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Cognitive work analysis for safe and efficient driving

Cognitive work analysis for safe and efficient driving

In order to achieve its goals of changing driving style while avoiding negative effects of distraction or workload, the in-car interface in particular needs to be designed with the driver’s information requirements in mind. The research presented in this paper is part of a wider workpackage specifically focused on the ergonomics of the product – determining the driver behaviour parameters by conducting a cognitive work analysis, and designing an interface to optimise performance. There is already much research in ergonomics regarding driving safety, with a lot of attention on advanced driver assistance systems (ADAS). Many authors have commented on the potential positive (Carsten & Tate, 2005; Shinar et al, 1998) and negative (Dominez et al, 2007; Young and Stanton, 2007) effects of such devices on driver performance, and models of human interaction with technology are abundant. However, to date there has been relatively little ergonomics research dedicated to improving performance factors specifically related to environmental impact. Moreover, these factors need to be traded off against their impact on safety. In driving, there may be specific behaviours which are both safe and ‘green’; likewise, there may be occasions when these goals are in conflict. Enabling drivers to develop the skills for managing these conflicts is a challenge for ergonomics. Before decisions on any particular technology solution can be made, the project needs to assess the system’s purposes, values, priorities and functions by undertaking a systems-led approach where both technical and human system components are equally as important.
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SAVING FUEL. Safe and fuel efficient driving tips for trucks and buses. Supported by

SAVING FUEL. Safe and fuel efficient driving tips for trucks and buses. Supported by

The SAFED NZ course is a full day training course, which includes practical driving assessments, theory-based exercises covering accident prevention and reduction, and fuel effi cient driving styles. Below are some checklists to help fl eet managers and drivers improve fuel effi ciency.

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Efficient Driving Forces to CMMI Development using Dynamic Capabilities

Efficient Driving Forces to CMMI Development using Dynamic Capabilities

The Capability Maturity Model Integration CMMI provides models for acquiring products CMMI-ACQ, models for quality services CMMI-SRV, and models for development CMMI-DEV.. The CMMI follo[r]

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Energy Efficient Hybrid System For Comfortable and Ecofriendly Driving in Metropolitan Cities

Energy Efficient Hybrid System For Comfortable and Ecofriendly Driving in Metropolitan Cities

*Energy-efficient driving, using the gas/petrol engine as the main power source Hybrid vehicles use the gas/petrol engine in the speed range in which it operates with good energy efficiency. The power produced by the gas/petrol engine is used to drive the wheels directly, and depending on the driving conditions, part of the power is distributed to the generator. By making use of the engine/motor dual powertrain, the energy produced by the gas/petrol engine is transferred to the road surface with minimal loss.

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Design, Development and Test of a Practical Train Energy Optimization using GA-PSO Algorithm

Design, Development and Test of a Practical Train Energy Optimization using GA-PSO Algorithm

One of the strategies for reduction of energy consumption in railway systems is to execute efficient driving by presenting optimized speed profile considering running time, energy consumption and practical constraints. In this paper, by using real route data, an approach based on combination of Genetic and Particle swarm (GA-PSO) algorithms in order to optimize the fuel consumption is provided. The model of train takes into account the length and mass of train, running resistance, tractive effort curves for each notch, signaling system, variations of the motor efficiency with respect to speed and effort ratio, auxiliary equipment consumption and rotary inertia. The route characteristics included in the model are speed limits, gradients, gradient transitions (and its effect along the train) and curves. GA-PSO algorithm combining the benefits of both the original algorithms GA and PSO is validated by formulating the optimization problem. The GA-PSO performance is evaluated by comparing it with a GA algorithm. Further, it is used for obtaining the optimal speed profiles for a locomotive equipped with a GT26CW engine on Tehran- Tappe_sefid block.
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Pocket Guide. Fuel Saving Tips

Pocket Guide. Fuel Saving Tips

When it comes to delivering fuel economy, the driver is king. For the vehicle operator the benefits of fuel efficient driving style are not just lower fuel bills but also lower maintenance costs and lower insurance costs. The best way to illustrate this is with real-life examples.

