scholarly journals Multiple Lanes Identification using Novel Region-Based Iterative Seed Method

2019 ◽  
Vol 8 (9S4) ◽  
pp. 171-177
Keyword(s):  
Distance Measure ◽  
Point Of View ◽  
Lane Detection ◽  
Learning Approaches ◽  
Driver Assistance ◽  
The Road ◽  
Performance Point ◽  
Segmented Image ◽  
Car Accidents ◽  
Seed Method

Now a days, in each year thousands of car accidents occurs in India. Therefore, most of the automobile companies tries to give best Advanced Driver Assistance System (ADAS) to avoid the accidents. The lane detection is one of the approach to design the ADAS, if the vehicles follows the lane then there is less chance to get an accident. The detected information of lane path is used for controlling the vehicles and giving alerts to drivers. Therefore most of the researchers are attracted towards this field. But, due to the varying road conditions, it is very difficult to detect the lane. The computer vision and machine learning approaches are presents in most of the articles. In this paper, a seed method is designed for the road picture segmentation for the multi-lane detection. The sparking method is applied to the segmented image to increase the speed of computer. In this proposed method, the target grids are selected form the road lane. Distance is calculated for road and lane. Based on the distance measure, the optimal segments are chosen, following an iterative procedure. The accuracy, sensitivity and specificity are considered for the performance point of view for this paper. The calculated maximum detected accuracy is 98.89 %.

scholarly journals (DCNN) Deep Convolution Neural Network Classifier and (EW-CSA) Earth Worm-Crow Search Algorithm for Lane Detection

2019 ◽  
Vol 9 (1) ◽  
pp. 4892-4901
Keyword(s):  
Neural Network ◽  
Search Algorithm ◽  
Lane Detection ◽  
Second Phase ◽  
Vehicle Speed ◽  
Learning Approaches ◽  
The Road ◽  
Optimal Weights ◽  
Car Accidents ◽  
Two Phases

Every year in India, most of the car accidents are occurs and affects on number of lives. Most of the road accidents are occurs due to driver’s inattention and fatigue. Drivers require to focus on different circumstances, together with vehicle speed and path, the separation between vehicles, passing vehicles, and potential risky or uncommon events ahead. Also the accident occurs due to the who bring into play cell phones at the same time as driving, drink and drive, etc. Due to this, most of the companies of automobiles tries to make available best Advanced Driver Assistance System (ADAS) to the customer to avoid the accidents. The lane detection approach is one of the method provided by automobile companies in ADAS, in which the vehicle must follows the lane. Therefore, there is less chance to get an accident. The information obtained from the lane is used to alert the driver. Therefore most of the researchers are attracted towards this field. But, due to the varying road circumstances, it is very difficult to detect the lane. The computer apparition and machine learning approaches are presents in most of the articles. In this article, we presents the deep learning scheme for identification of lane. There are two phases are presents in this work. In a first phase the image transformation is done and in second phase lane detection is occurred. At first, the proposed model gets the numerous lane pictures and changes the picture into its relating Bird's eye view picture by using Inverse perspective mapping transformation. The Deep Convolutional Neural Network (DCNN) classifier to identify the lane from the bird’s eye view image. The Earth Worm- Crow Search Algorithm (EW-CSA) is designed to help DCNN with the optimal weights. The DCNN classifier gets trained with the view picture from the bird’s eye image and the optimal weights are selected through newly developed EW-CSA algorithm. All these algorithms are performed in MATLAB. The simulation results shows that the exact detection of lane of road. Also, the accuracy, sensitivity, and specificity are calculated and its values are 0.99512, 0.9925, and 0.995 respectively.

scholarly journals Multilane Detection Entropy-Based Fusion Model by using Iterative Seed and Optimized Deep Convolutional Neural Network

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1967-1974
Keyword(s):  
Neural Network ◽  
Search Algorithm ◽  
Lane Detection ◽  
Learning Approaches ◽  
Driver Assistance ◽  
Fusion Model ◽  
Driver Assistance Systems ◽  
Proposed Model ◽  
Segmentation Approach ◽  
Deep Convolution Neural Network

