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1
Kovačić, Matija, Maja Mutavdžija, and Krešimir Buntak. "New Paradigm of Sustainable Urban Mobility: Electric and Autonomous Vehicles—A Review and Bibliometric Analysis." Sustainability 14, no. 15 (August 3, 2022): 9525. http://dx.doi.org/10.3390/su14159525.
Повний текст джерелаАнотація:
The growing relevance of sustainability, as well as the necessity to replace traditional forms of transportation with sustainable ones, has made sustainable urban mobility an imperative. In order to respond to the ever-increasing need to develop sustainable modes of transport, the importance of electric, autonomous, and electric autonomous vehicles is increasingly emphasized. In addition, as trends of growth and development in electric autonomous vehicle technology are increasing, one of the questions that has appeared is whether autonomous electric vehicles represent one of the mechanisms that will be used to increase the sustainability of urban mobility. With this in mind, the results of a systematic analysis of existing research in the WOS and Scopus databases using the keywords “urban mobility”, “electric vehicles”, and “autonomous vehicles” was carried out to identify research trends in the use of autonomous electric vehicles in urban areas. The research showed that authors focus on the advantages and disadvantages of autonomous electric vehicles and their usage in the urban mobility system, but an insufficient number of authors consider and define the need to plan the transition towards incorporating autonomous electric vehicles into the urban system. The results of this research also indicate an insufficient number of papers that research and describe the application of autonomous electric vehicles in distribution logistics. This paper provides an overview of existing research related to autonomous electric vehicles and the challenges of transition in the context of infrastructure and the development of a culture of sustainability among urban residents.
2
Ongel, Aybike, Erik Loewer, Felix Roemer, Ganesh Sethuraman, Fengqi Chang, and Markus Lienkamp. "Economic Assessment of Autonomous Electric Microtransit Vehicles." Sustainability 11, no. 3 (January 26, 2019): 648. http://dx.doi.org/10.3390/su11030648.
Повний текст джерелаАнотація:
There is rapidly growing interest in autonomous electric vehicles due to their potential in improving safety, accessibility, and environmental outcomes. However, their market penetration rate is dependent on costs. Use of autonomous electric vehicles for shared-use mobility may improve their cost competitiveness. So far, most of the research has focused on the cost impact of autonomy on taxis and ridesourcing services. Singapore is planning for island-wide deployment of autonomous vehicles for both scheduled and on-demand services as part of their transit system in the year 2030. TUMCREATE developed an autonomous electric vehicle concept, a microtransit vehicle with 30-passenger capacity, which can complement the existing bus transit system. This study aims to determine the cost of autonomous electric microtransit vehicles and compare them to those of buses. A total cost of ownership (TCO) approach was used to compare the lifecycle costs. It was shown that although the acquisition costs of autonomous electric vehicles are higher than those of their conventional counterparts, they can reduce the TCO per passenger-km up to 75% and 60% compared to their conventional counterparts and buses, respectively.
3
Ashwin Kavasseri Venkitaraman and Venkata Satya Rahul Kosuru. "A review on autonomous electric vehicle communication networks-progress, methods and challenges." World Journal of Advanced Research and Reviews 16, no. 3 (December 30, 2022): 013–24. http://dx.doi.org/10.30574/wjarr.2022.16.3.1309.
Повний текст джерелаАнотація:
Electric vehicles have gained significance owing to its unavoidable supporting factors including environmental impacts and climate features. It has been noticed over last few decades that the increased number of manufacturers have focused on electric propulsion-based technology either pure electric or hybrid form with the support of electric vehicles in the automotive market. The adoption of these electric vehicle has obviously increased its competitive nature while compared to traditional internal combustion engine system. Moreover, the electric vehicles (EVs) possess substantial potential, not only in minimizing carbon emission but also in assisting required energy storage to contribute to the distributed renewable generation. There exist several increases in electric vehicle usage, but their level of massive adoption and existence by automotive consumers is connected with its delivered performance. One such important feature is the autonomous electric vehicle communication networks. This research provides a comprehensive review on overview of the electric vehicles and will discuss various existing works on autonomous driving vehicles. The paper compares existing communication networks and nuances associated in the context of an autonomous electric vehicle. Also, it critiques the existing technology and provides suggestive future work in the field to make communication networks resilient. An extensive review makes it possible to ascertain future research directions in the EV research field, which would result in massive future and instantaneous EV perception in the automotive market.
4
Hogeveen, Peter, Maarten Steinbuch, Geert Verbong, and Auke Hoekstra. "The Energy Consumption of Passenger Vehicles in a Transformed Mobility System with Autonomous, Shared and Fit-For-Purpose Electric Vehicles in the Netherlands." Open Transportation Journal 15, no. 1 (October 15, 2021): 201–9. http://dx.doi.org/10.2174/1874447802115010201.
Повний текст джерелаАнотація:
Aims: This article explores the tank-to-wheel energy consumption of passenger transport at full adoption of fit-for-purpose shared and autonomous electric vehicles. Background: The energy consumption of passenger transport is increasing every year. Electrification of vehicles reduces their energy consumption significantly but is not the only disruptive trend in mobility. Shared fleets and autonomous driving are also expected to have large impacts and lead to fleets with one-person fit-for-purpose vehicles. The energy consumption of passenger transport in such scenarios is rarely discussed and we have not yet seen attempts to quantify it. Objective: The objective of this study is to quantify the tank-to-wheel energy consumption of passenger transport when the vehicle fleet is comprised of shared autonomous and electric fit-for-purpose vehicles and where cheap and accessible mobility leads to significantly increased mobility demand. Methodology: The approach consists of four steps. First, describing the key characteristics of a future mobility system with fit-for-purpose shared autonomous electric vehicles. Second, estimating the vehicle miles traveled in such a scenario. Third, estimating the energy use of the fit-for-purpose vehicles. And last, multiplying the mileages and energy consumptions of the vehicles and scaling the results with the population of the Netherlands. Results: Our findings show that the daily tank-to-wheel energy consumption from Dutch passenger transport in full adoption scenarios of shared autonomous electric vehicles ranges from 700 Wh to 2200 Wh per capita. This implies a reduction of 90% to 70% compared to the current situation. Conclusion: Full adoption of shared autonomous electric vehicles could increase the vehicle-miles-travelled and thus energy use of passenger transport by 30% to 150%. Electrification of vehicles reduces energy consumption by 75%. Autonomous driving has the potential of reducing the energy consumption by up to 40% and implementing one-person fit-for-purpose vehicles by another 50% to 60%. For our case study of the Netherlands, this means that the current 600 TJ/day that is consumed by passenger vehicles will be reduced to about 50 to 150 TJ/day at full adoption of SAEVs.
