Identification of Hazardous Road Locations for Pedestrians

AbstractHot zone methodology is promising in the identification of hazardous road locations. The key steps involve geo-validation of road crashes, segmentation of road network into basic spatial units (BSUs), calculation of actual crash intensity, definition of threshold value, and examination of spatial proximity of BSUs. This research applies the hot zone methodology to identify dangerous road locations for pedestrians during the study period of 2005 to 2007 in Kwun Tong District of Hong Kong. In particular, the crash intensity was calculated by a casualty-weighted method, which assigns different weights to different injury severity types. Two negative binomial regression models were employed to determine the threshold values. One could be treated as a base model which includes the length of BSU as the only explanatory variable. The other, regarded as a full model, introduces diverse environmental variables that might have influenced the distribution of pedestrian casualties

Naïve Bayes Classifier to Mitigate the DDoS Attacks Severity in Ad-Hoc Networks

Ad-Hoc networks are becoming more popular due to their unique characteristics. As there is no centralized control, these networks are more vulnerable to various attacks, out of which Distributed Denial of Service (DDoS) attacks are considered as more severe attacks. DDoS attack detection and mitigation is still a challenging issue in Ad-Hoc Networks. The existing solutions consider the fixed or dynamic threshold value to detect the DDoS attacks without any trained data, and very few existing solutions use machine learning algorithms to detect these attacks. However, existing solutions are inefficient to handle when DDoS attackers’ perform this attack through bursty traffic, packet size, and fake packets flooding. We have proposed DDoS attack severity mitigation solution. Out DDoS mitigation solution consists of new network node authentication module and naïve bayes classifier module to detect and isolate the DDoS attack traffic patterns. Our simulation results show that naïve bayes DDoS attack traffic classification out performs in the hostile environment and secure the legitimate traffic from DDoS attack

Walkable City and Military Enclaves: Analysis and Decision-Making Approach to Support the Proximity Connection in Urban Regeneration

Accessibility and urban walkability are the cornerstones of urban policies for the contemporary city, which needs to be oriented towards sustainable development principles and models. Such aims are included in the objectives of the 2030 Agenda, as well as in the ambitious objectives of the ‘European Green Deal’. These concepts are closely linked to the paradigm of a sustainable city—livable, healthy and inclusive—based on a system of high-quality public spaces and on a network of services and infrastructures, both tangible and intangible, capable of strengthening and building new social, economic and environmental relationships. It is necessary to recognize potential opportunities for connection and permeability in consolidated urban environments. These are very often fragmented and are characterized by enclaves of very different kinds. Ghettoes and gated communities, old industrial plants and military installations and facilities, to cite a few, represent examples of cases where closures on urban fabrics are realized, impeding full walkability and accessibility. Within such a framework, the present research is aimed at focusing on a particular set of enclaves, such as those represented by the military sites being reconfigured to civilian use, a phenomenon that characterizes many urban areas in the world; in Europe; and in Italy, in particular, given the recent history and the Cold War infrastructure heritage. In such a sense, the city of Cagliari (Sardinia Island, Italy) represents an interesting case study as it is characterized by the presence of a series of military complexes; real ‘enclaves’ influencing the proximity connections; and, more generally, walkability. Building on previous research and analysis of policies and projects aimed at reintroducing, even partially, this military asset into civilian life (Green Barracks Project (GBP)-2019), this paper proposes and applies a methodology to evaluate the effects of urban regeneration on walkability in a flexible network logic, oriented to the ‘15 min city’ model or, more generally, to the renewed, inclusive, safe “city of proximity”, resilient and sustainable

Development of a Remotely Accessible Wireless Testbed for Performance Evaluation of AMI Related Protocols

