International Journal of Vehicle Information and Communication Systems (33 papers in press)
End-to-end delay and backlog bound analysis for hybrid vehicular ad hoc networks: a stochastic network calculus approach
by Shivani Gupta, Vandana Khaitan
Abstract: This paper studies a hybrid Vehicular Ad-hoc Network (VANET) that incorporates two different technologies, i.e., IEEE 802.11p and the long-term evolution. End-to-end delay and backlog are acknowledged as major performance measures of vehicular networks that characterise its Quality of Service (QoS), therefore, in this paper we focus on obtaining some measures of these two attributes. We obtain the probabilistic upper bounds on the end-to-end delay and backlog instead of evaluating the delay and backlog in view of the fact that providing the probabilistic bounds is more reasonable as in some real-life scenarios it may be intricate to obtain the closed-form results. To obtain the probabilistic bounds on delay and backlog, a queueing network model is proposed that represents the message dissemination scheme used in the hybrid VANET architecture. The novelty of this paper lies in the fact that instead of considering a Markovian queueing network, the arrival and service processes in the proposed queueing network are assumed to be self-similar and heavy-tailed distributed, as such characteristics are extensively reported in communication networks. The mathematical analysis of the proposed queueing network follows the stochastic network calculus approach for the reason that it supports generally distributed arrival and service processes. Further, the probabilistic upper bounds on the end-to-end delay obtained using heavy-tailed arrival and service times are compared with the delay bounds obtained using exponential arrival and service times to validate the appropriateness of using heavy-tailed characteristics of the network traffic. In addition, a comparative study of hybrid VANET with the other two conventional architectures of VANET, i.e. ad-hoc network only and cellular network only, is also provided in the paper.
Keywords: hybrid VANET; queueing network; stochastic network calculus; end-to-end delay; backlog; probabilistic bounds; heavy-tailed traffic.
Camouflage-based location privacy preserving scheme in vehicular ad hoc networks
by Leila Benarous, Benamar Kadri, Saadi Boudjit
Abstract: Location privacy is critical and preserving it is essential. The tracking exposes the real time location, history of visited places and parsed trajectories. Metaphorically speaking, it is the cyber equivalent of physical stalking and as dangerous as it is. In vehicular networks in particular, this issue is serious because autonomous vehicles timely transmit their locations, headings, speed and identity to neighbouring vehicles and/or service infrastructures. To preserve the location privacy, various pseudonym-based approaches exist, mainly focusing on unlinkable pseudonym change strategies. In this paper, we propose a camouflage-based solution that prevents the linkability of pseudonyms even within low density roads where the tracking chances are high. The solution is simulated using NS2 against a global passive attacker that executes the semantic and syntactic linking attacks. The results demonstrate the effectiveness of the solution in protecting privacy.
Keywords: autonomous vehicle; vehicular network; privacy; attacker; simulation; linkability.
3D object detection based on image and LIDAR fusion for autonomous driving
by Guoqiang Chen, Huailong Yi, Zhuangzhuang Mao
Abstract: 3D object detection is the fundamental task of autonomous driving. The existing approaches are very expensive in computation owing to the high dimensionality of point clouds. We use the 3D data more efficiently by representing the scene from the RGB image and the Birds Eye View (BEV). The whole network is composed of two parts: one is the 2D proposal network for 2D region proposal generation, and the other is the 3D region-based fusion network to predict the 2D locations, orientations, and 3D locations of the objects. First, we fuse the BEV feature map and the RGB image to enhance the input. Second, we adopt the 3D encoding form with 2D-3D bounding box consistency constraints and design ROI-wise feature fusion to predict location information. Our experimental evaluation on both the KITTI as well as a large scale 3D object detection benchmark shows significant improvements over the state of the art.
Keywords: 3D object detection; image and LIDAR; deep learning; multisensory fusion; autonomous driving.
