International Journal of Vehicle Autonomous Systems (13 papers in press)

Regular Issues

• The safety potential of automatic emergency braking and adaptive cruise control and actions to improve the potential  
  by Roni Utriainen, Markus Utriainen And Pöllänen 
  Abstract: The study investigates the potential of automatic emergency braking (AEB) and adaptive cruise control (ACC) systems to prevent fatal rear-end, intersection and pedestrian crashes in Finland. The systems' possibilities to prevent crashes were assessed using data on 115 in-depth investigated fatal crashes. The data includes all fatal crashes in the three studied crash types in 2014-2016. This study considers the impact of estimated speed, weather conditions and intentionality on the systems operation. AEB and ACC could potentially have prevented 41% of the crashes. The highest safety potential in terms of share of hypothetically prevented crashes was recognised in rear-end (45%) and pedestrian crashes (45%) and the lowest in intersection crashes (36%). This study complements previous research, which amount is low especially considering the potential to reduce pedestrian and intersection crashes, and which has typically been limited in the aspects that are considered in analysing the safety potential. Additionally, issues related to systems operational conditions are discussed and the possibilities to further increase the safety potential are assessed.
  Keywords: automatic emergency braking; AEB; adaptive cruise control; ACC; safety potential; crash analysis; rear-end crashes; pedestrian crashes; intersection crashes.
  
  
• Indirect self-tuning controller for a two degree of freedom tracker model  
  by Amir Naderolasli 
  Abstract: Tracker systems have turned into an increasingly important issue in guidance systems and play a key role in navigational tracking. Accordingly, the aim of this study is to investigate a newly developed self-tuning adaptive strategy for increasing the precision of stabilisation and control in two-degree-of-freedom (2-DOF) tracker systems. For this purpose, a new self-tuning adaptive strategy is proposed for boosting the degree of stabilisation and regulation in 2-DOF tracker systems. The strategy is, in effect, an identifier-based adaptive strategy operating on Recursive Least Squares (RLS), which results in a non-minimum phase model. Together, the self-tuning stabiliser and tracker act as inner and outer loops of the targeted control system in order to track a desired command for ensuring a consistent and desirable stabilisation. The performance of the proposed method is further examined by using simulation techniques to show its functional capability in coupling with possible external disturbances and uncertainties.
  Keywords: two-DOF tracker; gimbal system; stabilisation mode; tracking mode; self-tuning; adaptive strategy,.
  
  
• Automated vehicle lateral guidance using multi PID steering control and look-ahead point reference  
  by Nolwenn Monot, Xavier Moreau, André Benine-Neto, Audrey RIZZO, François AIOUN 
  Abstract: In this paper, a complete analysis of the influence of a look-ahead distance and the longitudinal vehicle velocity on the vehicle lateral dynamics is made in order to choose an adequate control strategy for lane keeping. Since the longitudinal velocity can be easily and accurately measured, a gain scheduling strategy based on the longitudinal velocity is employed in the design of a robust multi PID for the lateral control. Implemented onboard of a C4 Picasso prototype vehicle, the proposed controller showed promising results at variable speed and a satisfactory accuracy for lateral positioning.
  Keywords: autonomous vehicles; robust control; driver assistance systems; self steering; steering behaviour; lane keeping; lane change assist.
  
  
• Developing a novel rear steering angle control strategy for a modern three-wheeler  
  by Saeid Shabzendehdar, Masoud Masih-Tehrani, Khashayar Moridpour 
  Abstract: In this paper, a new rear steering angle control strategy is developed. This strategy is derived from the nonlinear 3DOF bicycle model in order to improve three-wheeler stability and manoeuvrability. However, common strategies have derived from the linear 2DOF bicycle model which has simpler assumptions. This new strategy has additional input comprising lateral velocity in comparison with the common strategies. This additional input could be simply observed using a suitable sensor. The nonlinear 3DOF tricycle equations have been implemented in MATLAB/Simulink for the modelling of the three-wheeler. Configurations of the handmade MATLAB/Simulink model were obtained from the information of the CarSim three-wheeled car. The developed model is validated using CarSim three-wheeled car, which is in good agreement with the experimental results. The three-wheeler model is used to compare the results of the strategies under different moving conditions. The results confirm that the new strategy provides better stability at high velocities and better manoeuvrability at middle velocities. Furthermore, the new strategy has acceptable performance at low velocities (parking manoeuvres). In addition, the new strategy has a suitable settling time and overshoot performance at transient manoeuvres.
  Keywords: all-wheel steering system; manoeuvrability; rear steering angle control strategy; stability; three-wheeler.
  
