Relevant bibliographies by topics / PEDESTRIAN DIRECTION

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'PEDESTRIAN DIRECTION'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "PEDESTRIAN DIRECTION"

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Lu, Lili, Gang Ren, Wei Wang, Chen Yu, and Chenzi Ding. "Exploring the Effects of Different Walking Strategies on Bi-Directional Pedestrian Flow." Discrete Dynamics in Nature and Society 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/150513.

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Three types of different walking behaviors (right preference, conformity, and space priority) are taken into account to model bi-directional pedestrian flow in the channel with cellular-automata formulation. The fundamental diagrams ofR-pedestrian flow,C-pedestrian flow, andS-pedestrian flow are obtained from the simulation result to analyze the effect of these behaviors on bi-direction flow. TheC-pedestrian flow has the minimum critical density andR-pedestrian flow has the highest, while theS-pedestrian flow has higher average-speed than other two types of pedestrian flow under the same density. Further, through the study of pedestrian distribution in the channel and the proportion of pedestrians not able to move to the front cell, reasons leading to different characteristics of these three types of pedestrian flow are analyzed. Moreover, the simulation experiment based on BehaviorSearch is designed to explore the optimal percentages ofR-pedestrian,C-pedestrian, andS-pedestrian in pedestrian flow. The result of the experiment shows that the condition that makes the highest average speed of pedestrian flow is not that pedestrian flow consists of purely one type of pedestrians, but pedestrian flow mixed withS-pedestrians as majority andC-pedestrians andR-pedestrians as minority.
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Zhu, Nuo, Bin Jia, and Chun Fu Shao. "Pedestrian Evacuation Based on a Dynamic Parameters Model." Applied Mechanics and Materials 97-98 (September 2011): 956–59. http://dx.doi.org/10.4028/www.scientific.net/amm.97-98.956.

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A dynamic parameters model is presented based on cellular automata for pedestrian evacuation in this paper. The dynamic parameters: Direction-parameter, Empty-parameter and Cognition-parameter are formulated to simplify tactically the decision-making process of pedestrians, which can reflect the pedestrian judgment on the surrounding conditions and decide the pedestrian’s choice of action. Pedestrian moving rules were established, according to two-dimensional cellular automaton. The simulation results of the model are analyzed. It is observed that there is a linear relationship between evacuation time and pedestrian density, however, there is a negative exponential relationship between evacuation time and exit width. The simulation results correspond with the actual, it is instructional significant for pedestrian evacuation.
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Zhao, Rongyong, Ping Jia, Chuanfeng Han, Yan Wang, Cuiling Li, and Zhishu Zhang. "Analysis of dynamic model based on pedestrian’s abnormal posture." MATEC Web of Conferences 355 (2022): 03010. http://dx.doi.org/10.1051/matecconf/202235503010.

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It is significant to detect abnormal postures of pedestrians in the crowd to crowd stability control. This study locates the joint points of pedestrians based on the pose estimation algorithm OpenPose. After the analysis of 18 nodes and six body parts, the sudden value of node acceleration is obtained, which is compared with the acceleration of the pedestrian’s centre of mass. When there is at least one difference in the direction or acceleration value of the two, it means that the pedestrian has abnormal behaviour. Furthermore, this study analyses the result of comparing the change of z-coordinate value in pedestrian movement with 20% of pedestrian height. These two judgment methods together constitute the dynamic criterion of pedestrian abnormal posture, and judge whether the pedestrian has abnormal behaviour. Compared with the previous dynamic analysis of pedestrian abnormal posture, the accuracy of abnormal posture judgment is improved. This provides a theoretical basis for crowd stability analysis.
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Hajari, Kamal Omprakash, Ujwalla Gawande, and Yogesh Golhar. "Robust Pedestrian Detection and Path Prediction using Improved YOLOv5." ELCVIA Electronic Letters on Computer Vision and Image Analysis 21, no. 2 (September 13, 2022): 40–61. http://dx.doi.org/10.5565/rev/elcvia.1538.

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In vision-based surveillance systems, pedestrian recognition and path prediction are critical concerns. Advanced computer vision applications, on the other hand, confront numerous challengesdue to differences in pedestrian postures and scales, backdrops, and occlusion. To tackle these challenges, we present a YOLOv5-based deep learning-based pedestrian recognition and path prediction method. The updated YOLOv5 model was first used to detect pedestrians of various sizes and proportions. The proposed path prediction method is then used to estimate the pedestrian's path based on motion data. The suggested method deals with partial occlusion circumstances to reduce object occlusion-induced progression and loss, and links recognition results with motion attributes. After then, the path prediction algorithm uses motion and directional data to estimate the pedestrian movement's direction. The proposed method outperforms the existing methods, according to the results of the experiments. Finally, we come to a conclusion and look into future study.
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Wang, Weili, Jiayu Rong, Qinqin Fan, Jingjing Zhang, Xin Han, and Beihua Cong. "Data-Driven Simulation of Pedestrian Movement with Artificial Neural Network." Journal of Advanced Transportation 2021 (August 28, 2021): 1–16. http://dx.doi.org/10.1155/2021/5580910.

