An idealized model of interaction between fronds of the large seaweed Durvillaea antarctica

The effect of interactions between individual fronds in a bed of the large intertidal seaweed Durvillaea antarctica, when forced by breaking waves, is studied using a computational model. The model simulates the response of a seaweed bed using a sequence of connected oscillators which are excited by a propagating forcing function representing a breaking ocean wave. Two new facets of the interplay between seaweeds and hydrodynamics are considered: (i) wave forcing due to breaking waves is often not sinusoidal in the rocky intertidal zone and (ii) a frond interaction term is included. The addition of frond interaction reduces the maximum loading on individuals within the bed by around 30% using estimated biomechanical parameters. The rate of change of the loading on the holdfast (equivalent to the “jerk”) is affected in a similar or greater fashion.     

Dynamic system-optimal traffic assignment using a state space model

We propose a new mathematical formulation for the problem of optimal traffic assignment in dynamic networks with multiple origins and destinations. This problem is motivated by route guidance issues that arise in an Intelligent Vehicle-Highway Systems (IVHS) environment. We assume that the network is subject to known time-varying demands for travel between its origins and destinations during a given time horizon. The objective is to assign the vehicles to links over time so as to minimize the total travel time experienced by all the vehicles using the network. We model the traffic network over the time horizon as a discrete-time dynamical system. The system state at each time instant is defined in a way that, without loss of optimality, avoids complete microscopic detail by grouping vehicles into platoons irrespective of origin node and time of entry to network. Moreover, the formulation contains no explicit path enumeration. The state transition function can model link travel times by either impedance functions, link outflow functions, or by a combination of both. Two versions (with different boundary conditions) of the problem of optimal traffic assignment are studied in the context of this model. These optimization problems are optimal control problems for nonlinear discrete-time dynamical systems, and thus they are amenable to algorithmic solutions based on dynamic programming. The computational challenges associated with the exact solution of these problems are discussed and some heuristics are proposed.     

The existence, uniqueness and stability of traffic equilibria

The paper considers, in a simple case, the interaction between Webster's Method and drivers' route-choice decisions. In the example considered the overall network capacity is severely reduced by using Webster's Method. This shows that Webster's Method does not, in general, maximize the travel capacity of a road network. The analysis of this simple case suggests a signal-setting policy which does maximize the travel capacity of a general network.     

Structural models for the analysis of traveler attitude-behavior relationships

Traveler attitudes and behavior have been shown to correlate in numerous previous studies. However, the correlation by itself leaves open the nature of the interrelationships between traveler attitudes and behavior. For example, attitudes could either cause or be caused by behavior. In fact, both options are concurrently possible. Structural equations are applied to a set of data gathered from Los Angeles central business district workers to ascertain the direction and nature of interrelationships between attitudes and behavior with respect to frequency of taking the bus to work. A mutual dependence between attitudes and behavior is demonstrated in the context of this dataset and behavioral choice situation; behavior and attitudes concurrently cause each other. In addition, it is found that two attitudinal components, perceptions of and affect toward a mode, function differently with respect to travel behavior.     

Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes

Cycling is attracting renewed attention as a mode of transport in western urban environments, yet the determinants of usage are poorly understood. In this paper we investigate some of these using intraday bicycle volumes collected via induction loops located at ten bike paths in the city of Melbourne, Australia, between December 2005 and June 2008. The data are hourly counts at each location, with temporal and spatial disaggregation allowing for the impact of meteorology to be measured accurately for the first time. Moreover, during this period petrol prices varied dramatically and the data also provide a unique opportunity to assess the cross-price elasticity of demand for cycling. Over-dispersed Poisson regression models are used to model volumes at each location and at each hour of the day. Seasonality and the impact of weather conditions are modelled as semiparametric and estimated using recently developed multivariate penalized spline methodology. Unlike previous studies that use aggregate data, the empirical results show a substantial meteorological and seasonal component to usage. They also suggest there was substitution into cycling as a mode of transport in response to increases in petrol prices, particularly during peak commuting periods and by commuters originating in wealthy and inner city neighbourhoods. Last, we extend the approach to a multivariate longitudinal count data model using a Gaussian copula estimated by Bayesian data augmentation. We find first order serial dependence in the hourly volumes and a ‘return trip’ effect in daily bicycle commutes.     

A splitting rate model of traffic re-routeing and traffic control

The paper presents an idealised dynamical model of day-to-day or within-day re-routeing using splitting rates at nodes, or node-exit flows, rather than route-flows. It is shown that under certain conditions the dynamical model gives rise to a sequence of link flow vectors which converges to a set of approximate Wardrop equilibria. A special dynamical signal green-time re-allocation model is added; the combination is also shown (in outline) to converge to the set of approximate consistent equilibria under certain conditions. Finally the paper uses model network results to illustrate a method of designing fixed time signal timings to meet different scenarios.