  

Special Issue on: Embedded Autonomous Architecture and Its Connectivity for Automotives

• A hybrid approach to perform test case prioritisation and reduction for software product line testing  
  by Satendra Kumar, Raj Kumar, Mohit Mittal 
  Abstract: Software Product Line (SPL) is a popular research area in software engineering which deals with numerous products generated simultaneously. There is requirement for a tool or framework that can test all the products. Owing to an increase in the number of products there is an exponential increase in the number of features. SPL implies Test Case Prioritization (TCP) and Test Case Reduction (TCR) techniques to alleviate the problem of testing. This paper proposes a hybrid approach which combined K-means and Principal Component Analysis (PCA) approaches to perform SPL testing. The hybrid approach provides the solution to SPL testing using K-means clustering and PCA. We use Euclidean distance equation to perform K-means clustering. PCA helps in reducing the dimension of data from multidimensional to two dimensional (2D) data, and as a result, it can plot the clusters using K-means clustering. The experimental results show that hybrid approach provides better results than the random, similarity, and ICPL algorithm order the APFD metric. Our proposed approach reduces the test cases to the minimum amount and it can also be used to perform efficient SPL testing that not only improves the effectiveness and efficiency of fault detection but also improves the effectiveness of Test Suite Reduction (TSR). Thus this hybrid approach can be useful to alleviate the effort of SPL tester
  Keywords: feature model; software product line testing; test case prioritisation; test case reduction; principal component analysis; K-means clustering.
  
  
• Design and modelling of a hybrid fuel cell and sloar-based electric vehicle  
  by Ravipati Srikanth, M. Venkatesan 
  Abstract: Design and modelling of a hybrid electric vehicle using two different energy sources (fuel cell and photovoltaic array) are presented in this paper. In this proposed model, a High Gain Interleaved Boost Converter (HGIBC) is used to extract the maximum power from the PV array and fuel cell. To optimise the maximum power, a single MPPT system has been applied to both the fuel cell stack and the solar panel. A Brushless DC Motor (BLDC) is used to evaluate the performance of the electric vehicle. A BLDC motor has been designed to coerce the hybrid electric vehicle using a three phase inverter. The performance characteristics of the system have been analysed in terms of rise time, peak overshoot and efficiency. Finally, the simulation results are verified through MATLAB/Simulink.
  Keywords: hybrid electric vehicle; HGIBC; fuel cell; photovoltaic array; brushless DC motor; MATLAB/Simulink.
  
  
• A hybrid three-wheeler electronic gear using a three-stage inverter  
  by Micheal Lordwin Cecil Prabhaker, Revathi Munirathinam, Ramu Pitchaikkanu 
  Abstract: This work is intended to design and analyse the permanent magnet synchronous motor (PMSM) motor for three-phase inverter and electronic gear equivalent circuit with two three-stage inverters for the same specification to find its suitability for three-wheel traction application. In recent times, Permanent Magnetic Brushless DC (PMBLDC) and PMSM motor drive have gained attention by becoming established as a potential alternative for conventional variable speed drives. This is due to their performance, which was better than conventional variable speed drives. The PMSM is widely used in many applications owing to its high efficiency, torque ripple, high torque and high performance, and low and high speed operation. Finite Element Analysis (FEA) software, such as MAGNET and ANSYS, is used to design motors suitable for three-wheeler traction applications with the required electromagnetic, thermal and vibration properties. The main purpose of the work is to design a hybrid electronic gear using three stage inverter circuits for three-wheeler traction applications and comparing the performance parameters with the conventional gear. It includes inverter simulation using MATLAB simulation for speed and torque performance. By analysing the results, it can be seen that the proposed three-stage inverter-based e-gear for three-wheeler transmission offers better performance in continuous output power and torque compared with conventional gears.
  Keywords: finite element analysis; permanent magnet synchronous motor; three-phase inverter; electronic gear.
  
  
• Design and analysis of a composite micro aerial vehicle  
  by M. Saleem, Nishant Kumar Raj, Shreshth Gupta, Sunny Ramesh Izate 
  Abstract: Nowadays, getting materials that suit our requirements is very tough, so almost all the industries are going to composite materials. Reinforced and matrix combination gives new materials that have high strength and reduced weight ratio. These materials are called composites. This research work represents an aluminium matrix composite produced by stir casting techniques. Aluminium matrix composites have less weight, lower cost and higher stiffness. Composites are used in aerospace industries for reduction in weight. Aluminium matrix composites are tested under various mechanical tests and the characteristics are reported. In this work, a micro aerial vehicle is designed by using CATIA. Structural and flow analyses were carried out by computational methods.
  Keywords: composite; LM5; structural analysis; MAV; micro aerial vehicle.
  
  
• Detection of DOS attacks using machine learning techniques  
  by Deepak Kumar, Vinay Kukreja, Virender Kadyan, Mohit Mittal 
  Abstract: The growth of the IoT has been reinforced by the advances, when used with other technologies such as embedded systems, hardware and software enhancements, networking devices, but still there are so many threats in the IoT including security, accuracy, performance, networks, and privacy. The increased use of smart services, remote access, and frequent changes in networks has raised many security and privacy concerns. Therefore, security threats in the IoT is one of the main issues during data transmission. Thus, network challenges and security issues concerning the IoT can be resolved by using machine learning techniques and algorithms. The current study outlines the security standards for IoT applications to enhance the performance and efficiency of the network and user services. The study's focus is also on comparing the support vector machine and decision trees for detection of denial of service attacks.
  Keywords: IoT threats; IoT challenges; intrusion detection system; machine learning techniques.
  
