Safety

Travel and transportation play a central role in the lives of most of the world’s population. Transportation provides both a means of trade in moving goods and a way of moving people to engage in employment, education, social, and other activities. If we had observed the same geographical area over a period of past decades, we would likely have seen that the size and structure of employment, production, and residential areas had changed over time, and these changes had in turn changed the requirements and pressures on the transportation system. At the same time, these changes will have made environmental, social, and economic impacts, some positive and some negative, with some winners and some losers. It is natural then to ask whether we can hold a mirror to the past, and use it to see into the future; at least then we may be able to react in a better way to the inevitable changes the mirror shows us, and thereby as a society expend resources more efficiently (in the sense of less negative and more positive impacts). It is only one more step to then realise that the mirror analogy is limited, that unless we believe the future is pre-determined we may influence it by our actions, both as individuals and as organisations. Understanding such influences and their likely consequences then provides a way of not only ‘managing’ a transportation system more effectively, but also positively engineering it to improve the lives of the people using it. The current book fits into this wide area of ‘transportation planning’, particularly the field of traffic flow modelling, and control that directly can support the definition of traffic management policies. Space and time are two intrinsically important aspects of understanding travellers’ needs and what transportation systems can supply. Let us first consider space. The type and density of activities are not distributed evenly across a city or region, and there are fixed geographical features (rivers, mountains, valleys, etc.) that influence the feasibility of different transportation options across an area. Dense, ‘vertical’ residential areas provide very different challenges to more sparsely distributed ones. There are also complex interactions that play out in the transport infrastructure; a congested road or overcrowded bus may be partially the result of travellers avoiding overloaded facilities, meaning that a good solution will not be understood without considering system-level interactions between the various travel needs of people/ organisations and the services and facilities which are provided. Over the last 50 years, the transportation community has developed rather sophisticated ways of representing these kinds of spatial interactions, typically by representing the infrastructure as a network (mathematical ‘graph’), and by considering various levels of sophistication in representing the behavioural responses of travellers (e.g., from the perfectly informed traveller to random utility approaches). At the same time, however, it should be mentioned that whilst the individual fields have developed to a high level, it is relatively rare to find a consistent integration of demand modelling and network modelling. There are rather well-developed (if not always consistent) methods, then, for considering ‘space’; so what about ‘time’? Whilst travel time, as a disincentive in making travel choices, is a central aspect of transportation planning, by the word ‘time’ we are instead referring here to changes that occur over time (‘dynamics’). As there is considerable potential for confusion, let us very early on make a clear Preface xxi distinction: changes on a ‘within-day’ time-scale are the kind of changes that we would expect to see as we made a journey on a particular day, or if we compared our travel experience with someone travelling by the same route/service but at a different time on that day (there are many other ways to characterise this kind of time, but these examples suffice for now). On the other hand, changes on a ‘between-day’ time-scale concern, for example, the way in which we might adapt our travel choice next time we make a journey, based on our travel experiences today. Whilst researchers have been aware of both ‘within-day’ and ‘between-day’ effects for several decades, it is only relatively recently that a concerted effort has been made to develop tools and methods to explicitly model them. On the within-day scale, this has been achieved by introducing and adapting methods from traffic flow theory for use in network models. On the between-day scale, it has involved bringing in new techniques from both applied mathematics (for deterministic dynamical systems) and probability theory (for stochastic processes). The subject area of the book will be Traffic Engineering and in particular Traffic Analysis and Control. The methods for traffic analysis, usually derived from Traffic Flow Theory, will be discussed. Under steady-state conditions, the most used model to describe vehicles flowing along a street (railway, airway, . . . ) is the so-called fundamental diagram (FD) whilst when steady-state conditions do not hold, within-day dynamics should explicitly be considered through three kinds. Regarding the methods for traffic flow control, these are based on the description and prediction of traffic flows without any modelling of routing choice behaviour. They include the fixed timing strategies, as well as the variable timing strategies. The latter may be applied offline to support transportation planning or in simple cases when there is no need for adaptive control or online to support real-time traffic management. Online applications require sensors for flow monitoring and within-day dynamic models for flow prediction, or simple data-driven methods. All these topics are within the scope of this book. The book is conceived as a research monograph and at the same time intends to be both a textbook and a reference work for transportation academic researchers and upper-level undergraduate and graduate students as well as professionals and consultants. It will be the first to present the theory concerning the fixed and adaptive urban signal setting design at a single junction and network level. Furthermore, the most recent enhancements about the Intelligent Transportation Systems and the impact of connected and cooperative vehicles on traffic analysis and control will be considered. Finally, the main strategies aiming at the impacts (i.e., safety, consumption, emissions) optimisation will be also included.