scholarly journals A multi-objective evolutionary scheme for control points deployment in intelligent transportation systems

2021 ◽  
Vol 11 (2) ◽  
pp. 1641
Author(s):  
Martin Luther Mfenjou ◽  
Ado Adamou Abba Ari ◽  
Arouna Ndam Njoya ◽  
Kolyang Kolyang ◽  
Wahabou Abdou ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Optimization Methods ◽  
Transportation Systems ◽  
Control Points ◽  
Nsga Ii ◽  
Multi Objective ◽  
Strength Pareto Evolutionary Algorithm ◽  
Evolutionary Scheme ◽  
And Performance ◽  
Good Coverage

One of the problems that hinder emergency in developing countries is the problem of monitoring a number of activities on inter-urban roadway networks. In the literature, the use of control points is proposed in the context of these countries in order to ensure efficient monitoring, by ensuring a good coverage while minimizing the installation costs as well as the number of accidents across these road networks. In this work, we propose an optimal deployment of these control points from several optimization methods based on some evolutionary multi-objective algorithms: the non-dominated sorting genetic algorithm-II (NSGA-II); the multi-objective particle swarm optimization (MOPSO); the strength Pareto evolutionary algorithm -II (SPEA-II); and the Pareto envelope based selection algorithm-II (PESA-II). We performed the tests and compared these deployments using Pareto front and performance indicators like the spread and hypervolume and the inverted generational distance (IGD). The results obtained show that the NSGA-II method is the most adequate in the deployment of these control points.

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

MAC and Routing Protocols for Vehicle to Vehicle Communications

2010 ◽  
pp. 105-119
Author(s):  
Xiaobo Long ◽  
Biplab Sikdar
Keyword(s):  
Routing Protocols ◽  
Intelligent Transportation Systems ◽  
Communication Systems ◽  
Transportation Systems ◽  
Node Mobility ◽  
Medium Access ◽  
High Data ◽  
Vehicle To Vehicle ◽  
And Performance ◽  
Access To Data

Numerous efforts are currently under progress to enhance the safety and efficiency of vehicular traffic through intelligent transportation systems. In addition, the growing demand for access to data and information from human users on the go has created the need for advanced vehicle-to-vehicle and vehicleto- roadside communication systems capable of high data rates and amenable to high degrees of node mobility. Vehicular communications and networks are expected to be used for a number of purposes such as for enabling mobile users to transfer data and information from other networks such as the Internet and also for implementing services such as Intersection Decision Systems (IDS), Automated Highway Systems (AHS), and Advanced Vehicle Safety Systems (AVS). In this chapter the authors describe medium access control (MAC) and routing protocols for vehicular networks and the various factors that affect their design and performance.

Guided Search-Based Multi-Objective Evolutionary Algorithm for Grid Workflow Scheduling

2019 ◽  
pp. 166-195
Author(s):  
Ritu Garg
Keyword(s):  
Performance Metrics ◽  
Scheduling Algorithm ◽  
Economic Cost ◽  
Nsga Ii ◽  
Guided Search ◽  
Multi Objective ◽  
Grid Workflow ◽  
Global Computing ◽  
Search Mechanism ◽  
And Performance

The computational grid provides the global computing infrastructure for users to access the services over a network. However, grid service providers charge users for the services based on their usage and QoS level specified. Therefore, in order to optimize the grid workflow execution, a robust multi-objective scheduling algorithm is needed considering economic cost along with execution performance. Generally, in multi-objective problems, simulations rely on running large number of evaluations to obtain the accurate results. However, algorithms that consider the preferences of decision maker, convergence to optimal tradeoff solutions is faster. Thus, in this chapter, the author proposed the preference-based guided search mechanism into MOEAs. To obtain solutions near the pre-specified regions of interest, the author has considered two MOEAs, namely R-NSGA-II and R-ε-MOEA. Further, to improve the diversity of solutions, a modified form called M-R-NSGA-II is used. Finally, the experimental settings and performance metrics are presented for the evaluation of the algorithms.

Video Event Detection Technology and its Application in Intelligent Transportation

2012 ◽  
Vol 198-199 ◽  
pp. 1225-1230
Author(s):  
Jin Hui Lan ◽  
Min Guo ◽  
Xiao Jie Liu
Keyword(s):  
Event Detection ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Surveillance Systems ◽  
Advantages And Disadvantages ◽  
Video Event ◽  
Detection Technology ◽  
Video Event Detection ◽  
And Performance

Video event detection technology has become a hot issue in the Intelligent Transportation Systems(ITS) research. It mainly uses in highways, tunnels, urban roads and other video surveillance systems. This paper makes a brief overview on the development of video detection technology at home and abroad. It describes the working principles and key technologies of the two kinds of incident detection technology based on virtual detection loop and video vehicle tracking, compare above two technology to sum up their advantages and disadvantages. At last it introduces the typical products of the domestic and foreign video event detection technology, their applications and performance index.