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Efficient taxation of fuel and road use

Efficient taxation of fuel and road use

Many countries have implemented taxes on fuel to curb externalities linked to both fuel and mileage. However, the tax-induced gain in terms of reduced externalities is diminished as less than half of the reduction in fuel use is due to reduced driving, see Parry and Small (2005) which argue that the optimal tax rates on gasoline are reduced accordingly. The remaining reduction is due to improved fleet fuel efficiency. Fleet fuel efficiency improves as households avoid the mileage-related tax component on fuel by purchasing more fuel-efficient vehicles. Bjertnæs (2019) however shows that such avoidance should be prevented by imposing heavier taxation of fuel-efficient vehicles compared to fuel-intensive vehicles, and hence, that it is sub-optimal to lower the tax rate on gasoline. However, fleet fuel efficiency also improves as households choose a more fuel-efficient driving-style. The tax on fuel may create an incentive to save fuel rather than lowering mileage-related damage. The present study contributes to the literature by exploring how taxes on fuel and road use should be designed to combat driving related externalities when agents choose driving-style.
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The Virtual Driving Coach - design and preliminary testing of a predictive eco-driving assistance system for heavy-duty vehicles

The Virtual Driving Coach - design and preliminary testing of a predictive eco-driving assistance system for heavy-duty vehicles

Purpose The commercial vehicle sector is characterized by high competitive pressure. Fuel consumption is one major factor that influences the transport efficiency and competitive- ness of logistics companies. Therefore, an eco-driving assis- tance system (EDAS) is developed in order to support the driver in sustainably maintaining an efficient driving style— the Virtual Driving Coach (ViDCo). In this paper, we describe the design and development process of ViDCo as well as results of the first steps of evaluation and preliminary testing. Methods An EDAS is developed that uses knowledge of in- frastructure based on digital maps in order to proactively and predictively provide the driver with driving advice. The sys- tem’s algorithms are structured within the modules Bsituation detection^, Bdriving error detection^, and Bmessage filtering and prioritization ^ . The evaluation of ViDCo comprises pre- liminary field-testing on public roads as well as a driving simulator experiment.
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Reducing driving forces for pressed-in piles

Reducing driving forces for pressed-in piles

Pile jacking techniques use static loading to install sheet piles with minimal environmental effects, such as noise and ground vibrations, which are often associated with other methods of driven piling. This paper describes a series of 20g centrifuge tests conducted to investigate two methods of reducing the large driving forces that can be associated with jacked sheet piles in stiff clay. In practice, pre-auguring at the clutch positions and water jetting techniques are routinely carried out prior to the installation of sheet piling in order to reduce the driving forces. However, these methods are known to contribute to ground movements and can detract from the advantages of jacked sheet piles. The tests involved driving model sheet piles, which were modified either by installing driving shoes to the base of the pile, or by ribbing the profile of the pile shaft. The driving forces of the modified piles were compared with those of a plain pile. The tests showed that the use of driving shoes and ribs can lead to the reduction of driving forces at greater depth.
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Learning to drive in young adults with language impairment

Learning to drive in young adults with language impairment

Finally, international evidence over the last couple of decades points to substantial and ongoing reductions in the propor- tions of contemporary young people who are learning to drive, compared to earlier generations (Delbosc & Currie, 2013; Noble, 2005; Sivak & Schoettle, 2016). The reasons for this are multifaceted, and include rising costs (of lessons, vehicles, fuel, insurance), changing social patterns (such as increased peer contact via social media), but one factor highlighted by Noble (2005) was that the introduction of theory tests had led to approximately one year’s delay in the progress of young people in general towards obtaining licences. The present findings resonate with this point, suggesting that those with LI are particularly likely to be affected by this requirement. We are indebted to an anonymous reviewer for pointing out that it is also possible that the wider contextual dynamics may influence the behavioural decisions of those with LI (for example, by making it more acceptable in the peer community not to seek or have acquired a licence). Hence, it would be valuable in future large sample studies to take account of developmental disabilities such as LI (but also ADHD, dyslexia, and other con- ditions) to examine whether these young people contribute disproportionately to the numbers of the non-licensed or later- licensed. This is important not simply for comparison purposes but because length of driving experience is a predictor of driving skill (Mayhew, Simpson, & Pak, 2003; Wikman, Nieminen, & Summala, 1998). In sum, entry to driving is challenging for young people with LI and, as a group, they do not all proceed at the same rate as AMPs. This study indicates that, as antic- ipated, the difficulties of those with LI tend to arise in relation to the language/textual demands of learning and being tested. In the UK, the theoretical test appears to be the primary locus of difficulties. For those with LI who overcome this hurdle, there is no evidence here that they begin their driving careers as more risky or more rule violating than peers without LI; contrary to expectations, those who do learn to drive and possess licences are no less confident in driving. The main policy implication of these findings is that, to ensure that young people with LI experience the same opportunities as other young people to achieve autonomous road use, it would be desirable to inquire specifically about any language, reading or commu- nication needs young people may have. With such information the facilities to help individuals with disabilities and special needs can be extended to provide language support and to consider where testing procedures might be adapted to accom- modate language needs.
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How To Sentence For Drunk Driving In Canada

