Smart Vehicles Research Articles

A Fine-Grained Access Control and Security Approach for Intelligent Vehicular Transport in 6G Communication System

The area of intelligent transport systems (ITS) is attracting growing attention because of the integration of the smart IoT with vehicles that improve user safety and overall travel experience. Vehicular ad hoc network (VANET) is the part of ITS; that deals with the routing protocols and security of smart vehicles. However, due to the rapid increase in the number of smart vehicles, the existing network technology’s resources unable to handle the traffic load. It expects that the 6G communication system has the ability to fulfill the requirements of VANETs. Only a few studies explore this area, but they also overlooked the security aspect of VANETs in 6G communications networks. In this paper, we present an approach to address authentication and security issues for vehicles in VANET. By authenticating cars in the VANET and identifying various cyber assaults such as DDoS, our method significantly contributes to the intelligent transport communication network. Our approach uses the concepts of identity-based encryption to provide access control to the vehicles and deep learning-based techniques for filtering malicious packets. Our identity-based encryption technique is IND-sID-CCA secure, and a state-of-the-art deep learning algorithm detects malicious packets with an accuracy of 99.72%. These results emphasize the validity of our proposed approach for VANETs in 6G communication systems.

A Secure Dynamic Mix Zone Pseudonym Changing Scheme Based on Traffic Context Prediction

Traffic context plays an important role in supporting automated driving and intelligent transportation systems. Smart vehicles explore surrounding environments by analyzing sensor data and periodically communicating with neighbors and road infrastructures. The context can be well learned in this way to support driving, but the vehicle trajectory can be also easily exposed under eavesdropping attacks. The pseudonym is proposed to hide the real identity of the vehicles. However, the effectiveness of anonymity, the safety of driving, the convenience of implementation and the utilization of resources in previous approaches have not been well-balanced. Therefore, focusing on efficiently replacing pseudonyms with the premise of ensuring driving safety, we propose a secure dynamic silent mix zone pseudonym changing scheme (TLAS) based on the real-time traffic context prediction for urban regions. It naturally takes the area in front of the red traffic light as a silent mix zone, which avoids the driving security issue caused by signal silence. Besides, the area length is dynamically configured according to the traffic context predicted in the last green light cycle, so the anonymous effect can be improved. In addition, considering the resource utilization and accuracy requirement, the adaptive prediction algorithm is applied. We conduct simulation experiments with real-world traffic history using SUMO and OMNET++, the results show that TLAS strategy can indeed achieve a better anonymous effect (reducing standardized traceability rate by 8.2%) with lower driving speed for safety concern.

Smart Vehicle Service Management System Using IoT

Abstract: To ensure the proper operation and efficient operation of the vehicle, regular vehicle service is necessary to monitor various parts of the vehicle. This paper “Smart Vehicle Service Management System using IoT” is being proposed to detect some problems in vehicle and also it provides a platform to book online service to the vehicles. It sends an alert message in form of SMS to the user if any problem is detected and suggests that servicing to vehicle is now required. The system is integrated with different sensors like FSR, adxl, DHT11, level etc to detect problem in vehicle and being displayed in LCD, so if any problem is detected the buzzer will give alert sound indicating the vehicle has a problem. Along this a Node MCU and GSM module is being placed to get live updates in cloud and also in a form of SMS and the same data is stored data in cloud. The alert message received in form of SMS is redirected to the SVSMS website which will allow the user to book online service. The proposed system helps the user to detect the problems in prior and act precisely so that efficiency of the vehicle is maintained and cost/ inconvenience could be avoided.

