Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

Pedestrian steering behaviour modelling within the built environment

Prediction of pedestrians’ steering behaviours within the built environments under normal and non-panic situations is useful for a wide range of applications, which include social science, psychology, architecture, and computer graphics. The main focus is on prediction of the pedestrian walking paths and the influences from the surrounding environment from the engineering point of view

Design and realization of precise indoor localization mechanism for Wi-Fi devices

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.Peer ReviewedPostprint (published version

Combining multi-criteria and space syntax analysis to assess a pedestrian network: the case of Oporto

This paper describes a GIS-based integrated approach to assess a pedestrian network by combining multi-criteria and space syntax. The analysis combines pedestrian attributes with street connectivity and both factors were evaluated by a group of experts. The approach was adopted in the city of Oporto. Results show that the city centre offers various conditions; however, overall they are poor for pedestrians. Moreover, the streets which scored best are not integrated into the network. The described approach can potentially be replicated in other cities in terms of improving the walkability and promoting sustainable urban mobility.This research was funded by the CIVITAS CAPITAL (Ref. No. MOVE/FP7/604778/CAPITAL) and by the Centre for Territory, Environment and Construction of the School of Engineering of University of Minho.info:eu-repo/semantics/publishedVersio

Accessibility and connectivity criteria for assessing walkability: an application in Qazvin, Iran

Distance is a recognized key determinant of walking. Pedestrians tend to choose the shortest route between two points. Shortest routes can be spatially described in terms of distances between two points or topologically described as the number of turns/directional changes between these points. This paper presents a methodology to evaluate the conditions provided by a street network to pedestrians, by using two space syntax measures. Accessibility was calculated through Angular Segment Analysis by Metric Distance (ASAMeD), a measure of street integration and choice strongly correlated with pedestrian movement pattern. Street Connectivity was calculated by using the space syntax measure of connectivity, which shows the direct connection of street nodes to each individual nodes. The streets criterion values of both approaches were normalized by using fuzzy logic linear functions. The method was applied in the city center of Qazvin, Iran. Results showed that the urban structure of Qazvin has a strong impact on the performance of the network. The old neighborhood centers widespread in the city center presented a high topological accessibility, while the most connected street are those streets crossing and surrounding the neighborhood areas. The method can be used to evaluate and improve pedestrian networks, as it can distinguish the most and least attractive streets according to the criteria used. These findings can be used to guide policies towards improving walkability and to create more walkable and sustainable cities.This research was funded by the JPI Urban Europe and FCT, grant number ENSUF/0004/2016

Aerial social force model: a new framework to accompany people using autonomous flying robots

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.We proposed a novel Aerial Social Force Model (ASFM) that allows autonomous flying robots to accompany humans in urban environments in a safe and comfortable manner. To date, we are not aware of other state-of-the-art method that accomplish this task. The proposed approach is a 3D version of the Social Force Model (SFM) for the field of aerial robots which includes an interactive human-robot navigation scheme capable of predicting human motions and intentions so as to safely accompany them to their final destination. ASFM also introduces a new metric to fine-tune the parameters of the force model, and to evaluate the performance of the aerial robot companion based on comfort and distance between the robot and humans. The presented approach is extensively validated in diverse simulations and real experiments, and compared against other similar works in the literature. ASFM attains remarkable results and shows that it is a valuable framework for social robotics applications, such as guiding people or human-robot interaction.Peer ReviewedPostprint (author's final draft

Aesthetical cognitive perceptions of urban street form. Pedestrian preferences towards straight or curvy route shapes

ABSTRACTHuman perception of space is not purely metric. Route angularity and complexity-minimizing paths suggest that pedestrians, consciously or not, tend to reduce the number and the angle of tur..

Level of service criteria of urban walking environment in indian context using cluster analysis

To know how well roadways accommodate pedestrian travel or how they are pedestrian friendly it becomes necessary to assess the walking conditions. It would also help evaluating and prioritizing the needs of existing roadways for sidewalk construction. Estimation of Pedestrian Level of Service (PLOS) is the most common approach to assess the quality of operations of pedestrian facilities. The focus of this study is to identify and access the suitable methodology to evaluate PLOS for off-street pedestrian facilities in Indian context. Defining the level of service criteria for urban off-streets pedestrian facilities are basically classification problems. Cluster analysis is found to be the most suitable technique for solving these classification problems. Cluster analysis groups object based on the information found in the data describing their relationships. K-means, Hierarchical Agglomerative Clustering (HAC), Fuzzy c-means (FCM), Self Organizing MAP (SOM) in Artificial Neural Network (ANN), Affinity Propagation (AP) and Genetic Algorithm Fuzzy (GA Fuzzy) clustering are the six methods are those employed to define PLOS criteria in this study. Four parameters such as pedestrian space, flow rate, speed and volume to capacity (v/c) ratio are considered to classify PLOS categories of off-street pedestrian facilities. And from the analysis six LOS categories i.e. A, B, C, D, E and F which are having different ranges of the four parameters are defined. From the study it found that pedestrian faces a good level of service of “A”, “B” and “C” are more often than at poor levels of service of “D”, “E” and “F”. From all the six clustering methods K-means is found to be the most suitable one to classify PLOS in Indian context

