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2020 ITS Year End Index IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-11-10
Presents the 2020 subject/author index for this publication.
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Testing and Evaluating Driverless Vehicles' Intelligence: The Tsinghua Lion Case Study IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-02 Yulin Ma; Zhixiong Li; Miguel Angel Sotelo
It is crucial to test and evaluate the intelligence capacity of driverless vehicles, which impacts the commercialization process of autonomous cars and trucks. This overview aims to summarize the challenging problems in testing and evaluating the intelligence capacity of driverless vehicles. First, the grading of the behavioral intelligence of driverless vehicles is described. Then, to achieve a quantitative
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From Particles to Self-Localizing Tracklets: A Multilayer Particle Filter-Based Estimation for Dynamic Grid Maps IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-03 Andrei Vatavu; Melissa Rahm; Suresh Govindachar; Gunther Krehl; Abhishek Mantha; Sagar Ravi Bhavsar; Manuel Ravi Schier; Janis Peukert; Michael Maile
One of the indispensable functions of a self-driving vehicle is to estimate its dynamic world, which includes various traffic participants within complex driving scenarios. The estimation mechanism has to be flexible, fast, and robust; however, achieving these requirements is still challenging. Dynamic grid maps are one of the possible ways to combine and estimate multisensory information at an intermediate
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A Sequential Clustering Method for the Taxi-Dispatching Problem Considering Traffic Dynamics IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-09 Negin Alisoltani; Mahdi Zargayouna; Ludovic Leclercq
Taxis are an important transportation mode in many cities due to their convenience and accessibility. In the taxi-dispatching problem, sometimes it is more beneficial for the supplier if taxis cruise in the network after serving the first request to pick up the next passenger, while sometimes it is better that they wait in stations for new trip requests. In this article, we propose a rolling-horizon
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Statistical and Nature-Inspired Modeling of Vehicle Flows by Using Finite Mixtures of Simple Circular Normal Distributions IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-02 Pavel Kromer; Martin Hasal; Jana Nowakova; Jana Heckenbergerova; Petr Musilek
The representation, visualization, and modeling of traffic data is at the heart of intelligent transportation systems. Different types of traffic data exist, and novel ways of their accurate representation and modeling, which are useful for further analyses, simulations, and optimizations, are sought. In this work, location-specific traffic flows are represented by finite mixtures of circular normal
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Modeling and Analyzing Modeling and Analyzing Impact Factors of Metro Station Ridership: An Approach Based on a General Estimating Equation Factors Influencing Metro Station Ridership: An Approach based on General Estimating Equation IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-01 Yuxin He; Yang Zhao; Kwok Leung Tsui
Modeling and analyzing metro station ridership is of great importance to passenger flow management and transportation planning operations. In practice, ridership can be affected by multiple factors, including spatial factors (distance and network topology), temporal factors (e.g., period and trend), and external factors (e.g., land use and socioeconomics). However, existing studies mainly focus on
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Shared Autonomous Mobility on Demand: A Learning-Based Approach and Its Performance in the Presence of Traffic Congestion IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-03 Maxime Gueriau; Federico Cugurullo; Ransford A. Acheampong; Ivana Dusparic
Mobility-on-demand (MOD) systems consisting of shared autonomous vehicles (SAVs) are expected to improve the efficiency of urban transportation through reduced vehicle ownership and parking demand. However, several issues related to their implementation remain open, such as unifying the vehicle and ridesharing (RS) assignment with rebalancing (RB) unoccupied vehicles.
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Disruption Management for Dial-A-Ride Systems IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-09-03 Ramesh Ramasamy Pandi; Song Guang Ho; Sarat Chandra Nagavarapu; Twinkle Tripathy; Justin Dauwels
Mobility on demand has been gaining more attention from the research community as a way to offer smart and efficient transportation services to people. Despite the advancements in vehicular technologies, vehicle breakdown (VB) remains one of the major contributors to the disruption of fleet operations, which may inflict large recovery costs and damage the service provider?s reputation. However, modeling
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Queensland University of Technology Transport Research Group [ITS Research Lab] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-10-26 Cristina Olaverri-Monreal
The Queensland University of Technology (QUT) Transport Research Group (Figure 1) focuses on advancing knowledge, engineering, and science in traffic management and control; travel behavior; performance evaluation; traffic safety; data analytics; and public and active transportation. Our work is underpinned by a strong intelligent transportation systems foundation. We have a long-standing, productive
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Front Cover IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22
Presents the front cover for this issue of the publication.
