Through an examination of transport planning in Australia, this book challenges conventional wisdom by showing, through original research, how 'car dependence' is as much an institutional as a ...technical phenomenon. The authors' case studies in three metropolitan cities show how transport policy has become institutionally fixated on a path dominated by private, road-based transport and how policy systems become encrusted around investment to accommodate private cars, erecting an impenetrable barrier against more sustainable mobility and accessibility solutions. The findings are applicable to most cities of the developed world, and to fields beyond transport planning.
Car Country Wells, Christopher W; Cronon, William
05/2013
eBook
For most people in the United States, going almost anywhere begins with reaching for the car keys. This is true, Christopher Wells argues, because the United States is Car Country a nation dominated ...by landscapes that are difficult, inconvenient, and often unsafe to navigate by those who are not sitting behind the wheel of a car.
The prevalence of car-dependent landscapes seems perfectly natural to us today, but it is, in fact, a relatively new historical development. In Car Country, Wells rejects the idea that the nation's automotive status quo can be explained as a simple byproduct of an ardent love affair with the automobile. Instead, he takes readers on a tour of the evolving American landscape, charting the ways that transportation policies and land-use practices have combined to reshape nearly every element of the built environment around the easy movement of automobiles. Wells untangles the complicated relationships between automobiles and the environment, allowing readers to see the everyday world in a completely new way. The result is a history that is essential for understanding American transportation and land-use issues today.
Watch the book trailer: http://www.youtube.com/watch?v=48LTKOxxrXQ
Before the advent of the automobile, users of city streets were diverse and included children at play and pedestrians at large. By 1930, most streets were primarily a motor thoroughfares where ...children did not belong and where pedestrians were condemned as "jaywalkers." In Fighting Traffic, Peter Norton argues that to accommodate automobiles, the American city required not only a physical change but also a social one: before the city could be reconstructed for the sake of motorists, its streets had to be socially reconstructed as places where motorists belonged. It was not an evolution, he writes, but a bloody and sometimes violent revolution. Norton describes how street users struggled to define and redefine what streets were for. He examines developments in the crucial transitional years from the 1910s to the 1930s, uncovering a broad anti-automobile campaign that reviled motorists as "road hogs" or "speed demons" and cars as "juggernauts" or "death cars." He considers the perspectives of all users--pedestrians, police (who had to become "traffic cops"), street railways, downtown businesses, traffic engineers (who often saw cars as the problem, not the solution), and automobile promoters. He finds that pedestrians and parents campaigned in moral terms, fighting for "justice." Cities and downtown businesses tried to regulate traffic in the name of "efficiency." Automotive interest groups, meanwhile, legitimized their claim to the streets by invoking "freedom"--a rhetorical stance of particular power in the United States. Fighting Traffic offers a new look at both the origins of the automotive city in America and how social groups shape technological change.Peter D. Norton is Assistant Professor in the Department of Science, Technology, and Society at the University of Virginia.
Faced with intolerable congestion and noxious pollution, cities around the world are rethinking their reliance on automobiles. In the United States a loosely organized livability movement seeks to ...reduce car use by reconfiguring urban space into denser, transitoriented, walkable forms, a development pattern also associated with smart growth and new urbanism. Through a detailed case study of San Francisco, Jason Henderson examines how this is not just a struggle over what type of transportation is best for the city, but a series of ideologically charged political fights over issues of street space, public policy, and social justice. Historically San Francisco has hosted many activist demonstrations over its streets, from the freeway revolts of the 1960s to the first Critical Mass bicycle rides decades later. Today the city’s planning and advocacy establishment is changing zoning laws to limit the number of parking spaces, encouraging new carfree housing near transit stations, and applying “transit first” policies, such as restricted bus lanes. Yet Henderson warns that the city’s accomplishments should not be romanticized. Despite significant gains by livability advocates, automobiles continue to dominate the streets, and the city’s financially strained bus system is slow and often unreliable. Both optimistic and cautionary, Henderson argues that ideology must be understood as part of the struggle for sustainable cities and that three competing points of view—progressive, neoliberal, and conservative—have come to dominate the contemporary discourse about urban mobility. Consistent with its iconic role as an incubator of environmental, labor, civil rights, and peace movements, San Francisco offers a compelling example of how the debate over sustainable urban transportation may unfold both in the United States and globally.
