The interaction of tidal advection, diffusion and mussel filtration in a tidal channel

Time series measurements of flow and pigment concentrations (Chl) in the Menai Strait have revealed that the strong residual flow in a tidal channel ( 500 m³ s^− 1) transports phytoplankton from the open sea into the channel where much of it is consumed by suspension feeders, mainly in commercial beds of Mytilus edulis. The progressive depletion of phytoplankton along the channel results in a strong horizontal gradient of plankton and hence Chl. Tidal displacement of this gradient causes large (± 50% of mean) oscillations of Chl in the vicinity of the mussel beds. Vertical mixing by the strong tidal flows is sufficiently vigorous for most of the tidal cycle to ensure that downward diffusion can resupply the near-bed layer although there are indications of some transient depletion around slack water.This paradigm of the interaction of advection, diffusion and filtration determining the distribution of plankton and its supply to mussels has been encapsulated in a series of simple models forced only by boundary values. In the first, a 1-D model of tidal flow in the channel reproduces the principal features of the observed currents including the unusually large spatial change in phase of the currents and the variation of the residual transport with tidal range. The flow field from this physical model is used to drive a second model based on the advection diffusion equation for Chl with a source at the Irish Sea boundary and a sink over the mussel bed. This model illustrates the formation of a strong Chl gradient along the channel and simulates the amplitude and phase of the M₂ oscillations of Chl and the development of the M₄ variation apparent in the observations. This second model has been extended to 2-D over the mussel beds to allow investigation of the effects of water column mixing. The model indicates that only for a short period ( 30 min), close to slack water, is mixing sufficiently reduced to permit the development of a depletion boundary layer and then only within  1 m from the bottom, a result which is consistent with the observations.     

Analysis of taxi demand and supply in New York City: implications of recent taxi regulations

This paper investigates temporal and weather-related variation in taxi trips in New York City. A taxi trip data-set with 147 million records covering 10 months of activity is used. It is shown that there are substantial variations in ridership, taxi supply, trip distance, and pickup frequency for different time periods and weather conditions. These variations, in turn, cause variations in driver revenues which is one of the main measures of taxi supply–demand equilibrium. The findings are then used to discuss the anticipated impacts of two recently enacted taxi regulation changes: the first fare increase since 2006 and the E-Hail pilot program which allows taxi hailing with smart phone applications. The fare increase is estimated to cause varying levels of revenue increase for different time periods. E-Hail apps are not expected to offer considerable improvements at all times, but rather when both adequate taxi supply and demand occur simultaneously.     

A methodology to estimate travel time using dynamic traffic assignment (DTA) under incident conditions

This paper presents results from a research case study that examined the distribution of travel time of origin–destination (OD) pairs on a transportation network under incident conditions. Using a transportation simulation dynamic traffic assignment (DTA) model, incident on a transportation network is executed under normal conditions, incident conditions without traveler information availability, and incident conditions assuming that users had perfect knowledge of the incident conditions and could select paths to avoid the incident location. The results suggest that incidents have a different impact on different OD pairs. The results confirm that an effective traveler information system has the potential to ease the impacts of incident conditions network wide. Yet it is also important to note that the use of information may detriment some OD pairs while benefiting other OD pairs. The methodology demonstrated in this paper provides insights into the usefulness of embedding a fully calibrated DTA model into the analysis tools of a traffic management and information center.     

Nature and/or nurture? Analyzing the determinants of transit ridership across US urbanized areas

Public subsidy of transit services has increased dramatically in recent years, with little effect on overall ridership. Quite obviously, a clear understanding of the factors influencing transit ridership is central to decisions on investments in and the pricing and deployment of transit services. Yet the literature about the causes of transit use is quite spotty; most previous aggregate analyses of transit ridership have examined just one or a few systems, have not included many of the external, control variables thought to influence transit use, and have not addressed the simultaneous relationship between transit service supply and consumption. This study addresses each of these shortcomings by (1) conducting a cross-sectional analysis of transit use in 265 US urbanized areas, (2) testing dozens of variables measuring regional geography, metropolitan economy, population characteristics, auto/highway system characteristics, and transit system characteristics, and (3) constructing two-stage simultaneous equation regression models to account for simultaneity between transit service supply and consumption. We find that most of the variation in transit ridership among urbanized areas – in both absolute and relative terms – can be explained by factors outside of the control of public transit systems: (1) regional geography (specifically, area of urbanization, population, population density, and regional location in the US), (2) metropolitan economy (specifically, personal/household income), (3) population characteristics (specifically, the percent college students, recent immigrants, and Democratic voters in the population), and (4) auto/highway system characteristics (specifically, the percent carless households and non-transit/non-SOV trips, including commuting via carpools, walking, biking, etc.). While these external factors clearly go a long way toward determining the overall level of transit use in an urbanized area, we find that transit policies do make a significant difference. The observed range in both fares and service frequency in our sample could account for at least a doubling (or halving) of transit use in a given urbanized area. Controlling for the fact that public transit use is strongly correlated with urbanized area size, about 26% of the observed variance in per capita transit patronage across US urbanized areas is explained in the models presented here by service frequency and fare levels. The observed influence of these two factors is consistent with both the literature and intuition: frequent service draws passengers, and high fares drive them away.     

The effects of lighting on driver's injury severity at highway‐rail grade crossings

This study estimates the safety effect of illumination on accidents at highway‐rail grade crossings in the United States, using data from exhaustive data from Federal Railroad Administration database covering the period 2002–2011. Using mixed logit modeling approach, the study explores the determinants of driver injury severity at unlighted highway‐rail grade crossings compared with lighted highway‐rail grade crossings in the United States. Several key issues are explored including availability of relevant highway‐rail grade crossing accident inventory data; relevant data element structures; specification and estimation of models to estimate driver's injury severity with lighting and without lighting; and techniques to interpret model parameters. Overall, highway‐rail grade crossing lighting improves safety by reducing the probability of high‐level injury severity through improvements in driver's visibility compared with unlighted intersections. Copyright © 2015 John Wiley & Sons, Ltd.