International Conference on Vehicle Technology and Intelligent Transport Systems最新文献_第2页

Lane Effect of Traffic Flow Analysis in India 印度交通流分析的车道效应

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-26 DOI: 10.5220/0007239302680276

T. Tsuboi

{"title":"Lane Effect of Traffic Flow Analysis in India","authors":"T. Tsuboi","doi":"10.5220/0007239302680276","DOIUrl":"https://doi.org/10.5220/0007239302680276","url":null,"abstract":"The aim of this research is to develop quantitative analysis method for emerging countries, especially focusing on major city in India where they are facing negative impact by transportation such as CO2 emission growth, many traffic fatalities, large fuel consumption, and air pollution as a result. In this research, we installed more than ten traffic monitoring traffic counter cameras in Ahmedabad city of Gujarat state of India. The monitoring cameras detect traffic vehicle and capture several traffic data such as vehicle numbers, vehicle speed, traffic occupancy, vehicle density, gap length between vehicle to vehicle and so on. And each data is collected by every minutes per roads. Therefore the collected data becomes more than 432,000 points per months. In order to analyse the traffic data, author recognize special features of the collected traffic data and the Envelope Observation (EO) for traffic flow characteristics by measurement data is useful for obtaining traffic flow equation. The unique feature of emerging counties traffic data is widely spread plots at the traffic basic characteristics such as traffic density to speed curve and traffic density to traffic volume curve. But there is clearly boundary line in those curves. Author uses EO analysis to fit traffic flow parameters to these boundary lines. By defining traffic flow parameters, it is able to obtain the traffic flow value such as free speed traffic flow, critical traffic volume, and critical traffic density. After obtaining traffic parameters, it is able to create traffic flow equation for each measured road and even each lane of its road. The uniqueness of this research is extension of analysis for the road lane effect for the traffic congestion by correlation ratio analysis between driving lane and passing lane of each road. As the result of this analysis, it becomes clear that congestion condition of roads makes the different traffic flow characteristics by driving and passing lane. This is the first time to explain the lane effect for traffic congestion on the basis of the EO method.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133060555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart Parking Zones using Dual Mode Routed Bluetooth Fogged Meshes 使用双模式路由蓝牙雾化网格的智能停车区

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-26 DOI: 10.5220/0007734802110222

Paul Seymer, D. Wijesekera, C. Kan

引用次数: 4

A Traffic Signal Controller for an Isolated Intersection using Fuzzy Logic Model 基于模糊逻辑模型的孤立交叉口交通信号控制器

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-19 DOI: 10.5220/0007709603960403

Nada B. AlNaser, Y. Hawas

引用次数: 0

Mental Imagery for Intelligent Vehicles 智能车辆的心理意象

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-19 DOI: 10.5220/0007657500430051

Alice Plebe, R. Donà, G. P. R. Papini, M. Lio

{"title":"Mental Imagery for Intelligent Vehicles","authors":"Alice Plebe, R. Donà, G. P. R. Papini, M. Lio","doi":"10.5220/0007657500430051","DOIUrl":"https://doi.org/10.5220/0007657500430051","url":null,"abstract":"The research in the design of self-driving vehicles has been boosted, in the last decades, by the developments in the fields of artificial intelligence. Despite the growing number of industrial and research initiatives aimed at implementing autonomous driving, none of them can claim, yet, to have reached the same driving performance of a human driver. In this paper, we will try to build upon the reasons why the human brain is so effective in learning tasks as complex as the one of driving, borrowing explanations from the most established theories on sensorimotor learning in the field of cognitive neuroscience. The contribution of this work would like to be a new point of view on how the known capabilities of the brain can be taken as an inspiration for the implementation of a more robust artificial driving agent. In this direction, we consider the Convergencedivergence Zones (CDZs) as the most prominent proposal in explaining the simulation process underlying the human sensorimotor learning. We propose to use the CDZs as a “template” for the implementation of neural network models mimicking the phenomenon of mental imagery, which is considered to be at the heart of the human ability to perform sophisticated sensorimotor controls such driving.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114945073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Object Detection Probability for Highly Automated Vehicles: An Analytical Sensor Model 高度自动化车辆的目标检测概率:一个解析传感器模型

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-16 DOI: 10.5220/0007767602230231

F. Schiegg, I. Llatser, T. Michalke

引用次数: 10

On-demand Ride-sharing Services with Meeting Points 带会议点的按需拼车服务

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-12 DOI: 10.5220/0007709101170125

Sevket Gökay, Andreas Heuvels, Karl-Heinz Krempels

引用次数: 5

Training and Validation Methodology for Range Estimation Algorithms 距离估计算法的训练和验证方法

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-12 DOI: 10.5220/0007717004340443

Patrick Petersen, Adam Thor Thorgeirsson, Stefan Scheubner, S. Otten, F. Gauterin, E. Sax