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To predict pedestrian movement is of vital importance in a wide range of applications. Recently, data-driven models are receiving increasing attention in pedestrian dynamics studies, demonstrating a great potential in enhancing simulation performance. This paper presents a pedestrian movement simulation model based on the artificial neural network, in which two submodels are, respectively, used to predict velocity displacement and velocity direction angle at each time step. Destination information, the pedestrian’s historical movement information, neighboring pedestrians, and environmental obstacles within a semicircular-shaped perception area are used as inputs to learn pedestrian movement behavioral rules. In the velocity direction angle submodel, a novel division method on pedestrian’s perception area is adopted. Specifically, perception radius is divided into several bands, and perception angle range is divided into a number of sectors, establishing a weighted spatial matrix to represent varied influences of neighboring pedestrians and obstacles. Experiments on two typical scenarios, the unidirectional flow and bidirectional flow in a long straight corridor, were conducted to obtain pedestrian movement datasets. Then, a series of simulation cases were conducted to investigate the proper values for critical parameters, including perception radius, perception angle division, weights of the spatial matrix, and historical movement adoption. In comparison of pedestrian trajectory between simulation results and real data, the mean trajectory error (MTE) and mean destination error (MDE) are, respectively, 0.114 m and 0.171 m in the unidirectional flow scenario, which are, respectively, 0.204 m and 0.362 m in the bidirectional flow scenario. In addition, the fundamental diagram representing density-velocity and density-flow relationships in simulation results agree well with that in real data. The results demonstrate great capacity and credibility of the presented model in simulating pedestrian movement in real applications.
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Kim, Kwangsoo, Yangho Kim, and Sooyeong Kwak. "Vision Sensor Based Fuzzy System for Intelligent Vehicles." Sensors 19, no. 4 (February 19, 2019): 855. http://dx.doi.org/10.3390/s19040855.

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Those in the automotive industry and many researchers have become interested in the development of pedestrian protection systems in recent years. In particular, vision-based methods for predicting pedestrian intentions are now being actively studied to improve the performance of pedestrian protection systems. In this paper, we propose a vision-based system that can detect pedestrians using an on-dash camera in the car, and can then analyze their movements to determine the probability of collision. Information about pedestrians, including position, distance, movement direction, and magnitude are extracted using computer vision technologies and, using this information, a fuzzy rule-based system makes a judgement on the pedestrian’s risk level. To verify the function of the proposed system, we built several test datasets, collected by ourselves, in high-density regions where vehicles and pedestrians mix closely. The true positive rate of the experimental results was about 86%, which shows the validity of the proposed system.
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Felcman, Jiří, and Petr Kubera. "A cellular automaton model for a pedestrian flow problem." Mathematical Modelling of Natural Phenomena 16 (2021): 11. http://dx.doi.org/10.1051/mmnp/2021002.

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The evacuation phenomena in the two dimensional pedestrian flow model are simulated. The intended direction of the escape of pedestrians in panic situations is governed by the Eikonal equation of the pedestrian flow model. A new two-dimensional Cellular Automaton (CA) model is proposed for the simulation of the pedestrian flow. The solution of the Eikonal equation is used to define the probability matrix whose elements express the probability of a pedestrian moving in finite set of directions. The novelty of this paper lies in the construction of the density dependent probability matrix. The relevant evacuation scenarios are numerically solved. Predictions of the evacuation behavior of pedestrians, for various room geometries with multiple exits, are demonstrated. The mathematical model is numerically justified by comparison of CA approach with the Finite Volume Method for the space discretization and Discontinuous Galerkin Method for the implicit time discretization of pedestrian flow model.
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Hu, Xiangmin, Tao Chen, Kaifeng Deng, and Guanning Wang. "Effects of the direction and speed strategies on pedestrian dynamics." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 6 (June 2022): 063140. http://dx.doi.org/10.1063/5.0091240.

