Pub Date : 2024-07-16DOI: 10.1109/OJVT.2024.3428976
A. Elaidy;R. Rayner;C. Kalyvas
Pedestrians are exceptionally vulnerable in road accidents, and despite the advancements in airbag technology for vehicle occupants, fatal injuries still occur due to contact between pedestrians and vehicle components. To address this issue, an innovative solution is introduced in this research: an external airbag system designed to safeguard pedestrians in cases of brake failure. The proposed system includes four airbag modules strategically positioned within the front bumper of the vehicle. These modules are specifically designed to deploy during a collision, providing protection for the pedestrian's head, legs, and body. Equipped with a highly sensitive sensor, the system triggers the airbag electronic controller unit (ECU) upon collision detection. The external airbag curtains deploy, shielding the pedestrian's head from striking the bonnet, while an additional airbag safeguards the pedestrian's legs from impact with the front bumper. With the introduction of this innovative external airbag system, the main goal is to significantly improve road safety for all individuals and prevent numerous fatalities. The introduction of the innovative external airbag system marks a significant advancement in pedestrian safety within the realm of road accidents. By strategically positioning four airbag modules within the vehicle's front bumper and equipping them with a highly sensitive sensor, this system effectively deploys during collisions to protect pedestrians' heads, legs, and bodies. The deployment of external airbag curtains shields pedestrians' heads from striking the bonnet, while an additional airbag safeguards their legs from impact with the front bumper. Through this research and implementation, the primary objective is to enhance road safety for all individuals and mitigate the occurrence of numerous fatalities resulting from pedestrian-vehicle collisions.
{"title":"Innovative Design of External Airbag System for Improved Automotive Safety","authors":"A. Elaidy;R. Rayner;C. Kalyvas","doi":"10.1109/OJVT.2024.3428976","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3428976","url":null,"abstract":"Pedestrians are exceptionally vulnerable in road accidents, and despite the advancements in airbag technology for vehicle occupants, fatal injuries still occur due to contact between pedestrians and vehicle components. To address this issue, an innovative solution is introduced in this research: an external airbag system designed to safeguard pedestrians in cases of brake failure. The proposed system includes four airbag modules strategically positioned within the front bumper of the vehicle. These modules are specifically designed to deploy during a collision, providing protection for the pedestrian's head, legs, and body. Equipped with a highly sensitive sensor, the system triggers the airbag electronic controller unit (ECU) upon collision detection. The external airbag curtains deploy, shielding the pedestrian's head from striking the bonnet, while an additional airbag safeguards the pedestrian's legs from impact with the front bumper. With the introduction of this innovative external airbag system, the main goal is to significantly improve road safety for all individuals and prevent numerous fatalities. The introduction of the innovative external airbag system marks a significant advancement in pedestrian safety within the realm of road accidents. By strategically positioning four airbag modules within the vehicle's front bumper and equipping them with a highly sensitive sensor, this system effectively deploys during collisions to protect pedestrians' heads, legs, and bodies. The deployment of external airbag curtains shields pedestrians' heads from striking the bonnet, while an additional airbag safeguards their legs from impact with the front bumper. Through this research and implementation, the primary objective is to enhance road safety for all individuals and mitigate the occurrence of numerous fatalities resulting from pedestrian-vehicle collisions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"967-978"},"PeriodicalIF":5.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.1109/OJVT.2024.3428645
Zhiqiang Zhang;Lei Zhang;Mingqiang Wang;Cong Wang;Zhenpo Wang
Comprehensive and accurate understanding of the interactive traffic environment facilitates reasonable motion planning for automated vehicles. This paper presents an overall risk assessment method for the host vehicle to achieve efficient motion planning considering uncertainties of the predicted driving behaviors of surrounding vehicles. A Social Temporal Convolutional Long Short-Term Memory network is constructed to capture the interactive characteristics among the host and surrounding vehicles and to predict the statistical distribution of the trajectory prediction uncertainty in the prediction horizon. Then a two-dimensional Gaussian distribution-based dynamic risk assessment with a soft update method is developed to spatially and temporally quantify the driving risk by constructing the occupancy map based on the multi-modal distribution of the predicted trajectories for the surrounding vehicles. The optimal motion of the host vehicle is determined by minimizing a multi-objective function of the alternative driving behaviors. The effectiveness of the proposed scheme is verified under typical driving scenarios extracted from the NGSIM dataset. The results show that the proposed method can comprehensively evaluate the potential risk and efficiently achieve motion planning while minimizing the driving risk.
