Night Analysis

According to the NHTSA, approximately 55% of all motor vehicle crashes and 49% of all fatal collisions occur at nighttime, despite the fact that only 25% of travel occurs during hours of darkness. A variety of factors influence the causes of these accidents, making them unique from those occurring during the day. The impairments associated with darkness may be important in determining accident causation and assessing the potential for avoiding an accident. A comprehensive nighttime analysis approach requires a combination of standard accident reconstruction techniques and more specialized and human factors analyses to consider the effects of darkness on the events leading up to and during an accident. NBI’s experts are experienced in techniques for considering the effects of visibility conditions, and utilizing accident reconstruction and human factors approaches concurrently to provide a complete analysis of nighttime accidents.

The extent of lighting is an important factor in both reconstruction and human factors analysis of nighttime accidents, as a key component of visibility conditions. The amount and brightness of ambient light, such as provided by streetlights on a road or sidewalk, are important in the determination of visibility distance and the ability to detect objects along a travelling path. In cases involving motor vehicles, the extent of headlight illumination is an important additional factor in determining visibility limits. NBI’s experts perform scene inspections when conditions are similar to that of the given accident, in order to assess the amount and quality of light. Additionally, in motor vehicle collision cases, visibility distance in the striking vehicle may be assessed to better understand sight conditions at the time of an accident. This gathered information, in addition to the provided accident data, allows our experts to perform a comprehensive analysis of an accident, considering both general accident parameters and the effects of visibility at nighttime.

Standard accident reconstruction techniques, such as skid and momentum-based analyses when considering motor vehicle accidents, are primarily used for nighttime accidents, but additional consideration for pre-accident human behavior is often required. A person approaching a stopped car in limited visibility conditions may begin braking later than expected in daylight conditions, for example, due to an inability to see the obstacle from a greater distance. Pre-accident information may be gathered by our experts through a vehicle’s EDR, if available, or may be determined through a human factors-based analysis of the accident conditions. By considering effects of low nighttime visibility in addition to known facts, our reconstruction experts are able to provide a comprehensive analysis of the events leading up to an accident.

Human factors-based accident analysis provides information regarding the expected behavior before and during an accident. The increase in perception-reaction time in darkness, by as much as 1 – 2 seconds, is a major consideration when analyzing the human aspect of an accident. The delay in time for perception of and reaction to an obstacle caused by low visibility may be a predominant cause of an accident, as there may not be sufficient time to avoid collision by the time it is noticed. Darkness reduces contrast sensitivity and the ability to detect objects, and the unexpected nature of an obstacle may additionally delay reaction time, or cause a poor reaction. An understanding of these factors plays an important role in our expert’s determination of an individual’s expected pre-accident behavior, which may provide information for accident reconstruction analysis. Additionally, analysis of the scene, combined with accident parameters known through reconstruction analysis, such as speed, allows NBI’s human factors experts to comment on the expected ability of the driver to detect and perceive an obstacle, as well as their potential ability to react in order to avoid an accident.

Leading Expert

Felix Lee, MS, PE