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Table of Contents IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22
Presents the table of contents for this issue of the publication.
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Masthead IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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On Global Navigation Satellite System-Assisted Intelligent Transportation Systems [Editor's Column] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Ljubo Vlacic
Presents the introductory editorial for this issue of the publication.
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Navigating an Ever-Changing Landscape [President's Message] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Wei-Bin Zhang
Presents the President’s message for this issue of the publication.
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Toward Autonomous Driving in Arctic Areas IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-12 Laura Ruotsalainen; Valerie Renaudin; Ling Pei; Marco Piras; Juliette Marais; Emerson Cavalheri; Sanna Kaasalainen
This article provides an overview of the use of inertial and visual sensors and discusses their prospects in the Arctic navigation of autonomous vehicles. We also examine the fusion algorithms used thus far for integrating vehicle localization measurements as well as the map-matching (MM) algorithms relating position coordinates with road infrastructure. Our review reveals that conventional fusion
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An Experimental Evaluation of Global Navigation Satellite System/Inertial Navigation System-Verification Strategies for Vehicular Applications IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-04 Daniele Borio
An effective way to detect the presence of a spoofing attack is to verify Global Navigation Satellite System (GNSS) data with measurements from other sensors, such as inertial navigation systems (INSs). In this article, uncoupled GNSS/INS-verification approaches are experimentally evaluated in an automotive context. The approaches are uncoupled in the sense that GNSS and INS sensors are operated independently
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Robust Vehicular Localization and Map Matching in Urban Environments Through IMU, GNSS, and Cellular Signals IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-25 Zaher Zak M. Kassas; Mahdi Maaref; Joshua J. Morales; Joe J. Khalife; Kimia Shamei
A framework for ground vehicle localization that uses cellular signals of opportunity (SOPs), a digital map, an inertial measurement unit (IMU), and a Global Navigation Satellite System (GNSS) receiver is developed. This framework aims to enable localization in an urban environment where GNSS signals could be unusable or unreliable. The proposed framework employs an extended Kalman filter (EKF) to
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Object-Detection-Aided GNSS and Its Integration With Lidar in Highly Urbanized Areas IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-09 Weisong Wen; Guohao Zhang; Li-Ta Hsu
Positioning is a key function for autonomous vehicles that requires globally referenced localization information. Lidarbased mapping, which refers to simultaneous localization and mapping (SLAM), provides continuous positioning in diverse scenarios. However, SLAM error can accumulate through time. Besides, only relative positioning is provided by SLAM. The Global Navigation Satellite System (GNSS)
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Vision-Enhanced Low-Cost Localization in Crowdsourced Maps IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-12 Benedict Flade; Axel Koppert; Gorka Velez; Anweshan Das; David Betaille; Gijs Dubbelman; Oihana Otaegui; Julian Eggert
The lane-level localization of vehicles with low-cost sensors is a challenging task. In situations in which Global Navigation Satellite Systems (GNSSs) suffer from weak observation geometry or from the influence of reflected signals, the fusion of heterogeneous information presents a suitable approach for improving the localization accuracy. We propose a solution based on a monocular front-facing camera
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GNSS Integrity Monitoring Schemes for Terrestrial Applications in Harsh Signal Environments IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-10 Ni Zhu; David Betaille; Juliette Marais; Marion Berbineau
Global Navigation Satellite System (GNSS) integrity is defined as a measure of trust that can be placed in the correctness of the information supplied by the total system. Initially developed for safetycritical applications in the aeronautic domain, this concept has attracted more and more attention from terrestrial GNSS-based applications in recent years. The main problem of integrity monitoring for
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Analysis of High-Accuracy Satellite Messages for Road Applications IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-15 Ignacio Fernandez-Hernandez; Tommaso Senni; David Calle; Simon Cancela; Giovanni Arturo Vecchione; Gonzalo Seco-Granados
Future road applications will require positioning accuracy on the order of one or a few decimeters and a convergence time measured in seconds. A high-accuracy service (HAS) provided by the Global Navigation Satellite System becomes a key enabler to meet these requirements. In particular, the Galileo program has committed to provide a free HAS. This entails several design challenges; namely, to achieve
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Deep-Urban Unaided Precise Global Navigation Satellite System Vehicle Positioning IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-12 Todd E. Humphreys; Matthew J. Murrian; Lakshay Narula
