Stratis Kanarachos

Coventry University | CU · Faculty of Engineering and Computing

An algorithm is developed in order to record a vehicle’s fuel consumption using data from a smartphone’s sensors. Six field tests were conducted: (1) Ford Fiesta car with automatic transmission driven around Coventry, UK, with “passive” and “restless” driving behaviors, (2) Ford Fiesta car with manual transmission under heavy traffic driven around...

The aim of this paper is to understand consumer's perceptions towards new energy services. A comprehensive literature review was conducted prior to implementing an online questionnaire with 212 respondents. Consequently, a qualitative in-depth interview was conducted with six representative early adopters of new energy services. The main identified...

In this paper, a deep learning approach is proposed to accurately position wheeled vehicles in Global Navigation Satellite Systems (GNSS) deprived environments. In the absence of GNSS signals, information on the speed of the wheels of a vehicle (or other robots alike), recorded from the wheel encoder, can be used to provide continuous positioning i...

In this paper, a deep learning approach is proposed to accurately position wheeled vehicles in Global Navigation Satellite Systems (GNSS) deprived environments. In the absence of GNSS signals, information on the speed of the wheels of a vehicle (or other robots alike), recorded from the wheel encoder, can be used to provide continuous positioning i...

Laser shock peening (LSP) as a surface treatment technique can improve the fatigue life and corrosion resistance of metallic materials by introducing significant compressive residual stresses near the surface. However, LSP-induced residual stresses are known to be dependent on a multitude of factors, such as laser process variables (spot size, puls...

Recurrent Neural Networks (RNNs) are known for their ability to learn relationships within temporal sequences. Gated Recurrent Unit (GRU) networks have found use in challenging time-dependent applications such as Natural Language Processing (NLP), financial analysis and sensor fusion due to their capability to cope with the vanishing gradient probl...

Low-cost Inertial Navigation Sensors (INS) can be exploited for a reliable solution for tracking autonomous vehicles in the absence of GPS signals. However, position errors grow exponentially over time due to noises in the sensor measurements. The lack of a public and robust benchmark dataset has hindered the advancement in the research, comparison...

An approach based on Artificial Neural Networks is proposed in this paper to improve the lo-calisation accuracy of Inertial Navigation Systems (INS)/Global Navigation Satellite System (GNSS) based aided navigation during the absence of GNSS signals. The INS can be used to con-tinuously position autonomous vehicles during GNSS signal losses around u...

The safety of vulnerable road users is of paramount importance as transport moves towards fully automated driving. The richness of real-world data required for testing autonomous vehicles is limited and furthermore, available data do not present a fair representation of different scenarios and rare events. Before deploying autonomous vehicles publi...

Inertial Navigation Systems (INS) are commonly used to localise vehicles in the absence of Global Navigation Satellite Systems (GNSS) signals. However, they are plagued by noises, which grow exponentially over time during the triple integration computation, leading to a poor navigation solution. We explore the wheel encoder as an alternative to the...

Inertial Navigation Systems (INS) are commonly used to localise vehicles in the absence of Global Navigation Satellite Systems (GNSS) signals. However, they are plagued by noises, which grow exponentially over time during the triple integration computation, leading to a poor navigation solution. We explore the wheel encoder as an alternative to the...

An algorithm based on Artificial Neural Networks is proposed in this paper to improve the accuracy of Inertial Navigation System (INS)/ Global Navigation Satellite System (GNSS) integrated navigation during the absence of GNSS signals. The INS which can be used to continuously position autonomous vehicles during GNSS signal losses around urban cany...

Road localisation of autonomous vehicles is reliant on consistent accurate GNSS (Global Navigation Satellite System) positioning information. Commercial GNSS receivers usually sample at 1 Hz, which is not sufficient to robustly and accurately track a vehicle in certain scenarios, such as driving on the highway, where the vehicle could travel at med...

Swarm intelligence has been extensively adopted to develop and deploy optimization algorithms to almost all branches of science and engineering. In this paper, a visual contrast–based fruit fly algorithm (c-mFOA) is presented to push further the improvement of intelligent optimization when it comes to general engineering problem solving with emphas...

