Using an Imbalanced Classification Algorithm and Floating Car Data for Predicting Real-Time Traffic Crash Risk on Expressways

2021 ◽  
Author(s):  
Ahmad Yehia ◽  
Xuesong Wang ◽  
Tonggen Wang
Keyword(s):  
Real Time ◽  
Classification Algorithm ◽  
Crash Risk ◽  
Traffic Crash ◽  
Imbalanced Classification ◽  
Floating Car Data ◽  
Real Time Traffic

Examining imbalanced classification algorithms in predicting real-time traffic crash risk

2020 ◽  
Vol 144 ◽  
pp. 105610 ◽  
Author(s):  
Yichuan Peng ◽  
Chongyi Li ◽  
Ke Wang ◽  
Zhen Gao ◽  
Rongjie Yu
Keyword(s):  
Real Time ◽  
Crash Risk ◽  
Classification Algorithms ◽  
Traffic Crash ◽  
Imbalanced Classification ◽  
Real Time Traffic

Crash risk analysis during fog conditions using real-time traffic data

2018 ◽  
Vol 114 ◽  
pp. 4-11 ◽  
Author(s):  
Yina Wu ◽  
Mohamed Abdel-Aty ◽  
Jaeyoung Lee
Keyword(s):  
Risk Analysis ◽  
Real Time ◽  
Crash Risk ◽  
Traffic Data ◽  
Real Time Traffic

scholarly journals A Single Intersection Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 409 ◽  
Author(s):  
Vittorio Astarita ◽  
Vincenzo Pasquale Giofrè ◽  
Giuseppe Guido ◽  
Alessandro Vitale
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Traffic Safety ◽  
New Technologies ◽  
Traffic Signal ◽  
Pollutant Emissions ◽  
Connected Vehicles ◽  
Floating Car Data ◽  
Real Time Traffic ◽  
Signal Systems

New technologies such as "connected" and "autonomous" vehicles are going to change the future of traffic signal control and management and possibly will introduce new traffic signal systems that will be based on floating car data (FCD). The use of floating car data to regulate traffic signal systems, in real time, has the potential for an increased sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. However, research has never explored how not "connected" vehicles would benefit by the implementation of such systems. This paper explores the use of floating car data to regulate traffic signal systems in real-time in a single intersection and in terms of cooperative-competitive paradigm between "connected" vehicles and conventional vehicles. In a dedicated laboratory, developed for testing regulation algorithms, results show that "invisible vehicles" for the system (which are not "connected") in most simulated cases also benefit when real time traffic signal settings based on floating car data are introduced. Moreover, the study estimates the energy and air quality impacts of a single intersection signal regulation by evaluating fuel consumption and pollutant emissions. Specifically, the study demonstrates that significant improvements in air quality are possible with the introduction of FCD regulated traffic signals.

scholarly journals Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data

2018 ◽  
Author(s):  
Vittorio Astarita ◽  
Vincenzo Pasquale Giofrè ◽  
Giuseppe Guido ◽  
Alessandro Vitale
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Traffic Safety ◽  
New Technologies ◽  
Traffic Signal ◽  
Pollutant Emissions ◽  
Connected Vehicles ◽  
Floating Car Data ◽  
Real Time Traffic ◽  
Signal Systems

New technologies such as "connected" and "autonomous" vehicles are going to change the future of traffic signal control and management and possibly will introduce new traffic signal systems that will be based on floating car data (FCD). The use of floating car data to regulate, in real-time, traffic signal systems has the potential for an increased sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. However, research has never explored how not "connected" vehicles would benefit by the implementation of such systems. This paper explores the use of floating car data to regulate in real-time traffic signal systems in terms of cooperative-competitive paradigm between "connected" vehicles and conventional vehicles. In a dedicated laboratory, developed for testing regulation algorithms, results show that "invisible vehicles" for the system (which are not "connected") in most simulated cases also benefit when real time traffic signal settings based on floating car data are introduced. Moreover, the study estimates the energy and air quality impacts of signal regulation by evaluating fuel consumption and pollutant emissions. Specifically, the study demonstrates that significant improvements in air quality are possible with the introduction of FCD regulated traffic signals.

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