{"title":"An Uncertainty-Aware Lane Change Motion Planning Algorithm Based on Probabilistic Trajectory Prediction Distribution","authors":"Zhiqiang Zhang;Lei Zhang;Mingqiang Wang;Cong Wang;Zhenpo Wang","doi":"10.1109/OJVT.2024.3428645","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3428645","url":null,"abstract":"Comprehensive and accurate understanding of the interactive traffic environment facilitates reasonable motion planning for automated vehicles. This paper presents an overall risk assessment method for the host vehicle to achieve efficient motion planning considering uncertainties of the predicted driving behaviors of surrounding vehicles. A Social Temporal Convolutional Long Short-Term Memory network is constructed to capture the interactive characteristics among the host and surrounding vehicles and to predict the statistical distribution of the trajectory prediction uncertainty in the prediction horizon. Then a two-dimensional Gaussian distribution-based dynamic risk assessment with a soft update method is developed to spatially and temporally quantify the driving risk by constructing the occupancy map based on the multi-modal distribution of the predicted trajectories for the surrounding vehicles. The optimal motion of the host vehicle is determined by minimizing a multi-objective function of the alternative driving behaviors. The effectiveness of the proposed scheme is verified under typical driving scenarios extracted from the NGSIM dataset. The results show that the proposed method can comprehensively evaluate the potential risk and efficiently achieve motion planning while minimizing the driving risk.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1386-1399"},"PeriodicalIF":5.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.1109/OJVT.2024.3427326
Takamasa Higuchi;Lei Zhong;Ryokichi Onishi
The increasing network traffic from connected vehicles is putting a strain on the limited bandwidth resources of cellular networks. Delay-tolerant networking (DTN) over vehicle-to-vehicle (V2V) communications has been considered as an effective means of offloading the cellular data traffic, while its quantitative performance in urban road traffic remains unclear in many aspects. In this paper, we unveil the benefits of data offloading over vehicular DTNs by city-scale network simulations in Nagoya, Japan. The simulation scenario embraces more than 8 million vehicle trips over five consecutive days. The vehicle routes are carefully calibrated against public statistics on the road traffic volume to enable realistic simulations of V2V communication opportunities between vehicles on the road. The results indicate the strong potential of vehicular DTNs in mixed urban road traffic, comprised of both public transport and privately owned vehicles – a large amount data traffic can be offloaded from cellular networks to V2V communication networks even with the limited ratio of vehicles participating the vehicular DTNs.
