Analysing Noisy Driver Physiology Real-Time Using Off-the-Shelf Sensors: Heart Rate Analysis Software from the Taking the Fast Lane Project.

This paper describes the functioning and development of HeartPy: a heart rate analysis toolkit designed for photoplethysmogram (PPG) data. Most openly available algorithms focus on electrocardiogram (ECG) data, which has very different signal properties and morphology, creating a problem with analysis. ECG-based algorithms generally don’t...

A Conceptual Model for Persuasive In-Vehicle Technology to Influence Tactical Level Driver Behaviour

Persuasive in-vehicle systems aim to intuitively influence the attitudes and/or behaviour of a driver (i.e. without forcing them). However, the challenge in using these systems in a driving setting, is to maximise the persuasive effect without infringing upon the driver's safety. This paper proposes a conceptual model for driver persuasion at...

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...

HeartPy: A novel heart rate algorithm for the analysis of noisy signals

Heart rate data are often collected in human factors studies, including those into vehicle automation. Advances in open hardware platforms and off-the-shelf photoplethysmogram (PPG) sensors allow the non-intrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms...

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...

Multi-Level Driver Workload Prediction Using Machine Learning and Off-The-Shelf Sensors

The present study aims to add to the literature on driver workload prediction using machine learning methods. The main aim is to develop workload prediction on a multi-class basis, rather than a binary high/low distinction as often found in litearature. The presented approach relies on measures that can be obtained unobtrusively in the driving...

Multi-level driver workload prediction using machine learning and off-the-shelf sensors

The present study aims to add to the literature on driver workload prediction using machine learning methods. The main aim is to develop workload prediction on a multi-level basis, rather than a binary high/low distinction as often found in literature. The presented approach relies on measures that can be obtained unobtrusively in the driving...

Heart Rate Analysis for Human Factors: Development and Validation of an Open Source Toolkit for Noisy Naturalistic Heart Rate Data

Heart rate data are collected often in human factors studies. Advances in open hardware platforms and offtheshelf photoplethysmogram (PPG) sensors allow the nonintrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms differs from electrocardiogram (ECG)...

Modelling decisions of control transitions and target speed regulations in full-range Adaptive Cruise Control based on Risk Allostasis Theory

Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion and accidents. Recently, an on-road study has shown that drivers may prefer to deactivate full-range ACC when closing in on a slower leader and to overrule it by pressing the gas pedal a few seconds after the activation of the system. Notwithstanding...

Continuous-discrete choices of control transitions and speed regulations in full-range adaptive cruise control

Driving assistance systems such as Adaptive Cruise Control (ACC) and automated vehicles can contribute to mitigate traffic congestion, accidents, and levels of emissions. Automated vehicles may increase roadway capacity, improve traffic flow stability, and speed up the outflow from a queue (1). The functionalities of automated systems have been...

Resuming manual control or not? Modeling 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...

Towards Real-Time, Nonintrusive Estimation of Driver Workload in a Simulated Environment

The aim of this research is to work towards building an open-source, platform-independent algorithm capable of predicting driver workload in real-time and in a non-intrusive way. To work towards a system that can also be implemented in on-road settings, we aimed at using off-the-shelf, non-intrusive sensors that could be implemented into the...

The Use of Persuasive In-Car Technology to Persuade Drivers at the Tactical Level

The use of in-car technology has become more prevalent, both as driver assistance systems as well as connectivity or entertainment systems. Driver assistance systems can be built-in, after-market or run on a smartphone. The challenge however, is to increase drivers’ compliance with these systems. Stimulating the driver to adopt certain...

Interactions between vulnerable road users and automated vehicles: A synthesis of literature and framework for future research

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. Most fatal accidents of vulnerable road users (VRUs), pedestrians, cyclists and mopeds, involve a motorized vehicle. In addition, most of...

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...

Comparative assessment of safety indicators for vehicle trajectories on the highway

Safety measurement and analysis have been a challenging and well-researched topic in transportation. Conventionally, surrogate safety measures have been used as safety indicators in simulation models for safety assessment, in control formulations for driver assistance systems, and in data analysis of naturalistic driving studies. However,...