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The timely transportation of goods to customers is an essential component of economic activities. However, heavy-duty diesel trucks used for goods delivery significantly contribute to greenhouse gas (GHG) emissions within many large metropolitan areas, including Los Angeles, New York, and San Francisco. To reduce GHG emissions by facilitating freight electrification, this paper proposes Joint Routing and Charging (JRC) scheduling for electric trucks. The objective of the associated optimization problem is to minimize the cost of transportation, charging, and tardiness. A large number of possible combinations of road segments as well as a large number of combinations of charging decisions and charging durations leads to a combinatorial explosion in the possible decisions electric trucks can make. The resulting mixed-integer linear programming (MILP) problem is thus extremely challenging because of the combinatorial complexity even in the deterministic case. Therefore, a Surrogate Level-Based Lagrangian Relaxation (SLBLR) method is employed to decompose the overall problem into significantly less complex truck subproblems. In the coordination aspect, each truck subproblem is solved independently of other subproblems based on the values of Lagrangian multipliers. In addition to serving as a means of guiding and coordinating trucks, multipliers can also serve as a basis for transparent and explanatory decision-making by trucks. Testing results demonstrate that even small instances cannot be solved using the off-the-shelf solver CPLEX after several days of solving. The SLBLR method, on the other hand, can obtain near-optimal solutions within a few minutes for small cases, and within 30 min for large ones. Furthermore, it has been demonstrated that as battery capacity increases, the total cost decreases significantly; moreover, as the charging power increases, the number of trucks required decreases as well. • Present a formulation of a joint heavy-duty vehicle fleet routing & charging problem. • Use surrogate level-based Lagrangian relaxation approach to solve the problem. • The proposed method obtains near-optimal solutions for realistic testing cases. [ABSTRACT FROM AUTHOR]

This paper explores the topographical and socio-cultural developments during the Golden Age in New York, Los Angeles and San Francisco, three Beat Generation epicenters, which determined the deconstruction of traditional norms. Modifications at both city and society levels were represented by the emergence of countercultures, such as the Beat. The visibility received by urban problems, due to the increase in social demonstrations and activism, fostered the formation of a unified front that demanded equality and encouraged social and political movements, such as the Civil Rights and the Second Wave Feminism. The socio-political challenges which the American society was confronted with from the 1950s to the 1970s in these three cities, also reveal a few problems regarding the status of the Beats as well as of minorities in metropolises. [ABSTRACT FROM AUTHOR]

Critics often mourn a loss of publicness in cities due to the increased presence of antiterror security zones and related behavioral and access controls, although recent work suggests that security landscapes have shifted from the hard, intense, militarized architecture of the late 1990s-early 2000s to a softer, less obtrusive approach more commonly seen today. Nonetheless, these studies are mostly anecdotal in nature: few studies attempt to back these claims with empirical evidence and even fewer connect this physical security imposition with the policies and plans governing its implementation and operation. In this paper I describe results of site visits to Civic Centers and Financial Districts in New York City, Los Angeles, and San Francisco. In each neighborhood I catalog security landscapes using a simple tool to assess the intensity, duration, and location of individual security zones. I find that the security landscape covers between 3.4% and 35.7% of publicly accessible space in the districts studied, and that this landscape is most prevalent and intense in New York City. I also find that security zones governed by multistakeholder networks are more intense and militarized than zones managed by a single entity. By understanding how the policies impact physical security, albeit in a relatively small sample of cities and districts, we can better predict what the future of urban security measures might hold. This paper provides empirical grounding to more common theoretical speculations regarding the future of the urban security landscape in the global West. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a detailed empirical description of airport connectivities in four major multiple airport cities (London, New York, Los Angeles, and San Francisco). Our analysis draws on data derived from a previously largely untapped information source, i.e. the so-called ‘Marketing Information Data Transfer’ (MIDT). This dataset contains information on actually flown transnational routes, which allows for a thorough assessment of the chief connectivity characteristics of specific airports. Combined with information derived from a number of other sources, our results point to functional divisions among airports, both in terms of their geographical scale (e.g. national, regional, and international airports) and their specific role in the airline network (e.g. origin/destination versus hub airports). The implications of the results are discussed, and some avenues for future research are considered. [Copyright &y& Elsevier]

Transportation impact analyses begin with a trip generation estimation process—estimating motorized vehicle and person trip counts coming and going from the proposed site. Data commonly used is often insensitive to urban contexts (such as employment densities) and socioeconomic conditions. This insensitivity results in sometimes exaggerated estimates, an increase associated transportation impact fees, and a need for additional mitigation of impacts which may further hinder land development. In this study, we collected and analyzed person and motorized vehicle count data from 26 affordable housing developments in Los Angeles and San Francisco. Counts were regressed upon site and built environment characteristics known to influence site-level travel behavior (e.g., parking supply, employment density), and regressions were validated using externally collected data. The findings indicate the average square footage of dwelling units, parking ratios, and nearby retail employment densities to be important predictors. The findings also indicate that increasing the parking supply from one space to two for each dwelling unit will result in a significant predicted increase of approximately 0.26 and 0.18 motorized vehicle trips per dwelling unit for AM and PM peak periods, respectively. These findings reiterate the need for trip generation methodologies sensitive to the built environment and sociodemographics. • This paper describes the transportation impacts at 26 subsidized housing developments in San Francisco and Los Angeles. • Four models were developed estimating motorized vehicle and person trip counts for the AM and PM peak hour periods. • Motorized vehicle models were validated using externally collected data from Los Angeles. • Total dwelling units and on-site parking ratios were significant and positive predictors of vehicle trip generation. [ABSTRACT FROM AUTHOR]