Assessment of Alternative Polynomial Fuel Consumption Models for Use in Intelligent Transportation Systems Applications

2013 ◽  
Vol 17 (4) ◽  
pp. 294-303 ◽  
Author(s):  
Bart Saerens ◽  
Hesham Rakha ◽  
Kyoungho Ahn ◽  
Eric Van Den Bulck
Keyword(s):  
Fuel Consumption ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems

scholarly journals Emissions and Fuel Consumption Modeling for Evaluating Environmental Effectiveness of ITS Strategies

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yuan-yuan Song ◽  
En-jian Yao ◽  
Ting Zuo ◽  
Zhi-feng Lang
Keyword(s):  
Fuel Consumption ◽  
Intelligent Transportation Systems ◽  
Vehicle Emissions ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Estimation Accuracy ◽  
Road Transportation ◽  
Emission Data ◽  
Vehicle Operation ◽  
Environmental Effectiveness

Road transportation is a major fuel consumer and greenhouse gas emitter. Recently, the intelligent transportation systems (ITSs) technologies, which can improve traffic flow and safety, have been developed to reduce the fuel consumption and vehicle emissions. Emission and fuel consumption estimation models play a key role in the evaluation of ITS technologies. Based on the influence analysis of driving parameters on vehicle emissions, this paper establishes a set of mesoscopic vehicle emission and fuel consumption models using the real-world vehicle operation and emission data. The results demonstrate that these models are more appropriate to evaluate the environmental effectiveness of ITS strategies with enough estimation accuracy.

scholarly journals Driver Rating: a mobile application to evaluate driver behavior

2021 ◽  
Vol 2 (2) ◽  
pp. 1147-1160
Author(s):  
Nielson S. Trindade ◽  
Artur H. Kronbauer ◽  
Helder G. Aragão ◽  
Jorge Campos
Keyword(s):  
Carbon Dioxide ◽  
Urban Environment ◽  
Fuel Consumption ◽  
Intelligent Transportation Systems ◽  
Mobile Application ◽  
Driver Behavior ◽  
Carbon Dioxide Emission ◽  
Intelligent Transportation ◽  
Transportation Systems

The combination of data from sensors embedded in vehicles and smartphones promises to generate great innovations in intelligent transportation systems. This article presents Driver Rating, a mobile application to evaluate the behavior of drivers based on the data gathered from vehicles´ and smartphones´ sensors. The Driver Rating application analyzes five variables (fuel consumption, carbon dioxide emission, speed, longitudinal acceleration, and transverse acceleration) to evaluate driver´s behaviors while driving. To test the Driver Rating application and identify its potentialities, an experiment was carried out on an urban environment, showing promising results regarding the classification of drivers’ behavior.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

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