{"title":"Data Offloading Over Vehicular DTNs: City-Wide Feasibility Study in Nagoya","authors":"Takamasa Higuchi;Lei Zhong;Ryokichi Onishi","doi":"10.1109/OJVT.2024.3427326","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3427326","url":null,"abstract":"The increasing network traffic from connected vehicles is putting a strain on the limited bandwidth resources of cellular networks. Delay-tolerant networking (DTN) over vehicle-to-vehicle (V2V) communications has been considered as an effective means of offloading the cellular data traffic, while its quantitative performance in urban road traffic remains unclear in many aspects. In this paper, we unveil the benefits of data offloading over vehicular DTNs by city-scale network simulations in Nagoya, Japan. The simulation scenario embraces more than 8 million vehicle trips over five consecutive days. The vehicle routes are carefully calibrated against public statistics on the road traffic volume to enable realistic simulations of V2V communication opportunities between vehicles on the road. The results indicate the strong potential of vehicular DTNs in mixed urban road traffic, comprised of both public transport and privately owned vehicles – a large amount data traffic can be offloaded from cellular networks to V2V communication networks even with the limited ratio of vehicles participating the vehicular DTNs.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"940-949"},"PeriodicalIF":5.3,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598345","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.1109/OJVT.2024.3427722
Vladimir Prakht;Vladimir Dmitrievskii;Vadim Kazakbaev;Eduard Valeev;Aleksey Paramonov;Alecksey Anuchin
Synchronous homopolar machines (SHMs) have established their merit in various applications, including pulse heating generators and automotive generators. They offer such advantages as a simple and dependable rotor design devoid of windings and permanent magnets, and a reliable field winding consisting of a small number of concentrated coils on the stator. This makes SHMs promising as traction motors for off-highway vehicles, such as mining dump trucks. Mining dump trucks confront the challenges of transporting hefty loads on dirt roads at speeds up to 60 km/h and conquering steep inclines. Although conventional induction motors (IMs) are widely used in these trucks, they suffer from rotor overheating, vulnerability to broken rotor bar faults, and substantial low-frequency current oscillations when braking on a slope. These problems stimulate the search for alternatives. This article conducts a theoretical analysis comparing optimized designs of IM and SHM for driving a mining dump truck with a payload of 90 tons. The comparison encompasses critical parameters such as efficiency, losses, torque ripple, required inverter power, dimensions, weight, active material cost, and inverter reliability. The study employs the downhill simplex method for optimization and the finite element method. The study shows that the benefits of SHM include reduced active material costs and improved motor and inverter reliability.
同步同极性机器（SHMs）在脉冲加热发电机和汽车发电机等各种应用中都有不俗的表现。它们具有转子设计简单可靠、无绕组和永久磁铁、定子上由少量集中线圈组成的可靠磁场绕组等优点。这使得 SHM 很有希望成为非公路车辆（如采矿倾卸卡车）的牵引电机。矿用自卸卡车面临着在泥土路上以最高 60 km/h 的速度运输重型货物以及征服陡峭斜坡的挑战。虽然传统的感应电机（IM）被广泛应用于这些卡车中，但它们存在转子过热、转子杆容易断裂以及在斜坡上制动时出现大量低频电流振荡等问题。这些问题促使人们寻找替代品。本文对用于驱动有效载荷为 90 吨的矿用自卸卡车的 IM 和 SHM 优化设计进行了理论分析比较。比较包括效率、损耗、扭矩纹波、所需逆变器功率、尺寸、重量、活性材料成本和逆变器可靠性等关键参数。研究采用下坡单纯形法和有限元法进行优化。研究表明，SHM 的优点包括降低有源材料成本、提高电机和变频器的可靠性。
{"title":"Assessment of the Feasibility of Using a Synchronous Homopolar Motor Instead of an Induction Motor in a Traction Drive With a Wide Constant Power Speed Range","authors":"Vladimir Prakht;Vladimir Dmitrievskii;Vadim Kazakbaev;Eduard Valeev;Aleksey Paramonov;Alecksey Anuchin","doi":"10.1109/OJVT.2024.3427722","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3427722","url":null,"abstract":"Synchronous homopolar machines (SHMs) have established their merit in various applications, including pulse heating generators and automotive generators. They offer such advantages as a simple and dependable rotor design devoid of windings and permanent magnets, and a reliable field winding consisting of a small number of concentrated coils on the stator. This makes SHMs promising as traction motors for off-highway vehicles, such as mining dump trucks. Mining dump trucks confront the challenges of transporting hefty loads on dirt roads at speeds up to 60 km/h and conquering steep inclines. Although conventional induction motors (IMs) are widely used in these trucks, they suffer from rotor overheating, vulnerability to broken rotor bar faults, and substantial low-frequency current oscillations when braking on a slope. These problems stimulate the search for alternatives. This article conducts a theoretical analysis comparing optimized designs of IM and SHM for driving a mining dump truck with a payload of 90 tons. The comparison encompasses critical parameters such as efficiency, losses, torque ripple, required inverter power, dimensions, weight, active material cost, and inverter reliability. The study employs the downhill simplex method for optimization and the finite element method. The study shows that the benefits of SHM include reduced active material costs and improved motor and inverter reliability.