Aerial Computing: A New Computing Paradigm, Applications, and Challenges

In existing computing systems, such as edge computing and cloud computing, several emerging applications and practical scenarios are mostly unavailable or only partially implemented. To overcome the limitations that restrict such applications, the development of a comprehensive computing paradigm has garnered attention in both academia and industry. However, a gap exists in the literature owing to the scarce research, and a comprehensive computing paradigm is yet to be systematically designed and reviewed. This study introduces a novel concept, called aerial computing, via the amalgamation of aerial radio access networks and edge computing, which attempts to bridge the gap. Specifically, first, we propose a novel comprehensive computing architecture that is composed of low-altitude computing, high-altitude computing, and satellite computing platforms, along with conventional computing systems. We determine that aerial computing offers several desirable attributes: global computing service, better mobility, higher scalability and availability, and simultaneity. Second, we comprehensively discuss key technologies that facilitate aerial computing, including energy refilling, edge computing, network softwarization, frequency spectrum, multi-access techniques, artificial intelligence, and big data. In addition, we discuss vertical domain applications (e.g., smart cities, smart vehicles, smart factories, and smart grids) supported by aerial computing. Finally, we highlight several challenges that need to be addressed and their possible solutions.

A Review on Integration of Vehicular Ad-Hoc Networks and Cloud Computing

The vehicular network is becoming a prominent area of research in the field of smart transportation systems. In such systems, smart vehicles are embedded with the onboard unit, which includes computing systems, communication devices, and storage equipment, and these vehicles are used to provide efficient traffic management and road safety. For many years, several solutions are addressed by many practitioners regarding different issues and challenges that arise in a vehicular network. One of the solutions is vehicular cloud computing (VCC). VCC is a promising technology that has created a great impact on the services and applications of vehicular ad-hoc networks (VANETs) by exploiting the vehicular resources effectively. In this paper, we present a survey on VCC, which integrates VANETs and cloud computing (CC). The basic overview and characteristics of VANETs are discussed. The architecture and several features of VCC are explored. We also discuss various privacy and security-related issues in VCC. Lastly, we focus on open issues, existing work, and future research directions.

Trusted Blockchain-Based Signcryption Protocol and Data Management for Authentication and Authorization in VANETs

Vehicular Ad hoc Networks (VANETs) are the industrial cornerstone of intelligent transportation system (ITS), which are widely used in traffic management, automatic driving, and road optimization. With the expansion of the scale of the mobile ad hoc networks (MANETs) and smart vehicles (SV), VANETs will produce a large amount of data. In the open access environment of VANETs, the security of information transmission and the authenticity of user identity need to be considered when different vehicles communicate. In order to solve the cybersecurity risks of large-scale deployment of VANET, this paper proposes a trusted blockchain-based signcryption protocol and data management (TB-SCDM) for authentication and authorization (A&A) in VANETs. In the existing attack model, TB-SCDM can ensure the confidentiality and undeniability of information, as well as can effectively resist 51% attacks, eclipse attacks and double-spending attacks, etc. Through benchmark analysis, this scheme has higher computing efficiency and lower storage cost compared with other existing schemes.

Slow and Steady Wins the Race: A Comparative Analysis of Standing Electric Scooters’ European Regulations Integrated with the Aspect of Forensic Traumatology

Fuel-driven cars are widely considered unsustainable and contrary to the new paradigm of smart growth planning. The need to reform transport behavior, policies, and infrastructure is among the priorities in urban policies around the world. Electric vehicles are an emerging technology that could advance sustainability programs. In the past year, there has been a rapid increase in the diffusion of electric scooters in several European cities, but various states have been unprepared for the rapid spread of green micro-mobility from a regulatory point of view. In addition, in parallel with the spread, there have been numerous road collisions involving standing electric scooters. The aim of this study was to obtain a detailed view of this phenomenon. We focused on the current legislation on electric micro-mobility at the European level to study and summarize the different attitudes adopted by various states whose regulations are present on the web. (It was not possible to evaluate the regulations of all European countries because they are not all available on online platforms.) The elements assessed in the various regulation were age limits, speed limits, compulsory use of helmets, administrative penalties, and the obligation to insure the new e-vehicle (standing scooter). In this study, we analyze the state of the art in electric micro-mobility, highlight the current situation’s limits, and propose new strategies to adequately integrate this new smart vehicle into the urban transport network.

