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Driver behaviour can strongly affect fuel consumption, and driver training in eco-driving techniques has been shown to reduce fuel consumption by 10% on average. However the effects of this training can be short-lived, so there is an apparent need for continuous monitoring of driver behaviour. This study presents a driver advisory tool which encourages eco-driving, and its evaluation in the field. The system, developed by Ashwoods Automotive Ltd (UK) and the University of Bath (UK), is aimed at fleet operators of light commercial vehicles, where the driver is typically a company employee. A significant strength of the system is that it has been designed for easy integration with the vehicle CAN-bus, reducing complexity and cost. By considering the Inertial Power Surrogate (speed times acceleration) the core algorithm is able to identify behaviour which is likely to increase fuel consumption.

The Advanced Lighting Simulation (ALS) is a development tool for systematically investigating and optimizing the Adaptive Light Control (ALC) system to provide the driver with improved headlamps and light distributions. ALS is based on advanced CA-techniques and modern validation facilities. To improve night time traffic safety the BMW lighting system ALC has been developed and optimized with the help of ALS. ALC improves the headlamp illumination by means of continuous adaptation of the headlamps according to the current driving situation and current environment. BMW has already implemented ALC prototypes in real vehicles to demonstrate the advantages on the real road.

Precise, repeatable and representative testing is a key tool for developing and demonstrating automotive fuel and lubricant products. This paper reports on the first findings of a project that aims to determine the requirements for highly repeatable test methods to measure very small differences in fuel economy and powertrain performance. This will be underpinned by identifying and quantifying the variations inherent to this specific test vehicle, both on-road and on Chassis Dynamometer (CD), that create a barrier to improved testing methods. In this initial work, a comparison was made between on-road driving, the New European Drive Cycle (NEDC) and World harmonized Light-duty Test Cycle (WLTC) cycles to understand the behavior of various vehicle systems along with the discrepancies that can arise owing to the particular conditions of the standard test cycles.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

When investigating the posture comfort in vehicles two important influencing factors can be distinguished: In order to evaluate these influences a combined laboratory-field-experiment was carried out. A real car was equipped with cameras to record the body posture and the joint angles. The static forces exerted by the driver on his contact points were recorded in a corresponding mock-up. The forces to maintain the body posture were calculated. The following results were found:

Electric coolant pumps for IC engines are under development by a number of suppliers. They offer packaging and flexibility benefits to vehicle manufacturers. Their full potential will not be realised, however, unless an integrated approach is taken to the entire cooling system. The paper describes such a system comprising an advanced electric pump with the necessary flow controls and a supervisory strategy running on an automotive microprocessor. The hardware and control strategy are described together with the simulation developed to allow its calibration and validation before fitting in a B/C class European passenger car. Simulation results are presented which show the system to be controllable and responsive to deliver optimum fuel consumption, emissions and driver comfort.

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver''s chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features.