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"950-966"},"PeriodicalIF":5.3,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598229","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.1109/OJVT.2024.3426989
Hossam M. Abdelghaffar;Mónica Menéndez
Autonomous vehicles will be widely operated on roadways in the near future. Prior to the broad adoption of autonomous vehicles (AVs), conventional human-driven vehicles would coexist with their AVs counterparts on the same roads, resulting in traffic scenarios that had never been observed before. One such scenario involves the merging of AVs onto a main road. This study assesses the effects of incorporating AVs into a transportation system at different levels of AV penetration. This research analyzes AVs' influence by examining performance metrics such as travel time, delay, number of stops, and stop delay. The results demonstrate that introducing AVs at penetration rates of 10%, 25%, and 50% leads to an average total network delay increase of 4%, 7%, and 18%, respectively. A variety of parameters influence AV performance. To improve AV performance and, consequently, performance metrics, it is critical to identify and effectively control the influential parameters that have a significant impact on AV performance. Consequently, in this paper, we employ the quasi-optimized trajectory elementary effect sensitivity analysis approach, to identify the parameters whose variations are anticipated to significantly impact the performance metrics. The research findings reveal that the time gap, standstill distance, acceleration from a standstill, and the following distance oscillation are all influential parameters affecting the performance metrics of the network, the merging road, and the main road at various levels of AV penetration rate.
在不久的将来，自动驾驶汽车将在道路上广泛运行。在广泛采用自动驾驶汽车（AVs）之前，传统的人类驾驶汽车会与自动驾驶汽车在同一条道路上并存，从而导致前所未有的交通场景。其中一种情况是自动驾驶汽车并入主干道。本研究评估了在不同的自动驾驶汽车普及水平下，将自动驾驶汽车纳入交通系统的影响。研究通过考察旅行时间、延误、停车次数和停车延误等性能指标来分析自动驾驶汽车的影响。结果表明，在 10%、25% 和 50%的渗透率下引入自动驾驶汽车，会导致网络总延迟平均分别增加 4%、7% 和 18%。AV 性能受多种参数影响。要提高 AV 性能，进而改善性能指标，关键是要识别并有效控制对 AV 性能有重大影响的参数。因此，在本文中，我们采用了准优化轨迹基本效应灵敏度分析方法，以确定预计其变化会对性能指标产生重大影响的参数。研究结果表明，时间间隙、静止距离、静止加速度和跟随距离振荡都是影响网络、合流道路和主干道在不同水平的自动驾驶普及率下的性能指标的影响参数。
{"title":"Influential Control Parameters for Autonomous Vehicles in a Mixed Environment","authors":"Hossam M. Abdelghaffar;Mónica Menéndez","doi":"10.1109/OJVT.2024.3426989","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3426989","url":null,"abstract":"Autonomous vehicles will be widely operated on roadways in the near future. Prior to the broad adoption of autonomous vehicles (AVs), conventional human-driven vehicles would coexist with their AVs counterparts on the same roads, resulting in traffic scenarios that had never been observed before. One such scenario involves the merging of AVs onto a main road. This study assesses the effects of incorporating AVs into a transportation system at different levels of AV penetration. This research analyzes AVs' influence by examining performance metrics such as travel time, delay, number of stops, and stop delay. The results demonstrate that introducing AVs at penetration rates of 10%, 25%, and 50% leads to an average total network delay increase of 4%, 7%, and 18%, respectively. A variety of parameters influence AV performance. To improve AV performance and, consequently, performance metrics, it is critical to identify and effectively control the influential parameters that have a significant impact on AV performance. Consequently, in this paper, we employ the quasi-optimized trajectory elementary effect sensitivity analysis approach, to identify the parameters whose variations are anticipated to significantly impact the performance metrics. The research findings reveal that the time gap, standstill distance, acceleration from a standstill, and the following distance oscillation are all influential parameters affecting the performance metrics of the network, the merging road, and the main road at various levels of AV penetration rate.