Federal consistency and state expectations

Abstract

The requirement in the Coastal Zone Management Act of 1972 that federal projects be consistent with approved state coastal zone management programs is an important incentive for states to complete their programs. As a condition of program approval, states must first consult with the federal agencies concerned and provide opportunities for comment, with the hope of avoiding conflicts. The consistency requirement is also subject to various exceptions whose scope remains to be determined. One such exception of uncertain extent is the exclusion from the coastal zone of federal lands “the use of which is subject solely to the sole discretion ... of the Federal Government....”; Despite these uncertainties, however, the consistency provision represents a major change in federal policy, which has traditionally allowed federal agencies to operate largely without concern for state land or water use requirements.     

Tragedy of the San Francisco bay commons

Abstract

Although the early efforts to save San Francisco Bay in the 1960's provided the role model for protection of California's 1100 mile ocean coastline, neither Proposition 20 of 1972 nor the California Coastal Act of 1976 provided any benefits to San Francisco Bay. One result is that the Bay is locked into its urban, shoreline‐use dominated plan of 1969 while every other estuary and coastal wetland in California receives much stronger protection of its resources. Furthermore, due to the complexity of California's water laws, there is no instream flow protection for receiving waters such as San Francisco Bay. This is particularly critical considering that 70% of the Bay's freshwater inflow has been diverted. The Bay's present decline as the largest and most important estuary on the West Coast, as well as its possible death as an estuary, may be irreversible. The problem requires the immediate attention of engineering, scientific, economic and legal disciplines if San Francisco Bay is to be saved.     

Enhanced, multi criteria based site selection to measure mobile source toxic air pollutants

A multi-criteria-based site selection process that was developed for the Las Vegas near-road study is used to select the most appropriate near-road measurement sites in the Detroit area. The study measures particulate matter with aerodynamic diameters ?2.5 μm and mobile source air toxic compounds, and to document the rationale for selecting or rejecting specific sites. An application of this multi-criteria decision analysis may be the recent US Environmental Protection Agency rule requiring the siting of NO₂ monitors within 50 m of major roads as well as siting for the measurement of community-wide NO₂ concentrations.     

A reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

Reliable Shortest Path Problems in Stochastic Time-Dependent Networks

This study investigates the time-dependent reliable shortest path problem (TD-RSPP), which is commonly encountered in congested urban road networks. Two variants of TD-RSPP are considered in this study. The first variant is to determine the earliest arrival time and associated reliable shortest path for a given departure time, referred to as the “forward” TD-RSPP. The second problem is to determine the latest departure time and associated reliable shortest path for a given preferred arrival time, referred as the “backward” TD-RSPP. It is shown in this article that TD-RSPP is not reversible. The backward TD-RSPP cannot be solved by the algorithms designed for the forward problem using the reverse search from destination to origin. In this study, two efficient solution algorithms are proposed to solve the forward and backward TD-RSPP exactly and the optimality of proposed algorithms is rigorously proved. The proposed solution algorithms have potential applications in both advanced traveler information systems and stochastic dynamic traffic assignment models.     

Priorities in urban transport research

Research should be fundamental to transportation as a phenomenon, and yet central to the problems that need to be solved. This paper looks at the history of transportation research in the U.S. with a view toward understanding the bases of past research priorities, and deriving a basis for proposing future priorities. As a result, varieties of research are proposed. They include research which is progressive by criteria of the field during past decades, research which is critical or established as needed by rejection of those criteria, and research which arises as newly required by recent mandates to the field. As the most significant conclusion, it is proposed that research models be built — models which put the understanding of urban structure dynamics ahead of accuracy in forecasting.The authors wish to acknowledge the assistance of Ray Blessing, Department of Urban Studies and Planning, and Thomas McKim, Department of Civil Engineering, M.I.T. This paper has profited from criticism by Professor Daniel Brand. The original version was prepared with support from the National Science Foundation.     

Impacts of commuting efficiency on congestion and emissions: case of the Hamilton CMA, Canada

This study uses IMULATE (Integrated Model of Urban LAnd use, Transportation, energy and Emissions) to examine the impacts of commuting efficiency on congestion and automobile emissions—specifically, non-methane hydrocarbons, carbon monoxide and nitrogen oxides—in the Hamilton Census Metropolitan Area. Estimates of these externalities are compared for two commuting scenarios: a base scenario of estimated commuting flows for 1991 and an optimal scenario in which the mean commuting time for all workers is minimized. The findings indicate that significant reductions in congestion and automobile emissions are possible by advocating policies that encourage greater commuting efficiency in the locational choices of workers. The analysis of jobs–housing balance as one such means suggests that a considerable proportion of commuting cannot be explained by geographical imbalances in the distributions of jobs and housing, and that workers consider many factors besides commuting costs in their locational choices. It is concluded that policies promoting jobs–housing balance as the principal strategy for facilitating more efficient commuting may not meet the expectations of policy-makers.     

The Mixed Logit model: The state of practice

The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated choice data. It is timely to review progress in model estimation since the learning curve is steep and the unwary are likely to fall into a chasm if not careful. These chasms are very deep indeed given the complexity of the mixed logit model. Although the theory is relatively clear, estimation and data issues are far from clear. Indeed there is a great deal of potential mis-inference consequent on trying to extract increased behavioural realism from data that are often not able to comply with the demands of mixed logit models. Possibly for the first time we now have an estimation method that requires extremely high quality data if the analyst wishes to take advantage of the extended behavioural capabilities of such models. This paper focuses on the new opportunities offered by mixed logit models and some issues to be aware of to avoid misuse of such advanced discrete choice methods by the practitioner.