This article presents the most thorough study to date of vehicular carrier-phase differential Global Navigation Satellite System (CDGNSS) positioning performance in a deep urban setting unaided by complementary sensors. Using data captured during approximately 2 h of driving in and around the dense urban center of Austin, Texas, a CDGNSS system is demonstrated to achieve 17-cm-accurate 3D urban positioning
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Enabling Assistance Functions for the Safe Navigation of Inland Waterways IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-10 Anja Hesselbarth; Daniel Medina; Ralf Ziebold; Martin Sandler; Michael Hoppe; Maik Uhlemann
Inland navigation and shipping are important pillars of the European Transport System. To support the skipper during safety-critical operations, precise position, navigation, and timing (PNT) data are required. This work discusses the role of PNT information for enabling inland waterway navigation-assistance functions, such as bridge-collision warning, mooring aiding, and automatic guidance. The real-time
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An Assessment of GPS Spoofing Detection Via Radio Power and Signal Quality Monitoring for Aviation Safety Operations IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-09 Damian Miralles; Aurelie Bornot; Paul Rouquette; Nathan Levigne; Dennis M. Akos; Yu-Hsuan Chen; Sherman Lo; Todd Walter
Due to the ever-growing threat of GPS spoofing, it has become necessary for the aviation sector to develop an effective means of detection. This article focuses on two complementary spoofing-detection techniques that are available on commercial GPS receivers and thus require no additional hardware to operate. The primary methodology for detection is using a combination of radio power monitoring metrics
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Integrated Control of Traffic Flow [PH.D. and M.PHIL. Theses' Abstracts] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Fernando Garcia Fernandez; Zhixiong Li
Presents abstracts of PH.D. and M.PHIL theses.
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A Framework for Robust Assimilation of Potentially Malign Third-Party Data, and Its Statistical Meaning IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-12 Matthew A. Wright; Roberto Horowitz
This article presents a model-based method for fusing data from multiple sensors with a hypothesis-test-based component for rejecting potentially faulty or otherwise malign data. Our framework is based on an extension of the classic particle filter algorithm for real-time state estimation of uncertain systems with nonlinear dynamics with partial and noisy observations. This extension, based on classical
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Mechatronics Research and Development Group at USB [ITS Research Lab] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Cristina Olaverri-Monrea
The Mechatronics Research and Development Group was created in 2002 by Prof. Gerardo Fern?ndez-L?pez and Prof. Juan Carlos Grieco of Simon Bol ivar University (USB) (Figure 1), Caracas, Venezuela. The group is focused on carrying out research and technological developments of excellence, both nationally and internationally. Its activities encompass mechatronics systems in general with special emphasis
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ITS Society Membership News [Member Activities] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Chunzhao Guo; Brendan Morris
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ITS Society Conferences [Conference Reports] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Brendan Morris
Presents information on ITS society conferences and meetings.
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[Calendar] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-07-22 Martin Lauer
Presents the ITS society calendar of upcoming events and meetings.
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Developing and Testing Robust Autonomy: The University of Sydney Campus Data Set IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-06-05 Wei Zhou; Julie Stephany Berrio; Charika De Alvis; Mao Shan; Stewart Worrall; James Ward; Eduardo Nebot
Vision and lidar are complementary sensors that are incorporated into many applications of intelligent transportation systems. These sensors have been used to great effect in research related to perception, navigation, and deep learning applications. Despite this success, the validation of algorithm robustness has recently been recognized as a major challenge for the massive deployment of these new
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Front Cover IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12
Presents the front cover for this issue of the publication.
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Table of Contents IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12
Presents the table of contents for this issue of the publication.
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Masthead IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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ITS: On a Mission of Advancing Technology for the Benefit of Humanity [Editor's Column] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12 Ljubo Vlacic
Presents the introductory editorial for this issue of the publication.
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Making a Difference [President's Message] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12 Wei-Bin Zhang
Presents the President’s message for this issue of the publication.
