Portable and Scalable In-vehicle Laboratory Instrumentation for the Design of i-ADAS

According to the WHO (World Health Organization), world-wide deaths from injuries are projected to rise from 5.1 million in 1990 to 8.4 million in 2020, with traffic-related incidents as the major cause for this increase. Intelligent, Advanced Driving Assis­ tance Systems (i-ADAS) provide a number of solutions to these safety challenges. We developed a scalable in-vehicle mobile i-ADAS research platform for the purpose of traffic context analysis and behavioral prediction designed for understanding fun­ damental issues in intelligent vehicles. We outline our approach and describe the in-vehicle instrumentation

Assessment of Driver\u27s Attention to Traffic Signs through Analysis of Gaze and Driving Sequences

A driver’s behavior is one of the most significant factors in Advance Driver Assistance Systems. One area that has received little study is just how observant drivers are in seeing and recognizing traffic signs. In this contribution, we present a system considering the location where a driver is looking (points of gaze) as a factor to determine that whether the driver has seen a sign. Our system detects and classifies traffic signs inside the driver’s attentional visual field to identify whether the driver has seen the traffic signs or not. Based on the results obtained from this stage which provides quantitative information, our system is able to determine how observant of traffic signs that drivers are. We take advantage of the combination of Maximally Stable Extremal Regions algorithm and Color information in addition to a binary linear Support Vector Machine classifier and Histogram of Oriented Gradients as features detector for detection. In classification stage, we use a multi class Support Vector Machine for classifier also Histogram of Oriented Gradients for features. In addition to the detection and recognition of traffic signs, our system is capable of determining if the sign is inside the attentional visual field of the drivers. It means the driver has kept his gaze on traffic signs and sees the sign, while if the sign is not inside this area, the driver did not look at the sign and sign has been missed

Vehicular Instrumentation and Data Processing for the Study of Driver Intent

The primary goal of this thesis is to provide processed experimental data needed to determine whether driver intentionality and driving-related actions can be predicted from quantitative and qualitative analysis of driver behaviour. Towards this end, an instrumented experimental vehicle capable of recording several synchronized streams of data from the surroundings of the vehicle, the driver gaze with head pose and the vehicle state in a naturalistic driving environment was designed and developed. Several driving data sequences in both urban and rural environments were recorded with the instrumented vehicle. These sequences were automatically annotated for relevant artifacts such as lanes, vehicles and safely driveable areas within road lanes. A framework and associated algorithms required for cross-calibrating the gaze tracking system with the world coordinate system mounted on the outdoor stereo system was also designed and implemented, allowing the mapping of the driver gaze with the surrounding environment. This instrumentation is currently being used for the study of driver intent, geared towards the development of driver maneuver prediction models

Driving maneuver detection using knowledge distillation networks

In this thesis, we examine the current state of Advanced Driving Assistance Systems (ADAS) and their relation to maneuver prediction in the literature. We then attempt to solve the problem of variable inter-driver behavior by applying a novel distillation learning system using RoadLab data on tracked driver cephalo-ocular gaze behavior in tandem with high-resolution CANbus data. Current training-based methods in maneuver prediction are potentially subject to underfitting as drivers may exhibit different behavior when preparing to maneuver, but it has been shown that drivers can be grouped into at least two distinct behavior models. We use this information to personalize a deep neural network ensemble by distilling knowledge from a larger teacher network to a smaller student network. We change the networks\u27 input data to a subset of that data during training. Various groupings of driving sequence data are tested for prediction accuracy within this system, particularly against a validation driving sequence belonging to a specific driver group