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Obaid, Mohammed, Arpad Torok, and Jairo Ortega. "A Comprehensive Emissions Model Combining Autonomous Vehicles with Park and Ride and Electric Vehicle Transportation Policies." Sustainability 13, no. 9 (April 22, 2021): 4653. http://dx.doi.org/10.3390/su13094653.
Повний текст джерелаАнотація:
Several transport policies reduce pollution levels caused by private vehicles by introducing autonomous or electric vehicles and encouraging mode shift from private to public transport through park and ride (P&R) facilities. However, combining the policies of introducing autonomous vehicles with the implementation of electric vehicles and using the P&R system could amplify the decrease of transport sector emissions. The COPERT software has been used to calculate the emissions. This article aims to study these policies and determine which combinations can better reduce pollution. The result shows that each combination of autonomous vehicles reduces pollution to different degrees. In conclusion, the shift to more sustainable transport modes through autonomous electric vehicles and P&R systems reduces pollution in the urban environment to a higher percentage. In contrast, the combination of autonomous vehicles has lower emission reduction but is easier to implement with the currently available infrastructure.
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Rojas-Rueda, David, Mark J. Nieuwenhuijsen, Haneen Khreis, and Howard Frumkin. "Autonomous Vehicles and Public Health." Annual Review of Public Health 41, no. 1 (April 2, 2020): 329–45. http://dx.doi.org/10.1146/annurev-publhealth-040119-094035.
Повний текст джерелаАнотація:
Autonomous vehicles (AVs) have the potential to shape urban life and significantly modify travel behaviors. “Autonomous technology” means technology that can drive a vehicle without active physical control or monitoring by a human operator. The first AV fleets are already in service in US cities. AVs offer a variety of automation, vehicle ownership, and vehicle use options. AVs could increase some health risks (such as air pollution, noise, and sedentarism); however, if proper regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments. Healthy models of AV use include fully electric vehicles in a system of ridesharing and ridesplitting. Public health will benefit if proper policies and regulatory frameworks are implemented before the complete introduction of AVs into the market.
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Hirz, Mario, Bernhard Walzel, and Helmut Brunner. "Autonomous Charging of Electric Vehicles in Industrial Environment." Tehnički glasnik 15, no. 2 (June 9, 2021): 220–25. http://dx.doi.org/10.31803/tg-20210428191147.
Повний текст джерелаАнотація:
Modern industrial manufacturing involves several manually and automated driven vehicles - not only for logistics and production purposes, but also for services, maintenance, resources supply and cleaning. These different types of vehicles are increasingly driven by electric powertrains that operate in the production halls, warehouses and other involved areas. Today, electric charging of these mobile devices is accomplished mainly manually and by use of a number of different not standardized charging interfaces, which leads to increased time and cost efforts. The paper evaluates different charging technologies for the use in industrial environments and introduces a new approach for automated, robot-controlled charging of electric vehicles, which is based on a standardized charging interface. The technology has been developed to fully automated charge different types of cars and other vehicles and consists of a vision system to identify the vehicle and the charging connector position in combination with a fully-controlled robotic system that plugs-in and -off the charging connector. In this way, the system is universally applicable for different types of autonomously and manually driven vehicles in a professional context, e.g. in production, logistics and warehouses.
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Alkheir, Ala Abu, Moayad Aloqaily, and Hussein T. Mouftah. "Connected and Autonomous Electric Vehicles (CAEVs)." IT Professional 20, no. 6 (November 1, 2018): 54–61. http://dx.doi.org/10.1109/mitp.2018.2876977.
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Yaakub, Salma, and Mohammed Hayyan Alsibai. "A Review on Autonomous Driving Systems." International Journal of Engineering Technology and Sciences 5, no. 1 (June 20, 2018): 1–16. http://dx.doi.org/10.15282/ijets.v5i1.2800.
Повний текст джерелаАнотація:
Autonomous vehicles are one of the promising solutions to reduce traffic crashes and improve mobility and traffic system. An autonomous vehicle is preferable because it helps in reducing the need for redesigning the infrastructure and because it improves the vehicle power efficiency in terms of cost and time taken to reach the destination. Autonomous vehicles can be divided into 3 types: Aerial vehicles, ground vehicles and underwater vehicles. General, four basic subsystems are integrated to enable a vehicle to move by itself which are: Position identifying and navigation system, surrounding environment situation analysis system, motion planning system and trajectory control system. In this paper, a review on autonomous vehicles and their related technological applications is presented to highlight the aspects of this industry as a part of industry 4.0 concept. Moreover, the paper discusses the best autonomous driving systems to be applied on our wheelchair project which aims at converting a manual wheelchair to a smart electric wheelchair
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Zhu, Guoming G., and Chengsheng Miao. "Real-Time Co-optimization of Vehicle Route and Speed Using Generic Algorithm for Improved Fuel Economy." Mechanical Engineering 141, no. 03 (March 1, 2019): S08—S15. http://dx.doi.org/10.1115/1.2019-mar-4.
Повний текст джерелаАнотація:
Making future vehicles intelligent with improved fuel economy and satisfactory emissions are the main drivers for current vehicle research and development. The connected and autonomous vehicles still need years or decades to be widely used in practice. However, some advanced technologies have been developed and deployed for the conventional vehicles to improve the vehicle performance and safety, such as adaptive cruise control (ACC), automatic parking, automatic lane keeping, active safety, super cruise, and so on. On the other hand, the vehicle propulsion system technologies, such as clean and high efficiency combustion, hybrid electric vehicle (HEV), and electric vehicle, are continuously advancing to improve fuel economy with satisfactory emissions for traditional internal combustion engine powered and hybrid electric vehicles or to increase cruise range for electric vehicles.
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Kaluva, Sai Teja, Aditya Pathak, and Aybike Ongel. "Aerodynamic Drag Analysis of Autonomous Electric Vehicle Platoons." Energies 13, no. 15 (August 4, 2020): 4028. http://dx.doi.org/10.3390/en13154028.
Повний текст джерелаАнотація:
Vehicle platooning has been proposed as one of the potential technologies for intelligent transport systems to improve transportation and energy efficiency in urban cities. Despite extensive studies conducted on the platooning of heavy-duty trucks, literature on the analysis of urban vehicle platoons has been limited. To analyse the impact of platooning in urban environments, this paper studies the influence of intervehicle distance, platoon size and vehicle speed on the drag coefficient of the vehicles in a platoon using computational fluid dynamics (CFD). Two vehicle models—a minibus and a passenger car—are analysed to characterise the drag coefficients of the respective platoons. An analysis of energy consumption is conducted to evaluate the energy savings with platooning using a longitudinal dynamics simulation. The results showed a reduction in the average drag coefficient of the platoon of up to 24% at an intervehicle distance of 1 m depending on the number of vehicles in the platoon. With a larger intervehicle distance of 4 m, the reduction in the drag coefficient decreased to 4% of the drag coefficient of the isolated vehicle. Subsequently, energy savings with platooning were calculated to be up to 10% depending on the driving cycle, intervehicle distance and platoon size.
