This textbook and OER material cover tools and basic knowledge required to prepare transportation engineers and planners to contribute towards a carbon-neutral mobility future. In addition, we will explore the potential for vehicle electrification, automation, connectivity, and ridesharing to reduce the carbon impacts of auto mobility. The textbook modules are intended to inform and teach students how to design streets for modes that have almost no carbon emissions. The goal of the textbook is to train engineering students on existing tools and policy levers that can be used to incorporate emerging transportation technologies in a sustainable, equitable, and efficient manner. The course is designed for graduate transportation engineering, and city and regional planning students. The undergraduate seniors will be able to absorb the materials given they have already taken fundamental courses on transportation engineering and planning, including traffic engineering and highway design.
This book is a follow-up on Adjustment theory. It extends the theory to the case of time-varying parameters with an emphasis on their recursive determination. Least-squares estimation will be the leading principle used. A least-squares solution is said to be recursive when the method of computation enables sequential, rather than batch, processing of the measurement data. The recursive equations enable the updating of parameter estimates for new observations without the need to store all past observations. Methods of recursive least-squares estimation are therefore particularly useful for applications in which the time-varying parameters need to be instantly determined. Important examples of such applications can be found in the fields of real-time kinematic positioning, navigation and guidance, or multivariate time series analysis. The goal of this book is therefore to convey the necessary knowledge to be able to process sequentially collected measurements for the purpose of estimating time-varying parameters.
The aim of computing a geodetic network is to determine the geometry of the configuration of a set of points from spatial observations (e.g. GPS baselines and/or terrestrial measurements). The configuration of points usually consists of newly established points, of which the coordinates still need to be determined, and already existing points, the so-called control points, of which the coordinates are known.