In today’s world, the conditions of road is drastically improved as compared with past decade. Most of the express highways are made up of cement concrete and equipped with increased lane size. Apparently speed of the vehicle will increase. Therefore there are more chances for accidents. To avoid the accidents in recent days driver assistance systems are designed to detect the various lane. The detected information of lane path is used for controlling the vehicles and giving alerts to drivers. In this paper the entropy based fusion approach is presents for detecting multi-lanes. The Earth Worm- Crow Search Algorithm (EW-CSA) which is based on Deep Convolution Neural Network(DCNN) is utilized for consolidating the outcomes. At first, the deep learning approaches for path location is prepared using an optimization algorithm and EW-CSA, which focus on characterizing every pixel accurately and require post preparing activities to surmise path data. Correspondingly, the region based segmentation approach is utilizing for the multi-lane detection. An entropy based fusion model is used because this method preserved all the information in the image and reduces the noise effects. The performance of proposed model is analyzed in terms of accuracy, sensitivity, and specificity, providing superior results with values 0.991, 0.992, and 0.887, respectively

scholarly journals Lane Detection and Lane Change Warning as Advanced Driver Assistance Systems using Computer Vision

2019 ◽  
Vol 9 (2) ◽  
pp. 5540-5543 ◽  
Keyword(s):  
Road Network ◽  
Cost Effective ◽  
Lane Detection ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
Growing Economy ◽  
On The Road ◽  
New Processing ◽  
Processing Techniques

Road ways are the life line of any economy, for a country like India where economy isgrowing rapidly it is putting its toll on every sector for meeting the needs of the growing economy. Good’s and personal transport are becoming vital with time and money aspects and the roads and vehicles on the roads are expected to perform optimally drastically increasing the speed on the road network and constantly increasing and modifying the infrastructure needed to meet the demands. As the speed of the vehicle increases the accident rate and the damage caused by the collision will also increase. Safety of the road network is not to be compromised and proper systems to ensure the safe passage of the vehicle and proper warning systems are to be implemented. This system should be viable in all the condition and should be cost-effective. In this paper we are implementing a vision based system to identify the lane and other vehicles from the video it captures from a properly calibrated camera mounted on the front side of the vehicle. The system is designed to automatically and continuously detect the lines exploiting the new processing techniques and warning the driver if any other is in the breaking distance of the vehicle or if the vehicle is moving out of the lane. Cost effectiveness of the system is a major aspect as many of the available systems use equipment which very good at performing their task but are not affordable. Effort is put in making the system cost effective and not compromising with the reaction time and accuracy..

scholarly journals Multiple Lanes Identification for Advanced Driver Assistance System (ADAS)

2019 ◽  
Vol 8 (5S3) ◽  
pp. 533-538
Keyword(s):  
Lane Detection ◽  
Detection Methods ◽  
Learning Approaches ◽  
Drowsy Driving ◽  
The Road ◽  
Perspective Distortion ◽  
Lane Departure ◽  
Lane Recognition ◽  
Feature Based ◽  
Straight Lines

Now a days, a multi-lane recognition technique that uses the ridge features and the inverse perspective mapping (IPM) is generally used to distinguish lanes since it can evacuate the perspective distortion on lines that lie in parallel in reality. The lane detection is one of the approach to design the ADAS, if the vehicles follows the lane then there is less chance to get an accident. The detected information of lane path is used for controlling the vehicles and giving alerts to drivers. Therefore most of the researchers are attracted towards this field. But, due to the varying road conditions, it is very difficult to detect the lane. The computer vision and machine learning approaches are presents in most of the articles. In this paper, a survey of different method is presents for the road picture segmentation for the multi-lane detection. The Lane Departure Warning (LDW) system can help to reduce vehicle crashes that are caused by careless or drowsy driving. There has been much research on vision based lane detection for the LDW system. In these lane detection methods, color or edge information is utilized as a feature of the lane. The feature-based methods are usually applied to localize the lanes in the road images by extracting low-level features. On the other hand, the model-based methods use several geometrical elements to describe the lanes, including parabolic curves, hyperbola and straight lines. Feature-based methods require a dataset containing several thousand images of the roads with well-painted and prominent lane markings that are subsequently converted to features. Moreover, these methods may suffer from noise.

