Weather has broad and significant effects on the roadway environment. Snow, rain, fog, ice, freezing rain, and other weather conditions can impair the ability of drivers to operate their vehicles safely, significantly reduce roadway capacity, and dramatically increase travel times. Multiple roadway activities, from roadway maintenance and construction to shipping, transit, and police operations, are directly affected by inclement weather. Some road weather information is available to users currently, however a disconnect remains between current research and operations, and additional research could yield important safety and economic improvements for roadway users. Meteorology, roadway technology, and vehicle systems have evolved to the point where users could be provided with better road weather information through modern information technologies. The combination of these technologies has the potential to significantly increase the efficiency of roadway operations, road capacity, and road safety. Where the Weather Meets the Road provides a roadmap for moving these concepts to reality.

How do people drive on roads and behave in traffic? How can we change driving habits and encourage more environmentally responsible modes of transportation? These are the two main questions to which the volume tries to answer. It tackles the problems of driving, traffic, transportation, and mobility fully, rather than from a single perspective, which has tended to be the norm so far. The authors describe how we can weave together qualitative and quantitative approaches, how useful interviews are for understanding driving comfort, the power ethnography has to help us understand the lifestyle of drivers, which technological tools and approaches are the most useful for analyzing styles of driving, how to explore vehicles and traffic by analyzing language, how traffic might improve or worsen our way of life from a psychological point of view, and how we can encourage environmentally friendly behavior and practices on both the road and in life in general. / Kako se prevažamo po cestah in vedemo v prometu? Kako lahko spreminjamo vozniške navade in spodbujamo bolj okoljsko odgovorne načine prevoza? To sta dve izhodiščni vprašanji, na kateri odgovarja zbornik, v katerem se avtorice in avtorji problematike vožnje, prometa, transporta in mobilnosti lotevajo celotno, namesto z enega zornega kota, kot je bilo to doslej bolj pogosto. Avtorice in avtorji predstavijo, kako lahko pri raziskovanju prepletemo kvalitativne in kvantitativne pristope, kako uporabni so intervjuji pri razumevanju udobja med vožnjo, kakšno moč ima etnografija pri spoznavanju načina življenja voznikov, kateri tehnološki pripomočki in pristopi so najbolj uporabni za analizo načinov vožnje z avtomobilom, kako lahko raziskujemo vozila in promet z analizo jezika, kako promet s psihološkega vidika izboljša in poslabša naš način življenja ter kako lahko spodbujamo okolju prijazne navade in prakse, in to tako na cesti kot tudi nasploh v življenju.

This book contains selected papers resulting from the 2020 International Conference on Road and Traffic Engineering (CRTE 2020) covering Road Engineering and Traffic Engineering, aiming to provide an academic and technical communication platform for scholars and engineers engaged in scientific research and engineering practice in the field of Road Engineering and Materials, Traffic Engineering and Management and Transportation Engineering. By sharing the research status of scientific research achievements and cutting-edge technologies, it helps scholars and engineers all over the world to comprehend the academic development trends and broaden research ideas. So as to strengthen international academic research, academic topics exchange and discussion, and promote the industrialization cooperation of academic achievements.

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.