Ali Boyali

Identifying tire and vehicle parameters is an essential step in designing control and planning algorithms for autonomous vehicles. This paper proposes a new method: Simulation-Based Inference (SBI), a modern interpretation of Approximate Bayesian Computation methods (ABC) for parameter identification. The simulation-based inference is an emerging m...

Visible camera-based semantic segmentation and semantic forecasting are important perception tasks in autonomous driving. In semantic segmentation, the current frame's pixel-level labels are estimated using the current visible frame. In semantic forecasting, the future frame's pixel-level labels are predicted using the current and the past visible...

Identifying tire and vehicle parameters is an essential step in designing control and planning algorithms for autonomous vehicles. This paper proposes a new method: Simulation-Based Inference (SBI), a modern interpretation of Approximate Bayesian Computation methods (ABC) for parameter identification. The simulation-based inference is an emerging m...

Deep learning-based visible camera semantic segmentation report state-of-the-art segmentation accuracy. However, this approach is limited by the visible camera’s susceptibility to varying illumination and environmental conditions. One approach to address this limitation is visible and thermal camera-based sensor fusion. Existing literature utilizes...

Jaywalking is an abnormal pedestrian behavior which significantly increases the risk of road accidents. Owing to this risk, autonomous driving applications should robustly estimate the jaywalking pedestrians. However, the task of robustly estimating jaywalking is not trivial, especially in the case of visible camera-based estimation. In this work,...

To significantly reduce the occurrence of severe traffic accidents, reducing the number of vehicles in urban areas should be considered. Personal mobility is essential for realizing this reduction, which requires consideration of the last-/first-mile problem. The overall objective of our research is to solve this problem using standing-type persona...

In this study, we detail the procedures for designing gain scheduling controllers by Linear Quadratic $H_\infty$ robust optimization methods in Linear Matrix Inequalities (LMI) framework. The controllers are aimed at steering control of the autonomous vehicles. We first construct the Linear Parameter Varying (LPV) vehicle models and synthesize the...

In this paper, we present the application of successive convexification methods to autonomous driving problems borrowed from recent aerospace literature. We formulate two optimization problems within the successive convexification framework. Using arc-length parametrization in the vehicle kinematic model, we solve the speed planning and model predi...

In this paper, we propose an algorithm for optimal generation of nonholonomic paths for planning parking maneuvers with a kinematic car model. We demonstrate the use of Successive Convexification algorithms (SCvx), which guarantee path feasibility and constraint satisfaction, for parking scenarios. In addition, we formulate obstacle avoidance with...

Personal mobility devises become more and more popular last years. Gyroscooters, two wheeled self-balancing vehicles, wheelchair, bikes, and scooters help people to solve the first and last mile problems in big cities. To help people with navigation and to increase their safety the intelligent rider assistant systems can be utilized that are used t...

In this study, we elaborate the procedure of designing a supervisory controller for the Autonomous Transit on Demand Vehicle (ATODV) system. Reinforcement learning is implemented to reduce the mean waiting time of the passengers, and a cost function is introduced to penalize the energy consumption of the electric vehicles. A stochastic simulation e...

In this paper, a monocular camera-based method is proposed to estimate the steering angle in autonomous driving. A second order particle filtering algorithm is used to estimate the steering angles. The filtering algorithm is modeled at the scene-level for varying driving patterns. For a given road scene, individual proposal and likelihood distribut...

This study investigated the necessity of automated vehicle control customization for individual drivers via a lane-changing experiment involving 35 subjects and an automated minivan. The experiment consisted of two automated driving conditions: one in which the subject was unable to override vehicle controls, the other with the option to override w...

In this tutorial, we detailed simple controllers for autonomous parking and path following for self-driving cars and provided practical methods for curvature computation.

In this report we give details of a Discrete Event Simulation (DES) framework coded in Python environment for simulation and analysis of a customized Personal Rapid Transport (PRT) with passenger behavior. The prior analysis of the system is a must before deployment of the autonomous PRT cars (carts) to make decision of initial investment, number o...

Human-computer interaction has become increasingly easy and popular using widespread smart devices. Gestures and sketches as the trajectory of hands in 3D space are among the popular interaction media. Therefore, their recognition is essential. However, diversity of human gestures along with the lack of visual cues make the sketch recognition proce...

In this paper, we investigate the impact of face direction during traveling by Standing-Type Personal Mobility Device (PMD). The use of PMD devices has been a popular choice for recreational activities in the developed countries such as in the USA and the countries in Europe. These devices are not completely risk free and various accidents have bee...

This study investigated the effects of supervision on autonomous wheelchairs, which are considered to be a means of future transportation. A rider using an automated wheelchair needs to be vigilant about the failure modes of the system. This study focused on the effects of human factors on an automated system. Several experiments were conducted in...

Autonomous driving requires continuous and reliable centimeter level positioning accuracy for acceptable lane level navigational performance. Centimeter level positioning accuracy cannot be achieved using a conventional DGPS/DR. To deal with the above problem this paper proposes the novel and effective bias/shift estimation of DGPS/DR. On this pape...

In a standard convolutional neural network the different layers are trained using the back propagation algorithm. Following training, it can be observed that the first convolutional layer structurally resembles the Gabor filter in spite of being randomly initialized. Consequently, in this study, we propose to directly use the Gabor filters within t...

Autonomous driving requires continuous and reliable centimeter level positioning accuracy for acceptable lane level navigational performance. Centimeter level positioning accuracy cannot be achieved using a conventional DGPS/DR. To deal with the above problem this paper proposes the novel and effective bias/shift estimation of DGPS/DR. On this pape...