The transition towards 'smarter' autonomous transport systems calls for a rethink in how transport is governed/who governs it, to ensure a step-change to a more sustainable future. This book ...critically reflects on these governance challenges analysing the role of the state; the new actors and discourses; and the implications for state capacity.
Transportation network companies (TNCs), such as Uber and Lyft, have been hypothesized to both complement and compete with public transit. Existing research on the topic is limited by a lack of ...detailed data on the timing and location of TNC trips. This study overcomes that limitation by using data scraped from the Application Programming Interfaces of two TNCs, combined with Automated Passenger Count data on transit use and other supporting data. Using a panel data model of the change in bus ridership in San Francisco between 2010 and 2015, and confirming the result with a separate time-series model, we find that TNCs are responsible for a net ridership decline of about 10%, offsetting net gains from other factors such as service increases and population growth. We do not find a statistically significant effect on light rail ridership. Cities and transit agencies should recognize the transit-competitive nature of TNCs as they plan, regulate and operate their transportation systems.
Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount ...of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper first reviews the history and characteristics of big data and intelligent transportation systems. The framework of conducting big data analytics in ITS is discussed next, where the data source and collection methods, data analytics methods and platforms, and big data analytics application categories are summarized. Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced. Finally, this paper discusses some open challenges of using big data analytics in ITS.
•We formulate the one-block train formation problem as a binary linear program.•The model incorporates the unitary rule and intree requirement from Chinese practice.•Provably optimal solutions are ...obtained for medium-scale real-world instances.•A novel tree-based decomposition algorithm is developed for large-scale instances.
We investigate the one-block train formation problem (TFP) in the railway freight transportation industry. The input to this problem is a railway network and a set of demands for transportation. Each demand is a request for shipping a number of rail cars from one station to another. The one-block TFP now addresses two subproblems in the tactical level: Which pairs of stations are directly connected via a block (or: train service); and which demands are transported by each block. The aim is to service all demands against minimal costs. Moving beyond current researches on service network design, the unitary rule and the intree rule are taken into account in this study based on the Chinese railway background. We develop a linear binary programming formulation to minimize the total sum of train accumulation costs and car classification costs, subject to limitations on the classification capacity and the number of sort tracks at each station. Furthermore, we propose a novel solution methodology that applies a tree-based decomposition algorithm. Here, we first decompose the whole network into a series of rooted trees for each destination separately. Then, we divide the trees further into sufficiently small subtrees, whose size is regulated by a node size parameter. Finally, we construct a restricted linear binary model for each subtree and solve these models sequentially to find their optimal solutions. The algorithm ensures that an overall feasible solution is obtained if one exists. Our computational results on a realistic network from the Chinese railway system with 83 stations, 158 links and 5700 randomly generated demands show that the proposed algorithm can derive high-quality solutions within a few hours of computation time. These solutions are on average 48.05% better than those obtained after solving the linear binary program with a commercial solver for 1 day.
We investigate the impact of the commencement of high-speed rail (HSR) services on airlines’ domestic available seats on affected routes in China, Japan, and South Korea. The study is based on a ...dataset covering the 1994–2012 period. We use the propensity score matching method to pair HSR affected routes with routes without HSR services. The difference-in-difference approach is used to estimate the impact of HSR entry. We find that HSR entries may, on average, lead to a more significant drop in airlines’ seat capacity in China than in Japan and Korea given similar HSR service speed. In China, HSR services with a maximum speed about 200km/h can produce strong negative impacts on medium-haul air routes but induce more air seat capacity on long-haul routes. HSR services with a maximum speed of 300km/h have little extra impact on medium-haul routes but a strong negative impact on long-haul routes. Finally, although HSR has a strong negative impact in Japan’s short-haul and medium-haul air markets, little impact is observed in its long-haul markets.
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