Efficient clustering for wireless sensor networks using modified bacterial foraging algorithm
by Dharmraj Biradar, Dharmpal D. Doye, Kulbhushan A. Choure
Abstract: The energy efficiency and clustering are directly related to each other in Wireless Sensor Networks (WSNs). A significant number of methods have been introduced for energy-efficient clustering in the last couple of decades. To limit energy use and improve network throughput, various methods for the clustering algorithm were introduced using an optimisation algorithm, fuzzy logic, and thresholding techniques. The optimisation algorithms such as Particle Swarm Optimisation (PSO), Genetic Algorithm (GA), Ant Colony Optimisation (ACO) and their variants were presented, but the challenge of selecting the efficient Cluster Head (CH) and cluster formation around it with minimum overhead and energy consumption is unresolved. In this paper, energy proficient and lightweight clustering algorithm for WSNs is proposed using the Modified Bacterial Foraging optimisation Algorithm (MBFA). The aim of designing the MBFA is to limit energy use, control overhead, and improve network throughput in this paper. The process of CH selection using MBFA is performed via a novel fitness function. The wellness capacity is planned using key parameters, for example, remaining energy, node degree, and geographical distance between sensors to base station. The MBFA selects the sensor node as CH using the fitness value. The proposed clustering protocol is simulated and evaluated with state-of-art protocols to justify efficiency.
Keywords: bacterial foraging optimisation; clustering; cluster head selection; energy efficiency; particle swarm optimisation.
Enhanced video-based traffic management application with virtual multi-loop crate
by Manipriya Sankaranarayanan, Mala Chelliah, Samson Mathew
Abstract: The growth in urban population leads to gridlock of vehicles in city roads. The quality of transportation is improved by the latest technologies of Intelligent Transportation Systems (ITS) applications. Any ITS application relies heavily on sensors for data collection for efficient management, control and planning of transportation. In this paper, the video-based traffic data collection systems and their techniques are improved by using the proposed Virtual Multi-Loop Crate (VMLC) framework. VMLC uses the all the spatial colour information for image processing without losing information. The results of the proposed framework are used to estimate traffic statistics and parameters that are essential for ITS applications. The parameter values obtained from VMLC are analysed for accuracy and efficiency using Congestion Level (CoLe) estimation application. The results show that the VMLC framework improves the quality of data collection for any video-based ITS applications.
Keywords: vehicle detection; traffic statistics and parameters; spatial colour information; image processing data management; video-based traffic data.
Improved stability through self-localisation scheme in heterogeneous vehicular clustering
by Iftikhar Ahmad, Zaheed Ahmed, Muhammad Ahmad Al-Rashid
Abstract: Intelligent local data processing within vehicular ad hoc networks (VANET) may increase the capabilities of the Internet of Vehicles (IoV). To share data effectively, vehicular clusters should be synchronised and stable. A vehicle needs an uninterrupted Global Positioning System (GPS) signal for synchronisation purposes, especially in the urban environment. GPS interruption leads to an unstable connection that is a big hurdle in developing cost-effective solutions for navigation and route planning applications. To solve this problem, a self-location calculation scheme within the vehicular clustering process is proposed. The proposed self-location calculation algorithm enables vehicles to calculate their coordinates in the absence of GPS signals. A clustering mechanism is developed for sharing traffic information system (TIS) data among multiple vehicles over a particular road segment. Sharing of vehicular data in real-time helps vehicles to synchronise well. The developed scheme is simulated and compared with existing known approaches. The results show the better stability of our proposed mechanism over others.
Keywords: VANET; stability; vehicular clustering; synchronisation; localisation.
Detection and prevention of various routing attacks in RPL for a smart vehicle environment using an enhanced privacy secure RPL routing protocol
by Paganraj Deepavathi, Chelliah Mala
Abstract: The recent advancements in the Internet of Things (IoT) play a significantly important role in the day-to-day activities of human beings to connect things-to-things; it reduces the efforts of an individual as well as increases the safety and smartness of people through smart phones. With the increase in population, there is a tremendous increase in the number of vehicles, which leads to more possibilities of road accidents. In a smart vehicle environment, various sensors are used to collect vehicle-related information from different locations and alert the driver about road traffic conditions to avoid accidents. This paper proposes an Enhanced Privacy Secure-Routing Protocols for Low Power and Lossy Networks (EnPS-RPL) routing protocol to detect various attacks and protect a vehicle from accidents. The proposed work is simulated in Cooja Platform Simulator, which is in Contiki Operating System. The simulation results show that the proposed algorithm improves networks' lifetime and throughput, and decreases the packet loss ratio and end-to-end delay compared with the existing RPL-based protocols.
Keywords: EnPS-RPL; smart vehicle environment; road traffic; packet loss; RPL-based protocols.
