AHV2021: Autonomous and Connected Heavy Vehicle Technology UPES Dehradun, India, March 30-31, 2021 |
Conference website | https://sites.google.com/view/hvt2021/home |
Submission link | https://easychair.org/conferences/?conf=ahv2021 |
Abstract registration deadline | January 15, 2021 |
Submission deadline | February 15, 2021 |
Call for Chapters for the forthcoming book:
Autonomous and Connected Heavy Vehicle Technology
Editor
Rajalakshmi Krishnamurthi, PhD (Department of Computer Science and Engineering Jaypee Institute of Information Technology, Noida, India. Email: k.rajalakshmi@jiit.ac.in )
Adarsh Kumar, PhD, (Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India. Email: adarsh.kumar@ddn.upes.ac.in)
Sukhpal Singh Gill, PhD, (School of Electronic Engineering and Computer Science , Queen Mary University of London, UK Email: s.s.gill@qmul.ac.uk)
Publisher
The book will be published in Elsevier, which is indexed in major indexes such as: Thomson/ISI, Scopus etc.
Theme
In the past decades the trend for vehicle technologies was more focused on passenger based vehicles. However, in recent years the development and enhancement for heavy vehicle technologis that include heavy freight vehicles and commercial truck vehicles has got specific attention. The reasons being are these heavy vehicles significantly contribute towards the economic growth and high return of investment (ROI). In addition, adverse environmental impacts like air pollution, carbon footprints, fuel economy, and fatal accidents necessitate research and development in HVT. Thus, the emerging opportunities that feature in heavy vehicle industry are autonomous and connected vehicle technologies that grant way to urbanization, insurance, security & privacy. The major stakeholders of HVT include truck drivers, citizens, truck industry, and policy and regulatory authorities. The objectives of HVT focus on fuel efficiency, driver ease, real time monitoring, cost optimization in terms of deployment and operations. The predominant areas that facilitate the enhancement of Autonomous and Connected Heavy Vehicle Technology (AC-HVT) are vehicle sensor technology, vehicle communication technology, and vehicle software and hardware integration. The various applications that endorse AC-HVT include driver alert system, lane guidance, collude avoidance system, automatic braking system, platooning, eco-driving, blind spot detection, cruise control and so on. However, some of the technical challenges such sensor quality, data handling, bandwidth allocations, communication protocols and standards, resource constraints, processing and controlling software systems. The challenges need solutions through enabling technologies such as cyber physical systems, cloud computing, Big Data, Fog Computing , Block Chain , Data Analytics, Artificial Intelligence and Pervasive computing. The heavy vehicle industry promises to have Return of Investment. However, the issues such as product development, cost of commercial deployment technological and performing cost , scaling need detailed field study and research. The architecture and frameworks for incorporating HVT is another perspective. The heavy vehicle platooning is highlighted to be effective solution for fuel energy conservation. However, the challenges are optimization mechanism real time control systems for distance and steering mechanism, cognitive and predictive analysis. This includes various physical factors like traffic, road status, distance, weather conditions exhibit dynamic changes and play crucial role in decision making of HVT systems. The regulation and regulatory are another aspect of HBVT where stakeholders role and responsibilities are drafted . In addition, the requirement analysis road capacity monitoring and compliance of the regulations at state and national level.
The primary objective of this special issue is to address the various issues identified pertaining to Heavy Vehicle Technology develop solution towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, Cloud computing, Cyber Physical Systems, and Cognition analysis. This special issue will facilitate the research group to publish novel work towards the advancement of emerging technologies in applications of heavy vehicle technology.
Topics
Topics of interest include, but are not limited to, the following:
Autonomous and Connected Heavy Vehicle technology
State -of-art (Cost, Deployment, Implication, Fuel Economy, Industry Players), Stake holders of Heavy Vehicle technology (Industry, drivers, civilians, policy makers), Frameworks for automated driving systems, Need for Autonomous and connected heavy vehicle technology, Key benefits and drawbacks.
Applications of autonomous and Connected Vehicle Technology
Driver Alert systems, Lane tracking assistance, Collision avoidance mechanism, Automatic Braking Systems, Truck Platooning, Eco-driving system, Blind Spot Detection, Automated/Manual Manuovering, Adaptive /Predictive Cruise Control, Telematic Systems.