14-02 Developing Public Health Performance Measures to Capture the Effects of Transportation Facilities on Multiple Public Health Outcomes

Increasingly, federal transportation and public health agencies are working together to identify transportation investments that improve public health. Investments in transportation infrastructure represent one method to utilize transportation to improve public health outcomes. The ideal transportation investment is one that not only provides safe access for pedestrians, bicyclists, motorists and transit riders, but it also promotes more utilitarian or recreational trips for walking and biking in an environment of safe air quality. However, public health objectives can be at conflict when designing transportation infrastructure to support active commuting. For example, infrastructure investments may be made that promote physical activity through utilitarian commuting, yet at the same time, the investment may be made in an area that is characterized by poor air quality or creates an unsafe condition. The purpose of the research is to identify potential performance measures that can foster improved decision making around these investments. The key research contribution is the development of performance measures that can be used in the field to evaluate multiple public health concerns and improve decision making. Secondly, it advances strategies to effectively capture the dimension of safety and physical activity in a manner that considers the conditions under which pedestrian and bicycling activity is likely to increase. The objectives of the project are accomplished through the use and integration of multiple methods, including student-based project learning, expert surveys, content analysis and quantitative statistical techniques

Path Planning for Robot and Pedestrian Simulations

The thesis is divided into two parts. The first part presents a new proposed method for solving the path planning problem to find an optimal collision-free path between the starting and the goal points in a static environment. Initially, the grid model of the robot's working environment is constructed. Next, each grid cell's potential value in the working environment is calculated based on the proposed potential function. This function guides the robot to move toward the desired goal location, it has the lowest value at the goal location, and the value increase as the robot moves further away. Next, a new method, called Boundary Node Method (BNM), is proposed to find the initial feasible path. In this method, the robot is simulated by a nine-node quadrilateral element, where the centroid node represents the robot's position. The robot moves in the working environment toward the goal point with eight-boundary nodes based on the boundary nodes' characteristics. In the BNM method, the initial feasible path is generated from the sequence of the waypoints that the robot has to traverse as it moves toward the goal point without colliding with obstacles. The BNM method can generate the path safely and efficiently. However, the path is not optimal in terms of the total path length. An additional method, called Path Enhancement Method (PEM), is proposed to construct an optimal or near-optimal collision-free path. The generated path obtained by BNM and PEM may contain sharp turns. Therefore, the cubic spline interpolation is used to create a continuous smooth path that connects the starting point to the goal point. The performance of the proposed method is compared with the other path planning methods in terms of path length and computational time. Moreover, the multi-goal path planning problem is investigated to find the shortest collision-free path connecting a given set of goal points in the robot working environment. Furthermore, to verify the performance of the proposed method, several experimental tests have been performed on the e-puck robot with different obstacle configurations and various positions of goal points. The experimental results showed that the proposed method could construct the shortest collision-free path and direct the real physical robot to the final destination point. At the end of the first part of the thesis, we investigate the multi-goal path planning problem for the multi-robot system such that several robots reach each goal. In the second part of this thesis, we proposed a new method for simulating pedestrian crowd movement in a virtual environment. The first part of this thesis concerning the generation of the shortest collision-free path is used. In this method, we assumed that the crowd consists of multiple groups with a different number and various types of pedestrians. In this scenario, each group's intention is different for visiting several goal points with varying sequences of the visit. The proposed method uses the multi-group microscopic model to generate a real-time trajectory for each pedestrian navigating in the pedestrianized area of the virtual environment. Additionally, an agent-based model is introduced to simulate pedestrian' behaviours. Based on the proposed method, every single pedestrian in each group can continuously adjust their attributes, such as position, velocity, etc. Moreover, pedestrians optimize their path independently toward the desired goal points while avoiding obstacles and other pedestrians in the scene. At the end of this part of the thesis, a statistical analysis is carried out to evaluate the performance of the proposed method for simulating the crowd movement in the virtual environment. The proposed method implemented for several simulation scenarios under a variety of conditions for a wide range of different parameters. The results showed that the proposed method is capable of describing pedestrian' behaviours in the virtual environment