Vehicle driving analysis in regards to fuel consumption using Fuzzy Logic and OBD-II devices

Pereira, Avner; Alves, Marcel Oliveira; Macedo, Hendrik

doi:10.1109/eatis.2016.7520160

Cited by 13 publications

(5 citation statements)

References 6 publications

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“…In the literature, some studies use these diagnostic devices to provide new services for intelligent transport systems. For example, the work of Pereira et al (2016) used an OBD to capture vehicle information with the purpose of inferring the fuel consumption based on the behavior of the driver. In order to identify the behavior of the driver, vehicle data are obtained through the OBD-II standard.…”

Section: Related Workmentioning

confidence: 99%

A Low-Cost Vehicular Infrastructure of Monitoring and Communicating Information for Intelligent Transport Systems

Rodrigues¹,

Severino²,

Cristiani³

et al. 2019

Journal of Computer Science

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Section: Related Workmentioning

confidence: 99%

A Low-Cost Vehicular Infrastructure of Monitoring and Communicating Information for Intelligent Transport Systems

Rodrigues¹,

Severino²,

Cristiani³

et al. 2019

Journal of Computer Science

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“…Some car data can be publicly gained through the On-Board Diagnostics (OBD) universal interface [32]. Increasing studies rely on OBD data to determine driving profiles (e.g., [33][34] [35]), to estimate FC (e.g., [36][37] [38] [39]) and to measure the gas emission of a car (e.g., [36] [40]).…”

Section: State Of the Artmentioning

confidence: 99%

“…FL has been used for driver fatigue and distraction identification (e.g. in [42]), scoring (e.g., in [43] [39]). Throttle position sensor (TPS), RPM and car speedthat are our selected sensors -have been used in [39] to develop an estimation system, that outputs a categorical level of FC (very low, low, medium, High, very high).…”

Section: State Of the Artmentioning

confidence: 99%

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A Fuzzy Logic Module to Estimate a Driver’s Fuel Consumption for Reality-Enhanced Serious Games

Massoud¹,

Poslad²,

Bellotti³

et al. 2018

IJSG

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Reality-enhanced gaming is an emerging serious game genre, that could contextualize a game within its real instruction-target environment. A key module for such games is the evaluator, that senses a user performance and provides consequent input to the game. In this project, we have explored an application in the automotive field, estimating driver performance in terms of fuel consumption, based on three key vehicular signals, that are directly controllable by the driver: throttle position sensor (TPS), engine rotation speed (RPM) and car speed. We focused on Fuzzy Logic, given its ability to embody expert knowledge and deal with incomplete information availability. The fuzzy models – that we iteratively defined based on literature expertise and data analysis – can be easily plugged into a reality-enhanced gaming architecture. We studied four models with all the possible combinations of the chosen variables (TPS and RPM; RPM and speed; TPS and speed; TPS, speed and RPM). Input data were taken from the enviroCar database, and our fuel consumption predictions compared with their estimated values. Results indicate that the model with the three inputs outperforms the other models giving a higher coefficient of determination (R2), and lower error. Our study also shows that RPM is the most important fuel consumption predictor, followed by TPS and speed.

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“…Such proposals were not in a real function, which shows the real versatility of such protocols but in simulators. Other works, as given in the literature, [16][17][18][19] utilize vehicle information registered by diagnostic devices to monitor vehicle conditions such as fuel consumption and CO 2 emissions. Nevertheless, these works do not make a relationship between the state of the vehicle and the vehicle route.…”

Section: Introductionmentioning

confidence: 99%

ITSMEI: An intelligent transport system for monitoring traffic and event information

Quessada

Pereira

Revejes

et al. 2020

International Journal of Distributed Sensor Networks

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The disorderly growth of urban centers can lead to serious socioeconomic disadvantages, such as health problems, due to long-term exposure to toxic gases and also monetary losses due to time stopped in congestion. Thus, there is a need for systems that help in the management and control of the flow of vehicles on the roads, seeking to reduce the damage resulting from a faulty transportation system and also avoiding the use of an inefficient system of information dissemination of urban roads. In this scenario, innovative systems are being developed to analyze the conjunction of road conditions to supervise and provide routes as needed for drivers to provide greater comfort and safety to vehicle traffic on urban roads. Thus, in this work, we propose the development of a system to monitor vehicle traffic, informing about events that are taking place on the roads in real time. The system can recommend new routes to drivers or allow drivers to take action based on information received from a particular road. As well as, the system uses driver location information for traffic monitoring, which will later be available for any devices, either a mobile device (smartphone) or a desktop. For the evaluation of the proposed system, a user case was developed for the Catanduva city in which we performed a test with the proposed system and was possible to verify a reduction in vehicle stopping time by 42% and a shorter travel time of 50% with an average speed of 33 km/h.

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Vehicle driving analysis in regards to fuel consumption using Fuzzy Logic and OBD-II devices

Cited by 13 publications

References 6 publications

A Low-Cost Vehicular Infrastructure of Monitoring and Communicating Information for Intelligent Transport Systems

A Low-Cost Vehicular Infrastructure of Monitoring and Communicating Information for Intelligent Transport Systems

A Fuzzy Logic Module to Estimate a Driver’s Fuel Consumption for Reality-Enhanced Serious Games

ITSMEI: An intelligent transport system for monitoring traffic and event information

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