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Gáspár, Péter. "Control Design for Electric Vehicles." Energies 15, no. 12 (June 7, 2022): 4193. http://dx.doi.org/10.3390/en15124193.
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König, Adrian, Sebastian Mayer, Lorenzo Nicoletti, Stephan Tumphart, and Markus Lienkamp. "The Impact of HVAC on the Development of Autonomous and Electric Vehicle Concepts." Energies 15, no. 2 (January 9, 2022): 441. http://dx.doi.org/10.3390/en15020441.
Повний текст джерелаАнотація:
Automation and electrification are changing vehicles and mobility. Whereas electrification is mainly changing the powertrain, automation enables the rethinking of the vehicle and its applications. The actual driving range is an important requirement for the design of automated and electric vehicles, especially if they are part of a fleet. To size the battery accordingly, not only the consumption of the powertrain has to be estimated, but also that of the auxiliary users. Heating Ventilation and Air Conditioning (HVAC) is one of the biggest auxiliary consumers. Thus, a variable HVAC model for vehicles with electric powertrain was developed to estimate the consumption depending on vehicle size and weather scenario. After integrating the model into a tool for autonomous and electric vehicle concept development, various vehicle concepts were simulated in different weather scenarios and driving cycles with the HVAC consumption considered for battery sizing. The results indicate that the battery must be resized significantly depending on the weather scenario to achieve the same driving ranges. Furthermore, the percentage of HVAC consumption is in some cases higher than that of the powertrain for urban driving cycles, due to lower average speeds. Thus, the HVAC and its energy demand should especially be considered in the development of autonomous and electric vehicles that are primarily used in cities.
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Chen, Shukai, Hua Wang, and Qiang Meng. "Optimal purchase subsidy design for human-driven electric vehicles and autonomous electric vehicles." Transportation Research Part C: Emerging Technologies 116 (July 2020): 102641. http://dx.doi.org/10.1016/j.trc.2020.102641.
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Moridian, Barzin, Nina Mahmoudian, Wayne W. Weaver, and Rush D. Robinett. "Postdisaster Electric Power Recovery Using Autonomous Vehicles." IEEE Transactions on Automation Science and Engineering 14, no. 1 (January 2017): 62–72. http://dx.doi.org/10.1109/tase.2016.2614927.
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König, Adrian, Daniel Telschow, Lorenzo Nicoletti, and Markus Lienkamp. "PACKAGE PLANNING OF AUTONOMOUS VEHICLE CONCEPTS." Proceedings of the Design Society 1 (July 27, 2021): 2369–78. http://dx.doi.org/10.1017/pds.2021.498.
Повний текст джерелаАнотація:
AbstractAutonomous driving will not just change vehicles themselves, but also the entire concept of mobility. New business models and the expansion of individual mobility to new groups of society are merely examples of possible impact. In order to create optimal vehicles for new technologies right from the start, vehicle concept optimization helps to find suitable solutions from numerous possible variations. The package as part of a vehicle concept is currently focused on passenger cars with steering wheels and pedals. Therefore, a new method is needed to plan the package of driverless and autonomous vehicles. In this paper, we present a possible method that separates the vehicle into the interior and the front and rear wagon. This way, different seating layouts can be considered and evaluated in terms of package efficiency. In the results, we check the plausibility by rebuilding a current battery electric vehicle (BEV) and, by way of example, show the variation of the gear angle and different seating layouts, and the resulting package efficiency.
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Shao, Yunli, Mohd Azrin Mohd Zulkefli, and Zongxuan Sun. "Vehicle and Powertrain Optimization for Autonomous and Connected Vehicles." Mechanical Engineering 139, no. 09 (September 1, 2017): S19—S23. http://dx.doi.org/10.1115/1.2017-sep-6.
Повний текст джерелаАнотація:
This article discusses the potential of using autonomous and connected vehicle (CV) technologies to save energy. It also focuses on the potential energy savings of internal combustion engine-based vehicles (ICVs) and hybrid electric vehicles (HEVs). An example of vehicle and powertrain co-optimization for HEV eco-approaching and departure is also given. CV technologies are gaining increasing attention around the world. Vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication enable real-time access to traffic information that was not available before, including preceding vehicles’ location, speed, pedal position, traffic signal phasing and timing (SPaT). The example shown in this article demonstrates the potential benefits from vehicle and powertrain co-optimization by investigating an eco-approaching and departure application. More research in this area can offer more mature solutions to implement such optimization in a real-production vehicle.
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Attia, Moussa, Fares Zaamouche, Ala Houam, and Rabah Daouadi. "Stability Control Modeling and Simulation Strategy for an Electric Vehicle Using Two Separate Wheel Drives." European Journal of Electrical Engineering 24, no. 5-6 (December 31, 2022): 239–45. http://dx.doi.org/10.18280/ejee.245-602.
Повний текст джерелаАнотація:
This study of modifying the frame forces of an electric vehicle offers benefits for controlling stability. We used a two-wheeled self-driving electric vehicle in this study. Taking into account important parameters such as vehicle speed, the vehicle's stability criterion is determined based on the torque level and lateral slip angle. It is equipped with a traction control system that integrates its dynamic system with a sporty design. This level of control improves the vehicle's stability and safety. A conventional regulator has been developed and trained to apply motor control to a sophisticated power supply system. The stability of the EVs was controlled by a simulation model. We validated the proposed stability criterion, and the wheel torque control algorithm. Stability control for two-wheeled autonomous vehicles can be developed on the basis of related research. We would like to stress that the controller can be used in a variety of modern electric vehicles because it is so easy to use. An overview of the modeling and simulation results for this system in the MATLAB-Simulink environment will be presented.
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Bathla, Gourav, Kishor Bhadane, Rahul Kumar Singh, Rajneesh Kumar, Rajanikanth Aluvalu, Rajalakshmi Krishnamurthi, Adarsh Kumar, R. N. Thakur, and Shakila Basheer. "Autonomous Vehicles and Intelligent Automation: Applications, Challenges, and Opportunities." Mobile Information Systems 2022 (June 6, 2022): 1–36. http://dx.doi.org/10.1155/2022/7632892.