Although smart meters are deployed in many countries, the data collection process from smart meters in Smart Grid (SG) still has some challenges related to consumer privacy that needs to be addressed. Referred to as Advanced Metering Infrastructure (AMI), the data collected and transmitted through the AMI can leak sensitive information about the consumers if it is sent as a plaintext. While many solutions have been proposed in the past, the deployment of these solutions in real-life was not possible since the actual AMIs were not accessible to researchers. Therefore, a lot of solutions relied on simulations which may not be able to capture the real performance of these solutions. In this thesis, two 802.11s wireless mesh-based SG AMI network testbeds are developed with Beaglebone Black and Raspberry Pi 3 boards to provide a baseline for the simulations. The Raspberry Pi 3 testbed is also configured to be remotely accessible

THREE TEMPORAL PERSPECTIVES ON DECENTRALIZED LOCATION-AWARE COMPUTING: PAST, PRESENT, FUTURE

Durant les quatre dernières décennies, la miniaturisation a permis la diffusion à large échelle des ordinateurs, les rendant omniprésents. Aujourd’hui, le nombre d’objets connectés à Internet ne cesse de croitre et cette tendance n’a pas l’air de ralentir. Ces objets, qui peuvent être des téléphones mobiles, des véhicules ou des senseurs, génèrent de très grands volumes de données qui sont presque toujours associés à un contexte spatiotemporel. Le volume de ces données est souvent si grand que leur traitement requiert la création de système distribués qui impliquent la coopération de plusieurs ordinateurs. La capacité de traiter ces données revêt une importance sociétale. Par exemple: les données collectées lors de trajets en voiture permettent aujourd’hui d’éviter les em-bouteillages ou de partager son véhicule. Un autre exemple: dans un avenir proche, les données collectées à l’aide de gyroscopes capables de détecter les trous dans la chaussée permettront de mieux planifier les interventions de maintenance à effectuer sur le réseau routier. Les domaines d’applications sont par conséquent nombreux, de même que les problèmes qui y sont associés. Les articles qui composent cette thèse traitent de systèmes qui partagent deux caractéristiques clés: un contexte spatiotemporel et une architecture décentralisée. De plus, les systèmes décrits dans ces articles s’articulent autours de trois axes temporels: le présent, le passé, et le futur. Les systèmes axés sur le présent permettent à un très grand nombre d’objets connectés de communiquer en fonction d’un contexte spatial avec des temps de réponses proche du temps réel. Nos contributions dans ce domaine permettent à ce type de système décentralisé de s’adapter au volume de donnée à traiter en s’étendant sur du matériel bon marché. Les systèmes axés sur le passé ont pour but de faciliter l’accès a de très grands volumes données spatiotemporelles collectées par des objets connectés. En d’autres termes, il s’agit d’indexer des trajectoires et d’exploiter ces indexes. Nos contributions dans ce domaine permettent de traiter des jeux de trajectoires particulièrement denses, ce qui n’avait pas été fait auparavant. Enfin, les systèmes axés sur le futur utilisent les trajectoires passées pour prédire les trajectoires que des objets connectés suivront dans l’avenir. Nos contributions permettent de prédire les trajectoires suivies par des objets connectés avec une granularité jusque là inégalée. Bien qu’impliquant des domaines différents, ces contributions s’articulent autour de dénominateurs communs des systèmes sous-jacents, ouvrant la possibilité de pouvoir traiter ces problèmes avec plus de généricité dans un avenir proche. -- During the past four decades, due to miniaturization computing devices have become ubiquitous and pervasive. Today, the number of objects connected to the Internet is in- creasing at a rapid pace and this trend does not seem to be slowing down. These objects, which can be smartphones, vehicles, or any kind of sensors, generate large amounts of data that are almost always associated with a spatio-temporal context. The amount of this data is often so large that their processing requires the creation of a distributed system, which involves the cooperation of several computers. The ability to process these data is important for society. For example: the data collected during car journeys already makes it possible to avoid traffic jams or to know about the need to organize a carpool. Another example: in the near future, the maintenance interventions to be carried out on the road network will be planned with data collected using gyroscopes that detect potholes. The application domains are therefore numerous, as are the prob- lems associated with them. The articles that make up this thesis deal with systems that share two key characteristics: a spatio-temporal context and a decentralized architec- ture. In addition, the systems described in these articles revolve around three temporal perspectives: the present, the past, and the future. Systems associated with the present perspective enable a very large number of connected objects to communicate in near real-time, according to a spatial context. Our contributions in this area enable this type of decentralized system to be scaled-out on commodity hardware, i.e., to adapt as the volume of data that arrives in the system increases. Systems associated with the past perspective, often referred to as trajectory indexes, are intended for the access to the large volume of spatio-temporal data collected by connected objects. Our contributions in this area makes it possible to handle particularly dense trajectory datasets, a problem that has not been addressed previously. Finally, systems associated with the future per- spective rely on past trajectories to predict the trajectories that the connected objects will follow. Our contributions predict the trajectories followed by connected objects with a previously unmet granularity. Although involving different domains, these con- tributions are structured around the common denominators of the underlying systems, which opens the possibility of being able to deal with these problems more generically in the near future