Joint User Association, Power Optimization and Trajectory Control in an Integrated Satellite-Aerial-Terrestrial Network

Internet-of-Things (IoT) is being widely embraced with the number of connected devices growing rapidly. Moreover, IoT applications are emerging in diverse verticals such as connected cars, connected factories, and smart agriculture. For new business models, in order to meet key network performance indicators, connectivity must be flexible and agile. An integrated satellite-aerial-terrestrial network (I-SAT) has recently stimulated interest in providing wireless communication due to its high maneuverability, versatile deployment, and pervasive connectivity. The resource planning, task distribution, and action management of an I-SAT can be accomplished through effective acquisition, coordination, transmission, and aggregation of diverse information. This paper considers an I-SAT network, in which multiple unmanned aerial vehicles (UAVs) with aerial stations and a terrestrial base station (BS), in a cognitive setting, in the presence of satellite-receiver communication, are deployed to support smart vehicles on the ground. By taking into account different limitations and Quality of Service (QoS) constraints, the goal is to maximize the average throughput among users by jointly optimizing user association, BS/UAV transmission power, and UAV trajectory. The formulated problem is a non-convex optimization problem with a complicated expression that is hard to solve. To tackle this problem, an alternating iterative algorithm based on the block descent method is proposed. Precisely, the problem is subdivided into three subproblems, transmitter-vehicle association optimization, BS/UAV power allocation optimization, and UAV trajectory control. Then, in an iterative process, these subproblems are solved sequentially. The proposed solution uses a segment-by-segment technique, which breaks the complete UAV flight trajectory into smaller time segments to reduce computation time when the network service period is considerable. As a result, each time segment’s optimization can be solved more quickly. Furthermore, the paper presents the results of network simulations carried out to assess the efficiency of the proposed solution. The findings show that the presented scheme outperforms different benchmark schemes in terms of the average user throughput when observing multiple different scenarios.

Managing Trade-off Between Subscription Load and Latency in Vehicular Edge Platform

Adding connectivity to vehicles is attracting much attention toward developing smarter vehicles such as autonomous cars. To obtain and utilize real-time information from vehicles, techniques that combine the concept of edge computing and publish/subscribe messaging model have been proposed. However, there is an issue that the increase in the number of edge servers imposes a heavy load upon a subscriber for managing connections to them. To address this issue, we propose an edge-based platform with the functionality of adjusting the number of connections to edge servers. Experimental results clarify the trade-off characteristic between subscription load and latency.

6Blocks: 6G-enabled trust management scheme for decentralized autonomous vehicles

In this paper, we propose a 6G-envisioned blockchain (BC)-based scheme for cellular vehicle-to-everything (C-V2X) ecosystems (termed as 6Blocks), which optimizes the edge-resource provisioning of 5G C-V2X nodes via network function virtualization (NFV)-enabled infrastructure. 6Blocks operates in three phases. In the first phase, a secure data aggregation through 6G sensors is performed at the data plane. Then, in the second phase, the aggregated data is sent to the 6G-enabled NFV control plane to leverage resource allocation to connected autonomous smart vehicles (CASVs) through edge nodes via service container operations. In the third phase, management plane operations are designed that includes registration and auction smart contracts (SC) for connected autonomous vehicle owner (CAVO) and CASVs over the BC with public/private pairs fetched from interplanetary file systems (IPFS). The proposed scheme is compared against existing NFV schemes like distant, edge, and SDN-based edge control. At 20 CASVs, 6Blocks achieves an edge-service latency of 0.05ms against 0.76ms, 0.27, and 0.15ms for cloud, edge, and SDN-edge schemes, respectively, with high connection density of 107 nodes, at maximum utilized IPFS bandwidth of 0.2 Mbps. Then, we validate the trust of our model through the automated validation of the internet security protocol and applications (AVISPA) tool and modeled the vehicle and sensor nodes. The obtained results show the efficacy of the proposed scheme against existing state-of-the-art approaches with respect to parameters such as network, security, transaction costs, and auction.