Vulnerable road user safety is of paramount importance as transport moves towards fully autonomous driving. The research question posed by this research is of how can we train a computer to be able to see and perceive a pedestrian’s movement. This work presents a dual network architecture, trained in tandem, which is capable of classifying the beha...

Ride comfort can heavily influence user experience and therefore comprises one of the most important vehicle design targets. Although ride comfort has been heavily researched there is still no definite solution to its accurate estimation. This can be attributed, to a large extent, to the subjective nature of the problem. Aim of this study was to ex...

Low-cost inertial navigation sensors (INS) can be exploited for a reliable tracking solution for autonomous vehicles. However, position errors grow exponentially due to noises in the measurements. Several deep learning techniques have been investigated to mitigate the errors for a better navigation solution [1-10]. However, these studies have invol...

Topology optimisation is an increasingly important process used in a variety of industries to improve the designs of manufacturable products. The higher reliance of optimisation software, used for instance in the automotive industry, highlights its importance for designing more efficient and refined mass-produced components. Post-processing of topo...

Self-driving cars are on the horizon, making it necessary to consider safety assurance and homologation of these autonomously operating vehicles. In this study, we systematically review literature that proposes new methods for these areas. The available methods were categorized into a novel taxonomy, dividing them into the strategies of combinatori...

Motion sickness is common within many forms of transport; it affects most of the population who experience some symptoms at some time. Automated vehicles (AV) offer productivity benefits but also increased incidence of motion sickness. There are mitigation methods with varying degrees of effectiveness to combating motion sickness. Bone conductive v...

Automated Vehicles and next generation ADAS hold the promise of disrupting mobility. However, public field trials have recently highlighted road anomalies, such as potholes and bumps, as a source of autopilot disengagements. In this paper, we research the influence of road anomalies on the performance of Artificial Intelligence-based vision systems...

A Vehicle with multiple drivetrains, like a hybrid electric one, is an over-actuated system that means there is an infinite number of combinations of torques that individual drivetrains can supply to provide a given total torque demand. Energy efficiency is considered as the secondary objective to determine the optimum solution among these feasible...

This article presents a dataset recorded with a sensor-equipped research vehicle on public roads in the city of Coventry in the United Kingdom. The sensor suite includes a monocular-, infrared- and smartphone-camera, as well as a LiDAR unit, GPS receiver, smartphone sensors and vehicle CAN bus data logger. Data were collected by day and night in a...

Automated vehicles will provide greater transport convenience and interconnectivity, increase mobility options to young and elderly people, and reduce traffic congestion and emissions. However, the largest obstacle towards the deployment of automated vehicles on public roads is their safety evaluation and validation. Undeniably, the role of cameras...

Testing & validation of high-level autonomy features requires large amounts of test data, which conventionally is achieved by accumulating miles on the road and dedicated proving grounds. This places an extreme burden not only on original equipment manufacturers (OEMs) of connected and autonomous vehicles (CAVs), but also on Tier 1 suppliers of CAV...

Motion sickness is common within most forms of transport; it affects most of the population who experience varied symptoms at some stage in their lives. Thus far, there has been no specific method to quantify the predicted levels of motion sickness for a given vehicle design, task and route. Objective To develop a motion sickness virtual predictio...

Over the past decade, several researchers have presented various optimisation algorithms for use in truss design. The no free lunch theorem implies that no optimisation algorithm fits all problems; therefore, the interest is not only in the accuracy and convergence rate of the algorithm but also the tuning effort and population size required for ac...

In recent years, researchers have presented various optimisation algorithms for truss design. The "no free lunch" theorem implies that no optimisation algorithm fits all problems; therefore, the interest is not only in their accuracy and convergence rate but also the tuning effort and population size to achieve the optimal result. The latter is par...

This paper presents an Optimized Unscented Kalman Filter for vehicle dynamics virtual sensing. An automated procedure to optimize the virtual sensor parameters based on metaheuristic algorithms is presented in order to avoid the time-consuming and complex manual tuning task. Specifically, Genetic Algorithm Optimization (GA) and contrast-based Fruit...

