Design and Testing of a Fuel Consumption Eco-Driving Coach System for Truck Drivers based on Geolocation and BI Technologies (original) (raw)
Related papers
Achieving energy-efficiency and on-time performance with Driver Advisory Systems
2013 IEEE International Conference on Intelligent Rail Transportation Proceedings, 2013
The development and use of Driver Advisory Systems (DAS) is a topic of growing importance in research and industry today as railways face continuous pressure and challenge to reduce operating costs, improve energy efficiency, increase capacity and minimize environmental impact. DAS provide advice to driver aiming for optimized traffic flow and energy efficient driving. Based on real-time data communication between trains and train control center in combination with a centralized system for calculation of optimal train movements, CATO (Computer Aided Train Operation) offers a state-of-art connected DAS allowing trains to run as efficiently as possible considering the overall traffic situation on a railway line. In order to develop a successful DAS, the requirements for practical operation have to be carefully evaluated and clearly understood before implementation. CATO has been successfully deployed in Sweden and won the UIC Innovation Award for sustainable development. This paper will describe our experiences of important factors needed to achieve a successful DAS deployment, such as humanmachine interaction issues, motivation factors, efficient communication and cooperation between train driver and dispatcher, good maintenance tools and continuous evaluation of the system performance.
A User Interactive and Assistive Fleet Management and Eco-Driving System
Today, in the era of Internet of Things, an enormous amount of research is going on in the direction of probing into vehicle’s engine control units for collecting kinematic and diagnostic information, analyzing and integrating them with software platforms and providing valuable services to drivers and passengers. This is largely facilitated by the car’s several sensors forming an in-vehicle network which communicates with cloud servers and acts as effective suppliers of massive data. With this objective of efficient data collection and analysis, in this paper, a framework for a low cost integrated web-based platform is proposed for On Board Diagnostic services, vehicle tracking, theft detection and evaluation of a vehicle’s performance in terms of fuel efficient driving behavior. A hardware and software tool for communication with vehicle and analysis purpose has been developed.
Renewable and Sustainable Energy Reviews, 2014
A large portion of energy consumption in the world is related to transportation. In recent decades, a variety of technologies have been innovated and applied in order to decrease vehicles energy consumption. In this paper, a comprehensive review on the use of driving data and traffic information for vehicles energy conservation is done. The main aim of this paper is the development of a framework for classification and comparative assessment of various methods and technologies, in which driving data or traffic information are utilized for vehicles energy conservation. The applications are classified into three main categories including (1) traffic monitoring and management systems, (2) intelligent energy management systems in vehicles and (3) intelligent management of charging issues. Research topics in each category are explained and their respective effectiveness in vehicles energy consumption reduction is discussed. The review concludes that the use of the driving data and traffic information leads to remarkable improvements in vehicles energy consumption reduction.
Design and Implementation of a CANBus-Based Eco-Driving System for Public Transport Bus Services
IEEE Access, vol. 8, no. 1, pp. 8114-8128, DOI: 10.1109/ACCESS.2020.2964119, 2020
Driving vehicles according to eco-driving principles and techniques have significant impact on decreasing both fuel consumption and carbon dioxide (CO 2) emissions. In addition to some kind of technical and/or mechanical features brought by today's new generation vehicles, driver behavior is also one of the greatest factors affecting the fuel consumption. Many studies show that the effect of eco-driving education on the drivers loses its impact in long term and there needs some sort of continuous monitoring and/or feedback mechanisms. This kind of driver monitoring becomes very critical especially in fleets composed of heavy-duty vehicles, such as municipality buses, truck fleets, etc. Moreover, in order to adapt behavior to drive more economically, information about instant fuel consumption has to be provided to the driver. Hence, in this paper, we introduce an eco-driving system in which data gathered from the controller area network (CANBus) of public transport vehicles are processed for both comparative and fair evaluation of bus drivers' eco-driving performance. Moreover, in-vehicle components of the system guide the drivers during their trips; provide feedbacks and real-time warnings considering the fuel consumption. Developed system was successfully deployed and evaluated in one of the public metrobus systems used by approximately 250000 passengers every day. Based on the 15-months evaluation period, the results are very promising in the sense that both drivers and operators found the system useful and the system provided fuel saving up to approximately 5% even in the short term of monthly comparisons. INDEX TERMS Controller area network (CANBus), eco-driving, eco-driving software, public transportation.
