Data Handling: Good Practices in the Context of Naturalistic Driving Studies

Naturalistic driving studies (NDS) have recently gained attention as a way of instrumenting vehicles in an unobtrusive way and collecting driving data over long periods of time. Aiming at eventually modeling driving behavior, NDS are often a part of larger scale studies. These studies involve several stakeholders who are responsible for...

Review and assessment of different perspectives of vehicle-pedestrian conflicts and crashes: Passive and active analysis approaches

The importance of investigating pedestrian safety has been evaluated repeatedly in safety studies. The present study attempts to evaluate the various methods used by previous researchers in a hierarchical process, to determine the characteristics, advantages, and limitations of each method. Two general analysis approaches (passive and active)...

ACC target performance setting via NDS big data analysis

Advanced Driving Assistance Systems (ADAS) technologies like Adaptive Cruise Control (ACC) are becoming the normality for many users, and many major car manufacturers are introducing SAE level 2 and 3 automation systems into the market. The main advantage of Automated Vehicles (AV) will be the significant decrease in road accidents and...

Validity and reliability of naturalistic driving scene categorization Judgments from crowdsourcing

A common challenge with processing naturalistic driving data is that humans may need to categorize great volumes of recorded visual information. By means of the online platform CrowdFlower, we investigated the potential of crowdsourcing to categorize driving scene features (i.e., presence of other road users, straight road segments, etc.) at...