scholarly journals A Secure, Lightweight, and Anonymous User Authentication Protocol for IoT Environments

2021 ◽  
Vol 13 (16) ◽  
pp. 9241
Author(s):  
Seunghwan Son ◽  
Yohan Park ◽  
Youngho Park
Keyword(s):  
Intelligent Transportation Systems ◽  
User Authentication ◽  
Formal Analysis ◽  
Bilinear Pairing ◽  
Transportation Systems ◽  
Authentication Scheme ◽  
Iot Devices ◽  
And Performance ◽  
Exclusive Or ◽  
The Internet Of Things

The Internet of Things (IoT) is being applied to various environments such as telecare systems, smart homes, and intelligent transportation systems. The information generated from IoT devices is stored at remote servers, and external users authenticate to the server for requesting access to the stored data. In IoT environments, the authentication process is required to be conducted efficiently, and should be secure against various attacks and ensure user anonymity and untraceability to ensure sustainability of the network. However, many existing protocols proposed in IoT environments do not meet these requirements. Recently, Rajaram et al. proposed a paring-based user authentication scheme. We found that the Rajaram et al. scheme is vulnerable to various attacks such as offline password guessing, impersonation, privileged insider, and known session-specific temporary information attacks. Additionally, as their scheme uses bilinear pairing, it requires high computation and communication costs. In this study, we propose a novel authentication scheme that resolves these security problems. The proposed scheme uses only hash and exclusive-or operations to be applicable in IoT environments. We analyze the proposed protocol using informal analysis and formal analysis methods such as the BAN logic, real-or-random (ROR) model, and the AVISPA simulation, and we show that the proposed protocol has better security and performance compared with existing authentication protocols. Consequently, the proposed protocol is sustainable and suitable for real IoT environments.

scholarly journals Subtleties of extrinsic calibration of cameras with non-overlapping fields of view

2019 ◽  
Vol 86 (7-8) ◽  
pp. 433-442
Author(s):  
Zaijuan Li ◽  
Volker Willert
Keyword(s):  
Intelligent Transportation Systems ◽  
Image Data ◽  
Optimization Methods ◽  
Transportation Systems ◽  
Quality Measure ◽  
Experimental Realization ◽  
Calibration Problem ◽  
Measurement Science ◽  
Calibration Accuracy ◽  
Planar Calibration

AbstractThe calibration of the relative pose between rigidly connected cameras with non-overlapping fields of view (FOV) is a prerequisite for many applications. In this paper, the subtleties of the experimental realization of such calibration optimization methods like in (Z. Liu, et al., Measurement Science and Technology, 2011, Z. Li, V. Willert, Intelligent Transportation Systems (ITSC), 2018) are presented. Two strategies that could be adapted to certain optimization processes to find better local minima are evaluated. The first strategy is a careful measurement acquisition of pose pairs for solving the calibration problem, which improves the accuracy of the initial value for the following non-linear refinement. The second strategy is the introduction of a quality measure for the image data used for the calibration, which is based on the projection size of the known planar calibration patterns on the image. We show that introducing an additional weighting to the optimization objective chosen as a function of that quality measure improves calibration accuracy and increases robustness against noise. The above strategies are integrated into different setups and their improvement is demonstrated both in simulation and real-world experiment.

scholarly journals Efficient multi-objective optimization methods for computationally intensive urban water resources models

2014 ◽  
Vol 17 (1) ◽  
pp. 36-55 ◽  
Author(s):  
Mohammad Mortazavi-Naeini ◽  
George Kuczera ◽  
Lijie Cui
Keyword(s):  
Ant Colony Optimization ◽  
Water Resource ◽  
Optimization Methods ◽  
Optimization Method ◽  
Ant Colony ◽  
Urban Water ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

Multi-objective optimization methods require many thousands of objective function evaluations. For urban water resource problems such evaluations can be computationally very expensive. The question as to which optimization method is the best choice for a given function evaluations budget in urban water resource problems remains unexplored. The main objective of this paper is to address this question. The second objective is to develop a new optimization algorithm, efficient multi-objective ant colony optimization-I (EMOACO-I), which exploits the good performance of ant colony optimization enhanced using ideas borrowed from evolutionary optimization. Its performance was compared against three established methods (NSGA-II, SMPSO, εMOEA) using two case studies based on the urban water resource systems serving two major Australian cities. The case study problems involved two or three objectives and 10 or 13 decision variables affecting infrastructure investment and system operation. The results show that NSGA-II was the worst performing method. However, none of the remaining methods was unambiguously superior. For example, while EMOACO-I converged more rapidly, its diversity was comparable but not superior to the other methods. Greater differences in performance were found as the number of objectives and case study complexity increased. This suggests that pooling the results from a number of methods could help guard against the vagaries in performance of individual methods.

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