Travel times in urban road networks are highly stochastic. However, most existing travel time estimation methods only estimate the mean travel times, while ignoring travel time variances. To this end, this paper proposes a robust travel time distribution estimation method to estimate both the mean and variance of travel times by using emerging low-frequency floating car data. Different from the...

We identify the statistical characterizers of congestion and decongestion for message transport in model communication lattices. These turn out to be the travel time distributions, which are Gaussian in the congested phase, and logarithmic normal in the decongested phase. Our results are demonstrated for two-dimensional lattices, such the Waxman graph, and for lattices with local clustering and...

In this paper we consider the potential for congestion collapse in a range of network scenarios. In particular, we are interested in the effect of the topology, the scheduling discipline (FIFO or FQ scheduling), the level of statistical multiplexing, the traffic characteristics, and other factors. We consider topologies more complex than a single congested link, or a single string of congested ...

Assigning and scheduling vehicle routes in a dynamic environment is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic and dynamic nature of travel times. In this paper, a vehicle routing problem with time-dependent travel times due to potential traffic congestion is considered. Th...

In this paper we show how the Färe, Grosskopf and Lovell (1985) input congestion nonparametric test can be performed to reach a statistical conclusion. To achieve this goal, we use Simar and Wilson (1998, 2000) radial distance functions bootstrap technique. An empirical illustration on airports congestion is provided. The results show that the technology is globally congested and that nine of t...