The development and demonstration of a real time vehicle performance and emissions monitoring system
2002
Problems posed by the environmental impact of transport are serious, growing and constitute a major challenge to policy makers at all levels. The current array of technological, institutional and planning tools available to deal with these problems are inadequate and need urgently to be upgraded. A key feature of these problems is that they arise from the interaction of human behavioural systems and physical systems. Thus, to improve our understanding of environmental and health problems associated with vehicle emissions, it is necessary to combine data on both travel and traffic behaviour with environmental data. This requires simultaneous data on travel, traffic and environmental variables. There are currently no such integrated databases available in the United Kingdom, and the inability to collect self-consistent traffic, travel and environmental data is a major impediment to the development of the necessary scientific underpinning for effective policy interventions. This paper presents a high level description of a real-time global positioning system based vehicle performance and emissions monitoring system currently under development in the United Kingdom, to contribute to the realisation of the data requirements highlighted above.
Truck Driver Behavior and Travel Time Effectiveness Using Smart GPS
Civil Engineering Journal, 2020
The pattern of coal transportation is very dependent on the behaviour of the driver, which influences the effectiveness of travel time. Good driver behaviour will affect the optimization of travel time, and scenarios need to reduce travel time wastage. This study aims to optimize travel time and sensitivity analysis based on the influence of driver behaviour, truck travel movements and the use of travel time on coal haul roads. The research method uses a field survey with a GPS tracker, a smart GPS server 3.3, google earth and statistics. The results showed that the driver's behaviour greatly influenced the pattern of use of travel time and truck travel speed. Coal transportation in the morning can be more optimal than night so that that travel time wastage can reduced by 40%. The proposed optimization scenarios can save 36.7% - 48.61% of the existing travel time and the transport cycle can be increased to four to five times. So that with the addition of the cycle, it will incre...
E3S web of conferences, 2021
According to the current issue of resource shortage, the reduction of fuel consumption or using alternative energies which has an environmentally friendly effect is the priority of governments in many countries. Besides, many studies mentioned that driver behaviors play an essential role to reduce fuel use and decrease vehicle exhaust emissions. On the other hand, the car-GPS tracking data in itinerary monitoring equipment is typically using in navigation, positioning, and vehicle management. Thus, this study aims to analyze the correlation between driver behaviors and fuel consumption based on the velocity, acceleration, fuel sensors data collected from car-GPS trackers device in association with Geographic Information System (GIS) to find out the solution to evaluate the effectiveness of ecodriving courses as well as assess the usability of using car-GPS tracking data from the GPS tracking device to analyze and adjust driver behavior in urban areas to save energy and protect the urban environment
The Foresight Vehicle Performance and Emissions Monitoring System
Problems posed by the environmental impact of transport are serious, growing and constitute a major challenge to policy makers at all levels. The current array of technological, institutional and planning tools available to deal with these problems are inadequate and need urgently to be upgraded. A key feature of these problems is that they arise from the interaction of human behavioural systems and physical systems. For example, the risks to health posed by motor vehicle emissions depend upon the number of people who spend time in areas of light and heavy traffic. But at the same time, the volume of traffic in different areas of a city is a reflection of the spatio-temporal patterns of individual driver's travel choice. Thus, to improve our understanding of environmental and health problems associated with vehicle emissions, it is necessary to combine data on both travel and traffic behaviour with environmental data. This requires simultaneous data on travel, traffic and environmental variables. There are currently no such integrated databases available in the UK, and the inability to collect self-consistent traffic, travel and environmental data is a major impediment to the development of the necessary scientific underpinning for effective policy interventions.
Nowadays, the improvement of communication technologies is widely applied to reduce energy use in cars. Several ecodriving application already appeared on the market. They consist in providing a feedback to the drivers describing their ecodriving behavior and they rely on embedded sensors signals (GPS speed and acceleration). However most of these applications does not take into account upcoming events such as curves, slopes or crossings to advise the driver on the best actions to undertake to lower energy consumption. Furthermore, they do not analyze data coming from vehicle sensors. In this paper, we present an application, developed within the FP7 European project ecoDriver, that provides several innovative properties: advice according to upcoming events, a real time evaluation of the driving behavior, the analysis of past actions, an interface with OBD2 connector, ... This paper further develops the complete architecture and links between each innovative function. Future works w...