IDENTIFICATION OF HIGH COLLISION LOCATIONS FOR THE CITY OF REGINA USING GIS AND POST-NETWORK SCREENING ANALYSIS

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released the first edition of the Highway Safety Manual (HSM). The HSM introduces a six-step safety management process which provides engineers with a systematic and scientific approach to managing road safety. The first step of this process, network screening, aims to identify the locations that will most benefit from a safety improvement program. The output obtained from network screening is simply a list of locations that have a high concentration of collisions, based on their potential for safety improvement. The ranking naturally tends to lead to the assumption that the most highly ranked locations are the obvious target locations where road authorities should allocate their often-limited road safety resources. Though these locations contain the highest frequency of collisions, they are often spatially unrelated, and scattered throughout the roadway network. Allocating safety resources to these locations may not be the most effective method of increasing road safety. The purpose of this research is to investigate and validate a two-step method of post-network screening analysis, which identifies collision hotzones (i.e., groups of neighboring hotspots) on a road network. The first step is the network screening process described in the HSM. The second step is new and involves network-constrained kernel density estimation (KDE), a type of spatial analysis. KDE uses expected collision counts to estimate collision density, and outputs a graphical display that shows areas (referred to here as hotzones) with high collision densities. A particularly interesting area of application is the identification of high-collision corridors that may benefit from a program of systemic safety improvements. The proposed method was tested using five years of collision data (2005-2009) for the City of Regina, Saskatchewan. Three different network screening measures were compared: 1) observed collision counts, 2) observed severity-weighted collision counts, and 3) expected severity-weighted collision counts. The study found that observed severity-weighted collision counts produced a dramatic picture of the City's hotzones, but this picture could be misleading as it could be heavily influenced by a small number of severe collisions. The results obtained from the expected severity-weighted collision counts smoothed the effects of the severity-weighting and successfully reduced regression-to-the-mean bias. A comparison was made between the proposed approach and the results of the HSM’s existing network screening method. As the proposed approach takes the spatial association of roadway segments into account, and is not limited to single roadway segments, the identified hotzones capture a higher number of expected EPDO collisions than the existing HSM methodology. The study concludes that the proposed two-step method can help transportation safety professionals to prioritize hotzones within high-collision corridors more efficiently and scientifically. Jurisdiction-specific safety performance functions (SPFs) were also developed over the course of this research, for both intersections (three-leg unsignalized, four-leg unsignalized, three and four-leg signalized), and roadway segments (major arterials, minor arterials, and collectors). These SPFs were compared to the base SPFs provided in the HSM, as well as calibrated HSM SPFs. To compare the different SPFs and find the best-fitting SPFs for the study region, the study used statistical goodness-of-fit (GOF) tests and cumulative residual (CURE) plots. Based on the results of this research, the jurisdiction-specific SPFs were found to provide the best fit to the data, and would be the best SPFs for predicting collisions at intersections and roadway segments in the City of Regina

