This paper takes an overall view of findings from the Positive Soundscape Project, a large inter-disciplinary soundscapes study. Qualitative fieldwork (soundwalks and focus groups) have found that soundscape perception is influenced by cognitive effects such as the meaning of a soundscape and its components, and how information is conveyed by a soundscape, for example on the behaviour of people within the soundscape. Three significant clusters were found in the language people use to describe soundscapes: sound sources, sound descriptors and soundscape descriptors.Results from listening tests and soundwalks have been integrated to show that the two principal dimensions of soundscape emotional response seem to be calmness and vibrancy. Further, vibrancy seems to have two aspects: organisation of sounds and changes over time. The possible application of the results to soundscape assessment and design are briefly discussed.
Driver training schemes and eco-driving techniques can reduce fuel consumption by 10%, but their effectiveness depends on the willingness of drivers to change their behavior, and changes may be short lived. Onboard driver assistance systems have been proposed, which encourage driving style improvement. Such systems, when fitted in commercial vehicles, can assume some authority since uneconomical driving styles can be reported to a fleet manager. A driver assistance system has been developed and tried in the field with commercial vehicle drivers. The system aims to reduce fuel consumption by encouraging two behaviors: reduced rates of acceleration, and early upshifting through the gears. Visual feedback is reinforced with audible warnings when the driver makes uneconomical power demands of the engine. Field trials of the system were undertaken in the U.K. using 15 light commercial vehicles, driven by their professional drivers from a range of commercial applications. The trials consisted of two-week baseline data collection, which drivers were not aware of, followed by two weeks of data collection with the system being active. During the trials a total of 39 300 km of trip data were collected, which demonstrated fuel savings of up to 12% and average fuel savings of 7.6%.Index Terms-Driver behavior, driver information systems, eco-driving, fuel economy, gear shift indicator (GSI), vehicle driving.
A number of technologies have been introduced into new automobiles with the aim of reducing CO 2 emissions. One method of improving fuel consumption is to improve driver behaviour, since eco-driving techniques can help save 10-15% of fuel. A retro-fittable driver behaviour improvement device has been developed and tested in real world conditions. The device provides real-time audio and visual feedback to the driver to improve his/her driving style. It was tested on 15 vans belonging to various companies in the UK and over 39,000km of data was collected. It was observed that use of the device saved an average 7.6% of fuel. Further analysis showed that the savings were obtained as a result of improvement in driving behaviour through reduction in harsh accelerations and early gear shifting into higher gears. There was also a reduction in the pedal busyness of drivers with the system fitted. A model was created using the data obtained to predict the fuel savings that can be achieved if the device is fitted onto a new vehicle.
The real-world fuel economy of vehicles is becoming increasingly important to manufacturers and customers. One of the major influences in this is driver behaviour, but it is difficult to study in a controlled and repeatable manner. An assessment of driver models for studying real-world driver behaviour has been carried out. It has been found that none of the currently existing driver models has sufficient fidelity for studying the effects of real-world driver behaviour on the fuel economy of the individual vehicle. A decision-making process has been proposed which allows a driver model with a range of driving tasks to be developed. This paper reports the initial results of a driver model as applied to the conceptually straightforward scenario of high-speed cruising. Data for the driver model have been obtained through real-world data logging. It has been shown that the simulation driver model can provide a good representation of real-world driving behaviour in terms of the vehicle speed, and this is compared with a number of logged driver speed traces. A comparison of the modelled fuel economy for logged and driver model real-world drivers shows good agreement.
With the increasing awareness and adoption of ecofriendly vehicle technologies such as hybrid electric vehicles (HEVs); most if not all major worldwide vehicle manufacturers have released an eco-friendly vehicle or have announced a future release (e.g. concept demonstrator vehicles). Such vehicles can meet current legislative emissions standards (with comparatively lower CO 2 tailpipe emissions compared to conventional combustion engine vehicle equivalents), yet performance in the real world is often far worse than quoted test figures (e.g. fuel economy).
In order to maintain and grow customer acceptance of such vehicle technologies it is important that real world usage is considered during the design and development processes. This paper describes the method of selecting a suitable all electric range (AER) to meet both legislative emissions and real world usage demands and demonstrates its use through a case study of a lightweight plug-in hybrid electric vehicle (PHEV).
Keywords-All Electric Range (AER); Electric Vehicle (EV);Hybrid Electric Vehicle (HEV); Plug-in Hybrid Electric Vehicle (PHEV); State-of-Charge (SoC); Well-to-Wheel (WTW) CO 2
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