The automotive world is currently shifting focus towards electric vehicles (EVs) and the market of connected, autonomous vehicles (CAVs) is steadily growing. Vehicle ride comfort is an attribute which for years now have been a factor which has a significant influence on vehicle development programmes. Due to the complexity of ride comfort, achievin...

Recurrent neural networks (RNN) are distinguishable form other classes of artificial neural networks by their ability to make nodal connections along temporal sequences. Gated Recurrent Unit (GRU) proposed by Cho et al have found use in several time dependent applications such as natural language processing (NLP), financial analysis and sensor fusi...

With the continued advancement of autonomous vehicles and their implementation in public roads, accurate detection of vulnerable road users (VRUs) is vital for ensuring safety. To provide higher levels of safety for these VRUs, an effective detection system should be employed that can correctly identify VRUs in all types of environments (e.g. VRU a...

Safety is an essential aspect in the facilitation of automated vehicle deployment. Current testing practices are not enough, and going beyond them leads to infeasible testing requirements, such as needing to drive billions of kilometres on public roads. Automated vehicles are exposed to an indefinite number of scenarios. Handling of the most challe...

BACKGROUND: Motion sickness is common within most forms of transport, it affects most of the population who experience varied symptoms at some stage in their lives. Thus far, there has been no specific method to quantify the predicted levels of motion sickness for a given vehicle design, task and route. OBJECTIVE: To develop a motion sickness virtu...

Abstract: Motion sickness is common within many forms of transport, it affects most of the population who experience some symptoms at some time. Automated Vehicles (AV) offer productivity benefits but also increased incidence of motion sickness. There are mitigation methods with varying degrees of effectiveness to combating motion sickness. Bone Co...

As autonomous vehicles become more common on the roads, their advancement draws on safety concerns for vulnerable road users, such as pedestrians and cyclists. This paper presents a review of recent developments in pedestrian and cyclist detection and intent estimation to increase the safety of autonomous vehicles, for both the driver and other roa...

With the development and deployment of lightweight vehicles to the market, inclusive of autonomous pods, a review of advanced crashworthy structures and the design methodology has been conducted as it is thought that super-lightweight vehicles may pose significant risk to the occupants if they are involved in a crash. It is suggested that tests sho...

Precipitation can adversely influence road safety. Slippery road conditions have traditionally been detected using reactive methods requiring considerable excitation of the tire forces. Alternatives rely on non-contact methods such as vision, sound or ultrasonic sensors. This study proposes a cost-effective wet road conditions detection method base...

Motion sickness is a persistent problem in many forms of transport. It affects most of the population, is debilitating for the sufferer and can disrupt the journey for the rest. Automated Vehicles (AV’s) offer greater flexibility in cabin design particularly in the future where no physical controls are required. This poses additional risks to passe...

To this day evaluation of both motion sickness and perceived comfort in vehicles has been predominantly based on the acceleration measurements. Introduction of autonomous vehicles forces the automotive industry to shift focus from driver towards passenger comfort. Studies conducted at Coventry University aim at exploring the possible correlation be...

To this day evaluation of both motion sickness and perceived comfort in vehicles has been predominantly based on the acceleration measurements. Introduction of autonomous vehicles forces the automotive industry to shift focus from the driver towards passenger comfort. Studies conducted at Coventry University aim at exploring the possible correlatio...

Automated vehicles (AV’s) offer greater flexibility in cabin design particularly in a future where no physical driving controls are required. One common concept for an automated vehicle is to have both forward and rearward facing seats. However, traveling backwards could lead to an increased likelihood of experiencing motion sickness due to the ina...

This paper presents a novel hybrid observer structure to estimate the lateral tire forces and road grip potential without using any tire–road friction model. The observer consists of an Extended Kalman Filter structure, which incorporates the available prior knowledge about the vehicle dynamics, a feedforward Neural Network structure, which is used...