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In this work, we propose a velocity-based model for pedestrian movements containing two sub-models to study how the direction and speed selection strategies affect pedestrian dynamics. Affected by others in the view, pedestrians deviate their moving direction from the desired one to resolve space and velocity conflicts, the sensitivity to which is adjusted by two proportional parameters. After determining the moving direction, they choose a reasonable speed to avoid immediate collisions. The tolerance of personal-space violations is considered given that people accept physical contacts in some contexts and may squeeze despite the lack of space instead of matching the speed of the one in front. Simulation results demonstrate that the direction and speed selection strategies affect pedestrian dynamics in several aspects, including the time and metabolic energy cost, density–velocity relations, and crowd stability. Intriguingly, the discrepant empirical fundamental diagrams of pedestrians can be reproduced and explained in a natural way.
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Aprilnico, Elven, and Martha Leni Siregar. "Pedestrian risk analysis at Jl. Raya Citayam – Jl. Boulevard Raya Grand Depok City intersection leg using pedestrian risk index." MATEC Web of Conferences 276 (2019): 03011. http://dx.doi.org/10.1051/matecconf/201927603011.

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Based on data obtained from Korps Lalu Lintas Kepolisian Negara Republik Indonesia there are 4,007 traffic accidents involving pedestrian in this period (October 2017-March 2018), where 499 of them happened at intersection. The purpose of this research is to analyze the risk level of pedestrian when crossing the intersection leg (using Pedestrian Risk Index (PRI). The concept of TCT (Traffic Conflict Technique) is adopted and a designed group(s) of pedestrians are observed while crossing the streets at a zebra cross and while crossing the street without a zebra cross. Pedestrians are observed when crossing individually and in groups. Data extracted include time and distance to accidents, crossing directions, and speed. Results indicate that compared to the existence of zebra crossing and crossing direction, the number of pedestrian in group significantly determines the risk level.
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Guo, Ning, Rui Jiang, SC Wong, Qing-Yi Hao, Shu-Qi Xue, Yao Xiao, and Chao-Yun Wu. "Experimental study on mixed traffic flow of bicycles and pedestrians." Collective Dynamics 5 (August 12, 2020): A108. http://dx.doi.org/10.17815/cd.2020.108.

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The mixed flow of bicycles and pedestrians is frequently observed on bicycle-pedestrian-shared roads. Unfortunately, studies on dynamics of this kind of mixed flow are very limited. This paper reports an experimental study of this kind of mixed traffic flow with equal numbers of pedestrians and cyclists asked to walk/ride in a ring-shaped track. In the uni-/bi-directional flow scenarios, pedestrians and bicycles moved in the same/opposite direction. Under both scenarios, bicycles and pedestrians formed their own lanes. Pedestrians walked in the inner lane and cyclists rode in the outer lane. Widths of both the pedestrian lane and the bicycle lane were more uniform in bidirectional flow. The pedestrian flow rate is larger in the unidirectional flow scenario than in the bidirectional flow scenario. In contrast, at low densities, the bicycle flow rate is essentially the same under the two scenarios. When the density is large, the bicycle flow rate becomes larger in the unidirectional flow scenario. Comparing the two modes, pedestrian flow rate is smaller/larger than bicycle flow rate at small/large densities under both scenarios.
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Dissertations / Theses on the topic "PEDESTRIAN DIRECTION"

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Shahabpoor, Erfan. "Dynamic interaction of walking humans with pedestrian structures in vertical direction experimentally based probabilistic modelling." Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/7241/.

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There is a lack of credible and usable knowledge, specifically related to human-structure interaction in the vertical direction despite of its importance and potentially huge economic impact. The research presented in this thesis addresses this problem via a systematic combined experimental and analytical study of the effects of people on dynamic properties of vibrating structures they excite by walking. Series of extensive frequency response function based modal tests were performed on a full-scale test structure with more than one hundred test subjects walking in different loading scenarios. The experimental results were then used to identify the parameters of a single-degree-of-freedom (SDOF) mass-spring-damper (MSD) model of a walking human. Four different approaches, including agent-based modelling, were used to simulate measured scenarios of multi-pedestrian traffic. It was found that normal distributions with μ=2.864 Hz and σ= 0.191 Hz, and μ=0.295 and σ= 0.023 can describe the natural frequency and damping ratio of the SDOF MSD model of a walking human, respectively, when total mass of the human body is assumed as the mass of the SDOF system. A new vibration serviceability assessment method was proposed that takes into account not only the variability of the human body MSD parameters and the forcing function but also their interaction with the structure. Application of this novel method on two full-scale structures under walking traffic load verified its excellent performance yielding a maximum 10% error in estimating the level of structural response compared to 200-500% error margins when key design guidelines currently used around the world were employed. This method is versatile and, being easy to apply in practice, has the potential to replace the existing methods for simulating single and multi-pedestrian traffic on footbridges and floors.
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Schroder, Catherine Jane. "Automated creation of pedestrian route descriptions." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/7720.