Performance analysis of a fog-computing-based vehicular communication
by Manoj Kumar, Pratik Gupta, Ankur Kumar
Abstract: Vehicular networking is an emerging research area. It enables vehicles equipped with sensing capacities to establish communication vehicle-to-vehicle or with available roadside infrastructure. It has significant applications in terms of information and traffic management and road safety. To attain effective communication in vehicular networking, a hybrid technological solution is proposed in terms of blockchain in vehicular communication using vehicular resources, cloud or fog computing environment. Blockchain-based fog computation is an alternative solution to get both security and privacy, especially in vehicular communication. As security and privacy are the key challenges in cloud-assisted vehicular communications owing to the adoption of the internet of things environment, a secure and efficient communication framework is required. This paper presents a model based on blockchain technology i.e. blockchain in fog nodes. This framework for vehicular communication ensures security and privacy. The presented frameworks are efficient being based on new blockchain design rather than the general cloud and fog-computing framework. This scheme has capabilities to establish an authenticated connection among the user, the fog node and the cloud server, where cloud services can respond to users treating fog node as a semi-trusted party. The effect of the proposed scheme was investigated and the obtained results are explained in the form of tables and graphs.
Keywords: blockchain; vehicular communication; elliptic curve cryptography,
authentication key agreement.
Route selection strategy with minimised mobile charger in wireless rechargeable sensor networks
by Cong-Xiang Wang, Chih-Min Chao
Abstract: How to design an efficient route for a mobile charger is an important issue in rechargeable sensor networks (WRSNs). Mobile chargers are costly and may take a lot of time to reach and charge sensor nodes. Existing route-planning algorithms either fail to minimise the number of mobile chargers or do not consider the actual traffic conditions. In this paper, we propose a Hybrid-Clustering-Minimum-Mobile (HCMM) charger route-planning algorithm for WRSNs. The charging route selected by the HCMM protocol prolongs the network lifetime by using a minimised number of mobile chargers. Simulation results verify that the charging efficiency achieved by HCMM is better than that of the m-MTS protocol, which is currently the best charging route-planning protocol for dispatching the least number of mobile chargers.
Keywords: wireless charging; mobile charger; wireless rechargeable sensor networks; route planning.
A proactive load-balanced handoff scheme for vehicular ad-hoc networks
by Rajeshwari Madli, G. Varaprasad
Abstract: The embracement of the wireless technology by the automobile industry has led to novel research interests in the field of Vehicular Ad-hoc Networks (VANETs). In addition to the ad-hoc mode, a VANET supports an infrastructure mode of communication, which provides access to internet services such as Hyper Text Transfer Protocol (HTTP), Voice over Internet Protocol (VoIP) and File Transfer Protocol (FTP), through access points known as Road Side Units (RSU). Vehicles can benefit from these services when associated with an RSU. However, because of uneven distribution and high mobility of vehicles, some RSUs are overloaded, resulting in network congestion and affecting the packet delivery ratio and throughput. This paper proposes a proactive load-balanced handoff scheme, in which vehicles evade overloaded RSUs and choose an alternative RSU based on signal strength, network load and service reliability. Simulation results indicate that vehicles using the load-balanced handoff method, experience a higher packet delivery ratio and throughput.
Keywords: VANET; handoff; load balance; RSU reliability; packet delivery ratio.
Data synchronisation method of intelligent transportation system based on internet of vehicles technology
by Fangling Zhang
Abstract: In order to overcome the problems of large error of traffic data synchronisation and high traffic congestion rate in traditional methods, a data synchronisation method of intelligent transportation system based on the internet of vehicles technology is proposed, using the car networking technology. The collected data is used to extract the road traffic flow, velocity and density online traffic flow characteristics. Combined with the data acquisition and traffic flow feature extraction result of intelligent transportation system for scheduling task, according to the result of task scheduling based on training symbol synchronisation method to construct scheduling task timing metric function. The function is used to calculate the data synchronisation estimation points of the intelligent transportation system and realise data synchronisation. The simulation results show that the traffic data synchronisation error rate and traffic congestion rate of the proposed method are low, and the practical application effect is good.
Keywords: internet of vehicles technology; intelligent transportation; data synchronisation; training symbol.
IoT-based smart parking system in smart city
by D.P. Gaikwad, Aadesh Agarwal, Omkar Rajale, Rushabh Agrawal, Sourav Ranalkar
Abstract: With increase in population along with urbanisation, artificial intelligence technology is playing a vital role in managing resources to make operations easier. The internet of things has converted the dream of the smart city into a possibility. In a smart city, IoT devices work together to make daily tasks such as transportation and parking easier and more efficient. With limited parking spots available and continuously growing vehicle consumption rate, finding a parking location is a major problem faced by vehicle owners. In this paper, an IoT-based parking system is proposed that can help drivers get an idea of parking availability at a particular location before even reaching the same. The system comprises IoT devices that help in monitoring the parking areas, along with a server and applications that will help vehicle owners to view and reserve the parking spot for their vehicle at their desired destination.
