Spatiotemporal Path Research Articles

Spatiotemporal structure of foraging and path integration errors by fiddler crabs, Leptuca pugilator

Path integration is the navigational process by which animals construct a memory of a previous location by continuously measuring and summing their movements to form a single home vector pointing to the starting location. It is intrinsically error prone, subject to random errors and, potentially, to systematic errors in either measurement or the summing algorithm. Both types of errors lead to an incorrect vector memory and thus to an error in homing. Because the errors are incurred when animals move, they are theoretically predictable from the movements. We analyzed the behavior of fiddler crabs (Leptuca pugilator) as they performed foraging excursions followed by homing with varying degrees of error. From video recordings we measured body orientations and locations and computed these spatiotemporal path characteristics: duration, distance, turns, bearing and arc sector. These were analyzed for their effect on, separately, the magnitude, and the direction, of crabs’ homing error. The magnitude of the homing error was predicted by arc sector, Δbearing and path length, and several interactions. The direction of the homing error was predicted by interactions including arc sector x Δbearing, arc sector x turns, and Δbearing x turns. Covariance among these factors results in a path that traces a large arc while maintaining body orientation toward the burrow direction and leads to an error with the same clockwise/counterclockwise sign as the arc and the body turns. These results place L. pugilator’s path integration mechanism among others with known systematic errors.

A Meteorological Drought Migration Model for Assessing the Spatiotemporal Paths of Drought in the Choushui River Alluvial Fan, Taiwan

Understanding drought evolution and its driving factors is crucial for effective water resource management and forecasting. This study enhances the analysis of drought probability by constructing bivariate distributions, providing a more realistic perspective than single-characteristic approaches. Additionally, a meteorological drought migration model is established to explore spatiotemporal paths and related characteristics of major drought events in the Choushui River alluvial fan. The results reveal a significant increase in the probability of southward-moving drought events after 1981. Before 1981, drought paths were diverse, while after 1981, these paths became remarkably similar, following a trajectory from north to south. This is primarily attributed to the higher rainfall in the northern region of the Choushui River alluvial fan from February to April, leading to a consistent southward movement of drought centroids. This study proposes that climate change is a primary factor influencing changes in the spatiotemporal paths of drought. It implies that changes in rainfall patterns and climate conditions can be discerned through the meteorological drought migration model. As a result, it provides the potential for simplifying drought-monitoring methods. These research findings provide further insight into the dynamic process of drought in the Choushui River alluvial fan and serve as valuable references for future water resource management.

Human-guided motion planner with perception awareness for assistive aerial teleoperation

Assistive aerial teleoperation in unknown environments can be challenging due to the limited sensing range of cameras and the insufficient human–computer interaction. Obstacles occluding the field of view (FOV ) of camera reduce the visibility of unknown environments, and it coupled with insufficient pilot instructions directly affect human intention recognition. To address this issue, the planned trajectory generated by assistive teleoperation should align with human intention while considering perception awareness (PA) of the FOV. However, most of the existing works considering PA solely increase the FOV visibility while neglect the human intention constraints. As a result, the PA constraints can cause the heading of the quadrotor to deviate from human expectation, requiring more human–computer interactions to correct it. In this paper, we propose a human-guided motion planner with perception awareness to solve these issues. Specifically, in the path-finding stage, we introduce a spatio-temporal path similarity metric method. This method, combined with motion primitive propagation, finds an initial path that is collision-free and roughly aligned with human intention. In the subsequent trajectory optimization stage, we jointly consider PA with respect to occlusion and human intention constraints, effectively optimizing FOV visibility without deviating the heading of quadrotor from human intention. Extensive experiments and benchmark comparisons demonstrate the effectiveness of our proposed method in solving assistive aerial teleoperation for even novice operators.

STP4: spatio temporal path planning based on pedestrian trajectory prediction in dense crowds

This article proposes a means of autonomous mobile robot navigation in dense crowds based on predicting pedestrians’ future trajectories. The method includes a pedestrian trajectory prediction for a running mobile robot and spatiotemporal path planning for when the path crosses with pedestrians. The predicted trajectories are converted into a time series of cost maps, and the robot achieves smooth navigation without dodging to the right or left in crowds; the path planner does not require a long-term prediction. The results of an evaluation implementing this method in a real robot in a science museum show that the trajectory prediction works. Moreover, the proposed planning’s arrival times is 26.4% faster than conventional 2D path planning’s arrival time in a simulation of navigation in a crowd of 50 people.