Повний текст джерелаАнотація:
Intelligent Automation (IA) in automobiles combines robotic process automation and artificial intelligence, allowing digital transformation in autonomous vehicles. IA can completely replace humans with automation with better safety and intelligent movement of vehicles. This work surveys those recent methodologies and their comparative analysis, which use artificial intelligence, machine learning, and IoT in autonomous vehicles. With the shift from manual to automation, there is a need to understand risk mitigation technologies. Thus, this work surveys the safety standards and challenges associated with autonomous vehicles in context of object detection, cybersecurity, and V2X privacy. Additionally, the conceptual autonomous technology risks and benefits are listed to study the consideration of artificial intelligence as an essential factor in handling futuristic vehicles. Researchers and organizations are innovating efficient tools and frameworks for autonomous vehicles. In this survey, in-depth analysis of design techniques of intelligent tools and frameworks for AI and IoT-based autonomous vehicles was conducted. Furthermore, autonomous electric vehicle functionality is also covered with its applications. The real-life applications of autonomous truck, bus, car, shuttle, helicopter, rover, and underground vehicles in various countries and organizations are elaborated. Furthermore, the applications of autonomous vehicles in the supply chain management and manufacturing industry are included in this survey. The advancements in autonomous vehicles technology using machine learning, deep learning, reinforcement learning, statistical techniques, and IoT are presented with comparative analysis. The important future directions are offered in order to indicate areas of potential study that may be carried out in order to enhance autonomous cars in the future.
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Hogeveen, Peter, Maarten Steinbuch, Geert Verbong, and Auke Hoekstra. "Quantifying the Fleet Composition at Full Adoption of Shared Autonomous Electric Vehicles: An Agent-based Approach." Open Transportation Journal 15, no. 1 (May 17, 2021): 47–60. http://dx.doi.org/10.2174/1874447802115010047.
Повний текст джерелаАнотація:
Aims: Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Background: Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. Objective: To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. Methods: An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. Results: The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Conclusion: Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.
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Stoian, Viorel. "A Control Algorithm for Autonomous Electric Vehicles by Fuzzy Logic." Advanced Engineering Forum 27 (April 2018): 103–10. http://dx.doi.org/10.4028/www.scientific.net/aef.27.103.
Повний текст джерелаАнотація:
The domain of autonomous vehicles is of great interest to researchers and engineers and much has been performed in this field. The paper proposes a fuzzy control algorithm for autonomous electric vehicles which are moving next to the obstacle (object) boundaries, avoiding the collisions with them (a “guard motion”). Four motion cycles (programs) which depend of the proximity levels and which are used by the vehicle on its trajectory are described. The directions of the movements corresponding to every cycle and for every reached neighbourhood level are indicated. The sequence of the programs and the conditions of their alternation are shown. The motion control algorithm describes the sequence of the functional cycles by a schernatic program code. The fuzzy rules for evolution (transition) of the cycles and for the motion on x-axis and y-axis respectively are expounded. Finally, some simulations are represented.
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Fan, Wenhui, Hongwen He, and Bing Lu. "Online Active Set-Based Longitudinal and Lateral Model Predictive Tracking Control of Electric Autonomous Driving." Applied Sciences 11, no. 19 (October 5, 2021): 9259. http://dx.doi.org/10.3390/app11199259.
Повний текст джерелаАнотація:
Autonomous driving is a breakthrough technology in the automobile and transportation fields. The characteristics of planned trajectories and tracking accuracy affect the development of autonomous driving technology. To improve the measurement accuracy of the vehicle state and realise the online application of predictive control algorithm, an online active set-based longitudinal and lateral model predictive tracking control method of autonomous driving is proposed for electric vehicles. Integrated with the vehicle inertial measurement unit (IMU) and global positioning system (GPS) information, a vehicle state estimator is designed based on an extended Kalman filter. Based on the 3-degree-of-freedom vehicle dynamics model and the curvilinear road coordinate system, the longitudinal and lateral errors dimensionality reduction is carried out. A fast-rolling optimisation algorithm for longitudinal and lateral tracking control of autonomous vehicles is designed and implemented based on convex optimisation, online active set theory and QP solver. Finally, the performance of the proposed tracking control method is verified in the reconstructed curve road scene based on real GPS data. The hardware-in-the-loop simulation results show that the proposed MPC controller has apparent advantages compared with the PID-based controller.
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König, Adrian, Lorenzo Nicoletti, Daniel Schröder, Sebastian Wolff, Adam Waclaw, and Markus Lienkamp. "An Overview of Parameter and Cost for Battery Electric Vehicles." World Electric Vehicle Journal 12, no. 1 (February 3, 2021): 21. http://dx.doi.org/10.3390/wevj12010021.
Повний текст джерелаАнотація:
The launch of both battery electric vehicles (BEVs) and autonomous vehicles (AVs) on the global market has triggered ongoing radical changes in the automotive sector. On the one hand, the new characteristics of the BEV powertrain compared to the combustion type have resulted in new central parameters, such as vehicle range, which then become an important selling point. On the other hand, electric components are as yet not optimized and the sensors needed for autonomous driving are still expensive, which introduces changes to the vehicle cost structure. This transformation is not limited to the vehicle itself but also extends to its mobility and the necessary infrastructure. The former is shaped by new user behaviors and scenarios. The latter is impacted by the BEV powertrain, which requires a charging and energy supply infrastructure. To enable manufacturers and researchers to develop and optimize BEVs and AVs, it is necessary to first identify the relevant parameters and costs. To this end, we have conducted an extensive literature review. The result is a complete overview of the relevant parameters and costs, divided into the categories of vehicle, infrastructure, mobility, and energy.
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E. Webber, Michael. "Electric Highway." Mechanical Engineering 141, no. 06 (June 1, 2019): 32–37. http://dx.doi.org/10.1115/1.2019-jun3.
Повний текст джерелаАнотація:
Electric and autonomous vehicles will change the layout and rhythm of our lives. Entwined with this story of change are the fuels and forms of energy we used to enable the engines and motors to propel us forward. In this excerpt from his upcoming book, noted energy expert Michael Webber makes the case that switching from oil to electricity for powering vehicles would cut transportation-related carbon emissions and create a pathway to quieter, zippier travel.
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Wu, Zhongming, Mufangzhou Zhu, Yu Guo, Li Sun, and Yuchen Gu. "Drive System Design for Small Autonomous Electric Vehicle: Topology Optimization and Simulation." Wireless Communications and Mobile Computing 2021 (December 16, 2021): 1–12. http://dx.doi.org/10.1155/2021/7192484.
Повний текст джерелаАнотація:
High driving efficiency remains challenging in autonomous electric vehicles, especially in small electric vehicle subtype. Here, we reported investigation of the structure and requirements of the drive system for those vehicles, while the motor-drive axle combined integrated driving scheme has been chosen. In the study, the power matching of drive motor as well as transmission ratio has been calculated based on the performance of the small electric vehicles, and the total gear ratio of 8.124 was determined. For better comprehensive performance and efficiency, the two-stage retarder has been designed, in which elements including high-speed shaft, low-speed shaft, gears, and differential have been examined to ensure their proof strength when the motor outputs reached the maximum torque. Notably, by utilizing topology optimization, Gear 4, the transmission unit with the heaviest weight percentage has been modified in a lightweight way, achieving a 41% reduction of the mass in emulation analysis and turned up to the target of optimization eventually.