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Providing unambiguous, succinct descriptions of routes for pedestrians to follow is very challenging. Route descriptions vary according to many things, such as route length and complexity, availability of easily identifiable landmarks, and personal preferences. It is well known that the inclusion of a variety of landmarks facilitates route following – either at key decision points, or as a confirmatory cue. Many of the existing solutions, however, behave like car navigation systems and do not include references to such landmarks. The broader ambition of this research is the automatic generation of route descriptions that cater specifically to the needs of the pedestrian. More specifically this research describes empirical evidence gathered to identify the information requirements for an automated pedestrian navigation system. The results of three experiments helped to identify the criteria that govern the relative saliency of features of interest within an urban environment. There are a large variety of features of interest (together with their descriptions) that can be used as directional aids within route descriptions (for example buildings, statues, monuments, hills, and roads). A set of variables were developed in order to measure the saliency of the different classes of features. The experiments revealed that the most important measures of saliency included name, size, age, and colour. This empirical work formed the basis of the development of a pedestrian navigation system that incorporated the automatic identification of features of interest using the City of Edinburgh as the study area. Additionally the system supported the calculation of the saliency of a feature of interest, the development of an intervisibility model for the route to be navigated to determine the best feature of interest to use at each decision point along the route. Finally, the pedestrian navigation system was evaluated against route descriptions gathered from a random set of individuals to see how efficiently the system reflected the more natural and richer route description that people typically generate. This work shows that modelling features of interest is the key to the automatic generation of route descriptions that can be readily understood and followed by pedestrians.
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Johansson, Anton. "Bi-directional flow in the Social Force Model." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43274.

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We use the social force model to study the behaviour of two crowds of pedestrians in a bi-directional flow. There are two main goals of the project. The first goal is to study the effects of perception anisotropy on lane formation of the two crowds. The perception anisotropy models the fact that people actually do not perceive their surroundings equally well in all directions, i.e they have a field of vision. The second goal is to develop pedestrian viscosity indices to characterize the motion of the crowds. Our concepts of viscosity indices estimate how fluid the motion of the crowds are. We develop two viscosity indices. A lane viscosity index which gives information of the flow on large timescales, and a space-dependent viscosity index which can pinpoint where in space the motion is less fluid. Our results indicate that there is a small correlation between the perception anisotropy and the lane formation of the two crowds. The two viscosity indices work as intended but more refinement is needed to cope with simultaneous space-time changes.
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Shatu, Farjana M. "Built environment impact on pedestrian route choice behaviour: Shortest vs. least directional change routes." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/126392/1/Farjana_Shatu_Thesis.pdf.

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This study investigates how students choose their walking routes to a university. Their observed walking routes were compared against the shortest path routes and against the least directional change routes. The urban design features (e.g. streets, benches, fountains, buildings) of these routes were also examined through physical and virtual (e.g. Google Earth image) surveys. The study reveals that students' route choice decision is highly influenced by street configuration – less directional changes are preferred over the shortest path distance – highlighting the need to design urban streets straighter to promote walking.
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Shimizu, Hiroaki, and Tomaso Poggio. "Direction Estimation of Pedestrian from Images." 2003. http://hdl.handle.net/1721.1/30397.

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The capability of estimating the walking direction of people would be useful in many applications such as those involving autonomous cars and robots.We introduce an approach for estimating the walking direction of people from images, based on learning the correct classification of a still image by using SVMs. We find that the performance of the system can be improved by classifying each image of a walking sequence and combining the outputs of the classifier.Experiments were performed to evaluate our system and estimate the trade-off between number of images in walking sequences and performance.
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Raman, Rahul. "Pedestrian Walk Direction Estimation for Smart Surveillance." Thesis, 2019. http://ethesis.nitrkl.ac.in/10071/1/2019_PhD_RRaman_513CS1040_Pedestrian.pdf.

