Benefit Sensitivities of Adaptive Traffic Control Strategies at Isolated Traffic Signals

This paper describes an artificial immune system approach (AIS) to modeling time-dependent (dynamic, real time) transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions) that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies) for different antigens (different traffic "scenarios"). This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

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Make Way: An Intelligent Real-Time Traffic Light Control System

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.b3575.129219 ◽

2019 ◽

Vol 9 (2) ◽

pp. 709-712

Keyword(s):

Control System ◽

Traffic Control ◽

Traffic Signals ◽

First Aid ◽

Light Control ◽

Traffic Light ◽

Rf Receiver ◽

Rf Transmitter ◽

Traffic Light Control ◽

Traffic Control System

Nowadays, automatic traffic light control is becoming an important requirement for travelers and number of road users especially for emergency service providers such as ambulance drivers, fire fighters etc... Various alternatives have been proposed, but it has certain limitations.One such example is using an RF transmitter mounted on the ambulance which will communicate with the RF receiver mounted on the signal post in the traffic control system. A special algorithm is provided to control the traffic signals automatically by pressing the key provided in the keybord on the ambulance by the driver.But in this case, there is big trouble for car accidents or road accidents, because of automatic adjustment and a large number of vehicles, and there is a problem of delay in first aid service, with these overcrowded roads. This paper describes a solution that is "Intelligent Ambulance with Automatic Traffic Control” which includes the accident detecting, alerting and tracking mechanism with an automatic traffic light controlling system to overcome this delay of first aid service. An ambulance can thereby easily finde a freeway to reach the victim in a minimal time and thereby providing first aid as soon as possible. This is possible by using an RF transmitter on the ambulance which will communicate with the RF receiver mounted on the signal post in the traffic control system. To control the traffic signals automatically, and to move towards the location in minimal time, a specific algorithm is proposed in this paper. Thus, the traffic light gets controlled by the intelligent ambulance itself, in such a way that it could provide free path to the ambulance[1].

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Preliminary Analysis of Light Rail Crashes in Denver, Colorado

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2275-02 ◽

2012 ◽

Vol 2275 (1) ◽

pp. 12-21 ◽

Cited By ~ 1

Author(s):

Pamela M. Fischhaber ◽

Bruce N. Janson

Keyword(s):

Traffic Control ◽

Preliminary Analysis ◽

Prediction Models ◽

Hazard Index ◽

Traffic Signals ◽

Control Device ◽

Light Rail ◽

Crash Prediction ◽

Grade Crossing ◽

Grade Crossings

This paper presents a preliminary analysis of light rail crashes at at-grade crossings in Denver, Colorado, based on Regional Transportation District data for 1999 through 2009. Differences in design and operation of at-grade crossings are discussed for light rail versus common carrier railroad (railroad). The differences appear to warrant the development of separate crash prediction and hazard index models because models developed for railroad at-grade crossing operations may not accurately predict the number and severity of crashes at light rail at-grade crossings. In addition, the models developed for railroads do not predict crashes at crossings for some traffic control device types such as traffic signals. The lack of information for crossings controlled by traffic signals in the railroad crash prediction equations is one reason why equations specific to light rail may need to be developed. This study identifies patterns in light rail crossing crash data that warrant further investigation and support the development of crash prediction models and hazard index equations specific to light rail at-grade crossing configurations and operations.

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