Departure from the onset-onset rule

Using a signal-detection task, the generality of Turvey's (1973) onset-onset rule was tested in four experiments. After seeing, in succession, (1) one or two letters (target display), (2) a multiletter detection display, and (3) a mask display, subjects decided whether or not the letter or letters in the target display reappeared in the succeeding detection display at different levels of detection-display duration in various situations. The subjects' sensitivity was inconsistent with the onset-onset rule. More specifically, sensitivity increased with increases in display duration within a fixed stimulus onset asynchrony of 150 msec. Display duration, however, had no effect on response bias. Nor was there any interaction between display duration and display size in terms of either sensitivity or response bias. The more complicated relationship between display duration and display size does not invalidate the departure from the onset-onset rule

Iconic store and partial report

The iconic store has recently been challenged on the grounds that data in its favor may have resulted from some procedural artifacts. The display-instruction compatibility and perceptual grouping hypotheses were reexamined in two experiments with the partial-report paradigm. When care was taken to rectify some procedural problems found in Merikle's (1980) study, it was established that the iconic store (as a hypothetical mechanism) can still be validly entertained. This report demonstrates one important procedural point in studying the iconic store with the partial-report task, namely, that subjects must be given more than token training on the partial-report task

User equilibrium, system optimum, and externalities in time-dependent road networks

This paper develops a comprehensive framework for analysing and calculating user equilibrium, system optimum, and externalities in time-dependent road networks. Under dynamic user equilibrium, traffic is assigned such that for each origin-destination pair in the network, the individual travel costs experienced by each traveller, no matter which combination of travel route and departure time he/she chooses, are equal and minimal. The system optimal flow is determined by solving a state-dependent optimal control problem, which assigns traffic such that the total system cost of the network system is minimized. The externalities are derived by using a novel sensitivity analysis. The analyses developed in this paper can work with general travel cost functions. Numerical examples are provided for illustration and discussion. Finally, some concluding remarks are given

Analysis of dynamic system optimal assignment with departure time choice

Most analyses on dynamic system optimal (DSO) assignment are done by using the control theory with an outflow traffic model. On the one hand, this control theoretical formulation provides some attractive mathematical properties for analysis. On the other hand, however, this kind of formulation often ignores the importance of ensuring proper flow propagation. Moreover, the outflow models have also been extensively criticized for their implausible traffic behaviour. This paper aims to provide another framework for analysing a DSO assignment problem based upon sound traffic models. The assignment problem we considered aims to minimize the total system cost in a network by seeking an optimal inflow profile within a fixed planning horizon. This paper first summarizes the requirements on a plausible traffic model and reviews three common traffic models. The necessary conditions for the optimization problem are then derived using a calculus of variations technique. Finally, a simple working example and some concluding remarks are given

Analysis of dynamic system optimum and externalities with departure time choice

This paper aims to analyse the dynamic system optimal assignment with departure time choice, which is an important, yet underdeveloped area. The main contribution of this paper is the necessary conditions and the sensitivity analysis for dynamic system optimizing flow. Following this, we revisit the issue of dynamic externality in a more plausible way. We showed that how the externality can be derived and interpreted from the control theoretic formulation and the sensitivity analysis of traffic flow. To solve the system optimal assignment, we propose a dynamic programming solution approach. We present numerical calculations and discuss the characteristics of the results. In particular, we contrast the system optimal assignment with its equilibrium counterpart in terms of the amount of travel generated, flow profiles, and travel costs