How To Sentence For Drunk Driving In Canada

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Learning to drive in young adults with language impairment

Learning to drive in young adults with language impairment

Finally, international evidence over the last couple of decades points to substantial and ongoing reductions in the propor- tions of contemporary young people who are learning to drive, compared to earlier generations (Delbosc & Currie, 2013; Noble, 2005; Sivak & Schoettle, 2016). The reasons for this are multifaceted, and include rising costs (of lessons, vehicles, fuel, insurance), changing social patterns (such as increased peer contact via social media), but one factor highlighted by Noble (2005) was that the introduction of theory tests had led to approximately one year’s delay in the progress of young people in general towards obtaining licences. The present findings resonate with this point, suggesting that those with LI are particularly likely to be affected by this requirement. We are indebted to an anonymous reviewer for pointing out that it is also possible that the wider contextual dynamics may influence the behavioural decisions of those with LI (for example, by making it more acceptable in the peer community not to seek or have acquired a licence). Hence, it would be valuable in future large sample studies to take account of developmental disabilities such as LI (but also ADHD, dyslexia, and other con- ditions) to examine whether these young people contribute disproportionately to the numbers of the non-licensed or later- licensed. This is important not simply for comparison purposes but because length of driving experience is a predictor of driving skill (Mayhew, Simpson, & Pak, 2003; Wikman, Nieminen, & Summala, 1998). In sum, entry to driving is challenging for young people with LI and, as a group, they do not all proceed at the same rate as AMPs. This study indicates that, as antic- ipated, the difficulties of those with LI tend to arise in relation to the language/textual demands of learning and being tested. In the UK, the theoretical test appears to be the primary locus of difficulties. For those with LI who overcome this hurdle, there is no evidence here that they begin their driving careers as more risky or more rule violating than peers without LI; contrary to expectations, those who do learn to drive and possess licences are no less confident in driving. The main policy implication of these findings is that, to ensure that young people with LI experience the same opportunities as other young people to achieve autonomous road use, it would be desirable to inquire specifically about any language, reading or commu- nication needs young people may have. With such information the facilities to help individuals with disabilities and special needs can be extended to provide language support and to consider where testing procedures might be adapted to accom- modate language needs.
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Efficient Eco-driving Strategies at Signalized Intersections Based on Engine Fuel Cut-off of a Vehicle

Efficient Eco-driving Strategies at Signalized Intersections Based on Engine Fuel Cut-off of a Vehicle

II. F UEL C ONSUMPTION IN A V EHICLE This section reviews fuel consumption characteristics of a vehicle in order to understand the eco-driving principles. Normally, once an engine is turned on, it continues rotating until its switch is turned off. Even when the accelerator pedal is not pressed at idling, fuel is automatically injected to rotate the engine at a marginal speed. Fuel consumption of a vehicle depends on torque, the twisting or rotating force that the engine exerts on the crankshaft, and rotational speed (given in round per minute or rpm) of the engine [14, 15]. The typical engine torque-speed characteristic curves of a vehicle are shown in Fig. 1. The constant efficiency of the engine is shown by the elliptical curves. The constant power curves in the map are obtained as the product of torque and the rotational speed of the engine.
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THE IMPACT OF TEXT DRIVING ON DRIVING SAFETY

THE IMPACT OF TEXT DRIVING ON DRIVING SAFETY

In the hand-held part of the experiment, participants held their own smartphones in their hand; and they received, read, and responded to text messages with varying levels of context complexity while driving. The participants were asked to use their personal smartphones to eliminate any variation caused by using an unfamiliar smartphone. In the hands-free part, participants did not touch either their smartphones or any button. The texts were read aloud to them by a computerized voice which was created to mimic the interaction that would occur with an integrated Bluetooth hands-free audio system which is common in modern automobiles. Using simple voice commands, participants received and sent text messages vocally. The sequence of prompts simulates the hands-free audio systems in the modern automobiles. A computerized voice notified the driver: “You have received a new message. Do you want me to read it, yes or no?” The driver simply would say, “Yes” in order to vocally receive the text message. After listening to the text, the drivers were asked, “Do you want to respond?” Then the driver based on forms of the text message, read-only or respond-required, would answer.
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ERP Driving and Cloud Mobility Driving It

ERP Driving and Cloud Mobility Driving It

A major shift has been taking place over the last few years in how enterprises run their businesses and how employees prefer to perform their tasks and duties. Manufacturers are hedging their bets in an uncertain economic environment on elastic provisioning and pay-as-you-go models for infrastructure and services. Innovation is driving wedges into rigid, time- tested systems and delivery models. An increasing number of manufacturers have begun to take some of their basic ERP functions to cloud.

