Abstract
A brief historical overview of empirical and theoretical investigations of vehicular traffic in traffic and transportation networks is presented. This critical overview is based on a consideration of works made by several generations of traffic researchers. It includes more than 1200 references to most well-known empirical results and theoretical approaches. The main focus of this overview is to explain the reason for a paradigm shift that happened in transportation science during last 20 years through the understanding of the empirical nucleation nature of traffic breakdown at highway bottlenecks. We consider also the basic terms and definitions of traffic characteristics of traffic and transportation networks that are used in the book, the objectives of this book as well as the book structure.
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Notes
- 1.
In other words, we do not consider travel decision behavior, which determines traffic demand. Models of travel decision behavior as well as traffic and transportation demand can be found, for example, in the book by Ben-Akiva and Lerman [74] as well as in reviews by Axhausen and Gärling [29] and by Goulias [338]; see also papers [33, 169] and references there. A challenge for transportation demand research following from results of this book is formulated in item 10 of Sect. 15.5
- 2.
It is often called also as Globe Position System (GPS).
- 3.
Definitions of traffic variables, traffic parameters, and traffic patterns can be found in Sec. 2.1 of the book [572].
- 4.
In empirical observations, to determine this minimum average speed in free flow, traffic variables (e.g., the average vehicle speed and flow rate), which are measured during a long enough time interval in a neighborhood of a bottleneck, are usually studied in the flow–density (Fig. 1.1a) or speed–flow planes (e.g., [662, 804]).
- 5.
Based on the differentiation of the synchronized flow phase and the wide moving jam phase in the three-phase theory, ASDA and FOTO methods for the reconstruction of spatiotemporal features of traffic congestion have been introduced and developed [589, 591, 627–634, 636, 921, 922, 983–985]. Based on ASDA and FOTO models, Rehborn, Aleksić, Haug, Palmer, and other colleagues of the Daimler Company have developed software-tools that are up to now used in on-line installations in traffic control centers. A detailed consideration of ASDA and FOTO models is out of scope of this book. For results of ASDA and FOTO applications, see a review by Rehborn and Klenov [983] as well as the book [556].
- 6.
Explanations of the terms “synchronized flow” and “wide moving jam” can be found in Sec. 2.4.4 of the book [572].
- 7.
- 8.
The exceptions are a brief consideration of the empirical and theoretical characteristic parameters of moving jam propagation, empirical features of phase transitions in congested traffic as well as features of moving synchronized flow patterns (MSP) and moving queues at traffic signal in city traffic. The consideration of these empirical and theoretical features of congested traffic are required for a more clear discussion of the subjects “classical traffic flow theories versus the three-phase theory” made in Chap. 8 as well as “time-delayed traffic breakdown at traffic signal in city traffic” considered in Chap. 9 A detailed consideration of empirical features and a theory of spatiotemporal congested traffic patterns occurring at highway bottlenecks can be found in the book [556] as well as in [570].
- 9.
In many cases, the total network inflow rate Q(t) changes in a traffic or transportation network over time very slowly in comparison with any characteristic times of dynamic traffic effects at network bottlenecks under free flow conditions in the network. For this reason, as it is usually assumed in classical theories of traffic and transportation networks, at any given Q free flow distribution in the network can be considered as a steady state (steady-state analysis of traffic and transportation networks) [1028]. This means that it is assumed that Q = Q out, where Q out(t) is the total network outflow rate.
- 10.
The author was fortunate to work in 1994–1995 for the traffic engineering consulting firm Heusch/Boesefeldt GmbH in Aachen (Germany), where he met many good traffic engineers. Here he had his first opportunity to begin a study of real field traffic data measured on many highways in Germany. The author thanks Heinz Heusch, Jochen Boesefeldt, Hubert Rehborn, Heribert Kirschfink, Ulrich Uerlings, and Thomas Scheiderer, for their help in the preparation of empirical data required for the data analysis, critical discussion of earlier traffic flow theories, and their fruitful cooperation. In particular, the author thanks Hubert Rehborn for his help in the discussion of the analysis of real field traffic data presented in [539–553, 555, 622–626].
- 11.
A detailed consideration of the S → J instability is out of the scope of the book.
- 12.
Clearly, already due to real flow fluctuations “pure” steady states of traffic flow do not exist. Therefore, steady states of synchronized flow cannot be observed in real field data: The fluctuations destroy 2D-steady states of synchronized flow transforming them into dynamic 2D-states of synchronized flow. However, in the book [556] (see, e.g., Secs. 4.3.4 and 6.3.3 of [556]) we have explained that real dynamic 2D-states of synchronized flow, at least when they are slightly non-homogeneous in space and time, should exhibit almost the same features as those postulated in the three-phase theory for hypothetical 2D-steady states of synchronized flow [539–552, 555, 556]. To make a proof of the most of the features of 2D-states of synchronized flow postulated in the three-phase theory [539–552, 555, 556], microscopic (single-vehicle) data should be measured. Only recently some microscopic (single-vehicle) measurements could be made (see, e.g., [492, 526, 1166]).
In particular, microscopic experimental results of Jiang et al. [492, 497, 526] are in agreement with the hypothesis of the three-phase theory about 2D-states of synchronized flow. Based on a statistical analysis of a microscopic real field traffic data measured in Singapore with a video camera, Yang et al. [1166] have found a region of nearly zero acceleration in the data that proves the empirical existence of the synchronization space gap and the speed adaptation effect within 2D-states of synchronized flow as stated in the three-phase theory [556, 572] (see explanations of the term synchronization space gap in Sect. 5.9). Recall that the focus of this book is an analysis of the breakdown in traffic networks. Therefore, a detailed consideration of the hypothesis about the 2D-states of synchronized flow (see Chap. 6 of the book [556]) is out the scope of this book. Respectively, in Sect. 5.9.1 we consider only some of the features of the 2D-states of synchronized flow [539–552, 555, 556] needed for the understanding of the physical mechanism of traffic breakdown at network bottlenecks.
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Kerner, B.S. (2017). Introduction—The Reason for Paradigm Shift in Transportation Science. In: Breakdown in Traffic Networks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54473-0_1
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