delays. This paper develops a mathematical safety buffer for intersecting vehicles, linearizes this time separation, and constructs a combined mixed-integer linear program. A complete protocol is presented and simulated for normal circumstances, emergency circumstances, and recovery circumstances. Sensitivity analyses on various reaction times show the tradeoff between low reaction times (more false positives) and high reaction times (greater safety buffer).
•We model the dynamics of crossing pedestrian streams at four-way intersections.•Experimental data and Approximate Bayesian Computation are used for model selection.•We show that at high inflow rates ...interactions between entire streams emerge.•When four streams intersect some streams may move whilst others are jammed.•Thus, intersections may influence pedestrian flows beyond their immediate vicinity.
The interactions between individual pedestrians can lead to emergent effects, such as the formation of lanes in bidirectional flows. Here, we expose properties of an emergent effect at a macroscopic level, namely interactions between pedestrian streams that arise when pedestrians walk into and through four-way intersections from different directions. We propose non-spatial models for the number of pedestrians from different streams inside an intersection. Each model encodes a different hypothesis for how streams interact and can produce dynamics fundamentally distinct from the other models. By fitting our models to large experimental data sets and determining which model explains the data best, we determine when and how entire streams of pedestrians start to interact. We find that as arrival rates increase, streams start to interact and compete for space. Our results suggest that these interactions result in an even balance of pedestrian numbers across two orthogonally intersecting streams. Neither of the streams can dominate. In contrast, for four intersecting streams, our findings suggest that jams in some streams can coincide with higher flow rates in other streams and that the relative dominance of streams can switch stochastically. By adapting existing methodology, we thus present a coherent conceptual approach for investigating emergent effects in temporal dynamics at aggregated levels in pedestrian flows that could be applied to other scenarios. Our approach is flexible and uses easily measured quantities, making it highly suitable for observational data in different scenarios or deployment in applications.
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For the last two decades, autonomous vehicles have been proposed and developed to extend the operational design domain from the motorway to urban environments. However, there have been few studies on ...autonomous driving for uncontrolled and blind intersections. This paper presents a proactive motion planning algorithm to enhance safety and traffic efficiency simultaneously for autonomous driving in uncontrolled blind intersections. The target states of approach motion are decided based on the field of view of the laser scanner and the pre-defined intersection map with connectivity information. The model predictive controller is used to follow the target states and determine the longitudinal motion of an autonomous vehicle. A Monte Carlo simulation with a case study was conducted to evaluate the performance of the proposed proactive motion planner. The simulation results show that the risk caused by approaching vehicles from the occluded region is properly managed. In addition, the traffic flow is improved by reducing the required time to cross the intersections.
The advent of connected vehicle technology brings forth a new set of possibilities for more efficient traffic control. Indeed, the ability to consider driver-specific attributes, such as value of ...time or willingness to pay, in intersection management through advanced communication protocols allows for reducing individual delay costs. In this context, this study presents an auction-based approach for signalized intersection control under a connected vehicle setting. A second-price sealed-bid auction is employed to assign green time to conflicting movements, while driver bids and bidding distance per lane vary based on delay accumulation. The proposed auction-based control is evaluated using various demand levels and flow patterns and compared against pre-timed signal control. Results show that the proposed mechanism may be a promising alternative for several flow patterns, achieving lower average delays while maintaining fairness.
•We present an unconditionally secure quantum Private Set Intersection Cardinality protocol, which requires O(1) communication cost.•We propose a novel anonymous authentication scheme, which can not ...only achieve two basic secure goals: secure authentication and anonymity, but can also easily and dynamically update the authorized clients.
In this paper, we proposed an unconditionally secure quantum Private Set Intersection Cardinality (PSI-CA) protocol. Compared with classical PSI-CA protocols, the proposed protocol can dramatically reduce the communication complexity, because it only requires O(1) communication cost, which is fully independent of the size of the sets. Furthermore, based on the proposed quantum PSI-CA protocol, we constructed a novel anonymous authentication scheme. This scheme can not only achieve two basic secure goals: secure authentication and anonymity, but can also dynamically update the authorized clients. When revoking any authorized client or adding a new client, it only needs to simply compute several set operations without any complex cryptographic operation, and thus it is very suitable for applications in some dynamic environments, e.g., large-scale client-server networks.
To ensure that the laser proximity fuze can detect the ground target during the intersection between the laser detection system and the ground target, based on the dual‐transmitter dual‐receiver ...laser circumferential scanning detection mechanism, we established the constraint functions of scanning frequency and laser pulse frequency without missing measurement. According to the surface characteristics of the plane target, we derived the calculation models of the laser echo power and the minimum detectable echo power of the detection system to the plane target under the random intersection attitude. The calculation function of the angle between adjacent laser beams is obtained based on the minimum detectable echo power. We discussed the relation of the scanning frequency, the laser pulse frequency, the angle between adjacent laser beams and the intersection angle, focused on the influence of the intersection angle and the detection distance on the laser echo power. The simulation experiments were carried out under different laser peak powers and detection distances, the experimental results fully demonstrate that the laser echo power calculation model established in this paper is correct; the detection ability of the system is improved to a certain extent by increasing the laser peak power.
•This paper invents the “automated pedestrian shuttle” (APS) to transport pedestrians at an autonomous intersection.•This paper models the optimum route choices for APSs based on virtual node ...technique.•This paper captures the conflicts between APSs and AVs by discretizing the intersection.•This paper explores the optimum entering time for each APS and AV to minimize the overall passenger delay.
This paper is among the first to address the problem of pedestrians’ crossing at an autonomous intersection without traffic lights. To guarantee pedestrians’ safety, all the pedestrians who intend to cross the street should firstly board into a fully enclosed automated transport unit, which is referred to as an “automated pedestrian shuttle” (APS) in this paper, then the APS carries the pedestrians across the street. Because APSs can shuttle back and forth through the intersection, the routing problem for APSs is modeled first. Then a Mixed Integer Linear Program (MILP) based AIM model is proposed to simultaneously optimize for the time of APSs and upcoming vehicles to enter the intersection. A numerical analysis is conducted to examine the performance and effectiveness of the proposed methods.
Pedestrians are vulnerable road users subject to severer injuries and higher fatality risk in motor vehicle crashes due to limited protection. An important portion of vehicle-pedestrian crashes ...occurred at intersections due to the complex movements of various types of road users and the conflicts among them. To address the safety concern, this paper investigates the contributing factors to the severity of vehicle-pedestrian crashes at intersections based on a 3-year crash dataset of Hong Kong. For the crash severity modelling process, the crash dataset is mass and complicated. To tackle the class imbalance issue of the crash severity level, data resampling method is firstly applied. Then, various data mining algorithms, namely, classification and regression tree (CART) model, gradient boosting (GB) model, random forest (RF) model, artificial neural network (ANN) model and support vector machine (SVM) model, have been applied. The performance of these models have also been compared with the logistic regression model commonly applied in the literature. The ANN model which has the best performance is selected to determine the most significant contributing factors to the fatal and severe crashes, and the marginal effects of these factors are also analysed. Results show that the likelihood of fatal and severe vehicle-pedestrian crashes at intersections increase when there is light rain and where the junction control type is traffic signal and no control. On the other hand, the crash severity tends to decrease when the weather condition is clear, the light condition is daylight and dark, and in the districts of Kwun Tong, Kowloon City, Central and Western, and Sham Shui Po. Based on the results, policy implications and counter-measures on reducing the fatal and severe vehicle-pedestrian crashes at intersections have been recommended.
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