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6 th annual PIN Conference

6 th annual PIN Conference

The new approach Normal driving Normal driving Deviation from normal driving Deviation from normal driving Emerging situation Emerging situation Critical situation Critical situati[r]

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Driving Transformation to Energy Efficient Buildings: Policies and Actions. Program Manager, Institute for Building Efficiency

Driving Transformation to Energy Efficient Buildings: Policies and Actions. Program Manager, Institute for Building Efficiency

designed building will be easier to keep cool on hot days and warm on cold days so occupants will be more comfortable if there are more extreme weather conditions. There are exteriors of buildings that are energy efficient that can reduce heat gain in the summer and better handle heat waves, help avoid some of the urban heat island effect. Often energy-efficient buildings will use the more passive cooling techniques, which can really help also with that heat island effect in the summer. So there are a number of benefits, sort of co-benefits of having energy-efficient buildings that if they're designed into those buildings can also be part of the picture of cities of the future. Going on to the next slide, this slide gives an overview of what we tried to accomplish in this report. If you look on the left, it represents the way that our cities and our buildings are being built today and that — and all of the stakeholders that are involved in that process. Over on the right you see the vision that we’d all like to see in the future where our buildings are more energy efficient and there are a number of barriers to getting there today. There are market barriers, financial barriers, technical barriers, awareness barriers, institutional barriers and I’ll talk a little bit more about each of those. You'll be able to read a lot more about them in the report itself. The real idea of the report was to look at the government policies that can help bridge that gap, that can help overcome those barriers and it's combination of policies that in any given location will really help transform the market to open up this possibility for more energy-efficient buildings which in the long term are more cost effective but often will have some upfront costs.
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Driving Behaviour Classification : An Eco driving Approach

Driving Behaviour Classification : An Eco driving Approach

Fleet management is defined as the organisation and management of commer- cial vehicles such as cars and trucks. The main objectives of fleet management are to reduce costs, improve efficiency and ensure compliance of the regulations across the entire fleet. Fuel alone accounts for 33% of the fleet’s operating costs [6]. To improve the fuel efficiency, companies invest in training the driver by gathering the data from the trips driven by them. Based on the trip’s data, feedback is provided to the driver for improving the efficiency. Surveys conducted in [7] shows that the feedback given to the drivers are qualitative in nature, and lacks quantitative sug- gestions. Qualitative suggestions are based on the observations made on the driving behaviour such as "efficient" or "inefficient". Quantitative suggestions generally re- fer to a value, score or a rating. One of the reasons for the feedback to be qualitative is the excessive amount of processing involved in quantitative analysis to generate a score or rating. This excessive processing is present due to the large number of parameters that describe the driver’s profile.
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The activation of eco driving mental models: can text messages prime drivers to use their existing knowledge and skills?

The activation of eco driving mental models: can text messages prime drivers to use their existing knowledge and skills?

et al. 2001; Waters and Laker 1980). However, no signifi- cant effects on fuel consumption could be found, neither for the entire Drives, nor regarding the cruising scenario sepa- rately. This could be attributed to inefficient behaviours such as driving too slowly, for example below a speed limit of 30 mph (Samaras and Ntziachristos 1998), and accelerating too mildly (Mensing et al. 2013, 2014). In a questionnaire study by McIlroy and Stanton (2017), 11.8% of the respond- ents were incorrectly stating low speeds as eco-driving prac- tice, while 10.6% worry about the impacts on travel time. The nature of the driving scenarios could have played a role as well, as they did not provide many opportunities to plan behaviour ahead. For example, slowly approaching a junc- tion with red traffic lights did not prevent the participants from stopping, because the scenario was designed for the car to stop. Similarly, events such a car crossing the road were triggered by the participants’ approach. Hence, their effect on speed fluctuations could not be avoided with anticipa- tory behaviours. At last, the fuel consumption modelling with PHEM could have contributed to the lack of effects for several reasons. The model is based on real-world measure- ments, which might not have been exact, the approximations in the simulator’s vehicle rendering as well as the assump- tions regarding the used vehicle model and type.
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Cambridge Junior College DRUG AND ALCOHOL PREVENTION PROGRAM NOTICE TO STUDENTS AND EMPLOYEES

Cambridge Junior College DRUG AND ALCOHOL PREVENTION PROGRAM NOTICE TO STUDENTS AND EMPLOYEES

California’s drunk driving law is also a drug driving law. It refers to "driving under the influence of alcohol and/or drugs." If an officer suspects that you are under the influence of drugs, the officer can legally require you to take a breath, blood or urine test. Drivers who refuse these tests are subject to longer license suspensions and revocations.

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