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"927-939"},"PeriodicalIF":5.3,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10596678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hardware impairments (HWI) are imperfections in hardware components that diminish wireless communication performance. Unlike Geometric-based Stochastic Models (GBSMs), existing works on the impact of HWI on cooperative-relay (CR) Non-Orthogonal Multiple Access (NOMA) systems employ the Correlated-based Stochastic Model (CBSM), which does not capture realistic propagation mechanisms. Moreover, studies on CR-NOMA with large antenna transmitters (LATs) using CBSM and GBSM have attracted little attention in academia. We consider this as a computational issue. Although considerable work has been done, there is still a significant knowledge gap about how HWI and imperfect successive interference cancellation affect far-users in CR-NOMA with the LAT system. In this study, the LAT is considered a cylindrical array, and parameters such as delay spread, angle of arrival, and departure are incorporated to achieve a CR-NOMA-GBSM system with amplify-and-forward (AF) or decode-and-forward (DF) relaying schemes. To reduce computing demands, we offer a novel concept of using the physical dimensions of the array to derive the location vector of the antenna element. Using Monte Carlo simulation, near and far users' BER performances deteriorate for AF and DF at 15 dB and 5 dB or below, respectively. As far-users can receive comparable performances as near-users for both AF and DF in terms of achievable rates, this demonstrates the potential rewards of CR-NOMA with LAT.
硬件损伤（HWI）是硬件组件中的缺陷，会降低无线通信性能。与基于几何的随机模型（GBSM）不同，现有关于硬件损伤对合作中继（CR）非正交多址（NOMA）系统影响的研究采用的是基于相关的随机模型（CBSM），该模型无法捕捉现实的传播机制。此外，学术界对使用 CBSM 和 GBSM 的带有大型天线发射器 (LAT) 的 CR-NOMA 的研究也很少关注。我们认为这是一个计算问题。虽然已经做了大量工作，但对于 HWI 和不完美的连续干扰消除如何影响带有 LAT 系统的 CR-NOMA 中的远端用户，仍然存在很大的知识差距。在本研究中，LAT 被视为一个圆柱形阵列，并纳入了延迟扩散、到达角和离去角等参数，以实现具有放大-前向（AF）或解码-前向（DF）中继方案的 CR-NOMA-GBSM 系统。为了减少计算需求，我们提出了一个新概念，即利用阵列的物理尺寸来推导天线元件的位置矢量。通过蒙特卡洛仿真，AF 和 DF 的近端和远端用户误码率性能分别在 15 dB 和 5 dB 或更低时恶化。在可实现速率方面，AF 和 DF 的远端用户可获得与近端用户相当的性能，这证明了带有 LAT 的 CR-NOMA 的潜在回报。
{"title":"Large-Scale MIMO Transmitters for CR-NOMA in Fixed Physical Space: The Effect of Realistic System Impairments Using Stochastic Geometry","authors":"Emmanuel Ampoma Affum;Samuel Tweneboah-Koduah;Owusu Agyeman Antwi;Benjamin Asubam Weyori;Willie Ofosu","doi":"10.1109/OJVT.2024.3425061","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3425061","url":null,"abstract":"Hardware impairments (HWI) are imperfections in hardware components that diminish wireless communication performance. Unlike Geometric-based Stochastic Models (GBSMs), existing works on the impact of HWI on cooperative-relay (CR) Non-Orthogonal Multiple Access (NOMA) systems employ the Correlated-based Stochastic Model (CBSM), which does not capture realistic propagation mechanisms. Moreover, studies on CR-NOMA with large antenna transmitters (LATs) using CBSM and GBSM have attracted little attention in academia. We consider this as a computational issue. Although considerable work has been done, there is still a significant knowledge gap about how HWI and imperfect successive interference cancellation affect far-users in CR-NOMA with the LAT system. In this study, the LAT is considered a cylindrical array, and parameters such as delay spread, angle of arrival, and departure are incorporated to achieve a CR-NOMA-GBSM system with amplify-and-forward (AF) or decode-and-forward (DF) relaying schemes. To reduce computing demands, we offer a novel concept of using the physical dimensions of the array to derive the location vector of the antenna element. Using Monte Carlo simulation, near and far users' BER performances deteriorate for AF and DF at 15 dB and 5 dB or below, respectively. As far-users can receive comparable performances as near-users for both AF and DF in terms of achievable rates, this demonstrates the potential rewards of CR-NOMA with LAT.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"907-926"},"PeriodicalIF":5.3,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10591394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.1109/OJVT.2024.3422253
Mohammed Almehdhar;Abdullatif Albaseer;Muhammad Asif Khan;Mohamed Abdallah;Hamid Menouar;Saif Al-Kuwari;Ala Al-Fuqaha