{"title":"Training and Validation Methodology for Range Estimation Algorithms","authors":"Patrick Petersen, Adam Thor Thorgeirsson, Stefan Scheubner, S. Otten, F. Gauterin, E. Sax","doi":"10.5220/0007717004340443","DOIUrl":"https://doi.org/10.5220/0007717004340443","url":null,"abstract":"Estimating the range of battery electric vehicles is one of the most challenging topics for the current trend in the automotive industry, the electrification of vehicles. Range anxiety still limits the adoption of battery electric vehicles. Since the range estimation is dependent on different influencing factors, complex algorithms to accurately estimate the vehicles consumption are required. To evaluate the accuracy of data-driven machine learning algorithms, an exhaustive training and validation procedure is mandatory. In this paper, we propose a novel methodology for the development and validation of range estimation algorithms based on machine learning validation approaches. The proposed methodology considers the evaluation of driver-specific and driver-unspecific performance. In addition, an error measure is introduced to assess the performance of range estimation algorithms. This approach is demonstrated and evaluated on a set of recorded real-world driving data. It is shown that our approach helps to analyze the performance of the range estimation algorithm and the influences of different parameter sets.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114639124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Time Zone Impact for Traffic Flow Analysis of Ahmedabad City in India 印度艾哈迈达巴德市交通流量分析的时区影响

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-12 DOI: 10.5220/0007708103880395

T. Tsuboi

{"title":"Time Zone Impact for Traffic Flow Analysis of Ahmedabad City in India","authors":"T. Tsuboi","doi":"10.5220/0007708103880395","DOIUrl":"https://doi.org/10.5220/0007708103880395","url":null,"abstract":"This paper describes time zone impact for traffic flow analysis in an one of major city in India based on one month real traffic monitoring big data. The target city is Ahmedabad of Gujarat state where is located in the west part of India. The current population in Ahmedabad is about 7.8 Million and it is one of rapid economic growing city. These days, the traffic congestion in the city become one of major issues. In order to analyse traffic congestion, large amount of the traffic big data is needed and it is collected through the traffic monitoring camera. The measurement of the data is traffic density, traffic occupancy and average of speed of vehicles which is measured at the road by every minute. The traffic data in emerging countries is not well analyzed so far because of difficulty of collecting traffic data. Author has a chance to involve one of traffic project which provides traffic condition to the drivers through traffic information boards and makes suggestions for avoiding traffic congestion. The current judgement of the traffic congestion is based on the occupancy of the road which is one of traffic flow parameters. This occupancy is not so accuracy sometimes because of difficulty of 100 % vehicle sensing. In this paper, it describes the time zone basis traffic flow analysis in the traffic flow characteristics such as traffic density to average vehicle speed curve, traffic density to traffic volume curve, and traffic volume to average vehicle speed. This analysis is able to identify the effect of time zone to traffic flow condition and provide more appropriate occupancy level for traffic congestion.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128086249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Where Am I: Localization and 3D Maps for Autonomous Vehicles 我在哪里:自动驾驶汽车的定位和3D地图

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-11 DOI: 10.5220/0007718404520457

Farzeen Munir, Shoaib Azam, A. Sheri, Yeongmin Ko, M. Jeon

引用次数: 10

Identification of the Impact of GNSS Positioning on the Evaluation of Informative Speed Adaptation GNSS定位对信息速度自适应评价影响的识别

International Conference on Vehicle Technology and Intelligent Transport Systems Pub Date : 2019-10-11 DOI: 10.5220/0007656903050311

J. Raiyn

{"title":"Identification of the Impact of GNSS Positioning on the Evaluation of Informative Speed Adaptation","authors":"J. Raiyn","doi":"10.5220/0007656903050311","DOIUrl":"https://doi.org/10.5220/0007656903050311","url":null,"abstract":"Autonomous vehicles (AVs) are self-driving vehicles that operate and perform tasks under their own power. They may possess features such as the capacity to sense environment, collect information, and manage communications with other vehicles. Many autonomous vehicles in development use a combination of cameras, various kinds of sensors, GPS, GNSS, radar, and LiDAR, with an on-board computer. These technologies work together to map the vehicle’s position and its proximity to everything around it. To estimate AV positioning, GNSS data are used. However, the quality of raw GNSS observables is affected by a number of factors that originate from satellites, signal propagation, and receivers. The prevailing speed limit is generally obtained by a real-time map matching process that requires positioning data based on a GNSS and a digital map with up to date speed limit information. This paper focuses on the identification of the impact of GNSS positioning error data on the evaluation of informative speed adaptation. It introduces a new methodology for increasing the accuracy and reliability of positioning information, which is based on a position error model. Applying the sensitivity analysis method to informative speed adaptation yields interesting results which show that the performance of informative speed adaptation is positively affected by minimizing positioning error.","PeriodicalId":218840,"journal":{"name":"International Conference on Vehicle Technology and Intelligent Transport Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134333629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0