The present study discusses the mechanical behaviour and modelling of a prototype automotive magnetorheological (MR) damper, which presents different viscous damping coefficients in jounce and rebound. The force generated by the MR damper is measured at different velocities and electrical currents, and a modified damper model is proposed to improve...

The high level of air pollution in urban areas, caused in no small extent by road transport, requires the implementation of continuous and accurate monitoring techniques if emissions are to be minimized. The primary motivation for this paper is to enable fine spatiotemporal monitoring based on crowd sensing, whereby the instantaneous fuel consumpti...

Prediction of human driving decisions is an important aspect of modeling human behavior for the application to Advanced Driver Assistance Systems (ADAS) in the intelligent vehicles. This paper presents a sensor based receding horizon model for the prediction of human driving commands. Human driving decisions are expressed in terms of the vehicle sp...

Rain, even shortfall rain, can adversely influence road safety. Currently, most methods for the detection of slippery road conditions require considerable excitation – by braking or steering – of the tyre forces. Thus, the safety margin between detection and reaction is minimal and dangerous situations can occur, for example hydroplaning. In this s...

Topology optimisation is a process that is becoming increasingly reliable and necessary in the pursuit of highly efficient components comprising of low mass with a high structural performance. These components are typically mass-produced on a large-scale in automotive sectors for instance, where components are usually metallic and pressed. The abil...

This paper introduces the setup of the European network ITEAM aimed at the training of early-stage researchers (ESR) in the field of multi-actuated ground vehicles (MAGV). A network concept includes three main domains, where fifteen interconnected individual research projects are allocated: MAGV Integration, Green MAGV, and MAGV Driving Environment...

Safe and reliable operation of power plants invariably relies on the structural integrity assessments of pressure vessels and piping systems. Welded joints are a potential source of failure, because of the combination of the variation in mechanical properties and the residual stresses associated with the thermomechanical cycles experienced by the m...

Chassis Active Safety Systems require access to a set of vehicle dynamics motion states which measurement is neither trivial nor cost-effective (e.g. lateral velocity). In this work, virtual sensing is applied to vehicle dynamics and proposed as a cost-effective solution to infer the vehicle planar motion states and three-axis tyre forces from sign...

This paper presents a novel approach to teach a vehicle how to drift, in a similar manner that professional drivers do. Specifically, a hybrid structure formed by a Model Predictive Controller and feedforward Neural Networks is employed for this purpose. The novelty of this work lies in a) the adoption of a data-based approach to achieve autonomous...

Nowadays, more than half of the world’s web traffic comes from mobile phones, and by 2020 approximately 70 percent of the world’s population will be using smartphones. The unprecedented market penetration of smartphones combined with the connectivity and embedded sensing capability of smartphones is an enabler for the large-scale deployment of Inte...

Presentation held at Shibaura institute of Technology, Tokyo. 15th International Workshop on Advanced Motion Control (AMC2018)

A comparison of popular optimisation algorithms with the improved cFOA using benchmark truss problems.

This paper explores the maximisation of the vehicle lateral dynamics on off-road conditions by means of active drifting and optimised wheel torque allocation. An Autonomous Drift Control (ADC) system based on a hierarchical control architecture is proposed to achieve this task. Specifically, the ADC consists of a high level layer that generates the...

The present study focuses on the automated learning of driver braking “signature” in the presence of road anomalies. Our motivation is to improve driver experience using preview information from navigation maps. Smartphones facilitate, due to their unprecedented market penetration, the large-scale deployment of Advanced Driver Assistance Systems (A...

Microscopic traffic simulation Safe, cheap and effective to evaluate Intelligent Transportation Systems. • Model calibration is the key to obtain meaningful results (GEH < 5). • Floating vehicle data (e.g. Smartphone) supplement traditional data from fixed detectors. • Optimization techniques support the modeller to tune and calibrate the model par...

This paper introduces the setup of the European network ITEAM aimed at the training of early-stage researchers (ESR) in the field of multi-actuated ground vehicles (MAGV). A network concept includes three main domains, where fifteen interconnected individual research projects are allocated: MAGV Integration, Green MAGV, and MAGV Driving Environment...