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Guo, Jinghua, Yugong Luo, and Keqiang Li. "Adaptive coordinated leader–follower control of autonomous over-actuated electric vehicles." Transactions of the Institute of Measurement and Control 39, no. 12 (May 20, 2016): 1798–810. http://dx.doi.org/10.1177/0142331216648374.
Повний текст джерелаАнотація:
In this paper, the leader–follower formation control problem of autonomous over-actuated electric vehicles on a highway is studied. As the autonomous over-actuated electric vehicles have the characteristics of non-linearities, external disturbances and strong coupling, a novel coordinated three-level control system is constructed to supervise the longitudinal and lateral motions of autonomous electric vehicles. Firstly, an adaptive terminal sliding high-level control algorithm is designed to compute a vector of total forces and torque of vehicles, and the stability of the high-level control system is proven via Lyapunov analysis where uniform ultimate boundedness of the closed-loop signals is guaranteed. Then, a pseudo-inverse control allocation algorithm, which can achieve fault tolerance and reconfiguration of the redundant tyre actuation system, is presented to generate the desired longitudinal and lateral tyre forces. Then, a separate low-level controller consisting of an inverse tyre model and two inner loops for each wheel is designed to achieve its desired forces. Finally, simulation results demonstrate that the proposed control system not only enhance the tracking performance, but also improve the stability and riding comfort of autonomous over-actuated electric vehicles in a platoon.
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Gandomani, Roxana, Moataz Mohamed, Amir Amiri, and Saiedeh Razavi. "System Optimization of Shared Mobility in Suburban Contexts." Sustainability 14, no. 2 (January 13, 2022): 876. http://dx.doi.org/10.3390/su14020876.
Повний текст джерелаАнотація:
Shared mobility is a viable choice to improve the connectivity of lower-density neighbourhoods or suburbs that lack high-frequency public transportation services. In addition, its integration with new forms of powertrain and autonomous technologies can achieve more sustainable and efficient transportation. This study compares four shared-mobility technologies in suburban areas: the Internal Combustion Engine, Battery Electric, and two Autonomous Electric Vehicle scenarios, for various passenger capacities ranging from three to fifteen. The study aims to provide policymakers, transportation planners, and transit providers with insights into the potential costs and benefits as well as system configurations of shared mobility in a suburban context. A vehicle routing problem with time windows was applied using the J-Horizon software to optimize the costs of serving existing intra-community demand. The results indicate a similar fleet composition for Battery Electric and Autonomous Electric fleets. Furthermore, the resulting fleet for all four technologies is dominated by larger vehicle capacities. Due to the large share of driver cost in the total cost, the savings using a fleet of Autonomous Electric Vehicles are predicted to be 68% and 70%, respectively, compared to Internal Combustion and Battery Electric fleets.
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Lee, Sungwon, Devon Farmer, Jooyoung Kim, and Hyun Kim. "Shared Autonomous Vehicles Competing with Shared Electric Bicycles: A Stated-Preference Analysis." Sustainability 14, no. 21 (November 2, 2022): 14319. http://dx.doi.org/10.3390/su142114319.
Повний текст джерелаАнотація:
Understanding the factors that affect the uptake of emerging transport modes is critical for understanding if and how they will be used once they are implemented. In this study, we undertook a stated-preference analysis to understand the factors that affect the use of shared autonomous vehicles and shared personal mobility (micromobility) as competing modes on a university campus in Korea. We applied a binary logit model, which included time and cost variables as well as the perceptions of convenience (in-car congestion and availability) and safety. For autonomous vehicles, the cost- and time-related demand elasticities were estimated to be −0.45 and −0.25, respectively, while the cost elasticity for shared electric bicycles was −0.42. The elasticities of perceived convenience (availability) and safety for the shared electric bicycle system were estimated to be 0.72 and 0.29, respectively. Finally, the elasticity for perceived convenience (in-car congestion) of the shared autonomous vehicle was 0.42. Our results show that there is an innate preference for shared autonomous vehicles when these are compared to shared personal mobility, and that the effect of subjective variables (convenience and safety) on the use of emerging transport modes is as important as traditional cost and time variables.
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Azam, Shoaib, Farzeen Munir, Ahmad Muqeem Sheri, Joonmo Kim, and Moongu Jeon. "System, Design and Experimental Validation of Autonomous Vehicle in an Unconstrained Environment." Sensors 20, no. 21 (October 22, 2020): 5999. http://dx.doi.org/10.3390/s20215999.
Повний текст джерелаАнотація:
In recent years, technological advancements have made a promising impact on the development of autonomous vehicles. The evolution of electric vehicles, development of state-of-the-art sensors, and advances in artificial intelligence have provided necessary tools for the academia and industry to develop the prototypes of autonomous vehicles that enhance the road safety and traffic efficiency. The increase in the deployment of sensors for the autonomous vehicle, make it less cost-effective to be utilized by the consumer. This work focuses on the development of full-stack autonomous vehicle using the limited amount of sensors suite. The architecture aspect of the autonomous vehicle is categorized into four layers that include sensor layer, perception layer, planning layer and control layer. In the sensor layer, the integration of exteroceptive and proprioceptive sensors on the autonomous vehicle are presented. The perception of the environment in term localization and detection using exteroceptive sensors are included in the perception layer. In the planning layer, algorithms for mission and motion planning are illustrated by incorporating the route information, velocity replanning and obstacle avoidance. The control layer constitutes lateral and longitudinal control for the autonomous vehicle. For the verification of the proposed system, the autonomous vehicle is tested in an unconstrained environment. The experimentation results show the efficacy of each module, including localization, object detection, mission and motion planning, obstacle avoidance, velocity replanning, lateral and longitudinal control. Further, in order to demonstrate the experimental validation and the application aspect of the autonomous vehicle, the proposed system is tested as an autonomous taxi service.
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Menyhárt, József, Gerald Mies, and István Komlósi. "Measurement Chamber Design for Testing Batteries of the Electric Vehicles." Repüléstudományi Közlemények 32, no. 2 (2020): 105–15. http://dx.doi.org/10.32560/rk.2020.2.8.
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Crucial factors with respect to modern autonomous vehicles include reliability and design. Researchers and engineers strive to increase the number of vehicles over the latest possibilities both in industrial and in military applications. A number of modern batteries are available on the market for the electric autonomous vehicles. The authors suggest the use of test chambers to investigate optimal battery use and performance in vehicles. The results of the theoretical research suggest that the use of test chambers during battery management system development is necessary.
