The Relationship between Vehicle Impact Speed and Pedestrian and Cyclist Projection Distance

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Many factors affect pedestrian and cyclist injury risk in a vehicle collision, but the most important determinant is the vehicle impact speed. This has been observed empirically (see Chapter 2) and is also evident from a theoretical basis, see Chapter 7. Vehicle impact speed therefore has implications for legislators in designing speed limits for urban areas, for automotive engineers to reduce vehicle aggressivity and for biomechanics research into injury causation. It also has legal implications in determining culpability following a collision [1] and driver statements of vehicle speed are therefore unreliable and other independent methods to estimate vehicle impact speed have been proposed.

The methods frequently used to estimate vehicle speed include the use of witness statements, tyre skid marks on the road, impact locations/damage on the vehicle and pedestrian projection distance. However, witness statements are subjective, tyre skid marks are now less common due to ABS braking and impact locations/damage on the vehicle depend on the collision configuration and are unreliable predictors of vehicle speed [2]. An alternative method is therefore necessary, and the strong correlation between vehicle impact speed and the distance that impacted pedestrians and cyclists are projected in an impact has been known for over 30 years (e.g. [3]). Since then, a variety of methods have been proposed to estimate vehicle impact speed based on measurement of the pedestrian projection distance.1 This chapter presents accident investigation data relating to pedestrian and cyclist projection distances and a comparison is made with staged tests involving pedestrian/cyclist dummies and cadavers. A theoretical framework for modelling pedestrian impact and projection is then proposed, and a review of models in the literature is given. There are many such models, but emphasis is placed on those predicated on representing the mechanics of the collision event rather than on the many regression models based on staged tests or accident data.