AN INVESTIGATION INTO CURRENT PROCEDURES FOR ESTIMATING HEAVE POTENTIAL IN CLAYS

Published ThesisAn investigation into current procedures for estimating heave potential in clays Several low-cost housing developments in South Africa are suffering major structural failures due to heaving clays. Despite geotechnical investigations and various precautionary measures, this remains an on-going trend. The aim of this study was to review the current procedures used in South Africa to estimate heave potential in view of either improving the current procedures or suggesting alternatives. To this end, the research question was as follows: Are the current procedures used in South Africa to estimate heave potential acceptable? In this context, the most popular procedure used in South Africa, van der Merwe’s method, was broken into parts and studied. The research question was answered in the variance of laboratory results obtained from seven leading commercial laboratories which proved that reliable input parameters to van der Merwe’s empirical method are not obtainable. Typically the Atterberg limits and clay fraction results varied significantly producing heave potential classifications that do not accurately reflect the soil characteristics of the samples studied. On this basis, an investigation into methods of estimating heave potential, which are not considered in current South African codes of practice, were studied in order to provide a foundation for future research. A weighed system is proposed to judge the heave potential of soils using various prediction models as a foundation for future research

The structure and function of diagrams in environmental design : a computational inquiry

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1989.Vita.Includes bibliographical references (leaves 252-261).by Stephen McTee Ervin.Ph.D

A design and optimization assistant for induction motors and generators

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.Includes bibliographical references (p. [173]-181).by Ujjwal Sinha.Ph.D

Advances in Asphalt Pavement Technologies and Practices

Unlike other construction materials, road materials have developed minimally over the past 100 years. However, since the 1970s, the focus has been on more sustainable road construction materials such as recycled asphalt pavements. Recycling asphalt involves removing old asphalt and mixing it with new (fresh) aggregates, binders, and/or rejuvenators. Similarly, there are various efforts to use alternative modifiers and technical solutions such as crumb rubber, plastics, or various types of fibres. For the past two decades, researchers have been developing novel materials and technologies, such as self-healing materials, in order to improve road design, construction, and maintenance efficiency and reduce the financial and environmental burden of road construction. This Special Issue on “Advances in Asphalt Pavement Technologies and Practices” curates advanced/novel work on asphalt pavement design, construction, and maintenance. The Special Issue comprises 19 papers describing unique works that address the current challenges that the asphalt industry and road owners face

Integrated planning and budget allocation for highway maintenance, rehabilitation, and capital construction projects

Highway infrastructure is one of the critical components of the infrastructure network needed for the socio-economic development of a country. However, increased urbanization, limited funds, the need to consider sustainability continue to challenge the planning process for developing and maintaining highway infrastructure. Accordingly, decision-makers are tasked with making optimal decisions while achieving the strategic goals set by federal, state, district, and/or local highway agencies. Pivotal to making such resource allocation decisions, is the availability and accuracy of asset-related data and planning constraints which can guide data-driven decisions to be made by State Highway agencies (SHAs). Currently, several decision-makers still depend significantly on subjective engineering judgment to make decisions on funds allocation. Hence, there is a need for more formal and logical approaches to resource allocation as well as evaluation metrics for conducting alternatives analysis. This notwithstanding, the development of multiple incompatible legacy systems and the presence of several funding categories with stringent project eligibility requirements underpins a “siloed” approach to planning for highway infrastructure. There are often multiple functional groups working on the same asset network but with heterogeneous information systems and distinct decision-making practices. This “siloed” approach can create inefficiencies in projects selection and lead to inter-project conflicts in the highway projects proposed by these different functional groups. When left unaddressed, these spatial-temporal conflicts among projects can result in the misuse of limited taxpayer dollars and ultimately, a lower performance of the network. To address these issues with budget allocation and integrated highway planning, this study contributes to the body of knowledge in three primary ways. First, the study provides a synthesized analysis of budget allocation methods and provides a comprehensive approach to evaluating the performance of different methods employed for M&R decision-making. Secondly, this study formulates and accounts for the impact of multiple funding categories and project eligibility restrictions in budget allocation models. The inclusion of this pragmatic characteristic of M&R decision-making demonstrates the inefficiencies that can result from having increasing restrictions on multiple funding categories. Thirdly, a shared ontology is developed to enable a dynamic link between planning information and projects information. The resulting formalized representation (ontology) was validated by using multiple approaches including automated consistency checking, task-based evaluation, and data-driven evaluation. An implementation tool was also developed and applied to an actual case study problem. The tool was validated by using a Charrette test and feedback from subject-matter experts.Civil, Architectural, and Environmental Engineerin