Perspectives for the implementation of a smart contract for the lease (rental) of a vehicle

The article is devoted to investigation of perspectives of implementation of the smart vehicle rental agreement. On the basis of current civil legislation the vehicle rental agreement is defined as an agreement under which a lessor transfers or undertakes to transfer to a lessee an air, sea, river vessel, ground self-propelled vehicle etc. in using for a fee for a certain period. A general legal characteristics of this agreement includes its reality or consensus, payment, timeliness and bilaterality. The list of features of the subject of the studied contract, which includes the inexhaustibility of types of vehicles, its technical features, the presence of signs of a source of increased danger, the existence of special legislation governing its use, and supplemented them by taking into account the volume and type of engine. Requirements to the form of the vehicle rental agreement, which generally is written, and if one of the parties is an individual, it is subject to notarization, are considered, and a possibility of its negotiation and further execution as a smart agreement is analyzed.
 The positions of scientists on the essence and main features of a smart contract which consist in its specifics regarding the form of negotiation and way of execution due to automation. The characteristics and problems of execution of the vehicle rental agreement which connected with activity of a lessee of a vehicle, bearing of expenses, insurance and causing a damage for a subject of the agreement and other person with using of a vehicle are followed. It is remarked the features of renting a vehicle with the crew which serves it.
 On the basis of the conducted investigation perspectives of implementation of the smart vehicle rental agreement are formulated, and they are seen in increasing the level of legality of the negotiated agreement, obtaining access to all necessary for parties information and electronic documents, automatic and timely payment of a rent, timely fulfillment of execution of a commitment and improvement of control over the subject of a rent.

High gain modified Vivaldi vehicular antenna for IoV communications in 5G network

While targeting the sixth generation (6G) wireless communication which incorporates mainly the Internet of Things (IoT), the Internet of Vehicles (IoV) becomes a vital component to be implemented. A vehicular antenna is designed by using the modified design of the Vivaldi antenna that can cover all the frequency bands for the long-term evolution (LTE) and the mid-band fifth-generation (5G) wireless systems (ranging from 3.3 GHz to 6.5 GHz). The proposed design is optimized by analyzing the effect of the variation in the dimensions of the antenna, changing the position of the taper, the rectangular slot dimensions and the diameter of the circular slot etc. The presented automotive antenna operates at four frequency bands ranging from 3.62 GHz - 4.03 GHz (410 MHz), 4.17 GHz–5.38 GHz (1210 MHz), 5.57 GHz–6.16 GHz (590 MHz) and from 6.23 GHz - 6.64 GHz (410 MHz) with the minimum reflection coefficient of -39 dB, -39.06 dB, -50.42 dB and -12.45 dB, respectively. The proposed antenna offers the high gain of 7.6 dB, 6.7 dB, 9.3 dB and 7.4 dB for the four bands of the operating spectrum, respectively. The analysis of the reflection and radiation characteristics of the antenna when placed on the vehicle confirms the suitability of an antenna for the smart vehicle to vehicle communications.

BACTmobile: A Smart Blood Alcohol Concentration Tracking Mechanism for Smart Vehicles in Healthcare CPS Framework

BACTmobile: A Smart Blood Alcohol Concentration Tracking Mechanism for Smart Vehicles in Healthcare CPS Framework

A multi-vector community energy system integrating a heating network, electricity grid and PV production to manage an electrified community

