A methodology to creating semi-artificial city driving cycle: case study of Istanbul

Aydin, Muhammet; Soruşbay, Cem

doi:10.1186/s44147-022-00132-1

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…varies from city to city or regionally [15]. Aydin and Soruşbay [16] created the driving cycles of İstanbul city called Artificial Istanbul Driving Cycle based on average real traffic data. They showed that the İstanbul cycles resulted in lower CO 2 emission factors than those of the WLTC for segments of rural, urban, and highway.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Framework for Driving Cycle Generation and Analysis

Keskin,

Yıldız,

Arslannur

2023

Preprint

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This paper presents a methodology for generating realistic driving cycles using Markov chain modelling, Monte Carlo simulation and dynamic time warping. The study focuses on the construction of a representative driving cycle for the city of Igdir, taking into account its unique traffic characteristics. The methodology involves segmenting the original driving datasets based on traffic conditions and road types, creating a detailed representation of driving behaviour. Dynamic time warping is used to identify reference segments for each group of segments, ensuring accurate matching with the generated driving cycles. The integration of Markov chain-Monte Carlo simulation introduces variability and randomness. The proposed methodology provides an advanced algorithm for generating highly accurate representative driving cycles, which can contribute to energy consumption analysis, vehicle performance and emission evaluation. The comprehensive approach provided by the methodology enables an accurate understanding of driving patterns, promoting the development of sustainable mobility solutions and advancing transport research.

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Section: Introductionmentioning

confidence: 99%

A Data-Driven Framework for Driving Cycle Generation and Analysis

Keskin,

Yıldız,

Arslannur

2023

Preprint

View full text Add to dashboard Cite

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Techno-economic assessment of hydrogen as a fuel for internal combustion engines and proton exchange membrane fuel cells on long haul applications

Lago Sari,

Fogue Robles,

Monsalve Serrano

et al. 2024

Energy Conversion and Management

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An innovative virtual sensing system for the vehicle-centric evaluation of emissions in the sustainable mobility transition

Strada,

Pagliaroli,

Savaresi

2024

Sci Rep

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The objective of the research is to develop a new methodology capable of quantifying the emissions of internal combustion engine cars based not only on their technology but also on the dynamic behavior of the individual vehicle. No complicated exhaust measurement apparatus is needed. Employing just a telematic device equipped with GNSS and an inertial measurement unit, which can be easily attached to the vehicle, we demonstrate how individualised, accurate climate-altering emissions result by using figures extracted from European test databases, appropriately combined with real travelled distances, speeds, and driving style of each individual car. Pollutant emissions are, in this paper, also assessed though in a more general manner, and this represents a starting point for a future complete vehicle-centric emissions evaluation. This research demonstrates that circulating car emissions have to be assessed considering not only the Euro class and type of fuel, but also how the vehicle is driven. In this work a new, implementation oriented methodology is proposed in order to properly merge average European standard emission data with car-based telematic measures to highlight a new paradigm for regulating in a more conscious way the transition of the internal combustion engine car park towards a large scale, sustainable mobility ecosystem. This approach would place greater responsibility on the driver, without leaving anyone behind and without compelling the car scrapping solely based on the Euro class of its engine. The key contribution is ultimately to establish an easy to handle methodology enabling targeted and behavior-based traffic management policies. In fact, through a massive telematics recent dataset, the proposed virtual emission sensing system reveals that an extensive and inefficient use of eco-friendly vehicles produces much more greenhouse gas emissions than older vehicles driven in an environmentally responsible way.

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A methodology to creating semi-artificial city driving cycle: case study of Istanbul

Cited by 4 publications

References 22 publications

A Data-Driven Framework for Driving Cycle Generation and Analysis

A Data-Driven Framework for Driving Cycle Generation and Analysis

Techno-economic assessment of hydrogen as a fuel for internal combustion engines and proton exchange membrane fuel cells on long haul applications

An innovative virtual sensing system for the vehicle-centric evaluation of emissions in the sustainable mobility transition

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