Keywords: internet of things; Nodemcu; mesh-network; microservices; CCTV; Go-Lang.
Compromised-resilient counter-measures against black-hole and worm-hole attacks in edge-based internet of vehicles
by Oladayo Olakanmi, Kehinde Odeyemi
Abstract: The Internet of Vehicles (IoV) is a distributed network that supports the use of data created by connected cars and vehicular ad-hoc networks (VANETs) for real-time communication among the vehicles and other infrastructures in the network. Although IoV increases safety and efficient information exchange in transportation, its inter-connectivity exposes the vehicles and the people to different cyber-attacks such as black-hole and worm-hole which are capable of disrupting the network. In this paper, we identify the black-hole and worm-hole attacks as the major security threats to the IoV network. We then propose periodic-time slicing and trust factor approaches to detect and prevent a black-hole attack, a cryptography procedure to detect and prevent worm-hole attacks and enforce integrity in the IoV networks.
Keywords: car connectivity; cyber-security ; cloud and fog-assisted; Internet of things; autonomous vehicles.
Special Issue on: Big Data Innovation For Sustainable VANET Management
An automatic moving vehicle detection system based on hypothesis generation and verification in a traffic surveillance system
by Smitha Jolakula Asoka, N. Rajkumar
Abstract: An intelligent transportation system has a major topic called traffic surveillance. In a complex urban traffic surveillance system, booming of vehicle detection and tracking is an problematic dilemma. To overcome this, a two-stage approach for a moving vehicle detection system is proposed in this paper. The proposed system mainly consists of two stages namely, hypothesis generation and hypothesis verification. At the first step, hypotheses are generated using the concept that shadows beneath the vehicles are darker than the road region. The second step verifies whether a generated hypothesis is correct or not using an optimal artificial neural network (ANN). The weights corresponding to the ANN are optimally selected using the grasshopper optimisation algorithm. Through experimental results, it is shown that the proposed moving vehicle detection system performs with better accuracy than other methods.
Keywords: traffic surveillance system; moving vehicle detection; tracking; hypothesis generation; hypothesis verification; feedforward neural network; grasshopper optimisation algorithm.
Special Issue on: Research Challenges and Emerging Technologies in Autonomous Systems
Fuzzy-based local agent routing protocol for delay-conscious MANETs
by C. Venkataramanan, B. Senthilkumar
Abstract: Owing to the demand on multimedia applications, most researchers still concentrate on the area of Mobile Ad hoc NETworks (MANETs) to ensure the quality of services. MANET is an infrastructure-less network, where the devices (i.e. nodes) are self-configuring together and form the network without any central coordinator. Owing to the absence of central monitoring, MANET experiences various issues such as packet loss, topological control and delay. In order to address those problems in this paper, the enhanced version of Ad hoc On Demand Distance Vector (AODV) routing protocol is proposed. According to this proposed approach, each node in the network has to find the number of packets in the queue and calculate the weight value, which is used to predict the best routing path for ongoing transmission. The local agents are nominated for collecting and processing the information. The local agent performs the decision-based routing by using fuzzy inference model (AODV-FLA).
Keywords: AODV; energy usage; fuzzy; MANETs; routing; QoS.
An experimental analysis of quad-wheel autonomous robot location and path planning using the Borahsid algorithm with GPS and Zigbee
by Siddhanta Borah, R. Kumar, Subhradip Mukherjee, Fenil. C.Panwala, A. Prasanna Lakshmi
Abstract: This paper presents a hardware system structure and wireless navigation system for both localisation and path navigation of a mobile robot, implementing a 32-bit ARM processor (LPC2148 Board) into the design process of a mobile robot integrated with GPS and a ZigBee wireless communication device. A novel path-navigation algorithm (Borahsid algorithm), with less complexity than the existing algorithms adopted for mobile robot realistic work, uses GPS localisation as well as ZigBee communication. For simulation purpose MATLAB programming language has been used to simulate the mobile robot localisation and path navigation, and the results show the effectiveness of the model and the feasibility of the Borahsid algorithm. However, the entire control structure is executed and the experimental results were obtained in a real time system. The experimental results authenticate the performance and steadiness of the implemented control system process.
Keywords: ARM processor; GPS; ZigBee-based communication; Borahsid algorithm; MATLAB.
Special Issue on: AIST2019 Empowering Intelligent Transportation Using Artificial Intelligence Technologies
Network traffic analysis using machine learning techniques in IoT network
by Shailendra Mishra
Abstract: End-node internet-of-things devices are not very intelligent and resource-constrained; thus, they are vulnerable to cyber threats. They have their IP address, and once the hacker traces the IP, it becomes easy to get into the network and exploit the other devices. Cyber threats can become potentially harmful and lead to infection of machines, disruption of network topologies, and denial of services to their legitimate users. Artificial intelligence-driven methods and advanced machine learning-based network investigation protect the network from malicious traffic. The support vector machine learning technique is used to classify normal and abnormal traffic. Network traffic analysis has been done to detect and protect the network from malicious traffic. Static and dynamic analysis of malware has been done. Mininet emulator is selected for network design, VMware fusion is used for creating a virtual environment, the hosting OS is Ubuntu Linux, and the network topology is a tree topology. Wireshark was used to open an existing packet capture file that contains network traffic. Signature-based and heuristic detection techniques were used to analyse the signature of the record, which is found using a hex editor, and proposed rules are applied for searching for and detecting these files that have this signature. The support vector machine classifier demonstrated the best performance with 99% accuracy
Keywords: network traffic analysis; IoT; cyber threats; cyber attacks; machine learning.
A novel framework for efficient information dissemination for V2X
by Ravi Tomar, Hanumat G. Sastry, Manish Prateek
Abstract: This paper is focused on presenting a robust framework for information dissemination in vehicular networks using both Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication modes. The framework is designed to first prioritise the generated information and then, based on the priority, the message is disseminated over the network using one of the techniques for V2V or V2I. The paper first discusses the need for information dissemination and further proposes the novel framework for efficient information dissemination. The framework comprises two techniques for disseminating the information through V2V or V2I. The two techniques are presented and supported by the experimental, simulation and statistical analysis results. The results obtained are compared with existing mechanisms for information dissemination and are found to be performing better than standard information dissemination mechanisms.
Keywords: information dissemination; V2V; V2I; priority based.
Automated storyboard generation with parameters dependencies for regression test cases
by Nishant Gupta, Vibhash Yadav, Mayank Singh
Abstract: In recent trends and advancement of agile technology, the industry demand is for an effective and useful specification from the customer to reduce the effort, time and cost of software development. The storyboard is an effective tool to cater for the customer's requirements in an efficient manner. Our proposed framework and tool STORB will provide the platform where customer and business analyst may use the tool to generate a storyboard based on provided functionalities and parameters. The tool will provide detailed information about the customers requirements and generate the storyboard. Further, test data can also be generated for testing test cases. The tool has been used for three functionalities and their parameters on login functionalities of web application. The tool also defines the dependencies among parameters so that regression test cases can be generated. The result shows a useful significance of the tool in the software industry for the current trend of agile development.
Keywords: agile testing; regression testing; storyboard;test cases; functionalities.
Machine learning techniques applied to call admission control in 5G mobile networks
by Charu Awasthi, Prashant Kumar Mishra
Abstract: Highly reliable applications with low latency are key feature in 5G networks. In the prevailing scenario of efficient mobile network systems, the Quality of Service (QoS) depends on the regulation of traffic volume in wireless communications, known as the Call Admission Control (CAC). 5G networks are also very important for Intelligent Transportation Systems (ITS) as they can be used for quick detection and controlling of traffic, hence can be informative, sustainable, and more effective. Machine learning is the concept of providing the power to learn and develop mechanically, by practising. It also provides the power to attain learning and development in the absence of classical methods such as programming. It also permits wireless networks such as 5G to be increasingly dynamic and predictive. With this feature, the formulation of the 5G vision seems possible. With the use of machine learning and neural networks, this paper proposes various CAC methods deployed for 5G multimedia mobile networks. This can be achieved by delivering the best from all the attributes of soft computing that are deployed in the current mobile networks for ensuring recovery of efficiency of the prevailing CAC methods.
Keywords: artificial intelligence; machine learning; neural networks; 5G mobile networks; wireless networks; intelligent transportation system.