Real-Time Path Planning for Obstacle Avoidance in Intelligent Driving Sightseeing Cars Using Spatial Perception

The increasing prevalence of intelligent driving sightseeing vehicles in the tourism industry underscores the critical importance of real-time planning for effective local obstacle avoidance paths when these vehicles encounter obstacles during operation. To fulfill this requirement, it is imperative to establish real-time dynamic perception as the foundational element. Thus, this paper introduces a novel local path planning algorithm founded on the principles of spatial perception. In the diverse array of road environments characterized by varying spatial features, sightseeing vehicles can effectively achieve safe and comfortable obstacle avoidance maneuvers. The proposed approach employs a high-precision positioning module and a real-time dynamic perception module to acquire real-time spatial information pertaining to the sightseeing vehicle and the road environment. It comprehensively integrates spatiotemporal safety constraints and obstacle avoidance curvature constraints to derive control points for the obstacle avoidance path. Specific control points undergo optimization and adjustment, ultimately resulting in the generation of the obstacle avoidance spatiotemporal path through discrete interpolation using B-spline curves. These locally tailored paths are subsequently compared with local obstacle avoidance paths generated using Bezier curves. The empirical validation of the proposed local obstacle avoidance path algorithm is conducted through a combination of simulation analysis and real vehicle verification. The research outcomes affirm that the algorithm can indeed produce smoother local obstacle avoidance paths, resulting in reduced front-wheel steering angles and yaw angle variations. This enhancement substantially contributes to the overall stability of sightseeing vehicles during obstacle avoidance maneuvers.

World‐Space Spatiotemporal Path Resampling for Path Tracing

AbstractWith the advent of hardware‐accelerated ray tracing, more and more real‐time rendering applications tend to render images with ray‐traced global illumination (GI). However, the low sample counts at real‐time framerates bring enormous challenges to existing path sampling methods. Recent work (ReSTIR GI) samples indirect illumination effectively with a dramatic bias reduction. However, as a screen‐space based path resampling approach, it can only reuse the path at the first bounce and brings subtle benefits for complex scenes. To this end, we propose a world‐space based spatiotemporal path resampling approach. Our approach caches more path samples into a world‐space grid, which allows reusing sub‐path starting from non‐primary path vertices. Furthermore, we introduce a practical normal‐aware hash grid construction approach, providing more efficient candidate samples for path resampling. Eventually, our method achieves improvements ranging from 16.6% to 41.9% in terms of mean squared errors (MSE) compared against the previous method with only 4.4% ∼ 8.4% extra time cost.

Incremental path planning: Reservation system in V2X environment

Previous work assumes that traffic flow evolves over time, and paths are planned based on traffic estimation and prediction, although such an assumption is simple and efficient for single vehicles, there is a self-contradictory problem when planning paths for multiple vehicles. If multiple vehicles choose the same uncongested road based on traffic forecasts, this may lead to congestion on that road, which in turn affects the efficiency of path planning. The V2X environment offers the possibility to solve the above problems. In this paper, a new perspective is developed where the traffic flow is considered as a superposition of spatiotemporal paths. From this perspective, a novel method is proposed in which the paths are planned incrementally according to the remaining spatiotemporal resources and the travel demands, which is referred to as Incremental Path Planning (IPP). IPP plans the paths of vehicles according to a predefined priority, after a vehicle’s path is planned, the occupancy of spatiotemporal resources is updated, and the remaining resources are then passed to the next vehicle for path planning. In IPP, an incrementally updated traffic model is proposed to obtain the traffic state. Based on this model, a time-dependent path search algorithm is proposed to reduce vehicle travel times. Simulation experiments based on real data sets have demonstrated the excellent performance of IPP in both improving traffic efficiency and driving experience.

Spatiotemporal path tracking via deep reinforcement learning of robot for manufacturing internal logistics

The development of engineering technology, the logistics system composed of wheeled mobile robots (WMR) and automated guided vehicles (AGV) have been widely used in industrial scenes. However, traditional manufacturing scenes with dense layout, such as weaving workshops, have higher requirements for automatic transportation of materials. How to realize the intelligent transportation and management of materials in the manufacturing workshop and balance the efficiency and safety of material processing and transportation is still a great challenge. To address this problem, we designed a logistics system based on cloth-roll handling robot (CHR) and its path tracking hybrid deep reinforcement learning (DRL) considering spatiotemporal efficiency and safety in weaving workshop. This research first focuses on the design of a dynamic observation Markov decision-making process that integrates scene features. Further, a deep reinforcement learning considering the heterogeneity of observation data is proposed to obtain the optimal action solution. Then, a distributed scenarios training is implemented to improve the interaction ability between agents and the environment in complex scenes. In addition, the balance between dynamic observation and on-site calculation is considered in the path tracking for actual weaving workshop.