scholarly journals The Road to Modern Logic—An Interpretation

2001 ◽  
Vol 7 (4) ◽  
pp. 441-484 ◽  
Author(s):  
José Ferreirós
Keyword(s):  
Order Logic ◽  
Point Of View ◽  
First Order Logic ◽  
Theoretical Point ◽  
Primary Role ◽  
Philosophical Discussion ◽  
Modern Logic ◽  
Core System ◽  
First Order ◽  
The Road

AbstractThis paper aims to outline an analysis and interpretation of the process that led to First-Order Logic and its consolidation as a core system of modern logic. We begin with an historical overview of landmarks along the road to modern logic, and proceed to a philosophical discussion casting doubt on the possibility of a purely rational justification of the actual delimitation of First-Order Logic. On this basis, we advance the thesis that a certain historical tradition was essential to the emergence of modern logic; this traditional context is analyzed as consisting in some guiding principles and, particularly, a set of exemplars (i.e., paradigmatic instances). Then, we proceed to interpret the historical course of development reviewed in section 1, which can broadly be described as a two-phased movement of expansion and then restriction of the scope of logical theory. We shall try to pinpoint ambivalencies in the process, and the main motives for subsequent changes. Among the latter, one may emphasize the spirit of modern axiomatics, the situation of foundational insecurity in the 1920s, the resulting desire to find systems well-behaved from a proof-theoretical point of view, and the metatheoretical results of the 1930s. Not surprisingly, the mathematical and, more specifically, the foundational context in which First-Order Logic matured will be seen to have played a primary role in its shaping.Mathematical logic is what logic, through twenty-five centuries and a few transformations, has become today. (Jean van Heijenoort)

Lane Detection Algorithm Based on Genetic Algorithm and its Parallel Computing Realization

2012 ◽  
Vol 479-481 ◽  
pp. 65-70
Author(s):  
Xiao Hui Zhang ◽  
Liu Qing ◽  
Mu Li
Keyword(s):  
Genetic Algorithm ◽  
Data Transmission ◽  
High Speed ◽  
High Performance ◽  
Large Data ◽  
Detection Algorithm ◽  
Lane Detection ◽  
The Road ◽  
Time Problem ◽  
High Speed Data

Based on the target detection of alignment template, the paper designs a lane alignment template by using correlation matching method, and combines with genetic algorithm for template stochastic matching and optimization to realize the lane detection. In order to solve the real-time problem of lane detection algorithm based on genetic algorithm, this paper uses the high performance multi-core DSP chip TMS320C6474 as the core, combines with high-speed data transmission technology of Rapid10, realizes the hardware parallel processing of the lane detection algorithm. By Rapid10 bus, the data transmission speed between the DSP and the DSP can reach 3.125Gbps, it basically realizes transmission without delay, and thereby solves the high speed transmission of the large data quantity between processor. The experimental results show that, no matter the calculated lane line, or the running time is better than the single DSP and PC at the parallel C6474 platform. In addition, the road detection is accurate and reliable, and it has good robustness.

Road Parameter-Based Driver Assistance System for Safe Driving

2019 ◽  
Vol 2 (4) ◽  
pp. 253-262
Author(s):  
Sai Charan Addanki ◽  
Keyword(s):  
Driver Assistance System ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
The Road ◽  
Lane Tracking ◽  
Road Type ◽  
Key Aspects ◽  
Type Classification

One of the key aspects of Advanced Driver Assistance Systems (ADAS) is ensuring the safety of the driver by maintaining a safe drivable speed. Overspeeding is one of the critical factors for accidents and vehicle rollovers, especially at road turns. This article aims to propose a driver assistance system for safe driving on Indian roads. In this regard, a camera-based classification of the road type combined with the road curvature estimation helps the driver to maintain a safe drivable speed primarily at road curves. Three Deep Convolutional Neural Network (CNN) models viz. Inception-v3, ResNet-50, and VGG-16 are being used for the task of road type classification. In this regard, the models are validated using a self-created dataset of Indian roads and an optimal performance of 83.2% correct classification is observed. For the calculation of road curvature, a lane tracking algorithm is used to estimate the curve radius of a structured road. The road type classification and the estimated road curvature values are given as inputs to a simulation-based model, CARSIM (vehicle road simulator to estimate the drivable speed). The recommended speed is then compared and analyzed with the actual speeds obtained from subjective tests.