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[PHD and MPHIL Theses' Abstracts] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12 Fernando Garcia Fernandez; Zhixiong Li
The objective of this dissertation is to develop a resilient control approach to secure cyberphysical systems (CPSs) against cyberattacks, communication network failures, and potential physical faults. A general CPS consists of three main components: 1) the physical part including sensors, actuators, and hardware of the plant; 2) the cyber part including the software and control ler logic of the plant;
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The CASTLab in CASIA [ITS Research Lab] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12 Cristina Olaverri-Monreal
The Complex Adaptive Systems for Transportation Laboratory (CASTLab) was established by Prof. Fei-Yue Wang in July 1999 for the task of designing and implementing the proposed intelligent traffic system for the city of Xinxiang, Henan, one of the first initiatives in intelligent transportation systems (ITS) in China. At the end of 1999, the CASTLab became a part of the newly created Center for Intelligent
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The 2019 IEEE Intelligent Vehicles Symposium [Conference Reports] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12 Arnaud de La Fortelle
Presents information on the The 2019 IEEE Intelligent Vehicles Symposium.
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[Calendar] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-05-12 Martin Lauer
Presents the CS calendar of upcoming events and meetings.
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Front Cover IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22
Presents the front cover for this issue of the publication.
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Table of Contents IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22
Presents the table of contents for this issue of the publication.
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Staff List IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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A Huge Thank You to Miguel Angel Sotelo and a Warm Welcome to Wei-Bin Zhang [Editor's Column] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22 Ljubo Vlacic
Presents the introductory editorial for this issue of the publication.
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[President's Message] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22 Wei-Bin Zhang
Presents the President's message for this issue of the publication.
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A Survey on Cooperative Longitudinal Motion Control of Multiple Connected and Automated Vehicles IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2019-12-27 Ziran Wang; Yougang Bian; Steven E. Shladover; Guoyuan Wu; Shengbo Eben Li; Matthew J. Barth
Connected and automated vehicles (CAVs) have the potential to address a number of safety, mobility, and sustainability issues of our current transportation systems. Cooperative longitudinal motion control is one of the key CAV technologies that allows vehicles to be driven in a cooperative manner to achieve system-wide benefits. In this paper, we provide a literature survey on the progress accomplished
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Automatic Lane Identification Using the Roadside LiDAR Sensors IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-10-29 Jianqing Wu; Hao Xu; Junxuan Zhao
How to collect the real-time information of unconnected vehicles has been a challenge for connected vehicle technologies. The LiDAR sensors deployed along the roadside and at intersections provide a solution to fill the data gap during the transition from the traditional traffic to the full connected traffic. The roadside LiDAR sensors can record the movement of all road users with a relative long
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V2V-Based Memetic Optimization for Improving Traffic Efficiency on Multi-Lane Roads IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-11-13 Alexandre Lombard; Abdeljalil Abbas-Turki; Abdellah El-Moudni
Within the next few years, autonomous vehicles will start being commercialized. In the same time, inter-vehicular communication is emerging. Using these new technologies allows designing new software to make cooperative cars. These cooperatives cars can exchange messages to improve traffic efficiency by, for instance, notifying about the presences of other cars, or managing the right-of-way at intersections
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Building an Autonomous Lane Keeping Simulator Using Real-World Data and End-to-End Learning IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-11-13 Zhilu Chen; Lening Li; Xinming Huang
Autonomous lane keeping is an important safety feature for intelligent vehicles. This paper presents a lane keeping simulator that is built with image projections of recorded data in conjunction with vehicle dynamics estimation. An end-to-end learning method using convolutional neural network (CNN) takes front-view camera data as input and produces the proper steering wheel angle to keep the vehicle
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Traffic Flow Impacts of Converting an HOV Lane Into a Dedicated CACC Lane on a Freeway Corridor IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2019-12-17 Lin Xiao; Meng Wang; Bart van Arem
Cooperative Adaptive Cruise Control (CACC) systems can increase roadway capacity, but the benefits are marginal at low market penetration rates (MPRs). Thus, a CACC dedicated lane is considered to group CACC vehicles for efficient traffic stream. Concepts of converting existing High Occupancy Vehicle (HOV) lanes into CACC lanes emerge, which leverages the infrastructural facilities and experience with
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Determining the Breakpoints of Fundamental Diagrams IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-10-26 Sheng Jin; Xiaoqin Luo; Dongfang Ma
The breakpoints of fundamental diagrams (FDs) are an important foundation for estimating capacity, identifying traffic conditions, and determining the phase regime of multi-regime FDs. Unfortunately, to our best knowledge, there has been little research on determining breakpoints in a scientific way. This paper applies a Gaussian mixture model (GMM) to describe multi-component traffic conditions, and
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Laboratory B3: Infrastructure and Traffic Management in Land Transport: Hellenic Institute of Transport - Centre for Research and Technology Hellas [ITS Research Lab] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22 Cristina Olaverri-Monreal
Reports on Mission Laboratory B3: Infrastructure and Traffic Management in land transport (Lab B3). Lab3 focuses on modeling and optimization of transportation systems networks and traffic flow. It develops interfaces for the integration of intelligent transport Systems (ITS) and related processes in the field of traffic management of surface transport systems (including integration of related managing
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The 22nd IEEE Intelligent Transportation Systems Conference-ITSC 2019 [Conference Reports] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22 Ljubo Vlacic
Presents informaiton on the 22nd IEEE Intelligent Transportation Systems Conference.