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Study of human behavior during a walk is crucial for surveillance, traffic control, assisted living, crowd flow in shopping malls, and various other domains. In this respect, direction of walk estimation is an imperative research issue. The challenge of pedestrian walk direction estimation needs to be addressed at different working environment, with different camera setup, at different light and noise levels, for different crowd types, and with different objectives. Hence, the challenges are multifold. This thesis presents an extensive study on different research works performed in last couple of decades towards pedestrian walk direction estimation, comparing their work at both quantitative and qualitative levels. The thesis also performs an elaborated study on existing databases for visual surveillance and proposes a suitable database for walk direction estimation. The thesis further proposes machine learning based classification of pedestrian walk direction among eight pre-identified equiangular discrete directions. Exploiting feature set from temporal domain, proposed method eradicates the low accuracy of classification among directions directly towards and away from camera, thus yielding overall higher accuracy of walk direction estimation. The thesis further proposes a kinesiology inspired spatial feature to be used along with temporal feature to yield a robust feature set originated from kinematics of pedestrian locomotion along sagittal plane. Overall pedestrian direction estimation result are more precise and gives correct result with sudden change in walk direction or even orientation of pedestrian to predict probable direction of motion. These results are generated using hidden Markov model (HMM) and Least Square Support Vector Machine (LS-SVM) methods with sufficient theoretic and experimental justification. The demand of higher accuracy of direction estimation result and not-so-discrete nature of pedestrian motion has further inspired to propose the fuzzy approach based direction estimation to yield direction of pedestrian motion by defuzzification of spatial feature. The proposed analysis and implementation of type-1 fuzzy based direction estimation over same feature set gives crisp angular direction (in degree) with respect to view axis. Proposed different levels of direction estimation suits different traffic, surveillance, and research related needs to counter different noise levesl of pedestrian video input and different levels of required precision for direction estimation result. Proposed direction estimation method is robust to partial occlusion, improper segmentation and can give discrete classification result and even beyond discrete levels which may be required for multiple applications.
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趙, 光哲, and Guangzhe Zhao. "Estimation of Pedestrian Walking Direction for Driver Assistance System." Thesis, 2012. http://hdl.handle.net/2237/17275.

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Lin, Chih-Chieh, and 林仕杰. "Design and Implementation of YOLO Deep Learning Network Based Pedestrian Collision Avoidance and Direction Detection Technology for Intelligent Self-propelled Vehicles." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5441090%22.&searchmode=basic.

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碩士
國立中興大學
電機工程學系所
107
In the past ten years, with the rapid development of the Internet and the maturity of hardware technology, artificial intelligence and big data analysis have become the key targets of high-tech in the future. The deep learning network can continuously learn and fix the weight of the data, and it allows the robot to perform high-complexity tasks, which are the goal of current research efforts. For intelligent self-propelled vehicles, the development of pedestrian direction detection technology is an important issue. Pedestrian direction information can avoid collision between intelligent self-propelled vehicles and crowds. By real-time object detection under the premise of big data, the deep learning can achieve higher accuracy and generalization ability more than the traditional methods. Compared with other neural networks, the YOLO based network model can obtain the effective results of object detection and object recognition in one test, and it has the advantages of high accuracy and fast operation. Besides, the YOLO model is also a one-stage classifier. In this thesis, a YOLO-PD network model is proposed by the characteristics of pedestrians. Based on the YOLOv2 algorithm and architecture improvement, this model trains a classifier that can identify six pedestrian directions, including front, left front, right front, left, right, and back. We collect several existing public pedestrian database and field samples, and define sample screening conditions to establish the pedestrian databases. The implementation process is divided into the training and testing phases. In the training phase, by using the graphics card on the personal computer, the features are extracted through the neural network, and trained by the stochastic gradient method until the loss function is converged. In the testing phase, pedestrian images were taken with a webcam with the resolution of 1920 x 1080 pixels, and the performance of YOLO-PD network model was tested on an embedded platform. The experimental results show that the YOLO-PD network model can achieve 65.52% mAP with the real-time operations by 29.80 FPS on the Xavier embedded platform. Compared with the original YOLOv1 network model, the operational speed of the proposed design is more than twice, and the mAP is also increased more than 15.86%. In addition, compared with the well-designed YOLOv2 network model, the mAP of the proposed design is slightly reduced by 0.72%, but the FPS performance can be increased by 1.45 times.
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Dutta, Sankha Baran. "GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement." 2014. http://hdl.handle.net/1993/23597.

