Benchmarking the driver acceleration impact on vehicle energy consumption and CO2 emissions

Suarez, Jaime; Makridis, Michail; Anesiadou, Aikaterini; Komnos, Dimitrios; Ciuffo, Biagio; Fontaras, Georgios

doi:10.1016/j.trd.2022.103282

Cited by 16 publications

(6 citation statements)

References 39 publications

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“…The application of the proposed adaptive approach improves the efficiency of each method with ordinary filtering strength by up to 80% in terms of error reduction. However, aggregated indicators do not give insights about the resulting microscopic dynamics after the trajectory reconstruction, essential for accurate traffic flow and energy-related conclusions 4 .…”

Section: Resultsmentioning

confidence: 99%

“…Vehicle trajectory extraction, reconstruction, filtering, or smoothing are closely related and have attracted research interest more than half a century ago with the seminal works of 1 (i.e., Wiener filter), and 2 (i.e., Rauch-Tung-Striebel smoother). It is an important topic that can enable investigations on various other topics, e.g., emissions or energy demand 3 , 4 , traffic dynamics 5 – 8 , modeling and control 9 – 11 , control 11 , connected and automated vehicles and driver understanding 12 , 13 , while this list is not exhaustive.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive physics-informed trajectory reconstruction exploiting driver behavior and car dynamics

Makridis

Kouvelas

2023

Sci Rep

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As more and more trajectory data become available, their analysis creates unprecedented opportunities for traffic flow investigations. However, observed physical quantities like speed or acceleration are often measured having unrealistic values. Furthermore, observation devices have different hardware and software specifications leading to heterogeneity in noise levels and limiting the efficiency of trajectory reconstruction methods. Typical strategies prune, smooth, or locally modify vehicle trajectories to infer physically plausible quantities. The filtering strength is usually heuristic. Once the physical quantities reach plausible values, additional improvement is impossible without ground truth data. This paper proposes an adaptive physics-informed trajectory reconstruction framework that iteratively detects the optimal filtering magnitude, minimizing local acceleration variance under stable conditions and ensuring compatibility with feasible vehicle acceleration dynamics and common driver behavior characteristics. Assessment is performed using both synthetic and real-world data. Results show a significant reduction in the speed error and invariability of the framework to different data acquisition devices. The last contribution enables the objective comparison between drivers with different sensing equipment.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive physics-informed trajectory reconstruction exploiting driver behavior and car dynamics

Makridis

Kouvelas

2023

Sci Rep

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“…Finally, CO 2 emissions are analyzed from the user's driving perspective, indicating that the way the driver accelerates has a significant impact on energy consumption and polluting emissions. In those cases that accelerate more aggressively, they emit a greater amount of CO 2 and the choice of vehicle influences this, since heavy vehicles emit more emissions during acceleration [34].…”

Section: Generation Of Polluting Emissionsmentioning

confidence: 99%

Measurement of Road Transport Emissions, Case Study: Centinela-La Rumorosa Road, Baja California, México

Calderón-Ramírez,

Gutiérrez-Moreno,

Montoya-Alcaraz

et al. 2024

Applied Sciences

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Air pollution is a global issue, and the transportation sector is recognized as the third-largest contributor to anthropogenic greenhouse gas emissions. Vehicles emit a range of chemical compounds because of the combustion process. The nature and quantity of these emissions depend on the vehicle’s characteristics, the road, and weather conditions. These emissions require special attention due to the adverse effects contributing to global warming and human health. In this regard, diagnosing and monitoring air quality is crucial for understanding the number of emissions generated by various sources. However, in developing countries, the necessary data for conducting such analyses are not always available. The purpose of this study is to estimate emissions specifically generated from road operations. To achieve this, the HDM-4 calculation tool is utilized to estimate emissions. This tool was applied in Baja California, Mexico, on the Centinela-La Rumorosa highway. The results obtained show that annually, 372.5 tons of pollutant emissions are generated, composed of HC, CO, CO2, NOx, PM, SO2, and PB, covering a mere 128 km of length within a state road network spanning 11,429 km. This highlights the necessity of implementing strategies to reduce the environmental impact generated by vehicular operations on roads in developing countries.

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“…Recent experimental studies, performed at both test benches and actual traffic conditions, that relate emission characteristics to acceleration have been published by Kim et al [17], Chadrashekar et al [18], and Kuppili et al [19]. In this context, a very comprehensive semi-empirical methodology to link instantaneous acceleration and CO 2 emissions has been published by Suarez et al [20]. Also, it is relevant to refer to the work of Zhang et al [21], which studied the influence of acceleration on vehicle emissions at intersections using the MOVES emission model (US Environmental Protection Agency, 2009) [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Conceptual Study on Car Acceleration Strategies to Minimize Travel Time, Fuel Consumption, and CO2-CO Emissions

Acosta,

Sastre,

Arias

et al. 2024

Vehicles

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A conceptual study was performed on intelligent driving acceleration strategies for vehicles equipped with internal combustion engines. Two archetypal acceleration scenarios of highway driving and urban driving were prescribed. Three trajectories were considered for each scenario. They involved (a) nearly constant acceleration, (b) fast acceleration first and slow acceleration later, and (c) slow acceleration first and fast acceleration later. The selected vehicle was a generic European small–medium passenger car. Engine inlet pressure and ignition time were optimized along each trajectory to minimize fuel consumption, CO, and CO2 emissions, and travel time. The optimization process involved a methodological approach based on the higher-order singular value decomposition of the tensor form of the engine model. The optimized trajectories were analyzed and compared among themselves. Conceptual acceleration design guidelines for intelligent driving were provided that could be of interest when integrating vehicle/engine performance into the surrounding traffic flow.

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Benchmarking the driver acceleration impact on vehicle energy consumption and CO2 emissions

Cited by 16 publications

References 39 publications

Adaptive physics-informed trajectory reconstruction exploiting driver behavior and car dynamics

Adaptive physics-informed trajectory reconstruction exploiting driver behavior and car dynamics

Measurement of Road Transport Emissions, Case Study: Centinela-La Rumorosa Road, Baja California, México

Conceptual Study on Car Acceleration Strategies to Minimize Travel Time, Fuel Consumption, and CO2-CO Emissions

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