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Hesami, Simin, Cedric De Cauwer, Evy Rombaut, Lieselot Vanhaverbeke, and Thierry Coosemans. "Energy-Optimal Speed Control for Autonomous Electric Vehicles Up- and Downstream of a Signalized Intersection." World Electric Vehicle Journal 14, no. 2 (February 17, 2023): 55. http://dx.doi.org/10.3390/wevj14020055.
Повний текст джерелаАнотація:
Signalized intersections can increase the vehicle stops and consequently increase the energy consumption by forcing stop-and-go dynamics on vehicles. Eco-driving with the help of connectivity is a solution that could avoid multiple stops and improve energy efficiency. In this paper, an eco-driving framework is developed, which finds the energy-efficient speed profile both up- and downstream of a signalized intersection in free-flow situations (eco-FF). The proposed framework utilizes the signal phasing and timing (SPaT) data that are communicated to the vehicle. The energy consumption model used in this framework is a combination of vehicle dynamics and time-dependent auxiliary consumption, which implicitly incorporates the travel time into the function and is validated with real-world test data. It is shown that, by using the proposed eco-FF framework, the vehicle’s energy consumption is notably reduced.
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Benarbia, Taha, Kyandoghere Kyamakya, Fadi Al Machot, and Witesyavwirwa Vianney Kambale. "Modeling and Simulation of Shared Electric Automated and Connected Mobility Systems with Autonomous Repositioning: Performance Evaluation and Deployment." Sustainability 15, no. 1 (January 3, 2023): 881. http://dx.doi.org/10.3390/su15010881.
Повний текст джерелаАнотація:
The boom seen in artificial intelligence in recent years has led to a revolution in the automotive industry. Numerous automakers around the world, such as Tesla, Toyota, Honda, and BMW, have achieved giant strides in the development of e-autonomous vehicles. Consequently, shared electric automated vehicle mobility (SEAVM) systems, which are a crucial part of future innovative transportation solutions, have attracted significant attention from the research community, particularly from a design perspective. However, the flexibility of shared automated mobility systems may lead to a self-operating technology issue (unequal distribution of vehicles), since users in these systems can pick up and drop off electric vehicles wherever they like. With this in mind, this paper addressed the issues of autonomous repositioning and the assignment of shared autonomous electric vehicle systems to balance a system’s network and fulfill its demand. Modeling, analysis and assessment of the system’s performance were carried out using stochastic Petri nets formalism, which included determining the average time areas were empty/congested and the number of unserved consumers, and estimating the redistribution service launch moment. Furthermore, many simulation scenarios were analyzed, including repositioning and without repositioning scenarios, in order to evaluate the efficiency of the model and to show the potential of using Petri nets as a probabilistic formalism approach for the modeling of e-automated mobility systems.
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Chen, Yuche, Ruixiao Sun, and Xuanke Wu. "Estimating Bounds of Aerodynamic, Mass, and Auxiliary Load Impacts on Autonomous Vehicles: A Powertrain Simulation Approach." Sustainability 13, no. 22 (November 10, 2021): 12405. http://dx.doi.org/10.3390/su132212405.
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Vehicle automation requires new onboard sensors, communication equipment, and/or data processing units, and may encourage modifications to existing onboard components (such as the steering wheel). These changes impact the vehicle’s mass, auxiliary load, coefficient of drag, and frontal area, which then change vehicle performance. This paper uses the powertrain simulation model FASTSim to quantify the impact of autonomy-related design changes on a vehicle’s fuel consumption. Levels 0, 2, and 5 autonomous vehicles are modeled for two battery-electric vehicles (2017 Chevrolet Bolt and 2017 Nissan Leaf) and a gasoline powered vehicle (2017 Toyota Corolla). Additionally, a level 5 vehicle is divided into pessimistic and optimistic scenarios which assume different electronic equipment integration format. The results show that 4–8% reductions in energy economy can be achieved in a L5 optimistic scenario and an 10–15% increase in energy economy will be the result in a L5 pessimistic scenario. When looking at impacts on different power demand sources, inertial power is the major power demand in urban driving conditions and aerodynamic power demand is the major demand in highway driving conditions.
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Ramesh, G., and J. Praveen. "Artificial Intelligence (AI) Framework for Multi-Modal Learning and Decision Making towards Autonomous and Electric Vehicles." E3S Web of Conferences 309 (2021): 01167. http://dx.doi.org/10.1051/e3sconf/202130901167.
Повний текст джерелаАнотація:
An electric vehicle with autonomous driving is a possibility provided technology innovations in multi-disciplinary approach. Electric vehicles leverage environmental conditions and are much desired in the contemporary world. Another great possibility is to strive for making the vehicle to drive itself (autonomous driving) provided instructions. When the two are combined, it leads to a different dimension of environmental safety and technology driven driving that has many pros and cons as well. It is still in its infancy and there is much research to be carried out. In this context, this paper is aimed at building an Artificial Intelligence (AI) framework that has dual goal of “monitoring and regulating power usage” and facilitating autonomous driving with technology-driven and real time knowledge required. A methodology is proposed with multiple deep learning methods. For instance, deep learning is used for localization of vehicle, path planning at high level and path planning for low level. Apart from this, there is reinforcement learning and transfer learning to speed up the process of gaining real time business intelligence. To facilitate real time knowledge discovery from given scenarios, both edge and cloud resources are appropriately exploited to benefit the vehicle as driving safety is given paramount importance. There is power management module where modular Recurrent Neural Network is used. Another module known as speed control is used to have real time control over the speed of the vehicle. The usage of AI framework makes the electronic and autonomous vehicles realize unprecedented possibilities in power management and safe autonomous driving. Key words: Artificial Intelligence Autonomous Driving Recurrent Neural Network Transfer Learning
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Dai, Deyun, Zonghai Chen, Peng Bao, and Jikai Wang. "A Review of 3D Object Detection for Autonomous Driving of Electric Vehicles." World Electric Vehicle Journal 12, no. 3 (August 30, 2021): 139. http://dx.doi.org/10.3390/wevj12030139.
Повний текст джерелаАнотація:
In recent years, electric vehicles have achieved rapid development. Intelligence is one of the important trends to promote the development of electric vehicles. As a result, autonomous driving system is becoming one of the core systems of electric vehicles. Considering that environmental perception is the basis of intelligent planning and safe decision-making for intelligent vehicles, this paper presents a survey of the existing perceptual methods in vehicles, especially 3D object detection, which guarantees the reliability and safety of vehicles. In this review, we first introduce the role of perceptual module in autonomous driving system and a relationship with other modules. Then, we classify and analyze the corresponding perception methods based on the different sensors. Finally, we compare the performance of the surveyed works on public datasets and discuss the possible future research interests.