PALCT: vehicle-to-vehicle communication based on pseudonym assignment and encryption scheme using delay minimisation cover tree algorithm
by Righa Tandon, P.K. Gupta
Abstract: Vehicle-to-Vehicle communication is one of the new paradigms of networking which should be secure, fast and efficient. In this paper, we propose a framework that implements the pseudonym-based authentication scheme in which communication among vehicles is encrypted by using matrix array symmetric key (MASK), digital signature algorithm (DSA) and intelligent water drop (IWD). The proposed security scheme also ensures handling of many security attacks such as key-guessing, non-repudiation, replay and modification. In the proposed scheme, to preserve the vehicles identity, we have provided different pseudonyms to each vehicle in the network, which ensures secure communication among vehicles. Furthermore, the proposed delay minimisation cover tree algorithm ensures the issue of time-delay during vehicle to vehicle communication. In this algorithm, we have used Dijkstras algorithm for finding the optimal shortest path during vehicular communication. Obtained results show that the proposed scheme is effective and efficient as it reduces the time-delay by 4% for 140 vehicle nodes and 28.4% for 1000 vehicle nodes.
Keywords: pseudonyms; vehicle-to-vehicle communication; security; time-delay.
Special Issue on: Emerging Technologies for Internet of Vehicles
Effectiveness evaluation method for traffic data acquisition based on vehicle-borne network
by Minglei Song, Binghua Wu, Rongrong Li
Abstract: In order to reduce the probability of traffic accidents and enhance the safety of vehicle traffic, a method for evaluating the effectiveness of traffic data collection based on a vehicle network is proposed. A virtual coil is set on the driving lane to detect vehicles through three features of texture change, foreground area and pixel movement within the coil. A traffic detector is introduced to collect traffic data for a long time. Based on the cognitive assessment theory, a comprehensive assessment index system for the effectiveness of traffic data collection is constructed to complete the assessment. The experimental results show that the evaluation time of this method is less than 18 s, and the evaluation energy consumption is lower than other methods above 20 J, which proves that the evaluation time of this method is shorter, the error is smaller and the energy consumption is lower.
Keywords: vehicle-borne network; traffic data acquisition; traffic data evaluation.
Path planning method of automatic driving for directional navigation based on particle swarm optimisation
by Xian Luo, Rongtao Liao, Huanjun Hu, Yuxuan Ye
Abstract: In order to overcome the low planning efficiency of the automatic driving trajectory planning method for directional navigation, a particle swarm optimisation (PSO) based trajectory planning method is proposed. The kinematic characteristics of the vehicle are analysed and the vehicle dynamic equation is constructed. The position coordinates, speed and other motion parameters of the directional navigation vehicle are transformed into a Frenet coordinate system. The trajectory quality evaluation model of automatic driving vehicle for directional navigation is constructed. The trajectory quality evaluation index is taken as the constraint, and each variable is iteratively optimised by the PSO algorithm, so as to effectively realise the trajectory planning of automatic driving of directional navigation. Simulation results show that the proposed method can effectively improve the efficiency of autopilot trajectory planning and enhance the safety of the whole method.
Keywords: particle swarm optimisation; directional navigation; automatic driving; path planning.
Moving target tracking method in intelligent transportation system based on vehicle networking environment
by Dong-yuan Ge, Xi-fan Yao, Wen-jiang Xiang, Ri-bo He
Abstract: In order to improve the anti-jamming ability of moving target tracking and to avoid noise interference, a moving object tracking method based on vehicle network environment is proposed in this paper. The method of internet of vehicles is used to collect the echo signal of moving vehicle target, and the wavelet entropy feature is selected by multi-wavelet scale feature decomposition. According to the correlation feature tracking and identifying inf, the information model of target signal detection under the environment of internet of vehicles is established. The time-frequency characteristics of target signal and the high-order statistical characteristics of signal are analysed by using discrete orthogonal wavelet transform. The adaptive ability is enhanced and the moving target tracking and recognition is realised. The simulation results show that the method has strong anti-jamming ability, improves tracking accuracy, and has good recognition and notification capabilities.
Keywords: vehicle networking; intelligent transportation system; moving target; tracking; signal detection.
Research on data forwarding delay estimation of intelligent transportation system based on internet of vehicles technology
by Jian Gao, Daxin Tian
Abstract: In order to solve the problems of high error rate and long time in traditional data forwarding delay estimation methods, a data forwarding delay estimation method based on internet of vehicles technology for intelligent transportation system is proposed. Based on the Node-Link-Arc-Rord model and internet of vehicles technology, the simulation traffic network is constructed to optimise the intelligent transportation system. Based on the optimised intelligent transportation system, the average delay of the link is calculated according to the message data timestamp information, and the continuous vibration time and vibration period of the signal are estimated by using the sliding rectangular window, and the estimation results of the data forwarding delay of the intelligent transportation system are obtained. The experimental results show that the error rate of time delay estimation is less than 7%, the maximum estimated time is only 0.3 s, and the number of forward queued tasks is reduced.