The rapid evolution of modern automobiles into intelligent and interconnected entities presents new challenges in cybersecurity, particularly in Intrusion Detection Systems (IDS) for In-Vehicle Networks (IVNs). This survey paper offers an in-depth examination of advanced machine learning (ML) and deep learning (DL) approaches employed in developing sophisticated IDS for safeguarding IVNs against potential cyber-attacks. Specifically, we focus on the Controller Area Network (CAN) protocol, which is prevalent in in-vehicle communication systems, yet exhibits inherent security vulnerabilities. We propose a novel taxonomy categorizing IDS techniques into conventional ML, DL, and hybrid models, highlighting their applicability in detecting and mitigating various cyber threats, including spoofing, eavesdropping, and denial-of-service attacks. We highlight the transition from traditional signature-based to anomaly-based detection methods, emphasizing the significant advantages of AI-driven approaches in identifying novel and sophisticated intrusions. Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. Additionally, we explore emerging technologies, such as Federated Learning (FL) and Transfer Learning, to enhance the robustness and adaptability of IDS solutions. Based on our thorough analysis, we identify key limitations in current methodologies and propose potential paths for future research, focusing on integrating real-time data analysis, cross-layer security measures, and collaborative IDS frameworks.
{"title":"Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks","authors":"Mohammed Almehdhar;Abdullatif Albaseer;Muhammad Asif Khan;Mohamed Abdallah;Hamid Menouar;Saif Al-Kuwari;Ala Al-Fuqaha","doi":"10.1109/OJVT.2024.3422253","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3422253","url":null,"abstract":"The rapid evolution of modern automobiles into intelligent and interconnected entities presents new challenges in cybersecurity, particularly in Intrusion Detection Systems (IDS) for In-Vehicle Networks (IVNs). This survey paper offers an in-depth examination of advanced machine learning (ML) and deep learning (DL) approaches employed in developing sophisticated IDS for safeguarding IVNs against potential cyber-attacks. Specifically, we focus on the Controller Area Network (CAN) protocol, which is prevalent in in-vehicle communication systems, yet exhibits inherent security vulnerabilities. We propose a novel taxonomy categorizing IDS techniques into conventional ML, DL, and hybrid models, highlighting their applicability in detecting and mitigating various cyber threats, including spoofing, eavesdropping, and denial-of-service attacks. We highlight the transition from traditional signature-based to anomaly-based detection methods, emphasizing the significant advantages of AI-driven approaches in identifying novel and sophisticated intrusions. Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. Additionally, we explore emerging technologies, such as Federated Learning (FL) and Transfer Learning, to enhance the robustness and adaptability of IDS solutions. Based on our thorough analysis, we identify key limitations in current methodologies and propose potential paths for future research, focusing on integrating real-time data analysis, cross-layer security measures, and collaborative IDS frameworks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"869-906"},"PeriodicalIF":5.3,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10582439","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1109/OJVT.2024.3420244
Eiman Elghanam;Akmal Abdelfatah;Mohamed S. Hassan;Ahmed H. Osman
The growing penetration of electric vehicles (EVs) and the increasing EV energy demand pose several challenges to the power grid, the power distribution networks and the transportation networks. This growing demand drives the need for effective demand management and energy coordination strategies to maximize the demand covered by the EV charging stations, ensure EV users' satisfaction and prevent grid-side overload. As a result, several optimization problems are formulated and solved in the literature to provide optimal EV charging schedules (i.e. temporal coordination) as well as optimal EV-to-charging-station assignments and routing plans (i.e. spatial coordination). This paper presents a review of the state-of-the-art literature on the utilization of different deterministic optimization techniques to develop optimal EV charging coordination strategies. In particular, these works are reviewed according to their domains of operation (i.e. time-based scheduling, spatial coordination, and spatio-temporal charging coordination), their respective objectives (user-, grid- and operator-related objectives), and the solution algorithms adopted to provide the corresponding optimal coordination plans. This helps in identifying key research gaps and provide recommendations for future research directions to develop comprehensive and computationally efficient charging coordination models.
