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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.

Impact noise, inside a car, due to tire-launched gravel on the road can lead to loss of quality perception. Gravel noise is mainly caused by small-sized particles which are too small to be seen on the road by the driver. The investigation focuses on the identification of the mechanisms of excitation and transfer. The spatial distribution of the particles flying from a tire is determined, as well as the probable impact locations on the vehicle body-panels. Finally the relative noise contributions of the body-panels are estimated by adding the panel-to-ear transfer functions. This form of Transfer-Path-Analysis allows vehicle optimization and target setting on the level of the tires, exterior panel treatment and isolation.

Tire-road interaction is one of the main concerns in the design of control strategies for active/semi-active differentials oriented to improve handling performances of a vehicle. In particular, the knowledge of the friction coefficient at the tire-road interface is crucial for achieving the best performance in any working condition. State observers and estimators have been developed at the purpose, based on the measurements traditionally carried out on board vehicle (steer angle, lateral acceleration, yaw rate, wheels speed). However, until today, the problem of tire-road friction coefficient estimation (and especially of its maximum value) has not completely been solved. Thus, active control systems developed so far rely on a driver manual selection of the road adherence condition (anyway characterized by a rough and imprecise quality) or on a conservative tuning of the control logic in order to ensure vehicle safety among different tire-road friction coefficients.

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.

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.

This work focuses on the analysis of the vertical dynamics of an agricultural tractor, investigating the influence of suspensions' parameters on riding comfort and contact forces. The use of lugged tires coupled with the operation over banked, irregular and deformable tracks, determines significant levels of vertical acceleration over several components of the tractor. These operating conditions have a direct effect on the driver, whose alertness and efficiency are undermined by the exposure to high levels of acceleration for a long time. Secondly, variations of the normal and traction forces provided by the tires affect the quality of tillage and other operations. The paper presents a multi-body vehicle model of a tractor interfaced with a tire-soil contact model allowing to take into account soil's deformation and tread pattern design.

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:

We introduce in this paper a new Instrumented Steering Wheel (ISW) for ADAS development. The ISW has been designed, constructed and employed with satisfactory results. The ISW is able to measure three forces, three moments and the grip force at each hand of the driver. The ISW has been used for ADAS activities on an instrumented road vehicle. The aim was to use both the vehicle states and the ISW data for evaluating the driver behaviour. Two research activities were performed. The first activity refers to monitoring the driver behaviour during tests on a track. The second activity refers to the use of haptic ISWs, able to improve the ADAS systems. Referring to the first activity, the greatest majority of drivers applied always the same sequence of forces (pull, radial, tangential) either during emergency manoeuvres, either during slow speed curving.

By the action on the steering wheel, the driver has the capability to control the trajectory of its vehicle. Nevertheless, the steering wheel has also the role of information provider to the driver. In particular, the torque level at the steering wheel informs the driver about the interaction between the vehicle and the road. This information flow is natural due to the mechanical chain between the road and the steering wheel. Many studies have shown that steering wheel torque feedback is crucial to ensure the control of the vehicle. In the context of uncoupled steering (steer-by-wire vehicle or driving simulators), the torque rendering on the steering wheel is a major challenge. In addition, of the trajectory control, the quality of this torque is a key for the immersion of drivers in virtual environment such as in driving simulators. The torque-rendering loop is composed of different steps.

The rising environmental awareness has led to a growing interest in electric and lightweight vehicles. Four-wheeled Ultra-Efficient Lightweight Vehicles (UELVs) have the potential to improve the quality of urban life, reduce environmental impact and make efficient use of land. However, the safety of these vehicles in terms of dynamic behaviour needs to be better understood. This paper aims to provide a quantitative assessment of the handling behaviour of UELVs. An analytical single-track model and a numerical simulation by VI-CarRealTime are analysed to evaluate the dynamic performance of a UELV compared to a city car. This analysis shows that the lightweight vehicle has a higher readiness (i.e. lower reaction time to yaw rate) for step steering and lower steering effort (i.e. higher steady-state value). Experimental analysis through real-time driving sessions on the Dynamic Driving Simulator assesses vehicle responses and subjective perception for different manoeuvres.

Renault believes that the behavior of the vehicle must always be consistent with the instantaneous orders given by the driver, whether braking, accelerating or lifting the foot off the accelerator. The vehicle must also inform its driver when it is near a point of limit. The first part of this paper details the vehicle with respect to its trajectory at stabilized speeds. The rigidity of the overall drift of the axle assemblies and tires, the steering angles induced by vehicle roll attitude, under- and over-steering behavior and vehicle roll attitude, under- and over-steering behavior and behavior of the tire under load are covered. A vehicle trajectory model is used to confirm test results.

The paper deals with the bifurcation analysis of a simple mathematical model describing an automobile running on an even surface. Bifurcation analysis is adopted as the proper procedure for an in-depth understanding of the stability of steady-state motion of cars (either cornering or running straight ahead). The aim of the paper is providing the fundamental information for inspiring further studies on vehicle dynamics with or without a human driver. The considered mechanical model of the car has two degrees of freedom, nonlinear tire characteristics are included. A simple driver model is introduced. Experimental validations of the model are produced. As a first step, bifurcation analysis is performed without driver (fixed control). Ten different combinations of front and rear tire characteristics (featuring understeer or oversteer automobiles) are considered. Steering angle and speed are varied. Many different dynamical behaviors of the model are found.