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[Calendar] IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2020-01-22 Martin Lauer
Presents the ITS society calendar of events and meetings.
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Recovery of Incapacitated Commercial Delivery Drones Using LPWAN Technology IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2019-04-11 Philip A. Catherwood; Michael Little; Dewar Finlay; James McLaughlin OBE
This paper proposes for the first time the use of an Internet of Things solution for the accurate recovery of incapacitated commercial and retail delivery drones. Since the use of drones will increase in popularity for a variety of uses, the problem of locating and recovering delivery drones is necessary. Using the emerging LoRaWAN and Sigfox networks (as examples of Low Power Wide Area Network (LPWAN)
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Positioning Accuracy Improvement of Automated Guided Vehicles Based on a Novel Magnetic Tracking Approach IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-12-06 Shijian Su; Xianping Zeng; Shuang Song; Mingqiang Lin; Houde Dai; Wanan Yang; Chao Hu
Automated guided vehicles (AGVs) have been widely adopted in the logistic delivering of modern manufacturing. As a key performance index for an AGV, the positioning accuracy of commercial AGVs based on the traditional magnetic tracking approach is bigger than ?5mm, which cannot meet the requirement of many industrial applications. Thus, we proposed a novel magnetic tracking approach to improve the
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Optimal Periodic Control of Connected Multiple Vehicles With Heterogeneous Dynamics and Guaranteed Bounded Stability IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-11-29 Shengbo Eben Li; Xiaoxue Zhang; Renjie Li; Zhitao Wang; Hailiang Chen; Zhe Xin
The platooning of connected and automated vehicles has the potential to significantly improve the fuel efficiency of road transportation. Shortening the carfollowing distance to reduce aerodynamic drag is often used to improve fuel economy in today's platoons, but suffers high risk of rear-end collision. This paper presents an alternative solution to reduce platoon fuel consumption, i.e., periodic
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Ecological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-11-27 Seyed Amin Sajadi-Alamdari; Holger Voos; Mohamed Darouach
Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological
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An Accurate Solution to the Cardinality-Based Punctuality Problem IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-11-22 Zhiguang Cao; Yaoxin Wu; Akshay Rao; Felix Klanner; Stefan Erschen; Wei Chen; Le Zhang; Hongliang Guo
This paper focuses on a specific stochastic shortest path (SSP) problem, namely the punctuality problem. It aims to determine a path that maximizes the probability of arriving at the destination before a specified deadline. The popular solution to this problem always formulates it as a cardinality minimization problem by considering its data-driven nature, which is approximately solved by the 1 , -norm
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Automation Kit for Dual-Mode Military Unmanned Ground Vehicle for Surveillance Missions IEEE Intell. Transp. Syst. Mag. (IF 3.363) Pub Date : 2018-11-20 Jose E. Naranjo; Felipe Jimenez; Manuel Anguita; Jose Luis Rivera
The field of autonomous vehicles is an area of great importance nowadays among Intelligent Transport Systems. These autonomous vehicles must meet high standards of robustness, safety and protection to make autonomous driving safer than human driving, thus improving current accident rates and energy efficiency, so its complete implementation in the market is expected in the long term. However, there