THE ROAD AHEAD TO BETTER MEDICAL CARE FOR CHILDREN

PEDIATRICS ◽  
1950 ◽  
Vol 6 (3) ◽  
pp. 553-556
Keyword(s):  
Child Health ◽  
Medical Care ◽  
Medical Center ◽  
Point Of View ◽  
Medical Services ◽  
High Quality ◽  
The Road ◽  
Provide Child Care ◽  
Ultimate Objective ◽  
The Many

THE road to better child health has been discussed in relation to the doctor and his training, health services and their distribution. We have dealt with the unavoidable question of costs. Particular attention has been given to some of the advantages and dangers of decentralization of pediatric education and services. Each of the various subjects has been discussed from the point of view of its bearing on the ultimate objective of better health for all children and the steps necessary to attain this goal. Now, we may stand back from the many details of the picture, view the whole objectively and note its most outstanding features. First is the fact that the improvement of child health depends primarily upon better training for all doctors who provide child care, general practitioners as well as specialists. This is the foundation without which the rest of the structure cannot stand. The second dominant fact is the need for extending to outlying and isolated areas the high quality medical care of the medical centers, without at the same time diluting the service or training at the center. The road to better medical care, therefore, begins at the medical center and extends outward through a network of integrated community hospitals and health centers, finally reaching the remote and heretofore isolated areas. Inherent in all medical schools is a unique potential for rendering medical services as well as actually training physicians. The very nature of medical education—whereby doctors in training work under the tutelage of able specialists in the clinic, hospital ward, and out-patient department—provides medical services of high quality to people in the neighboring communities.

The Potential of The Hotel Industry In Pandemic Era Based On Finance Performance Point Of View, Case Study: Indonesia

2021 ◽  
Vol 1 (1) ◽  
pp. 111-123
Author(s):  
Anton Effendi ◽  
◽  
Bambang Hadi Prabowo
Keyword(s):  
Hospitality Industry ◽  
Stock Exchange ◽  
Hotel Industry ◽  
Secondary Data ◽  
Reliable Data ◽  
Point Of View ◽  
Threshold Autoregressive ◽  
Performance Point ◽  
Occupancy Rates

This article aims to investigate and analyze the potential of the hospitality industry by comparing the potential occupancy rates and hotel revenues of foreign and domestic tourists. This investigation uses an investigation of company data obtained from reports from hotel companies throughout Indonesia which are listed on the Indonesia Stock Exchange and secondary data obtained from world banks and other reliable data. This study uses behavioral data analysis using Threshold Autoregressive from 2000 to 2019. It was found that domestic tourists are a new hope that needs to be considered in surviving and restoring the hospitality industry after being exposed to the COVID-19 pandemic which has led hotel companies. temporarily closed operations and part of the hotel went bankrupt. Optimization of domestic tourists allowed the hotel industry to develop rapidly after the Covid-19 pandemic ended.

scholarly journals Design & Weight Optimization of a Wheel Rim for Sport Utility Vehicle.

2018 ◽  
Vol 172 ◽  
pp. 03006
Author(s):  
Harish Panjagala ◽  
Balakrishna M ◽  
Shasikant Kushnoore ◽  
E L N Rohit Madhukar
Keyword(s):  
Structural Analysis ◽  
Point Of View ◽  
Weight Optimization ◽  
Strength Assessment ◽  
Suitable Material ◽  
The Road ◽  
Wheel Rim ◽  
Standard Values ◽  
Design Weight ◽  
Structural Point

Automobile have various parts which are important for good running of the vehicle. The most important safety components from a structural point of view are the road wheels. They are required to be lighter and more fascinating to the buyer all the time. This implies that it's important to perform a lot of accurate strength assessment on wheel styles. The wheel rim plays a major role in vehicle dynamics. This paper deals with the design and model of different wheel rims based on weight optimization and also structural analysis has been carried out. It has been compared with standard values by varying two different materials. In addition, from the obtained outputs of simulations and the weight optimization, we suggested Aluminium alloys as most suitable material for SUV. Model is created by using SOLIDWORKS software 2015 and structural analysis &; weight optimization is done by using ANSYS WORKBENCH 16.0.

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