  
• LabVIEW-based performance improvement of servo vacuum booster using programmable logic control  
  by Revathi Munirathinam, Navaz Mohamed, Ramu P 
  Abstract: The issue of safety is paramount in any automotive system, especially in automotive braking systems. Nowadays this safety is less regarded as the efficient testing is not being performed on the braking systems. It is one of the challenging tasks and keeps interest among researchers. Recently, researchers have focused on designing the braking system depending on the servo vacuum booster. In this paper, we propose a model to monitor the servo vacuum booster performance and also to improve the performance of the system. The virtual environment LabVIEW is the tool used to calibrate the system under test. The input stroke, which is the replicant of the pedalling motion, will be given through the servo motor at the rate required, which is helpful to control the programmable logic control (PLC). The parameters under measurement, such as performance, jump in and threshold, which are required for efficient braking, can be set by PLC programing in RS Logic 5000 software. On meeting the requirements while testing, the servo vacuum booster will be considered as being effective with no flaws and can be further processed.
  Keywords: auto-braking system; LabVIEW; programmable logic controller.
  
  
• Developing in-vehicular noise robust children ASR system using tandem-NN based acoustic modelling  
  by Virender Kadyan, Shashi Bala, Puneet Bawa, Mohit Mittal 
  Abstract: Processing of children's speech is always challenging owing to data scarcity and inefficient modelling input feature vectors. Accuracy of the modelling phase is always dependent on extracted input features. In this paper, posterior probabilities are estimated over a phone set using a discriminatively trained model through a neural network (NN) preprocessor. This NN classifier is first trained on original speech and then context-independent phone posterior probabilities are estimated on a tandem-NN system. The output vectors are employed as default features, which are processed on Deep Neural Network-Hidden Markov Model (DNN-HMM) models. The original data-based system performance is improved by extending it using data augmentation. To see the robustness of the augmented speech, various in-vehicle data are investigated and the model is found to be superior to other systems. Finally, we combine all augmented data to overcome data scarcity challenges to enhance system performance. It gives a relative improvement of 23.77% over the baseline system.
  Keywords: children speech recognition; data augmentation; GFCC; multi-layer perceptron; tandem-NN.
  
  
• Improved vehicle navigation using sensor fusion of inertial odometric sensors with global positioning system  
  by Allan Anbu, Arun Kumar Pinagapani, Geetha Mani, K.R. Chandran 
  Abstract: The primary objective of a navigation system is to continuously monitor the trajectory of a vehicle. Navigation for a land vehicle is implemented using different measurement systems, such as Inertial Navigation System (INS), radio navigation system, vision-based navigation and Global Positioning System. INS provides continuous information of position, velocity and attitude. However, its performance deteriorates with time since the errors tend to accumulate. GPS is an electromagnetic signal that is more accurate than INS but cannot provide continuous and reliable position all the time. The drawbacks of these individual systems have given rise to the need for higher accuracy, integrity and robustness. This has led to the fusion of measurements from these sensors to obtain an improved performance in measuring the position and velocity of a vehicle. This paper discusses the simulation and implementation of an integrated navigation system using inertial odometric sensors with GPS using the scaled unscented Kalman filter. The method discussed involves obtaining a state transition model and a measurement model of the sensors and processing the states using the scaled unscented Kalman filter to obtain better estimates of position and velocity.
  Keywords: global positioning system; inertial navigation system; scaled transformation; state estimation; stochastic system; unscented Kalman filter.
  
  
• Development of a low-cost smart vehicle start up and tracking system using Android and Arduino  
  by Sundresan Perumal, Mujahid Tabassum, Dayang Siti Nur Amirah Bt Ab Ahmad Zulkipli 
  Abstract: Today, the Information Technology (IT) field has developed enormously. Smart devices and smart networks are being used in industries to enhance their productivity and security. Smartphone technology has evolved enormously and is used for many purposes besides communication between two parties. In this paper, we have developed a low-cost vehicle monitoring system using an Arduino UNO microcontroller and GSM (Global System for Mobile communications) module. The primary purpose of this research was to develop a low-cost system to start and track an automobile or vehicle by integrating with GSM and Global Positioning System (GPS) modules. GPS and GSM modules were integrated with Arduino UNO microcontroller as a processor and controller for the whole system. An Android application was developed to communicate with the Arduino module and get the instruction from the user. The user can use the Android application to start their vehicle wirelessly by sending a signal to the installed SIM card on the GSM module inside the vehicle and track the vehicle using GPS. Locking and unlocking actions were programmed into the application for the vehicles security purpose. The system has the ability to send the location information to the user's email address as part of the security feature. The hardware system can be plugged into the USB port of the vehicle to get a power supply, or a backup battery can be equipped with the system whenever the vehicle is at rest. The system was successfully developed and tested in multiple real-time scenarios.
  Keywords: Arduino UNO; vehicle monitoring system; GSM; GPS; Android; wireless sensor network.