Autonomous and Connected Heavy vehicle Technologies
Vehicular Sensor Technologies ( Camera, Radar, -GPS units, LiDAR), Vehicular Communication Technologies ( Vehicle - to - Vehicle Communication, Vehicle - to-Infrastructure Communication, Short Range Communication, Mobile Network for Connected Vehicle Technology), Vehicle Software & Hardware, Vehicle control algorithms ( Artificial Intelligence -computing software systems-image processing- message handling between vehicles or infrastructure-software refinement- software validation), 5G technologies for heavy vehicles.
Enabling Technologies for Automated and Connected Heavy Vehicles
Sensor Quality & Data handling, Bandwidth Allocation problem for Vehicle Communication, Processing Software & Technology, Cyber Physical Systems, Internet of Things, Cloud Computing, Big Data, AI, Machine Learning, Deep learning
Economic Factors for Automated an Connected heavy vehicle technologies
Product Development, Technology incorporation Cost, Maintenance & Performing Cost, Return of Investment, Indirect and Direct economic in automation, Scaling of Technology Adaptation, Commercial Deploying of Automation Systems, Application platform for non-platnooing trucking (EPA, DAF, Faber, Daimler AG, ITF, NCST, NACFE)
Heavy Vehicle Platooning
State-of-art in Fuel Economy, Optimization of Fuel Savings, Enhancing Platooning Systems, Control Systems for Distance and steering, Minimization of Driver Errors, Accuracy, predictive , adaptive , eco-friendly , automated systems, Real world factors like traffic, road status, terrain, miles, climatic conditions
Regulation and regulators
Stakeholders (Truck Industry, Drivers , Civilians, regulating authorities, policy makers), Safety measures, Operational efficiency, Road Capacity monitoring, labour hours and wages, Legalization & Policy at the National level, Legalization & Policy at the state level, Environmental monitoring and Energy Governing laws.
Heavy Vehicle Road Safety
Real time mechanical condition monitoring of heavy vehicles, Heavy vehicle age and associated factors , Road condition deterioration prediction, Safety management, seat vibration and seat vibration analysis and driver fatigue and health monitoring, heavy vehicle dynamics on road.
Heavy Vehicle Traffic
Traffic flow prediction in Urban, rural and remote areas, heavy vehicle traffic monitoring in Smart City, critical traffic flows such as narrow roadways and level crossings, severe climatic conditions, estimating traffic frequency of HVT, impact of HVT traffic frequency on humans, role of emerging technologies such as 5G, IoT, Cloud Computing, Big data towards in heavy vehicle traffic control and monitoring.
Heavy Vehicle Routing
Oversize and/or overweight (OSOW) vehicles, routing services for OSOW vehicles, heavy vehicle identification using RFID, Bluetooth, Wi-Fi, Cellular networks (4G, LTE-V, 5G or hybrid), Vehicle centric heavy vehicle routing, eMaps or E-Big Data based vehicle routing approaches, Routing matching or speed evaluation mechanisms, Information data fusion, Mobility as a Service (MaaS) for heavy vehicles, Real Time Traffic Pattern generation algorithms, 5G enabled floating vehicle data, Traffic logistics and Geo-analytics, static and dynamic vehicular rout guidance algorithms, re-routing algorithms, 5G optimal routing, Urban vehicle routing algorithms.
Type of contributions and length
Book Chapter.
Chapter length: In general, your chapter should be approximately 25-35 double-spaced Microsoft Word pages, inclusive of references.
Figures/Tables/Charts/illustrations: All illustrations submitted in color will be reproduced in color in all iterations of the volume—at no cost to you. Figures must be sent as separate files (preferably TIFF or EPS with a resolution of at least 300 dpi; PDF, JPG, and PowerPoint files may also be acceptable for certain simple figures) and must not be embedded in the chapter.
Abstracts: Your chapter should include a succinct abstract—a preview for your chapter—that contains approximately 350-500 words/20 lines.
Callouts: You must indicate in the chapter where each figure, table, chart, etc. should be placed (for example, Insert Figure 1 here or Insert Figure 4.5 here).
Keywords: In the beginning of your chapter, please include 5-10 keywords. Keywords are important as they are indexed in Google Scholar and other search engines. This will also be used to generate a subject Index.
Corresponding author information: On the title page of your chapter, please indicate who among the chapter authors is the corresponding author of the chapter (that is, the chapter author responsible for submitting the chapter and whose contact information appears along with his/her name on the chapter). Please also include all appropriate contact information (email addresses) and affiliation information for the co-authors.
Deadlines
Submission of abstracts (500 words): January 01, 2021
Submission of full chapter: January 31, 2021
Final Book Manuscript should be submitted on or before March 1, 2021.