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Pedestrian movement, although ubiquitous and well-studied, is still not that well under-stood due to the complicating nature of the embedded social dynamics. Interest among researchers in simulating the nature of pedestrian movement and interactions has grown significantly in part due to increased computational and visualization capabilities afforded by high power computing. Different approaches have been adopted to simulate pedestrian movement under various circumstances and interactions. In the present work, bi-directional crowd movement is simulated where equal numbers of individuals try to reach the opposite sides of an environment. Two pedestrian movement modeling methods are considered. The reasonableness of these two models in producing better results is com-pared without increasing the computational complexity. First a Least Effort Model (LEM) is investigated, where agents try to take an optimal path with minimal changes from their intended path as possible. Following this, a modified form of Ant Colony Op-timization (ACO) is developed, where individuals are guided by a goal of reaching the other side in a least effort mode as well as being influenced by a pheromone trail left by predecessors. The objective is to increase agent interaction, thereby more closely reflect-ing a real world scenario. The methodology utilizes Graphics Processing Units (GPUs) for general purpose computing using the CUDA platform. Because of the inherent parallel properties associated with pedestrian movement, such as similar interactions of indi-viduals on a 2D grid, GPUs are a well suited computing platform. The main feature of the implementation undertaken here is the data driven parallelism model. The data driven implementation leads to a speedup up to 18x compared to its sequential counterpart run-ning on a single threaded CPU. The number of pedestrians considered in the model ranged from 2K to 100K, representing numbers typical of mass gathering events. A de-tailed analysis is also provided on the throughput of pedestrians across the environment. Compared to LEM model, there is an overall increment of 39.6% in the throughput of agents using the ACO model with a marginal increment of 11% in the computational time. A detailed discussion addresses implementation challenges faced and avoided.
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Books on the topic "PEDESTRIAN DIRECTION"

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Bachmann, Hugo, and Walter Ammann. Vibrations in Structures. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 1987. http://dx.doi.org/10.2749/sed003e.

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<p>«Vibrations in Structures» concentrates on vibrations in structures as excited by human motion or machine operation. Man-induced vibrations may arise from walking, running, skipping, dancing, etc. They occur mostly in pedestrian structures, office buildings, gym­nasia and sports halls, dancing and concert halls, stadia, etc. Existing publications treat by and large some isolated aspects of the problem; the present one attempts, for the first time, a systematic survey of man-induced vibrations. Machine-induced vibrations occur during the operation of all sorts of machinery and tools with rotating, oscillating or thrusting parts. The study concentrates rather on small and medium size machinery placed on floors of industrial buildings and creating a potential source of undesirable vibrations. The associ­ated questions have rarely been tackled to date; they entail probiems similar to those of man-induced vibrations.</p> <p>The book is consciously intended to serve the practising structural engineer and not primarily the dynamic specialist. It should be noted that its aim is not to provide directions on how to perform comprehensive dynamic computations. Instead, it attempts the following:</p> <ol> <li>to show where dynamic problems could occur and where a word of caution is good advice;</li> <li>to further the understanding of the phenomena encountered as well as of the underlying principles;</li> <li>to impart the basic knowledge for assessing the dynamic behaviour of the structures or structural elements;</li> <li>to describe suitable measures, both preventive to be applied in the design stage and remedial in the case of rehabilitation.</li> </ol>
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A step in the right direction: Assessing the London Red Routes from a pedestrian point of view. London: Pedestrians Association, 1993.

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Britain, Great. The Pelican" Pedestrian Crossings Regulations and General Directions 1987 (Statutory Instruments: 1987: 16). Stationery Office Books, 1987.

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Britain, Great. The Pelican and Puffin Pedestrian Crossings General (Amendment) Directions 1998 (Statutory Instruments: 1998: 901). Stationery Office Books, 1998.

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The Zebra, Pelican and Puffin Pedestrian Crossings Regulations and General Directions (Statutory Instruments: 1997: 2400). Stationery Office Books, 1997.

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Comfort, Kelly, and Marylaura Papalas. New Directions in Flânerie: Global Perspectives for the Twenty-First Century. Taylor & Francis Group, 2021.

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New Directions in Flânerie: Global Perspectives for the Twenty-First Century. Taylor & Francis Group, 2021.

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Comfort, Kelly, and Marylaura Papalas. New Directions in Flânerie: Global Perspectives for the Twenty-First Century. Routledge, 2021.

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Comfort, Kelly, and Marylaura Papalas. New Directions in Flânerie: Global Perspectives for the Twenty-First Century. Taylor & Francis Group, 2021.

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Book chapters on the topic "PEDESTRIAN DIRECTION"

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Dominguez-Sanchez, Alex, Sergio Orts-Escolano, and Miguel Cazorla. "Recognizing Pedestrian Direction Using Convolutional Neural Networks." In Advances in Computational Intelligence, 235–45. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59147-6_21.

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Lv, Jiaqi, Zhenyu Na, Xin Liu, Tingting Yao, and Zhian Deng. "Outlier Filtering Algorithm for Indoor Pedestrian Walking Direction Estimation." In Lecture Notes in Electrical Engineering, 2421–28. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6571-2_295.

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Zhu, Wei, and Harry Timmermans. "Bounded Rationality Choice Model Incorporating Attribute Threshold, Mental Effort, and Risk Attitude: Illustration to Pedestrian Walking Direction Choice Decision in Shopping Streets." In Pedestrian and Evacuation Dynamics 2008, 425–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04504-2_36.

