The aim of this project is to predict vehicle stopping distances for various types of braking conditions. A comprehensive vehicle braking model has been developed. The influences of several factors involved during braking are computed in this model with emphasis on the effects of tyres, brakes, suspensions, environment and driver. The model using experimental data from field sources has been validated. The model results in accurate stopping distance values (i.e. simulation outputs always remain within close range of track test stopping distances). By predicting stopping distances under given sets of vehicle, driver and environmental conditions, this model enables quick and accurate estimation of vehicle braking behaviour and capability.
Simulation of the sequence of dynamic events causing a vehicle to rollover could provide insight on the vehicle propensity to roll. It can also help in adapting control approaches to avoid vehicle rollover. Two analytical formulations of a similar vehicle modelling approach that reproduces the roll motion of a vehicle, including suspensions and tires, are derived. The effect of tire lift off during heavy cornering manoeuvres is considered. Disturbances such as lateral acceleration and road inputs causing vehicle roll can be applied. Critical vehicle dynamic conditions are simulated using the commercial human vehicle environment (HVE) three-dimensional simulation software and applied as inputs to the derived vehicle roll models. The vehicle dynamic behaviour simulated was validated by comparing with results from HVE. These models can serve as useful tools for testing vehicle roll stability algorithms for active suspension systems and for developing new anti-roll control strategies.
Intelligent speed adaptation (ISA) systems are in-vehicle systems that have the capability of either warning drivers of adverse speeding behaviours or limiting them from exceeding a prevailing speed limit or advisory. The former, called the warning-informational ISA system, has been noted to be ineffective in reducing speeding while being acceptable to drivers. However, the limiting ISA system, called the mandatory ISA system, has been effective in reducing speeds, yet highly unacceptable from research conducted largely in Europe. These tests of ISA systems have shown that there is a significant consumer acceptance hurdle on the one hand, and an efficacy hurdle on the other. This paper presents the results of a driving simulator experiment that tested the acceptance and effectiveness of a new type of ISA system, called the advanced vehicular speed adaptation system (AVSAS). AVSAS was designed as a speed-management system, rather than a speed-limiting system, based on individual driver speeding behaviours under different roadway scenarios. Statistical analyses were conducted to determine the effectiveness of AVSAS while a survey was used to gauge the acceptance of the system. The results showed that AVSAS contributed to the reductions in the drivers' speeds for two roadway scenarios. The survey results revealed a higher acceptance rating of AVSAS.
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