Extending travel-time based models for dynamic network loading and assignment, to achieve adherence to first-in-first-out and link capacities

AbstractAn important class of models for macroscopic dynamic network loading (DNL) and dynamic traffic assignment (DTA) is based on treating link travel times as a function of link occupancy. However, these models suffer from some problems or deficiencies namely (a) the link outflows can violate first-in-first-out (FIFO), (b) the link outflows can exceed the link outflow capacities, (c) the link inflows can exceed the link inflow capacities, and (d) the link occupancies can exceed the link occupancy capacities. In this paper we introduce methods to overcome each of these problems.To remove problems (a) and (b) we extend the link travel-time model to better reflect behaviour when traffic flow is varying over time. To remove problems (c) and (d) we introduce more substantial changes in the model, to introduce capacities, spillback and queues compatible with the model. These extensions strengthen the realism, behavioural basis and usability of the link travel-time model and the DNL and DTA models that are based on it. They have no obvious adverse implications or side effects and require little additional computational effort. The original model is a special case of the new/extended model: the above extensions are activated if and only if any of the problems (a)–(d) arise, otherwise the new model reduces to the original model

Travel-Time Models With and Without Homogeneity Over Time

In dynamic network loading and dynamic traffic assignment for networks, the link travel time is often taken as a function of the number of vehicles x(t) on the link at time t of entry to the link, that is, τ(t) = f(x(t)), which implies that the performance of the link is invariant (homogeneous) over time. Here we let this relationship vary over time, letting the travel time depend directly on the time of day, thus τ(t) = f(x(t), t). Various authors have investigated the properties of the previous (homogeneous) model, including conditions sufficient to ensure that it satisfies first-in-first-out (FIFO). Here we extend these results to the inhomogeneous model, and find that the new sufficient conditions have a natural interpretation. We find that the results derived by several previous authors continue to hold if we introduce one additional condition, namely that the rate of change of f(x(t), t) with respect to the second parameter has a certain (negative) lower bound. As a prelude, we discuss the equivalence of equations for flow propagation equations and for intertemporal conservation of flows, and argue that neither these equations nor the travel-time model are physically meaningful if FIFO is not satisfied. In §7 we provide some examples of time-dependent travel times and some numerical illustrations of when these will or will not adhere to FIFO

An investigation into E-business service in the UK telecommunication manufacturing industry

Nowadays, suppliers’ product and service quality has risen in importance with a manufacturer’s push to develop core competencies and capitalise on global operations and markets. However, due to the complex features of business service, suppliers are facing significant challenges in providing service effectively and developing business collaboration. This is further complicated by the development of information and communication technologies (ICTs). This paper thus attempts to investigate the factors influencing buyers’ e-service (EBS) requirements and the impact of these requirements on business collaboration. Based on a questionnaire survey with 500 UK telecommunication manufacturers, this research identifies buyers’ different EBS requirements for different types of suppliers and the impact of ICTs on EBS requirements. While for suppliers our findings provide insights into buyers’ EBS requirements, they can help buyers to develop appropriate supplier selection criteria. The findings also contribute to a better understanding of the development of buyer and supplier business collaboration