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Lu, Shunbao, Zhongliang Deng, Chen Xue, Yeqing Fang, Ruoyu Zheng, and Hui Zeng. "A Pedestrian Movement Direction Recognition Method Based on Inertial Sensors." In Lecture Notes in Electrical Engineering, 781–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46632-2_67.

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Hu, Zhichao, Gabrielle Halberg, Carolynn R. Jimenez, and Marilyn A. Walker. "Entrainment in Pedestrian Direction Giving: How Many Kinds of Entrainment?" In Signals and Communication Technology, 151–64. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21834-2_14.

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Chraibi, Mohcine, Martina Freialdenhoven, Andreas Schadschneider, and Armin Seyfried. "Modeling the Desired Direction in a Force-Based Model for Pedestrian Dynamics." In Traffic and Granular Flow '11, 263–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39669-4_25.

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Santoshi, G., and S. R. Mishra. "Pedestrian with Direction Detection Using the Combination of Decision Tree Learning and SVM." In Advances in Intelligent Systems and Computing, 249–55. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13728-5_28.

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Tubino, Federica. "Probabilistic Analysis of Human-Structure Interaction in the Vertical Direction for Pedestrian Bridges." In Conference Proceedings of the Society for Experimental Mechanics Series, 117–19. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54777-0_15.

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Tachikawa, Yuji. "Conclusions and Further Directions." In N=2 Supersymmetric Dynamics for Pedestrians, 201–5. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08822-8_13.

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Eledeisy, Mohamed. "Inclusive Neighborhoods in a Healthy City: Walkability Assessment and Guidance in Rome." In The Urban Book Series, 959–67. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29515-7_85.

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AbstractWith the increasingly global and European attention toward healthy inclusive cities, the focus on pedestrian-friendly environments, as a tool to encourage and support healthy lifestyles for people of all social groups and ages, continues to rise. This article aims to assess “walkability” as one of the main conditions of a built environment that enhances “healthy living”, a core theme of the Zagreb Declaration for Healthy Cities. Transit-Oriented Development Standard (TOD Standard) is used as a tool to evaluate the walkability level in San Giovanni area in Rome, Italy. Through urban plans and measurements of the pedestrian realms, the research evaluates the state of walkability through a metric scoring method of the walkways’ segments. The analysis demonstrates the percentages of all-accessible walkway segments and crosswalks that are safe in all directions; segments with visually active frontages; physically permeable frontages; and segments that incorporate adequate shade or shelter. The results show the pedestrian realm’s level of safety, completeness, accessibility to all; its activeness and vibrance; and its level of comfort. The conclusions provide guidance for areas of intervention to make walking accessible for everyone and support decision-making processes to develop inclusive neighborhoods, as a part of the future policies for equitable access and mobility in a healthy city.
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Conference papers on the topic "PEDESTRIAN DIRECTION"

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Larabi, S., and A. Bensebaa. "Pedestrian walking direction from video." In 8th International Conference on Imaging for Crime Detection and Prevention (ICDP 2017). Institution of Engineering and Technology, 2017. http://dx.doi.org/10.1049/ic.2017.0045.

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Larabi, Slimane, and Amina Bensebaa. "Estimation of pedestrian walking direction from video." In 2017 International Conference on Mathematics and Information Technology (ICMIT). IEEE, 2017. http://dx.doi.org/10.1109/mathit.2017.8259689.

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Ayub, Shahid, Behzad Momahed Heravi, Alireza Bahraminasab, and Bahram Honary. "Pedestrian Direction of Movement Determination Using Smartphone." In 2012 6th International Conference on Next Generation Mobile Applications, Services and Technologies (NGMAST). IEEE, 2012. http://dx.doi.org/10.1109/ngmast.2012.36.

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Mao, Lina, and Linyan Tang. "Pedestrian Detection Based on Gradient Direction Histogram." In 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC). IEEE, 2022. http://dx.doi.org/10.1109/ipec54454.2022.9777626.

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He, Bate, and Eisuke Kita. "Pedestrian Walking Direction Prediction Using Generative Adversarial Networks." In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2020. http://dx.doi.org/10.1109/smc42975.2020.9283115.

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S, Sukesh Babu V., and Rahul Raman. "Pedestrian Direction Estimation: An Approach via Perspective Distortion Patterns." In 2023 4th International Conference on Innovative Trends in Information Technology (ICITIIT). IEEE, 2023. http://dx.doi.org/10.1109/icitiit57246.2023.10068588.

