A Linear Model for the Estimation of Fuel Consumption and the Impact Evaluation of Advanced Driving Assistance Systems

Bifulco, Gennaro Nicola; Galante, Francesco; Pariota, Luigi; Spena, Maria Russo

doi:10.3390/su71014326

Cited by 48 publications

(31 citation statements)

References 26 publications

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“…The savings are clearly higher in the bypass (route 4) as it is longer and less dependent on traffic lights and rights of way. These relative savings are higher than those reported for larger cities such as Naples, Turin, Lisbon, Madrid, London, or Beijing [43][44][45][46][47][48].…”

Section: Conclusion and Policy Recommendationscontrasting

confidence: 38%

Green Eco-Driving Effects in Non-Congested Cities

et al. 2017

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Despite technological advances in engines and fuels, the transportation sector is still one of the largest emitters of greenhouse gas (GHG). Driving patterns, including eco-driving techniques, are a complementary measure for saving GHG emissions. Most eco-driving studies so far have been conducted in large cities suffering chronic congestion problems. The aim of this research is therefore to analyse the potential of driver behaviour for reducing emissions in a small non-congested city. Driver performance parameters such as travel speeds, number of stops, revolutions per minute, and maximum acceleration-deceleration are also studied. The methodology is designed to measure the effect of both eco-driving and eco-routing under real traffic conditions. A campaign was carried out in the city of Caceres (Spain) to collect data on various types of roads under different traffic conditions. This research concludes that eco-driving leads to CO 2 savings on all routes and road types of 17% in gasoline engines and 21% in diesel, although travel times are increased by 7.5% on average. The shortest route is also the most ecological, regardless of the traffic volume and characteristics, implying that consumption in non-congested cities depends mainly on distance travelled rather than driving patterns in terms of number of stops, speed and acceleration.

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Section: Conclusion and Policy Recommendationscontrasting

confidence: 38%

Green Eco-Driving Effects in Non-Congested Cities

et al. 2017

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“…This experiment type could not be fully replaced with mathematical modelling or computer simulation [7][8][9]. During such experiments (apart from fuel consumption and movement characteristics) it is possible to determine required engine operation parameters and based on that, to choose optimal engine control parameters.…”

Section: Introductionmentioning

confidence: 99%

“…There are specific road tests often being applied, and during that tests it is possible to identify indicator and effective engine parameters, and fuel consumption [4,6,8,14]. Literature sources contain description of the methods to identify fuel consumption based on -14].…”

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confidence: 99%

Investigations of diesel engine in the road test

Grytsyuk

Vrublevskyi

2018

Diagnostyka

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This article describes the details of the method designed to combustion engine with compression ignition (CI) during road tests. The method requires simultaneous measurements for the crankshaft rotation frequency, fuel pressure in the injector, pressure in the combustion chamber, air pressure and temperature in the intake system. More, this method utilizes possibilities of the GPS navigation -all the received data is being synchronized with navigation data and saved to the database. Fuel consumption was calculated using the original method based on processing the pressure data from inside the cylinder alongside with the fuel injection parameters, previously received from the injection system and engine tests in the laboratory. Obtained characteristics allow to perform detailed analysis for the engine single work cycle in the transient processes, which are the . Measurements results received with help of the created experimental gear were used to determine CI engine parameters. Those parameters may help in simulation of the engine work inside the vehicle, and could be used in engine parameters optimization tasks.

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“…The models in question can be classified into service frequency optimization (Salzborn [16], yu et al [17] and gallo et al [18,19]), joint design of frequencies and routes (laporte et al [20] and Van Nes et al [21]) or elastic demand approach models (lee & Vuchic [22] and marìn & garcìa-ròdenas [23]). However, there are also several contributions related to specific themes such as the budget reductions of public transport (D'acierno et al [24]), the definition of energy-efficient driving profiles (gallo et al [25]), effect of information on user choices (Pariota & bifulco [26] and bifulco et al [27]) or safety of transportation systems (Dell'acqua et al [28]). …”

Section: Introductionmentioning

confidence: 99%

A neighbourhood search algorithm for determining optimal intervention strategies in the case of metro system failures

Botte¹,

Salvo²,

Placido³

et al. 2017

Int. J. TDI

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In high-density contexts, such as urban or metropolitan areas, decision makers and mobility managers have to adopt suitable strategies to reduce the use of private cars and promote public transport. Indeed, such strategies may help abate the negative impacts of transportation systems (congestion, air and noise pollution, etc.). However, appropriate measures are only effective if based on the provision of high-quality public transport services. Such aims can be achieved by organizing public transport within an integrated framework where rail/metro services are the high-performing mobility backbone and bus services have a feeder function, increasing the geographical coverage of rail services. However, since a faulty train cannot be easily removed or overtaken, a rail/metro system is highly vulnerable to system breakdowns which could entail significant reductions in system quality. Suitable intervention strategies therefore have to be developed to manage rail system emergencies. The aim of this article is to provide a method to determine optimal intervention strategies in the case of a metro system failure. Since in real contexts an exhaustive approach has to be excluded due to the huge number of alternative solutions to be evaluated, it is necessary to adopt or develop appropriate algorithms to obtain sub-optimal solutions within suitable computational times. Hence a Neighbourhood Search Algorithm to identify the optimal solution is applied and tested in the case of a real metro line in order to show the feasibility of our proposal.

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A Linear Model for the Estimation of Fuel Consumption and the Impact Evaluation of Advanced Driving Assistance Systems

Cited by 48 publications

References 26 publications

Green Eco-Driving Effects in Non-Congested Cities

Green Eco-Driving Effects in Non-Congested Cities

Investigations of diesel engine in the road test

A neighbourhood search algorithm for determining optimal intervention strategies in the case of metro system failures

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