Keywords: internet of vehicles; intelligent transportation system; data forwarding; time delay estimation; simulation traffic network; sliding rectangular window.
A new prediction method of short-term traffic flow at intersection based on Internet of vehicles
by Ying Zheng, Ying Zhou
Abstract: In order to overcome the problems of large error and long time-consuming in the prediction of short-term traffic flow at intersections, a new short-term traffic flow prediction method based on the internet of vehicles (IoV) is proposed in this paper. In the IoV environment, the training samples are input into the prediction model of the IoV, the output value is calculated, and the error is obtained. Then, the weights and wavelet factors of the network are modified by a gradient descent algorithm. When the network error reaches the set accuracy or reaches the maximum training time, the training is stopped to get the predicted short-term traffic flow. The experimental results show that the mean square percentage error is about 0.01%, and the longest prediction time is 0.878 min. The fitting degree between the predicted value and the actual value of traffic flow is high, and the prediction effect is ideal.
Keywords: internet of vehicles; intersection; short-term traffic flow; prediction.
Special Issue on: Advances in Internet of Vehicles
Auto-reversing intelligent obstacle avoidance system based on optical fibre sensor
by Hongwei Yang, Zhenyi Chen, Xu Sun
Abstract: Aiming at the problems of low obstacle avoidance accuracy and long obstacle avoidance time in the traditional obstacle avoidance system, an automatic reversing intelligent obstacle avoidance system based on an optical fibre sensor is designed. The system hardware consists of an optical fibre sensor module, power module, microprocessor, display output module and voice alarm module. The wavelet packet analysis method is used to extract the obstacle features in the process of automatic reversing. According to the feature extraction results, the optical fibre sensor is used to measure the distance, calculate the spatial position of the obstacle features in the process of automatic reversing, so as to realise automatic reversing and intelligent obstacle avoidance. The simulation results show that the maximum obstacle avoidance deviation of the designed system is 0.8 mm, which is much smaller than the that of traditional obstacle avoidance systems; the obstacle avoidance response time of the proposed system is only 18 s, which is also much smaller than other systems. The proposed method obstacle exhibits higher avoidance accuracy, shorter obstacle avoidance response time, and excellent application performance.
Keywords: optical fibre sensor; auto-reverse; intelligent obstacle avoidance; voice alarm module; wavelet packet analysis.
High reliability metro integrated monitoring system based on ZigBee communication
by Guoquan Kong
Abstract: In order to improve the safety of subway operation, reduce the resource consumption rate of monitoring system and improve the communication efficiency of subway monitoring system, a new high reliability subway integrated monitoring system based on ZigBee communication is designed in this paper. In the hardware design of the monitoring system, the USB interface of the system, the core processor of ZigBee communication hardware network system and the circuit of the system are designed. The system software design mainly includes the algorithm of metro data signal reception and the system database. Through the results of system hardware and software, a high reliability metro integrated monitoring system based on ZigBee communication is completed. The experiment results show that the resource consumption rate of the system is about 10% when the number of iterations is 80, and the communication efficiency of the system is about 98% when the number of iterations is 100. Compared with the other methods, the method in this paper has low resource consumption rate and high communication efficiency.
Keywords: ZigBee communication; high reliability monitoring; metro integrated monitoring system; subway operation; subway safety.
Automatic control method of driving direction of unmanned ground vehicle based on association rules
by Min Yang, Zhuqiao Ma, Longyu Cai
Abstract: In order to overcome the problems of large position deviation and angular deviation in the traditional driving direction control method of unmanned ground vehicles, an automatic driving direction control method of unmanned ground vehicles based on association rules is proposed. First, the Apriori algorithm is used to find frequent itemsets of unmanned ground vehicle driving data, generate association rules, and determine the association between itemsets in unmanned ground vehicles (UGV) driving data. After determining the data attributes, the decision tree algorithm is used to complete the mining of UGV driving data. According to the mining results, the proportion integral differential (PID) feedback control algorithm is used to obtain the steering wheel angle control input required for trajectory tracking, and the automatic control of the driving direction is completed. The experimental results show that in various complex traffic environments, the method can control the position deviation of the unmanned ground vehicle between -0.28 and 0.43 m, and the angle deviation between -0.21 and 0.23 to minimise the deviation. The method in this paper has certain application value and is worthy of further promotion and application.
