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.

Method for warning traffic jams using e.g. vehicle-related location, speed and time information, involves creating prediction such that jam fronts run in upstream movement under latency periods during transmission of information in vehicle

Abstract: The method involves determining a vehicle-related information chain with speed, location and time information Vehicles are made to receive traffic information service and perform onboard state detection or receive traffic condition detection information Traffic jam fronts in a road network with assigned position and time point are determined based on the information chain and traffic condition determination in a computer center Prediction is created such that the jam fronts run in an upstream movement under latency periods during transmission of the information in the vehicle

Traffic mixing in deterministic two-lane model of Hurricane evacuation

Abstract: We study the mixing of vehicles on a two-lane highway in Hurricane evacuation. We present the deterministic model of two-lane traffic in which vehicles change the lane by a deterministic rule. We investigate the typical traffic induced by a slow vehicle on the first lane under the open boundary. The escape time of vehicles is determined by their order. The vehicular order changes by traffic mixing. The traffic mixing depends highly on the sensitivity. For high sensitivity, the escape time depends on the initial order of vehicles. For low sensitivity, the lane changing occurs irregularly by stop- and go-waves and vehicles then evacuate irregularly without keeping their initial order.

Speed-Density Model of Interrupted Traffic Flow Based on Coil Data

Abstract: As a fundamental traffic diagram, the speed-density relationship can provide a solid foundation for traffic flow analysis and efficient traffic management. Because of the change in modern travel modes, the dramatic increase in the number of vehicles and traffic density, and the impact of traffic signals and other factors, vehicles change velocity frequently, which means that a speed-density model based on uninterrupted traffic flow is not suitable for interrupted traffic flow. Based on the coil data of urban roads in Wuhan, China, a new method which can accurately describe the speed-density relation of interrupted traffic flow is proposed for speed fluctuation characteristics. The model of upper and lower bounds of critical values obtained by fitting the data of the coils on urban roads can accurately and intuitively describe the state of urban road traffic, and the physical meaning of each parameter plays an important role in the prediction and analysis of such traffic.

Modeling Left-Turn Driving Behavior at Signalized Intersections with Mixed Traffic Conditions

Abstract: In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions.