Auditory interfaces in automated driving: an international survey

This study investigated peoples’ opinion on auditory interfaces in contemporary<br/>cars and their willingness to be exposed to auditory feedback in automated driving. We used an Internet-based survey to collect 1,205 responses from 91 countries. The respondents stated their attitudes towards two existing auditory driver assistance systems, a...

A Reference Architecture for Blockchain-Based Crowdsourcing Platforms

Companies increasingly tender knowledge-intensive tasks using crowdsourcing platforms to gain access to scarce knowledge and skills otherwise out of reach, and in this way, gaining competitive advantage. Despite its potential, existing crowdsourcing platforms encounter several challenges, including (1) fragmentation of expertise, as there are...

Towards a human in the loop approach to preserve privacy in images

Current artificial intelligence and information retrieval systems need to be trained with a large amount of data to achieve satisfying performance. A popular solution to create such datasets is to employ crowdsourcing; however, the content to be annotated may contain private or sensitive information that can be extracted by workers, limiting...

How should external human-machine interfaces behave? Examining the effects of colour, position, message, activation distance, vehicle yielding, and visual distraction among 1,434 participants

External human-machine interfaces (eHMIs) may be useful for communicating the intention of an automated vehicle (AV) to a pedestrian, but it is unclear which eHMI design is most effective. In a crowdsourced experiment, we examined the effects of (1) colour (red, green, cyan), (2) position (roof, bumper, windshield), (3) message (WALK, DON'T...

Bio-inspired intent communication for automated vehicles

Various external human-machine interfaces (eHMIs) have been proposed that communicate the intent of automated vehicles (AVs) to vulnerable road users. However, there is no consensus on which eHMI concept is most suitable for intent communication. In nature, animals have evolved the ability to communicate intent via visual signals. Inspired by...

The effect of drivers’ eye contact on pedestrians’ perceived safety

Many fatal accidents that involve pedestrians occur at road crossings, and are attributed to a breakdown of communication between pedestrians and drivers. Thus, it is important to investigate how forms of communication in traffic, such as eye contact, influence crossing decisions. Thus far, there is little information about the effect of...

A review and experimental analysis of active learning over crowdsourced data

Training data creation is increasingly a key bottleneck for developing machine learning, especially for deep learning systems. Active learning provides a cost-effective means for creating training data by selecting the most informative instances for labeling. Labels in real applications are often collected from crowdsourcing, which engages...

How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?

The study of urban greenspaces typically relies on three types of data: people’s subjective perceptions collected via questionnaires, vegetation indices derived from satellite imagery, such as the Normalized Difference Vegetation Index (NDVI), and Land Use or Land Cover maps, such as OpenStreetMap (OSM). Data on people’s perceptions are...

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...

The MatchNMingle dataset: A novel multi-sensor resource for the analysis of social interactions and group dynamics in-the-wild during free-standing conversations and speed dates

We present MatchNMingle, a novel multimodal/multisensor dataset for the analysis of free-standing conversational groups and speed-dates in-the-wild. MatchNMingle leverages the use of wearable devices and overhead cameras to record social interactions of 92 people during real-life speed-dates, followed by a cocktail party. To our knowledge,...

Digital Excavation of Mediatized Urban Heritage: Automated Recognition of Buildings in Image Sources

Digital technologies provide novel ways of visualizing cities and buildings. They also facilitate new methods of analyzing the built environment, ranging from artificial intelligence (AI) to crowdsourced citizen participation. Digital representations of cities have become so refined that they challenge our perception of the real. However,...

Survey on eHMI concepts: The effect of text, color, and perspective

The automotive industry has presented a variety of external human-machine interfaces (eHMIs) for automated vehicles (AVs). However, there appears to be no consensus on which types of eHMIs are clear to vulnerable road users. Here, we present the results of two large crowdsourcing surveys on this topic. In the first survey, we asked...

When will most cars be able to drive fully automatically? Projections of 18,970 survey respondents

When fully automated cars will be widespread is a question that has attracted considerable attention from futurists, car manufacturers, and academics. This paper aims to poll the public's expectations regarding the deployment of fully automated cars. In 15 crowdsourcing surveys conducted between June 2014 and January 2019, we obtained answers...

Take-over requests in highly automated driving: A crowdsourcing survey on auditory, vibrotactile, and visual displays

An important research question in the domain of highly automated driving is how to aid drivers in transitions between manual and automated control. Until highly automated cars are available, knowledge on this topic has to be obtained via simulators and self-report questionnaires. Using crowdsourcing, we surveyed 1692 people on auditory,...