Spatio-Temporal Routing, Redundant Coding and Multipath Scheduling for Deterministic Satellite Network Transmission

Widespread deployment of Small Satellite Networks (SSN) fosters the foreseen integration of space-air-ground networks to provide worldwide Internet access to oceanic and remote airspace. However, the dynamic topology of SSN, the lossy wireless link, and the limited transmission resources induce unprecedented challenges to Deterministic Satellite Network Transmission (DSNT) for the sake of improving the utility of the SSN facility. Motivated by these challenges, this work aims to develop a Deterministic Satellite Network Transmission approach with deterministic Spatio-temporal routing, Redundant coding and Multipath scheduling (DSNT-SRM) for bolstering superior communications of SSN. DSNT-SRM uses the ephemeris information and dynamic resource update mechanism to predict all upcoming communication opportunities and construct the deterministic spatio-temporal routing paths. By combining sparse and redundant network coding mechanisms, DSNT-SRM no longer cares about the arrival of each packet, but the number of coded packets it receives, since the lost packets can be compensated with deterministic redundant traffic. Moreover, the adaptive traffic balance between multiple spatio-temporal paths is designed to provide a deterministic delay guarantee when facing limited node resources and multi-user competition. Extensive experiments show that DSNT-SRM can achieve satisfactory performance improvement in reducing delay and improving delivery rate.

A Lagrangian Method for Calculation of Passing Capacity on a Railway Hub Station

This research paper proposes a Lagrangian method to address the passing capacity of the calculation problem (PCCP) for a hub station in a high-speed railway (HSR) system. The passing capacity of a hub station is critical for determining the train timetable and maximizing the number of trains that can operate on different lines. The objective of this study is to determine the maximum number of trains that can pass through, start at, or end at a hub station. To achieve this objective, a mathematical model was introduced to solve the PCCP. The model was decomposed into two parts using a Lagrangian relaxation algorithm. The first part of the model was a simple train arrival problem (TAP) that reflected the timing of trains at the hub station with simultaneous arrival and departure time constraints. The second part of the model was a train spatio-temporal routing problem (TSRP) that aimed to solve the shortest spatio-temporal path of trains with free conflict with the train’s trajectory. A real instance was provided to demonstrate the feasibility of the proposed approach and the effectiveness of the Lagrangian method. The results showed that the proposed method can efficiently solve the PCCP and maximize the passing capacity of a hub station in an HSR system.

Spatiotemporal path inference model for urban rail transit passengers based on travel time data

AbstractAlthough the ‘one ticket transfer’ mode brings convenience to passengers, it also poses challenges to the passenger flow assignment. The current widely used multi‐path probability assignment model based on traffic cost realizes the passenger flow distribution from the macro‐perspective but lacks the consideration of passenger attributes and the time‐varying characteristics of passenger travel time. Here, a novel spatiotemporal path inference model is proposed for Urban Rail Transit (URT) passengers based on the travel time data and train operation information. In this study, the impact of passengers detained at the platform on passenger travel itinerary is considered by characterizing the passenger detention rate. The proposed method realizes the reverse inference of passenger path from the micro‐perspective, and can accurately describe the specific travel process of each passenger. Moreover, the real‐world data of Shenzhen Metro in China is taken to verify the rationality of the proposed model. The results show that the model is in good agreement with the existing clearance model and can accurately infer the passenger travel itinerary from the micro‐perspective. The proposed method provides a more refined solution for the spatial‐temporal assignment of URT passenger flow.

Optimizing Integrated All-Stop, Express, and Short-Turn Services on a Metro Line with Capacity Constraint Considering Passenger Spatio-Temporal Path Choice

Optimization of integrated train service is quite challenging under the situation of express trains overtaking local trains, because passenger path choice becomes more complicated and is largely unknown. To fill this gap, this study proposes a passenger spatio-temporal path choice model to replicate passenger behaviors given the real-time operation information in the metro system. Based on which, a non-linear programming model is developed to optimize integrated train services (i.e., all-stop, express, and short-turn) and the associated train timetables to minimize the total cost for a congested metro line, subject to a set of constraints (i.e., capacity, headway, service pattern, conditions of overtaking, etc.). The genetic algorithm with floating-point number coding is used to perform the optimization. It is applied to a real-world metro line in Chengdu, China, to assess its feasibility and effectiveness. The experimental results indicate that the integrated service is substantially improved in relation to total cost. The sensitivity analysis is conducted to explore the impacts of model parameters on various operation strategies. The proposed modeling approach is beneficial for transit agencies to improve their service planning.

