Modelling the adoption intention and installation choice of an automotive after-market mild-solar-hybridization kit

Luca, Stefano de; Pace, Roberta Di; Marano, Vincenzo

doi:10.1016/j.trc.2015.04.023

Cited by 19 publications

(12 citation statements)

References 113 publications

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“…At both levels, the effects of the adopted solutions can be investigated by using microscopic simulation tools, which allow the simulation of the interaction of vehicles in a traffic stream and the resulting kinematics (and dynamics) of the vehicles. Microscopic models make it possible to explicitly take into account different driving behaviors [11] and engine characteristics [12,13].…”

Section: Problem Formulationmentioning

confidence: 99%

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

et al. 2015

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Abstract:Reduction of the environmental impact of cars represents one of the biggest transport industry challenges. Beyond more efficient engines, a promising approach is to use eco-driving technologies that help drivers achieve lower fuel consumption and emission levels. In this study, a real-time microscopic fuel consumption model was developed. It was designed to be integrated into simulation platforms for the design and testing of Advanced Driving Assistance Systems (ADAS), aimed at keeping the vehicle within the environmentally friendly driving zone and hence reducing harmful exhaust gases. To allow integration in platforms employed at early stages of ADAS development and testing, the model was kept very simple and dependent on a few easily computable variables. To show the feasibility of the identification of the model (and to validate it), a large experiment involving more than 100 drivers and about 8000 km of driving was carried out using an instrumented vehicle. An instantaneous model was identified based on vehicle speed, acceleration level and gas pedal excursion, applicable in an extra-urban traffic context. Both instantaneous and aggregate validation was performed and the model was shown to estimate vehicle fuel consumption consistently with in-field instantaneous measurements. Very accurate estimations were also shown for the aggregate consumption of each driving session.

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Section: Problem Formulationmentioning

confidence: 99%

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

et al. 2015

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“…It is well-known that about 50% of pollution is from road transport and, in particular, from internal combustion engines [1]. Within this context, different actions have been deployed in the last few decades to reduce pollution, such as acting on the vehicle technology [2] or different types of fuels [3], and through different and sophisticated mobility/travel demand management policies [4] or traffic flow control strategies.…”

Section: Introductionmentioning

confidence: 99%

“…In this vein, new technologies deployed in the Intelligent Transportation Systems framework may easily support drivers to adopt a more sustainable behavior and/or may allow a more sustainable Sustainability 2020, 12, 726 2 of 20 management of traffic flows. In particular, real-time traffic control (TC) [5] and Route Guidance (RG) [6] represents one of the most effective strategies, as also highlighted by the EU project CARBOTRAF [7], in which TC and variable message signs (VMSs) have been jointly used to reduce CO 2 and black carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design

Luca

Pace

Memoli³

et al. 2020

Sustainability

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This paper focuses on the presentation of an integrated framework based on two advanced strategies, aimed at mitigating the effect of traffic congestion in terms of performance and environmental impact. In particular, the paper investigates the “operational benefits” that can be derived from the combination of traffic control (TC) and route guidance (RG) strategies. The framework is based on two modules and integrates a within-day traffic control method and a day-to-day behavioral route choice model. The former module consists of an enhanced traffic control model that can be applied to design traffic signal decision variables, suitable for real-time optimization. The latter designs the information consistently with predictive user reactions to the information itself. The proposed framework is implemented to a highly congested sub-network in the city center of Naples (Italy) and different scenarios are tested and compared. The “do nothing” scenario (current; DN) and the “modeled compliance” (MC) scenario, in which travelers’ reaction to the information (i.e., compliance) is explicitly represented. In order to evaluate the effectiveness of the proposed strategy and the modeling framework, the following analyses are carried out: (i) Network performance analysis; (ii) system convergence and stability analysis, as well as the compliance evolution over time; (iii) and emissions and fuel consumption impact analysis.

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“…The mitigation of environmental impact due to the traffic congestion is still a difficult challenge to be pursued; the considered strategies usually refer to the Intelligent Transportation Systems ( [1], [2]) and in particular to the enhanced ecodriving technologies [6] or on the application of transport policies (demand or supply).…”

Section: Introductionmentioning

confidence: 99%

Comparing Signal Setting Design Methods Through Emission and Fuel Consumption Performance Indicators

Luca

Pace

Memoli

et al. 2016

Advances in Intelligent Systems and Computing

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In order to address the Signal Setting Design at urban level two main approaches may be pursued: the coordination and the synchronisation approaches depending on the steps considered for the optimisation of decision variables (two steps vs one step). Furthermore, in terms of objective functions mono-criterion or multi-criteria may be adopted. In this paper the coordination approach is implemented considering the multicriteria optimisation at single junctions and mono-criterion optimisation at network level whereas the synchronisation is implemented considering the mono-criterion optimisation. The main purpose of the paper is the evaluation of the performances of two strategies not only considering indicators such as the total delay, the queue length etc. but also considering other indicators such as the emissions and the fuel consumption. The methodological framework is composed by three stages: i) the decision variables (green timings and offsets) computation through optimisation methods; ii) the implementation of optimal signal settings in a microscopic traffic flow simulator (Simulation of Urban MObility"-SUMO); iii) the estimation of emissions and f u e l consumption indicators.

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Modelling the adoption intention and installation choice of an automotive after-market mild-solar-hybridization kit

Cited by 19 publications

References 113 publications

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

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

Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design

Comparing Signal Setting Design Methods Through Emission and Fuel Consumption Performance Indicators

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