Electrification in energy supply–demand plays a critical role in domestic heating and road transport, delivering an electrified community to reduce carbon emissions. This solution, however, places a significant power demand increase on the distribution networks. To ensure the security of electricity supply, an efficient energy system and energy demand reduction are essential. In this paper, a multi-vector community energy system, applying an electrified heating network, electric vehicle smart charging, community-scale peak shaving and photovoltaic (PV) generation, is demonstrated in three models to manage an electrified community. Firstly, a heating network model, comprising a central ground source heat pump, low-temperature district heating system, electric heaters and thermal storage, is established to measure the optimum distribution temperature. Next, an electrified community model illustrates hourly electricity demands and performances of a community energy system, which is then used to identify the required degree of housing thermal efficiency improvement (i.e., heating demand reduction). The third model evaluates decentralised PV/storage units to maintain the power demand below a targeted power. Modelling results show that the demand ratio of domestic hot water to space heating determines the distribution temperature, which indicates the temperature is increasing with growing housing thermal efficiency. Moreover, the electrification of a community could increase the peak power demand on the highest demand day by over five times, converting heating demands into electricity directly. This significant peak demand can be possibly reduced to only a 33% increase by employing a community energy system. The model of PV/storage units is validated through a 12-week assessment. Ultimately, a modelling tool is developed by assembling the mentioned models, providing four pathways to attain electrification. Users can adjust specific parameters and database to align with the local conditions. The results indicate the requirements of building a community energy system and electricity demands in the highest consumption period.

Electric Vehicle Smart Charging Reservation Algorithm.

The widespread adoption of electromobility constitutes one of the measures designed to reduce air pollution caused by traditional fossil fuels. However, several factors are currently impeding this process, ranging from insufficient charging infrastructure, battery capacity, and long queueing and charging times, to psychological factors. On top of range anxiety, the frustration of the EV drivers is further fuelled by the uncertainty of finding an available charging point on their route. To address this issue, we propose a solution that bypasses the limitations of the “reserve now” function of the OCPP standard, enabling drivers to make charging reservations for the upcoming days, especially when planning a longer trip. We created an algorithm that generates reservation intervals based on the charging station’s reservation and transaction history. Subsequently, we ran a series of test cases that yielded promising results, with no overlapping reservations and the occupation of several stations without queues, assuring, thus, a proper distribution of the available energy resources, while increasing end-user satisfaction. Our solution is independent from the OCPP reservation method; therefore, the authentication and reservation processes performed by the proposed algorithm run only through the central system, authorizing only the creator of the reservation to start the charging transaction.

A noncooperative game‐theoretic approach applied to the service selection in the vehicular cloud

SummaryRecent advancements in the automotive area have aided in the development of smart vehicles with high processing, computing, and storage capabilities. These resources are leveraged to cope with the demands of consumer vehicles such as data analysis, optimization, and decision‐making. The first and foremost step in establishing this paradigm of computing so‐called vehicular cloud is the service selection. Nonetheless, vehicles' high mobility and the network's rapidly changing topology have addressed new challenges such as instability of resources, making their management complicated. Therefore, the vehicular cloud requires robust and efficient resource management solutions to be developed. In this article, we present a game theory‐based framework for vehicular resource selection where provider vehicles and consumer vehicles play a game against each other until reach equilibrium in order to enable consumer vehicles to select the most suitable provider vehicles that meet their requirements in terms of service quality and cost. Furthermore, a thorough study was carried out in order to study the interaction between players and predict their future behaviors. As this interaction will result in a pure and mixed equilibrium state, the convergence of the proposed theoretic model for both equilibrium states is rigorously demonstrated under certain assumptions. Effective search algorithms based on the best responses are designed to compute the pure and mixed Nash equilibrium. The suggested approach's verification is evaluated based on the satisfaction of the players and has shown better performance comparing previous algorithms.

A PSO-based computational framework to design active noise cancelation systems for smart vehicle enclosures

In this study, active noise cancelation (ANC) systems are developed by a computational optimization framework based on particle swarm optimization (PSO), aiming to attenuate engine noise inside smart cubic vehicle enclosures. To have rapid estimation of acoustic properties, the main PSO algorithm is coupled with an analytical solution based on modified modal interaction method to evaluate the cost function. The optimum configurations, i.e., best positions and volume velocities of secondary sound sources, are defined for each resonant frequency. For numerical simulations, two vehicle enclosures of different size are considered to assess the applicability of the optimization algorithm. The overall performance of determined ANC systems is investigated, and it is shown that substantial noise reduction is achieved.

