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.

Single-lane traffic simulation with multi-agent system

Abstract: Agent-based traffic simulation has emerged as an efficient tool to investigate traffic phenomenon. However, the main problem is how to reproduce realistic patterns of traffic flow at both macroscopic and microscopic levels with restricted computational resources. In this paper, we present a multi-agent framework of single-lane traffic simulation. We focus on the driver-vehicle agents, which is the most important ones in the framework. The three-layer architecture of driver-vehicle agents is proposed, the decision tree of tactical longitudinal movement is put forward, and the simplified formulas of acceleration and deceleration rate are derived. With parallel update mode of agent states, a one-dimension traffic simulation model is developed. To validate it at the macroscopic level, we reproduced the realistic flow-density and speed-density relation of traffic flow with periodic boundary condition. To validate it at the microscopic level, a platoon of 10 vehicles was simulated. Given four kinds of typical speed profiles of the leader, each follower can follow its leader safely and stably. The result shows that this model can reproduce realistic macroscopic and microscopic characteristics of single-lane traffic flow.

Traffic congestion and dispersion in Hurricane evacuation

Abstract: We study the traffic congestion and dispersion of vehicles occurring on a single lane highway in Hurricane evacuation. The traffic congestion depends on both sensitivity and speed of the leading vehicle. When the leading vehicle moves with low speed, the vehicular traffic exhibits the stop and go-wave (oscillating congested traffic) for low sensitivity, while the traffic results in the homogeneous congested traffic for high sensitivity. The traffic dispersion is measured by the time difference between the leading and rear vehicles. The time difference fluctuates highly for the oscillating congestion traffic, while it keeps a constant value for the homogeneous congested traffic. The traffic states in Hurricane evacuation is connected to the phase diagram of conventional traffic.

Method for recognizing disruptions in road traffic

Abstract: In a method for recognizing disruptions in road traffic within a road sector that is to be monitored at respective measurement cross-sections at the beginning and at the end of the sector, the number and the speed of the vehicles passing through the measurement cross-sections are continuously acquired as measured data, which are collected and compiled cyclically during finite measurement intervals to provide average values of the traffic flow and the speed, and are then evaluated. Each measurement cross-section thereby encompasses all lanes of traffic that can be used in one direction of travel. In order to recognize disruptions in road traffic, independent of the traffic condition and with the smallest possible loss in time and low investment in data processing, a prognosis value of the traffic flow for the vehicles passing through the end of the road sector is calculated cyclically from the average values determined for the beginning of the road sector, taking into consideration the length of the road sector and an assumption about the driving behavior of the detected vehicles. Describable uncertainties arising in determining the prognosis value are taken into consideration by fuzzy modeling. The prognosis value is compared with the average value of the traffic flow at the end of the road sector determined from the measured data acquired at the measurement cross-section at the end of the road sector and the respective difference in traffic flow is determined cyclically. A cycle-spanning summation of the values of the difference in traffic flow is carried out and the number of the additional vehicles remaining in the road sector to be monitored is continuously determined.

Cellular automata based traffic model that allows the cars to move with a small velocity during congestion

Abstract: A typical non-zero velocity of traffic is observed in congestion, which the classical CA (cellular automata) based traffic models fail to reproduce properly. This paper proposes a traffic model to address the issue. The proposed model is motivated from the properties of rule 226 CA, which can deterministically model such continuous movement of cars during congestion. The reported model allows a continuous flow of traffic with small (non-zero) velocity in congestion, as well as can reproduce the traffic data observed empirically on highways.