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Hoshi, Hisashi, Masahiro Fujii, Atsushi Ito, Yu Watanabe, and Hiroyuki Hatano. "A Study on Direction Estimation for Pedestrian Dead Reckoning." In 2014 Second International Symposium on Computing and Networking (CANDAR). IEEE, 2014. http://dx.doi.org/10.1109/candar.2014.68.

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Manos, Adi, Itzik Klein, and Tamir Hazan. "Gravity Direction Estimation and Heading Determination for Pedestrian Navigation." In 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2018. http://dx.doi.org/10.1109/ipin.2018.8533689.

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Itoh, Makoto, Toshiyuki Inagaki, and Hiroto Tanaka. "Haptic steering direction guidance for pedestrian-vehicle collision avoidance." In 2012 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2012. http://dx.doi.org/10.1109/icsmc.2012.6378305.

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Kolcu, Cihangir, and Bulent Bolat. "Yayaların yürüyüş rotalarının belirlenmesi detection of walking direction for pedestrian." In 2018 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT). IEEE, 2018. http://dx.doi.org/10.1109/ebbt.2018.8391426.

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Reports on the topic "PEDESTRIAN DIRECTION"

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Simizu, Hiroaki, and Tomaso Poggio. Direction Estimation of Pedestrian from Images. Fort Belvoir, VA: Defense Technical Information Center, August 2003. http://dx.doi.org/10.21236/ada459729.

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Kulhandjian, Hovannes. AI-based Pedestrian Detection and Avoidance at Night using an IR Camera, Radar, and a Video Camera. Mineta Transportation Institute, November 2022. http://dx.doi.org/10.31979/mti.2022.2127.

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In 2019, the United States experienced more than 6,500 pedestrian fatalities involving motor vehicles which resulted in a 67% rise in nighttime pedestrian fatalities and only a 10% rise in daytime pedestrian fatalities. In an effort to reduce fatalities, this research developed a pedestrian detection and alert system through the application of a visual camera, infrared camera, and radar sensors combined with machine learning. The research team designed the system concept to achieve a high level of accuracy in pedestrian detection and avoidance during both the day and at night to avoid potentially fatal accidents involving pedestrians crossing a street. The working prototype of pedestrian detection and collision avoidance can be installed in present-day vehicles, with the visible camera used to detect pedestrians during the day and the infrared camera to detect pedestrians primarily during the night as well as at high glare from the sun during the day. The radar sensor is also used to detect the presence of a pedestrian and calculate their range and direction of motion relative to the vehicle. Through data fusion and deep learning, the ability to quickly analyze and classify a pedestrian’s presence at all times in a real-time monitoring system is achieved. The system can also be extended to cyclist and animal detection and avoidance, and could be deployed in an autonomous vehicle to assist in automatic braking systems (ABS).
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Martinez, Kimberly D., and Gaojian Huang. Exploring the Effects of Meaningful Tactile Display on Perception and Preference in Automated Vehicles. Mineta Transportation Institute, October 2022. http://dx.doi.org/10.31979/mti.2022.2164.

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There is an existing issue in human-machine interaction, such that drivers of semi-autonomous vehicles are still required to take over control of the vehicle during system limitations. A possible solution may lie in tactile displays, which can present status, direction, and position information while avoiding sensory (e.g., visual and auditory) channels overload to reliably help drivers make timely decisions and execute actions to successfully take over. However, limited work has investigated the effects of meaningful tactile signals on takeover performance. This study synthesizes literature investigating the effects of tactile displays on takeover performance in automated vehicles and conducts a human-subject study to design and test the effects of six meaningful tactile signal types and two pattern durations on drivers’ perception and performance during automated driving. The research team performed a literature review of 18 articles that conducted human-subjects experiments on takeover performance utilizing tactile displays as takeover requests. Takeover performance in these studies were highlighted, such as response times, workload, and accuracy. The team then conducted a human-subject experiment, which included 16 participants that used a driving simulator to present 30 meaningful vibrotactile signals, randomly across four driving sessions measuring for reaction times (RTs), interpretation accuracy, and subjective ratings. Results from the literature suggest that tactile displays can present meaningful vibrotactile patterns via various in-vehicle locations to help improve drivers’ performance during the takeover and can be used to assist in the design of human-machine interfaces (HMI) for automated vehicles. The experiment yielded results illustrating higher urgency patterns were associated with shorter RTs and higher intuitive ratings. Also, pedestrian status and headway reduction signals presented shorter RTs and increased confidence ratings compared to other tactile signal types. Finally, the signal types that yielded the highest accuracy were the surrounding vehicle and navigation signal types. Implications of these findings may lie in informing the design of next-generation in-vehicle HMIs and future human factors studies on human-automation interactions.
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