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Khadhraoui, A., T. Selmi, and A. Cherif. "Energy Management of a Hybrid Electric Vehicle." Engineering, Technology & Applied Science Research 12, no. 4 (August 7, 2022): 8916–21. http://dx.doi.org/10.48084/etasr.5058.
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Electric Vehicles (EVs) are becoming more popular and gaining attention due to a combination of factors such as falling prices and increasing environmental awareness. EVs fall into several categories related to energy production and storage. Standard developed, tested, and commercialized EV technologies include Fuel Cell Electric Vehicles (FCEVs), All Electric Vehicles (AEVs), also known as Battery Electric Vehicles (BEVs), Plug-in Hybrid Electric Vehicles (PHEVs), Hybrid Electric Vehicles (HEVs), and Flexible Fuel Vehicles (FFVs). Still, the advantages of FCEVs are relatively small compared to other autonomous and refueling technologies. Considering the above aspects, this work presents a Matlab/Simulink model of an FCEV’s behavior and opportunities.
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Caiazzo, Bianca, Angelo Coppola, Alberto Petrillo, and Stefania Santini. "Distributed Nonlinear Model Predictive Control for Connected Autonomous Electric Vehicles Platoon with Distance-Dependent Air Drag Formulation." Energies 14, no. 16 (August 19, 2021): 5122. http://dx.doi.org/10.3390/en14165122.
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This paper addresses the leader tracking problem for a platoon of heterogeneous autonomous connected fully electric vehicles where the selection of the inter-vehicle distance between adjacent vehicles plays a crucial role in energy consumption reduction. In this framework, we focused on the design of a cooperative driving control strategy able to let electric vehicles move as a convoy while keeping a variable energy-oriented inter-vehicle distance between adjacent vehicles which, depending on the driving situation, was reduced as much as possible to guarantee air-drag reduction, energy saving and collision avoidance. To this aim, by exploiting a distance-dependent air drag coefficient formulation, we propose a novel distributed nonlinear model predictive control (DNMPC) where the cost function was designed to ensure leader tracking performances, as well as to optimise the inter-vehicle distance with the aim of reducing energy consumption. Extensive simulation analyses, involving a comparative analysis with respect to the classical constant time headway (CTH) spacing policy, were performed to confirm the capability of the DNMPC in guaranteeing energy saving.
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Katis, Christodoulos, and Athanasios Karlis. "Evolution of Equipment in Electromobility and Autonomous Driving Regarding Safety Issues." Energies 16, no. 3 (January 25, 2023): 1271. http://dx.doi.org/10.3390/en16031271.
Повний текст джерелаАнотація:
Over the years, an increase in the traffic of electric and hybrid electric vehicles and vehicles with hydrogen cells is being observed, while at the same time, self-driving cars are appearing as a modern trend in transportation. As the years pass, their equipment will evolve. So, considering the progress in vehicle equipment over the years, additional technological innovations and applications should be proposed in the near future. Having that in mind, an analytical review of the progress of equipment in electromobility and autonomous driving is performed in this paper. The outcomes of this review comprise hints for additional complementary technological innovations, applications, and operating constraints along with proposals for materials, suggestions and tips for the future. The aforementioned hints and tips aim to help in securing proper operation of each vehicle part and charging equipment in the future, and make driving safer in the future. Finally, this review paper concludes with a discussion and bibliographic references.
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Marin-Plaza, Pablo, David Yagüe, Francisco Royo, Miguel Ángel de Miguel, Francisco Miguel Moreno, Alejandro Ruiz-de-la-Cuadra, Fernando Viadero-Monasterio, Javier Garcia, José Luis San Roman, and José María Armingol. "Project ARES: Driverless Transportation System. Challenges and Approaches in an Unstructured Road." Electronics 10, no. 15 (July 21, 2021): 1753. http://dx.doi.org/10.3390/electronics10151753.
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The expansion of electric vehicles in urban areas has paved the way toward the era of autonomous vehicles, improving the performance in smart cities and upgrading related driving problems. This field of research opens immediate applications in the tourism areas, airports or business centres by greatly improving transport efficiency and reducing repetitive human tasks. This project shows the problems derived from autonomous driving such as vehicle localization, low coverage of 4G/5G and GPS, detection of the road and navigable zones including intersections, detection of static and dynamic obstacles, longitudinal and lateral control and cybersecurity aspects. The approaches proposed in this article are sufficient to solve the operational design of the problems related to autonomous vehicle application in the special locations such as rough environment, high slopes and unstructured terrain without traffic rules.
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Ren, Yue, Ling Zheng, Wei Yang, and Yinong Li. "Potential field–based hierarchical adaptive cruise control for semi-autonomous electric vehicle." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 10 (September 11, 2018): 2479–91. http://dx.doi.org/10.1177/0954407018797571.
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Adaptive cruise control, as a driver assistant system for vehicles, can adjust the vehicle speed to keep the appropriate distance from other vehicles, which highly increases the driving safety and driver’s comfort. This paper presents hierarchical adaptive cruise control system that could balance the driver’s expectation, collision risk, and ride comfort. In the adaptive cruise control structure, there are two controllers to achieve the function. The one is the upper controller which is established based on the model predictive control theory and used to calculate the desirable longitudinal acceleration. The collision risk is described by the Gaussian distribution. A quadratic cost function for model predictive control is formulated based on the potential field method through the contradictions between the tracking error, collision risk, and the longitudinal ride comfort. The other one is the lower optimal torque vectoring controller which is constructed based on the vehicle longitudinal dynamics. And it can generate the desired acceleration considering the anti-wheel slip limitations. Several simulations under different road conditions demonstrate that the proposed adaptive cruise control has significant performance on balancing the tracking ability, collision avoidance, ride comfort, and adhesion utilization. It also maintains vehicle stability for the complex road conditions.
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Zöldy, Máté, and Imre Zsombók. "Influence of External Environmental Factors on Range Estimation of Autonomous Hybrid Vehicles." System Safety: Human - Technical Facility - Environment 1, no. 1 (March 1, 2019): 472–80. http://dx.doi.org/10.2478/czoto-2019-0061.
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AbstractDuring our research, we focus on a less researched area in the development of autonomous vehicles. Automotive industry is turning more and more from conventional, internal combustion engine equipped vehicles to the electric cars. Today, electric driving is mostly limited to urban traffic, this is the area where range and refueling limits can be a real alternative. However, it is important to think of those who intend to use vehicle in longer distances, and hybrid technology can provide them a modern, environmentally conscious way of transport.In this article, we describe the method of creating the fuel consumption influencing factors matrix, which is the starting point of our research. We studied relevant researches and based on refueling studies we created the matrix. Based on results of real tests, we determined the factor mix that are the basis of our fuel consumption prediction model. These results will be inputs of planning routes of autonomous vehicles with optimized refueling and fuel consumption.