{"title":"Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review","authors":"Eiman Elghanam;Akmal Abdelfatah;Mohamed S. Hassan;Ahmed H. Osman","doi":"10.1109/OJVT.2024.3420244","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3420244","url":null,"abstract":"The growing penetration of electric vehicles (EVs) and the increasing EV energy demand pose several challenges to the power grid, the power distribution networks and the transportation networks. This growing demand drives the need for effective demand management and energy coordination strategies to maximize the demand covered by the EV charging stations, ensure EV users' satisfaction and prevent grid-side overload. As a result, several optimization problems are formulated and solved in the literature to provide optimal EV charging schedules (i.e. temporal coordination) as well as optimal EV-to-charging-station assignments and routing plans (i.e. spatial coordination). This paper presents a review of the state-of-the-art literature on the utilization of different deterministic optimization techniques to develop optimal EV charging coordination strategies. In particular, these works are reviewed according to their domains of operation (i.e. time-based scheduling, spatial coordination, and spatio-temporal charging coordination), their respective objectives (user-, grid- and operator-related objectives), and the solution algorithms adopted to provide the corresponding optimal coordination plans. This helps in identifying key research gaps and provide recommendations for future research directions to develop comprehensive and computationally efficient charging coordination models.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1294-1313"},"PeriodicalIF":5.3,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10577180","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1109/OJVT.2024.3420224
Jyri Hämäläinen;Rui Dinis;Mehmet C. Ilter
Recently, the paradigm of massive ultra-reliable low-latency Internet of Things (IoT) communications (URLLC-IoT) has gained growing interest. Reliable delay-critical uplink transmission in vehicular IoT is a challenging task since low-complex devices typically do not support multiple antennas or demanding signal processing tasks. However, in many IoT services, the data volumes are small and deployments may include massive number of devices. For this kind of setup, we consider on a clustered uplink transmission with two cooperation approaches: First, we focus on scenario where location-based channel knowledge map (CKM) is applied to enable cooperation. Second, we consider a scenario where scarce channel side-information is applied inuplink transmission. In both scenarios we also model and analyse the impact of erroneous channel information. As being different from the existing literature, in the performance evaluation, we apply the recently introduced data-oriented approach in the context of short-packet transmissions over vehicular IoT networks. Specifically, it introduces a transient performance metric for small data transmissions the so-called delay outage rate (DOR), where the amount of data and available bandwidth play crucial roles. Results show that cooperation between clustered IoT devices may provide notable benefits in terms of increased range. It is noticed that the performance is heavily depending on the strength of the static channel component in the CKM-based cooperation. Also, it is shown that the channel side-information based cooperation is robust against changes in the radio environment but sensitive to possible errors in the channel side-information. Even with large IoT device clusters, side-information errors may set a limit for the use of services assuming high-reliability and low-latency where DOR is the relevant metric. The analytical derivations are validated through corresponding Monte Carlo numerical simulations, with only minor differences at low probability values.