Secure Communication Protocol for Arduino-based IoT Using Lightweight Cryptography

We witness massive implementations of the Internet of Things (IoT) in smart homes, smart buildings, smart vehicles, smart wearables as well as Industry 4.0 initiatives. Along with the massive adoption, IoT security has become more important and crucial in this case. Arduino, as IoT hardware platform, also requires enhancements on its security to ensure that data it transmits and receives is secured and has not been tampered in any way. Transmitting of IoT data and telecommand in plaintext is not secure. Securing transmission using traditional block cipher is computationally intensive for embedded-systems with low memory and computing power like Arduino. This research proposes a novel lightweight security communication protocol that is lightweight enough to run on the Arduino platform. The proposed protocol shall be utilizing a lightweight key agreement scheme, the SPECK lightweight block cipher, and BLAKE2s hash function. This protocol is designed to support telemetry and telecommand by using publisher-subscriber, which also is aimed to be extensible but straightforward for future enhancements. This research shows that a secure IoT communication protocol can be designed and implemented on Arduino devices and another IoT platform running Arduino core such as the ESP32. The performance evaluation of this protocol in Arduino Mega shows that the INIT phase's average execution time is 26.83 milliseconds. The key agreement is 13.50 milliseconds, and the encryption-decryption of telemetry and telecommand messages requires 25 milliseconds execution time. The protocol performance evaluation in ESP32 has an average execution time for INIT phase 44.63 milliseconds. The key agreement phase, 13.90 milliseconds, and the encryption and decryption of telemetry and telecommand messages requires an execution time of 17.10 milliseconds.

TSN-Based Backbone Network of Train Control Management System

Time-sensitive network (TSN), as one of the latest real-time Ethernet techniques, has achieved great success in several scenarios that require strict communication latency and packet loss. This paper reviews the state-of-the-art in time-sensitive networks and investigates the drawbacks of current vehicle networks. By introducing TSN into the TCMS backbone network, next-generation smart vehicles can achieve high-quality data transmissions. This paper also analyzes the priority of the vehicle data and calculates the time-aware shaper slot to ensure that the control data is not affected by the multimedia data. Using the proposed structure, experimental results suggest that the network efficiency can be improved in the rail transit systems.

Enabling Road Detection Tasks via Collaborative Smart Vehicles

Vehicular cloud computing (VCC) has been widely utilized to enhance traffic management and road safety both in the static and dynamic scenarios. In VCC, the onboard resources of involved smart vehicles (SVs) would be integrated as a resource pool and collaboratively accommodate various computation tasks. In this system, SVs in a section of the road can be grouped as a vehicular cloud to complete the detection job, e.g., collecting and preprocessing the road data. Then, an SV will be selected to aggregate all SVs’ detection results in the road section and upload the results to the remote monitoring platform via base stations (BSs). However, due to the high dynamics of vehicular mobility and the poor coverage of BSs in some areas, this vision is challenging to achieve. In this article, we propose a collaborative road detection system and schedule the detection task to different SVs in the road section. Specifically, 1) we model the collaborative detection process and formulate it as a task scheduling problem to minimize the response time, which is NP-hard. An adaptive location-aware scheduling scheme is proposed for task scheduling and 2) as there are road sections without coverage of any BS, therefore we have to utilize the SVs on the opposite lane to transmit the aggregation result in these road sections. Accordingly, an uploading strategy is proposed to decide to upload the feedback through SVs on the opposite lane or in the coverage area of the next BS. Extensive experiments show that our scheme can significantly reduce the response time overall and is close to the optimal solution.