Keywords: association rules; unmanned ground vehicle; driving direction; automatic control.
Intelligent encryption method for wireless sensing signal of underwater vehicles
by Hao Wu, Yangming Wu, Yun Zhang, Yannian Zhang
Abstract: An intelligent encryption method of wireless sensing signal of underwater vehicles based on compressed sensing is proposed. The compressed sensing theory was used to collect the wireless sensing signal of underwater vehicles, observe the signal, reduce the dimension of signal, and then construct the observation matrix. Based on the constructed observation matrix, hamming window was used to process the wireless sensor signal. After the framing processing, discrete cosine transform was used to enhance the sparsity of wireless sensor signals and improve the effectiveness of encryption. Finally, the signal encryption and decryption were realised by chaotic scrambling and its inverse process. The experimental results showed that compared with the traditional encryption method, the proposed intelligent encryption method had a lower intrusion rate and had better encryption effect via resisting the interference of white noise. The maximum rate of the proposed method was 2.72 KB s-1, the maximum occupied space was 19 KB, and the residual error of the proposed method was the largest when the sparsity was 60, which was 4.5 X 10-14, which was much lower than that of the other two methods.
Keywords: underwater vehicle; wireless sensing signal; intelligent encryption; Hamming window.
Key technologies of automotive air conditioning control system based on CAN bus and intelligent control algorithm
by Lei Wu
Abstract: In order to explore the importance and application value of interconnection key technologies such as can bus (controller area network bus) and intelligent control algorithm in automobile air conditioning control system, and provide feasible reference for the development of automobile air conditioning control system, energy conservation and environmental protection. Combined with the analysis of application design examples of automobile air conditioning, this paper expounds the importance and application value of interconnection key technologies such as can bus and intelligent control algorithm in automobile air conditioning control system, and comprehensively analyses and prospects the research progress and benefits of the system. From the implementation effect, in the system design and research based on CAN bus and intelligent control algorithm, relying on the local interconnect network (Lin) protocol as the supplement of can network, the comprehensive control of all parts of the car body is realized. The research on intelligent control system of automobile air conditioning has important design and research value for reducing cost, reducing energy consumption, prolonging automobile life and reducing automobile operation cost. In the research of actual nodes and control system, the advantages of this design scheme provide a feasible reference for relevant design.
Keywords: CAN Bus; intelligent control algorithm; automobile air conditioning control system; key technology.
Research on EPS system control strategy of SUV based on CarSim/Simulink
by Cheng Li, Aiguo Wang
Abstract: In order to solve the problems existing in traditional electric power steering system control methods, such as poor operation angle control effect, low system control accuracy and long control time, this study designed an electric power steering system control strategy of a sports utility vehicle based on CarSim/Simulink. Firstly, the characteristics of electric power steering system are analysed, which provides the basis for subsequent control. Then, the dynamic model of sports utility vehicle is constructed. On this basis, the vehicle model is abstracted and simplified based on CarSim/Simulink software. Finally, according to the power assist characteristic curve model, the parameters such as steering wheel torque signal and vehicle speed sensor are optimised to complete the research on the control strategy of the electric power steering system. Experiment results show that the proposed method has a good effect on the operating angle control of SUV EPS system, the control accuracy of the system is always higher than 90%, and the maximum time consumption is only 7 s.
Keywords: CarSim/Simulink; SUV model; EPS system; parameter optimization; control strategy.
Special Issue on: Artificial Intelligence Driven Vehicular Communication Networks in Beyond 5G Era
Real-time separation optimisation algorithm for hybrid blind speech signal in vehicular communication networks in beyond the 5G era
by Guoan Hu
Abstract: In this paper, we conduct an in-depth analysis on the real-time separation optimisation algorithm for the hybrid blind signal in wireless communication networks. In the process of the real-time separation of blind signals in network communication, firstly, the hybrid signal in the network communication is whitened to remove the core correlation between the blind signals. In this foundation determined in the network correspondence the mixed signal matrix of linear transformation, it uses transformation matrix to separate in the network correspondence in the blind signal independent signal component, from this the network correspondence area south of core signal is restored. The data analytic framework is suggested to optimise the framework of the proposed tool. Then, the designed model is applied to the vehicular communication networks in beyond the 5G era, and the simulation gives the overall performance estimation to test the robustness.
Keywords: real-time separation; optimisation algorithm; blind signal; wireless communication; vehicular communication; 5G technology.