{"title":"Data-Oriented Analysis of Uplink Transmission in Massive IoT System With Limited Channel Information","authors":"Jyri Hämäläinen;Rui Dinis;Mehmet C. Ilter","doi":"10.1109/OJVT.2024.3420224","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3420224","url":null,"abstract":"Recently, the paradigm of massive ultra-reliable low-latency Internet of Things (IoT) communications (URLLC-IoT) has gained growing interest. Reliable delay-critical uplink transmission in vehicular IoT is a challenging task since low-complex devices typically do not support multiple antennas or demanding signal processing tasks. However, in many IoT services, the data volumes are small and deployments may include massive number of devices. For this kind of setup, we consider on a clustered uplink transmission with two cooperation approaches: First, we focus on scenario where location-based channel knowledge map (CKM) is applied to enable cooperation. Second, we consider a scenario where scarce channel side-information is applied inuplink transmission. In both scenarios we also model and analyse the impact of erroneous channel information. As being different from the existing literature, in the performance evaluation, we apply the recently introduced data-oriented approach in the context of short-packet transmissions over vehicular IoT networks. Specifically, it introduces a transient performance metric for small data transmissions the so-called delay outage rate (DOR), where the amount of data and available bandwidth play crucial roles. Results show that cooperation between clustered IoT devices may provide notable benefits in terms of increased range. It is noticed that the performance is heavily depending on the strength of the static channel component in the CKM-based cooperation. Also, it is shown that the channel side-information based cooperation is robust against changes in the radio environment but sensitive to possible errors in the channel side-information. Even with large IoT device clusters, side-information errors may set a limit for the use of services assuming high-reliability and low-latency where DOR is the relevant metric. The analytical derivations are validated through corresponding Monte Carlo numerical simulations, with only minor differences at low probability values.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"855-868"},"PeriodicalIF":5.3,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10577226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-24DOI: 10.1109/OJVT.2024.3418201
Safa Hamdare;David J. Brown;Yue Cao;Mohammad Aljaidi;Omprakash Kaiwartya;Rahul Yadav;Pratik Vyas;Manish Jugran
The widespread adoption of Electric Vehicles (EV) has emphasized the urgent need for efficient and secure charging infrastructure. While existing research in EV charging infrastructure has primarily concentrated on minimizing charging time at charging stations (CSs), neglecting security-centric charging optimization, particularly with scaled charging infrastructure considering multiple CSs. To address this gap, this paper presents an enhanced Hybrid-Electric Vehicle Charging Management and Security (H-EVCMS) framework. The H-EVCMS framework is meticulously designed to optimize charging price, manage load balancing, and provide security across multiple CS by leveraging the Open Charge Point Protocol (OCPP). The proposed framework's performance is evaluated by examining various charging scenarios and analyzing the booking and power consumption patterns of each CS. The results demonstrate the advantages of the hybrid approach used by the proposed H-EVCMS over traditional charging infrastructure management, showcasing its potential to address the challenges of scaling EV charging infrastructure while ensuring security and efficiency.
{"title":"EV Charging Management and Security for Multi-Charging Stations Environment","authors":"Safa Hamdare;David J. Brown;Yue Cao;Mohammad Aljaidi;Omprakash Kaiwartya;Rahul Yadav;Pratik Vyas;Manish Jugran","doi":"10.1109/OJVT.2024.3418201","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3418201","url":null,"abstract":"The widespread adoption of Electric Vehicles (EV) has emphasized the urgent need for efficient and secure charging infrastructure. While existing research in EV charging infrastructure has primarily concentrated on minimizing charging time at charging stations (CSs), neglecting security-centric charging optimization, particularly with scaled charging infrastructure considering multiple CSs. To address this gap, this paper presents an enhanced Hybrid-Electric Vehicle Charging Management and Security (H-EVCMS) framework. The H-EVCMS framework is meticulously designed to optimize charging price, manage load balancing, and provide security across multiple CS by leveraging the Open Charge Point Protocol (OCPP). The proposed framework's performance is evaluated by examining various charging scenarios and analyzing the booking and power consumption patterns of each CS. The results demonstrate the advantages of the hybrid approach used by the proposed H-EVCMS over traditional charging infrastructure management, showcasing its potential to address the challenges of scaling EV charging infrastructure while ensuring security and efficiency.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"807-824"},"PeriodicalIF":5.3,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10569090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141583486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：