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Anastasiadou, Konstantina. "Sustainable Mobility Driven Prioritization of New Vehicle Technologies, Based on a New Decision-Aiding Methodology." Sustainability 13, no. 9 (April 23, 2021): 4760. http://dx.doi.org/10.3390/su13094760.
Повний текст джерелаАнотація:
In an era of environmental and socio-economic crisis, sustainable transport planning is vital as ever, especially given that the transport sector is responsible for the greatest part of total air pollution and greenhouse gas emissions. New vehicle technologies, such as autonomous and electric vehicles, emerge as promising alternatives, creating, however, both opportunities and challenges and raising questions relating to their performance. Can these new vehicle technologies really perform better than conventional ones in terms of sustainable mobility? Which one of them constitutes the optimum solution? How does each alternative perform with regard to different evaluation criteria, such as air pollution or road safety? In order to answer such questions, and to select the optimum solution, a comparison between autonomous, electric, autonomous electric and conventional vehicles is executed, based on a set of social, economic and environmental criteria. For this purpose, a new decision-aiding methodology, allowing for a holistic evaluation of the alternatives through a comprehensive literature review and experts’ participation, is applied. It is mainly based on the combined application of two hybrid multi-criteria analysis models, creating a more solid background towards optimum decision-making, thus constituting an important decision support tool for project appraisal and funding within the framework of sustainability in any sector.
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Adegbohun, Feyijimi, Annette von Jouanne, and Kwang Lee. "Autonomous Battery Swapping System and Methodologies of Electric Vehicles." Energies 12, no. 4 (February 19, 2019): 667. http://dx.doi.org/10.3390/en12040667.
Повний текст джерелаАнотація:
The transportation industry contributes a significant amount of carbon emissions and pollutants to the environment globally. The adoption of electric vehicles (EVs) has a significant potential to not only reduce carbon emissions, but also to provide needed energy storage to contribute to the adoption of distributed renewable generation. This paper focuses on a design model and methodology for increasing EV adoption through automated swapping of battery packs at battery sharing stations (BShS) as a part of a battery sharing network (BShN), which would become integral to the smart grid. Current battery swapping methodologies are reviewed and a new practical approach is proposed considering both the technical and socio-economic impacts. The proposed BShS/BShN provides novel solutions to some of the most preeminent challenges that EV adoption faces today such as range anxiety, grid reliability, and cost. Challenges and advancements specific to this solution are also discussed.
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Donnellan, Paul R. "The Future of Mobility—Electric, Autonomous, and Shared Vehicles." IEEE Engineering Management Review 46, no. 4 (December 2018): 16–18. http://dx.doi.org/10.1109/emr.2018.2880987.
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Bouibed, Kamel, Abdel Aitouche, and Mireille Bayart. "Control and Reconguration of Train of Autonomous Electric Vehicles." Journal of Asian Electric Vehicles 10, no. 1 (2012): 1543–51. http://dx.doi.org/10.4130/jaev.10.1543.
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Bian, Chentong, Guodong Yin, Liwei Xu, and Ning Zhang. "Active collision algorithm for autonomous electric vehicles at intersections." IET Intelligent Transport Systems 13, no. 1 (January 1, 2019): 90–97. http://dx.doi.org/10.1049/iet-its.2018.5178.
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Quttoum, Ahmad Nahar. "AARM: An Autonomous Adaptive Routing Model for Electric-Vehicles." Procedia Computer Science 210 (2022): 28–35. http://dx.doi.org/10.1016/j.procs.2022.10.116.
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Goel, Mansi, Nargis Warsi, Bhavesh Batra, and Aman Singla. "A Review Paper on Development of e-Vehicles." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 952–55. http://dx.doi.org/10.22214/ijraset.2022.47995.
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Abstract: In this paper, we present a detailed chronological analysis of the achievements in autonomous automation, which is an area of interest for researchers. This paper can be useful for understanding the trends in autonomous vehicletechnology in the past, present, and future. The technology of autonomous vehicles has drastically changed since the 1920s, when radio controlled vehicles first appeared. Electric cars powered by embedded circuits on the road became fairly autonomous in the next few decades. By the 1960s, autonomous cars had similar electronic guide systems. The 1980s saw the introduction of vision guided autonomous vehicles, a major milestone in technology that we continue to use today. In modern cars, semi-autonomous features such as lane keeping,automatic braking, and adaptive cruise control are based on these systems. An extensive network of visionguided systems is the future of autonomous vehicles. It is predicted that the majority of companieswill launch fully autonomous vehicles by the turn of the century. We are entering an era of safe, comfortable, and efficient transportation with autonomous vehicles.
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Nadhilah, Muhammad Arif Budiyanto, Alif Hikmah Fikri, and Hanmah Ayuningtyas. "Study On The Application Of Thermoelectric Coolers Inside Unmanned Surface Vehicles." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 82, no. 1 (April 11, 2021): 12–20. http://dx.doi.org/10.37934/arfmts.82.1.1220.
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The development of unmanned surface vehicles for military and commercial needs is increasing as the development of autonomous control systems. The farther the operation range of unmanned surface vehicles makes the propulsion motor generated heat and decreased the performance of the vehicle. This study aims to analyze the application of a thermoelectric cooler to decrease the temperature of the electric motors as a propulsion system on the unmanned surface vehicle. The research was carried out by prototyping the thermoelectric cooler 12V and tested at the prototype of unmanned surface vehicles with a length overall 1.5 m. The results showed the application of a thermoelectric cooler potentially effective to decrease the electric motor temperature by as much as 26.3 ?C by neglect the heat loss due to convection. The results of this study contributed to the development of reliable unmanned surface vehicles.
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Xu, Liwei, Weichao Zhuang, Guodong Yin, Guangmin Li, and Chentong Bian. "Robust overtaking control of autonomous electric vehicle with parameter uncertainties." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 13 (January 22, 2019): 3358–76. http://dx.doi.org/10.1177/0954407018824522.
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In this paper, we propose a two-layer overtaking control framework of the autonomous electric ground vehicle, including trajectory planning and tracking control. In the upper layer, a stable overtaking trajectory is derived by considering the duration of the overtaking, driving comfort and vehicle stability simultaneously. Besides, the safety spacing between the overtaking and overtaken vehicles is analyzed to prevent the potential collision. To track the generated reference trajectory precisely, we design a robust model predictive controller adopting the input-to-state stability property in the lower layer to reduce the affection of disturbances and parameter uncertainties. Two driving strategies with different lateral accelerations, that is, mild and aggressive, are simulated to verify the effectiveness of the proposed control framework. By comparing to the driver-vehicle control system, the proposed control framework can not only achieve safe, smooth, and rapid overtaking but also realize the accurate state tracking in the presence of tire cornering stiffness uncertainty.