Multi-Hand Gesture Recognition Using Automotive FMCW Radar Sensor

With the development of human–computer interaction(s) (HCI), hand gestures are playing increasingly important roles in our daily lives. With hand gesture recognition (HGR), users can play virtual games together, control the smart equipment, etc. As a result, this paper presents a multi-hand gesture recognition system using automotive frequency modulated continuous wave (FMCW) radar. Specifically, we first constructed the range-Doppler map (RDM) and range-angle map (RAM), and then suppressed the spectral leakage, and dynamic and static interferences. Since the received echo signals with multi-hand gestures are mixed together, we propose a spatiotemporal path selection algorithm to separate the mixed multi-hand gestures. A dual 3D convolutional neural network-based feature fusion network is proposed for feature extraction and classification. We developed the FMCW radar-based platform to evaluate the performance of the proposed multi-hand gesture recognition method; the experimental results show that the proposed method can achieve an average recognition accuracy of 93.12% when eight gestures with two hands are performed simultaneously.

Research on Passenger Flow Assignment of Integrated Cross-Line and Skip-Stop Operation between State Railway and Suburban Railway

The passenger flow assignment in the rail transit network is the basis for determining the passenger spatiotemporal distribution and train operation organization plan. In previous studies, the passenger flow assignment problem mainly focused on lines within the same rail system. Few studies focus on lines with the integrated mode of cross-line and skip-stop operation between state and suburban railway due to fewer cases in practice. In this study, passenger congestion and fare policy are taken into account in the generalized travel cost function, and a passenger flow assignment model based on the path-sized logit (PSL) model considering train capacity is proposed. Meanwhile, a schedule-based spatiotemporal digraph is established to search for the shortest spatiotemporal travel path. Furthermore, an improved method of successive averages (MSA) algorithm is designed to solve the proposed model. The proposed model is verified by a numerical example. The sensitivities of three main parameters which influence the results are also analyzed. The results show that the assignment model based on PSL is practicable in integrated operation mode. The higher the passenger’s familiarity with network information, the more accurate the assignment results. State trains are more attractive when the fare is lower than 0.5 CNY/km or the hourly wage is higher than 50 CNY/h.

Microscale dynamics of electrophysiological markers of epilepsy

ObjectiveInterictal discharges (IIDs) and high frequency oscillations (HFOs) are established neurophysiologic biomarkers of epilepsy, while microseizures are less well studied. We used custom poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) microelectrodes to better understand these markers’ microscale spatial dynamics. MethodsElectrodes with spatial resolution down to 50 µm were used to record intraoperatively in 30 subjects. IIDs’ degree of spread and spatiotemporal paths were generated by peak-tracking followed by clustering. Repeating HFO patterns were delineated by clustering similar time windows. Multi-unit activity (MUA) was analyzed in relation to IID and HFO timing. ResultsWe detected IIDs encompassing the entire array in 93% of subjects, while localized IIDs, observed across < 50% of channels, were seen in 53%. IIDs traveled along specific paths. HFOs appeared in small, repeated spatiotemporal patterns. Finally, we identified microseizure events that spanned 50–100 µm. HFOs covaried with MUA, but not with IIDs. ConclusionsOverall, these data suggest that irritable cortex micro-domains may form part of an underlying pathologic architecture which could contribute to the seizure network. SignificanceThese results, supporting the possibility that epileptogenic cortex comprises a mosaic of irritable domains, suggests that microscale approaches might be an important perspective in devising novel seizure control therapies.

Impact of Shared Bus on Campus Travel and Space Optimization Based on Activity Travel Behavior

Based on the travel analysis of students in the Jiulonghu campus, this paper constructs a small-scale shared bus in the campus, explores the impact of shared traffic on campus travel, promotes the optimization design of campus space environment, and creates a more comfortable and convenient travel space. In order to overcome the shortcomings of the traditional trip-based research, this paper analyzes travel behavior from the perspective of activity-based travel concept framework, considering more activities and travel information. At the same time, in order to improve the richness of information, the explicit preference survey (RP) and the declarative preference survey (SP), which are added to the bus sharing customized travel platform, are used to collect data of personal attributes and travel diary. Firstly, based on the ArcGIS platform, this paper constructs the activity travel path generation tool, dynamic activity density distribution tool, and spatiotemporal path clustering tool and comprehensively analyzes the activity travel mode from the aspects of time distribution, spatial distribution, and category characteristics. Secondly, based on the travel activities, the location selection model (S-MNL) considering the heterogeneity of SP and RP data sources and the activity duration planning model (Cox regression), considering the nonnormal distribution of activity duration are established to analyze the impact of shared bus on students’ travel distance, travel time, and travel frequency. Finally, according to the analysis of modeling results, the impact of shared traffic on campus travel is analyzed, and the optimal design scheme of campus space is given. This paper uses the survey method based on declarative preference SP and the survey method based on explicit preference (RP) to get the actual and hypothetical travel response of travelers, which improves the data richness.

