Data-driven Semi-supervised Machine Learning with Surrogate Safety Measures for Abnormal Driving Behavior Detection

Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers' behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection. Most existing ML-based detectors rely on (fully)...

Behavioral adaptations of human drivers interacting with automated vehicles

Advancements in technology are bringing automated vehicles (AVs) closer to wider deployment. However, in the early phases of their deployment, AVs will coexist and frequently interact with human-driven vehicles (HDVs). These interactions might lead to changes in the driving behavior of HDVs. A field test was conducted in the Netherlands with...

Cyclists’ crossing intentions when interacting with automated vehicles: A virtual reality study

Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This...

Analysis of the effect of charging needs on battery electric vehicle drivers’ route choice behaviour: A case study in the Netherlands

Electric travelling appears to dominate the transport sector in the near future due to the needed transition from internal combustion vehicles (ICV) towards Electric Vehicles (EV) to tackle urban pollution. Given this trend, investigation of the EV drivers’ travel behaviour is of great importance to stakeholders including planners and...

Relationships between mobile phone usage and activity-travel behavior: A review of the literature and an example

Almost everyone has a mobile phone today. In addition to calls and text messages, people are utilizing mobile apps and websites to connect to the world and explore different content anytime and anywhere. The use of smart phones generates billions of records, including spatiotemporal trajectories, and various mobile phone usage details, such as...

Studying pedestrians’ crossing behavior when interacting with automated vehicles using virtual reality

Partially and fully automated vehicles (AVs) are being developed and tested in different countries. These vehicles are being designed to reduce and ultimately eliminate the role of human drivers in the future. However, other road users, such as pedestrians and cyclists will still be present and would need to interact with these automated...

WEpod WElly in Delft: Pedestrians’ crossing behavior when interacting with automated vehicles using Virtual Reality

Automated vehicles could have many impacts on society [1]. Taking the control of vehicles from human drivers, who by their nature make mistakes, and giving it to automated vehicles (AVs), which are believed to be accurate and reliable, could, in theory, increase safety. However, how non-automated road users will react and interact with...

Resuming manual control or not?: Modelling choices of control transitions in full-range adaptive cruise control

Automated vehicles and driving assistance systems such as Adaptive Cruise Control (ACC) are expected to reduce traffic congestion, accidents and levels of emissions. Field Operational Tests have found that drivers may prefer to deactivate ACC in dense traffic flow conditions and before changing lanes. Despite the potential effects of these...