Spatial Analysis for Crashes Involving 25- to 44- Year-Old Drivers in Kansas

In this study, a descriptive and spatial analysis was conducted using crash data, 2013-2017, for 25- to 44- year-old drivers involved in fatal and serious injury crashes that occurred in the state of Kansas. The database integrates crash characteristics, concerning factors like environment, human, roadway, socio-demographic, and vehicle data for all the counties in the state to explore and understand the relationships between fatal and serious injury crashes and potential contributing factors. To understand the trend of fatal and serious injury crashes over the study period, a series of descriptive analyses were performed, which showed crash characteristics analyzed in this study that followed similar trends to most of the past crash studies. This study included 891 fatal and 2491 serious injury crashes along with 19 potential explanatory variables that were analyzed using Ordinary Least Squares (OLS) Regression to identify statistically significant factors, along with hotspots and outliers, in various geographical locations. A spatial model was created using two statistically significant variables to predict the total number of fatal and serious injury crashes, which was validated with the actual 2018 crash data. This spatial analysis and modeling were performed using ArcGIS Pro Software. Most of the statistically significant fatal and serious injury crash hotspots were located in and around Sedgwick county and northeastern Kansas counties like Douglas, Johnson, Leavenworth, and Wyandotte. The model validation for the crashes that occurred in 2018 was underestimated by eight percent, which is considered an acceptable variance. This study is the extension of the previous work that analyzed teenage drivers and also adopted a similar research methodology

Secure and efficient routing in highly dynamic WLAN mesh networks

Recent advances in embedded systems, energy storage, and communication interfaces, accompanied by the falling prices of WLAN routers and a considerable increase in the throughput of a WLAN (IEEE 802.11), have facilitated the proliferation of WLAN Mesh Network (WMN) applications. In addition to their current deployments in less dynamic community networks, WMNs have become a key solution in various highly dynamic scenarios. For instance, WMNs are intended to interconnect self-organized, cooperative, and small Unmanned Aerial Vehicles (UAVs) in a wide range of applications, such as emergency response, environmental monitoring, and ad-hoc network provisioning. Nevertheless, WMNs still face major security challenges as they are prone to routing attacks. Consequently, the network can be sabotaged and, in the case of UAV-WMN-supported missions, the attacker might manipulate payload data or even hijack UAVs. Contemporary security standards, such as the IEEE 802.11i and the security mechanisms of the IEEE 802.11s mesh standard, are vulnerable to routing attacks, as experimentally shown in this research. Therefore, a secure routing protocol is indispensable for making feasible the deployment of WMNs in critical scenarios, such as UAV-WMN-assisted applications. As far as the author of this thesis knows, none of the existing research approaches for secure routing in WMNs have gained acceptance in practice due to their high overhead or strong assumptions. In this research, a new approach, which is called Position-Aware, Secure, and Efficient mesh Routing (PASER), is proposed. This new proposal defeats more attacks than the IEEE 802.11s/i security mechanisms and the well-known, secure routing protocol Authenticated Routing for Ad-hoc Networks (ARAN), without making restrictive assumptions. It is shown that PASER achieves —in realistic UAV-WMN scenarios— similar performance results as the well-established, nonsecure routing protocols Hybrid Wireless Mesh Protocol (HWMP) combined with the IEEE 802.11s security mechanisms. Two representative scenarios are considered: (1) on-demand ubiquitous network access and (2) efficient exploration of sizable areas in disaster relief. The performance evaluation results are produced using an experimentally validated simulation model of WMNs, realistic mobility patterns of UAVs, and an experimentally derived channel model for the air-to-air WMN link between UAVs. The findings of this evaluation are justified by the route discovery delay and the message overhead of the considered solutions