In this study, a vision based in-car entertainment user interface is presented. The user interface is designed using a hand posture and gesture recognition algorithm in deep learning framework. The hand posture recognition algorithm is formulated using the convolutional neural network to perform the fundamental tasks in the user interface. The hand...

In this paper, we propose a vision-based hand gesture recognition system for intelligent vehicles. Vision-based gesture recognition systems are employed in automotive user interfaces to increase the driver comfort without compromising their safety. In our algorithm, the long-term recurrent con-volution network is used to classify the video sequence...

Spotting signal patterns with varying lengths has been still an open problem in the literature. In this study, we describe a signal pattern recognition approach for continuous and simultaneous classification of a tracked hand's posture and gestures and map them to steering commands for control of a robotic wheelchair. The developed methodology not...

In this paper, we propose the use of Collaborative based Representation in Spectral Domain to recognize the postures and gestures from the Electromyography (EMG) recordings acquired by a recently introduced sensor; Thalmic Labs' MYO armband. The recognition accuracy obtained for a set of six hand gestures and postures is promising with an accuracy...

In this study, we introduce a novel variant and application of the Collaborative Representation based Classification in spectral domain for recognition of the hand gestures using the raw surface Electromyography signals. The intuitive use of spectral features are explained via circulant matrices. The proposed Spectral Collaborative Representation b...

In this study we describe the development of a ride assistance application which can be implemented on the widespread smart phones and tablet. The ride assistance application has a signal processing and pattern classification module which yield almost 100% recognition accuracy for real-time signal pattern classification. We introduce a novel framew...

This paper presents an approach to a driver assistant system for a two-wheeled self-balancing mobility vehicles in particular for a Segway. The approach is aimed for the readily available mobile devices, which become a part of our daily life such as a smartphone or a tablet. If a mobile device is well-positioned on a mobility vehicle, its front and...

Personal Mobility Robots, such as the Seqway may be the remedy for the transportation related problems in the congested environment, especially for the last and first mile problems of the elderly people. However, the vehicle segmentation issues for the mobility robots, impede the use of these devices on the shared paths. The mobility reports can on...

The Sparse Representation based Classification (SRC) method has been utilized for various pattern recognition problems, especially for face recognition. Upon its success, the SRC method is extended by introducing Block Sparsity (BS) for the signal to be recovered and much better results are reported in the related literature. In this study, we test...

Compressed Sensing (CS) and Sparse Representation (SR) influenced the ways of signals are processed half a decade. The elegant solution to sparse signal recovery problem has found ground in several research fields such as machine learning and pattern recognition. The use of sparse representation and the solution of equations using ℓ1 minimization w...

Designing in Virtual Reality systems may bring significant advantages for the preliminary exploration of the design concept in 3D. In this chapter, our purpose is to provide a design platform in VR, integrating data gloves and the sensor jacket that consists of piezo-resistive sensor threads in a sensor network. Unlike the common gesture recognitio...

There is an increasing demand for motion capture and full body gesture recognition due to fast paced ubiquitous computing developments and their requirements for natural input modalities. Analysis and synthesis of human body movements are significant issues in bio-medical applications for rehabilitation and identification purposes as in post-stroke...

In this study we describe the development of a six Degree of Freedom (6 DOF) pose estimation model of a tracked object and D user interface using stereo vision and Infra-Red (IR) cameras in the Matlab/Simulink and C# environments. The raw coordinate values of the IR light sources located on the tracked object are detected, digitized and Bluetooth b...

The goal of this paper is to present the development of a tracking technology to interact with a virtual object. This paper presents the general procedures of building a simple, low cost tracking system by using Wiimote (a remote of Nintendo game console) and the Open source Computer Vision (OpenCV) software library as well as interfacing the track...

The use of the neuro-dynamic programming method for real-time control of a parallel hybrid electric vehicle is addressed in this study. The validated model of a research prototype parallel hybrid electric light commercial vehicle, FOHEV I, is used in the numerical parts of this paper. A diesel engine and an electric motor power the front and rear a...

Hibrid elektrikli araçlar, atmosferi kirletmeyen taşıtların geliştirilmesinde ara çözüm olarak karşımıza çıkmaktadır. Global ısınmaya neden olduğu ve insan sağlığına zarar veren kirletici gazlar açığa çıkartmaları nedeniyle içten yanmalı motorlar ile çalışan yol taşıtlarında emisyonlara sıkı sınırlamalar getirilmekte, yenilenebilir ve temiz enerji...

In this study, modelling and control of Hybrid Electric Vehicles (HEVs) and contribution towards the conversion of a light-duty road vehicle which is propelled by an internal combustion engine to an HEV in the context of a university-industry collaboration project are explained. HEV models of different complexity are developed for the purposes of a...

In this paper, equivalent fuel consumption method is used offline for computing a compromise solution to generate optimum power distribution between the hybrid components for a given driving cycle. Due to the high number of variables, system complexity and high number of states, impede using dynamic programming technique real-timely. The control ru...

Modeling and control of a hybrid electric vehicle is presented in this paper. A four wheel drive parallel hybrid electric vehicle is built by assembling an auxiliary electrical machine and battery group. Some preliminary instrumentation such as accelerator pedal, brake, clutch pedal position sensors and gear ratio estimation are realized to split t...

In this paper, we present a simulation model and a rule based controller design for a four wheel drive parallel hybrid electric vehicle. First, a light commercial vehicle, equipped with inherited internal combustion engine, is assembled with a battery pack, permanent magnet direct current electrical actuator and power converter. The electrical actu...

The suspension is a very important subsystem of a vehicle as it affects both passenger ride comfort and the handling properties of the vehicle. This paper concentrates on two important aspects of suspension system design. One is the fine tuning of a passive suspension system design through an optimisation study using a virtual suspension system mod...