Traffic wave

About: Traffic wave is a research topic. Over the lifetime, 2106 publications have been published within this topic receiving 62117 citations. The topic is also known as: phantom traffic jam & ghost jams.

Probability Distributions of Travel Times on Arterial Networks: Traffic Flow and Horizontal Queuing Theory Approach

Abstract: In arterial networks, traffic flow dynamics are driven by the presence of traffic signals, for which precise signal timing is difficult to obtain in arbitrary networks or might change over time. A comprehensive model of arterial traffic flow dynamics is necessary to capture its specific features in order to provide accurate traffic estimation approaches. From hydrodynamic theory, arterial traffic dynamics are modeled under specific assumptions standard in transportation engineering. This flow model is used to develop a statistical model of arterial traffic. The statistical approach is essential to capture the variability of travel times among vehicles: (1) the delay experienced by a vehicle depends on the time when it enters the link (in relation to the signal green/red phases) and this entrance time can occur at any random time during the cycle and (2) the free flow speed of a vehicle depends both on the driver and on external factors (jaywalking, double parking, etc.) and is another source of uncertainty. These two sources of uncertainty are captured by deriving the probability distribution of delays (from hydrodynamic theory) and modeling the nominal free flow travel time as a random variable (which encodes variability in driving behavior). An analytical expression is derived for the probability distribution of travel times between any two locations on an arterial link, parameterized by traffic parameters (cycle time, red time, free flow speed distribution, queue length and queue length at saturation). The model is validated using probe vehicle data collected during a field test in San Francisco, as part of the Mobile Millennium system. The numerical results show that the new distribution derived in this article more accurately represents the actual distribution of travel times than other distributions that are commonly used to represent travel times (normal, log-normal and Gamma distributions). It is also shown that the model performs particularly well when the amount of data available is small. This is very promising as the volume of probe vehicle data available in real time to most traffic information systems today remains sparse.

Coupling traffic flow networks to pedestrian motion

Abstract: In this paper scalar macroscopic models for traffic and pedestrian flows are coupled and the resulting system is investigated numerically. For the traffic flow the classical Lighthill–Whitham Richards model on a network of roads and for the pedestrian flow the Hughes model are used. These models are coupled via terms in the fundamental diagrams modeling an influence of the traffic and pedestrian flow on the maximal velocities of the corresponding models. Several physical situations, where pedestrians and cars interact, are investigated.

Delays to road traffic at an intersection

Abstract: A model for road traffic delays at intersections is considered where vehicles arriving, possibly in bunches, in a Poisson process in a one way minor road yield right of way to traffic, which forms alternate bunches and gaps, in a major road. The gap acceptance times are random variables, and depend on whether or not a minor road vehicle is immediately following another minor road vehicle into the intersection or not. The transforms of the stationary waiting time and queue size distributions, and the mean stationary delay, for minor road vehicles are obtained by substitution of determined service time distributions into results for a generalisation of the M/G/1 queueing system. Some numerical results are given to illustrate the increase in the mean delay for variable gap acceptance times for a Borel-Tanner distribution of major road traffic, and a partial solution is given for a two way major road.