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The development of larger more productive innovative heavy vehicle combinations for public road operations relies heavily on proving new vehicle concepts to both government and local authorities. In a number of cases simulation modelling has proved to be a useful tool in showing that proposed innovative heavy vehicle concepts are safer and more efficient alternative to conventional equipment. This paper provides examples of the use of AUTOSIM™ in developing custom yaw/roll and yaw/roll/pitch models for investigating the dynamic performance of combination vehicles. Models are described for large innovative road trains which incorporate B-doubles units. Consideration is given to the modeling of the trailing fidelity of these vehicles on non-planar surfaces and examples of model outputs for combination vehicles operating on various three-dimensional features are presented.

Performance measures such as static roll stability, rearward amplification and load transfer ratio are a means to assess the engineering performance of heavy vehicles and to support truck size and weight policy decisions. It was expected that, for a particular vehicle configuration, there would be some degree of correlation between the various performance attributes. For example, a relatively high static roll stability may be associated with a relatively low load transfer ratio, at least within a particular vehicle configuration. In terms of developing performance measures such correlations are of great significance because (i) the number of performance attributes requiring specification may be reduced and (ii) potential conflicts between performance criteria in different attributes may be avoided. This type of analysis has not been carried out before, and requires a large database of performance numerics in order to determine relationships between each of the performance attributes.

Heavy vehicles with high centres of gravity are prone to rollover accidents. For a given height and width, stability is affected by suspension design. In articulated vehicles, the matching of the tractor and trailer suspensions, as well as the degree of coupling between tractor and trailer, affects the stability of the combination. A number of loaded articulated combinations with high centres of gravity were tested on a specially-constructed tilt deck. Parameters including lateral load transfer at each axle group, deflections of the sprung and unsprung parts of the suspensions, movement at the fifth wheel coupling and torsional deflection of the chassis were measured up to the point of first wheel lift. A computer model of the rollover process was also developed. The effects of suspensions, couplings, tyres and chassis on the rollover limit are discussed.

Automated driving systems (ADSs) for road vehicles are being developed that can perform the entire dynamic driving task without a human driver in the loop. However, current regulatory frameworks for assuring vehicle safety may restrict the deployment of ADSs that can use machine learning to modify their functionality while in service. A review was undertaken to identify and assess key initiatives and research relevant to the safety assurance of adaptive safety-critical systems that use machine learning, and to highlight assurance concepts that could benefit from further research. The primary objective was to produce findings and recommendations that can inform policy and regulatory reform relating to ADS safety assurance.