"Dancing" Together: Infant-Mother Locomotor Synchrony.

Pre-mobile infants and caregivers spontaneously engage in a sequence of contingent facial expressions and vocalizations that researchers have referred to as a social "dance." Does this dance continue when both partners are free to move across the floor? Locomotor synchrony was assessed in 13- to 19-month-old infant-mother dyads (N=30) by tracking each partner's step-to-step location during free play. Although infants moved more than mothers, dyads spontaneously synchronized their locomotor activity. For 27 dyads, the spatiotemporal path of one partner uniquely identified the path of the other. Clustering analyses revealed two patterns of synchrony (mother-follow and yo-yo), and infants were more likely than mothers to lead the dance. Like face-to-face synchrony, locomotor synchrony scaffolds infants' interactions with the outside world.

Spatio-temporal evolution path and driving mechanisms of sustainable urban renewal: Progress and perspective

Spatio-temporal evolution path and driving mechanisms of sustainable urban renewal: Progress and perspective

Spatio-Temporal Path Planning for Lunar Polar Exploration with Robustness against Schedule Delay

Spatio-Temporal Path Planning for Lunar Polar Exploration with Robustness against Schedule Delay

La producción del espacio social en la Amazonía brasileña a través de las represas hidroeléctricas: El caso del conflicto de Belo Monte

Durante las últimas décadas en Brasil se ha producido un incremento significativo de los conflictos hidrosociales a causa de la construcción de grandes complejos hidroeléctricos. Esta extensión de grandes proyectos de carácter extractivista en la región amazónica, sobre todo a partir de finales de la década de los años ochenta del siglo pasado, han conllevado todo un conjunto de transformaciones en las relaciones sociales, productivas y reproductivas, de cara avanzar en mecanismos para la integración regional y nacional, así como para la superación de crisis de acumulación propias de la escala global. Entre todos, por su trascendencia y dilatación en el tiempo, probablemente el que más destaca es el de la represa de Belo Monte en el río Xingú, próximo a la ciudad de Altamira. En él se ven involucrados una multiplicidad de actores (comunidades indígenas, campesinos, pescadores, el estado, Eletrobras, constructoras, instituciones supranacionales, etc) cuya disputa por el acceso a los recursos hídricos supone una modificación de la configuración de las relaciones de poder que se dan en el territorio. Este artículo, además de analizar el recorrido espacio-temporal de dicho conflicto, se propone dos objetivos adicionales. Por un lado la elaboración de un marco teórico, que conjugue las perspectivas de la producción de la naturaleza, la producción del espacio y la construcción de la escala, que pueda ser aplicado al análisis de conflictos ambientales que tienen lugar en el Sur Global. Por otro lado, y en consecuencia, a través de su empleo en el estudio de este caso particular, determinar las fortalezas y debilidades que presenta para su uso en futuros trabajos similares. De cara a ello se plantea una metodología basada en la revisión bibliográfica y el uso tanto de fuentes primarias como secundarias, mediante las cuales se puedan extraer y analizar el conjunto de prácticas, representaciones y relaciones que dan forma al conflicto en sí mismo. A su vez, el artículo se divide en cuatro partes principales: el planteamiento de articulación entre las distintas categorías y aspectos de los planteamientos teóricos para su uso en el estudio de caso; el análisis del desarrollo espacio-temporal del conflicto, desde el inicio de la planificación del proyecto hasta día de hoy; en tercer lugar se explica y detalla el papel de los actores hegemónicos en el avance de la construcción del complejo hidroeléctrico; y en última instancia se lleva a cabo la misma operación pero con los actores subalternos implicados. De entre los resultados obtenidos, destaca cómo este proyecto a nivel particular, y los macroproyectos hidroeléctricos en general en la región, han sido fundamentales para la integración económica en el marco de la extensión de las relaciones de producción capitalistas y los mecanismos para la acumulación a través de la realización del plusvalor, derivando resistencias ante este proceso de extracción. Así mismo, la perspectiva interescalar y la de la producción del espacio muestran potencialidades como marco para el estudio de conflictos ambientales, mientras que el de la producción de la naturaleza lo hace de manera parcial.