相关论文: Which cycling environment appears safer? Learning …

Scenario-based testing of automated driving functions has become a promising method to reduce time and cost compared to real-world testing. In scenario-based testing automated functions are evaluated in a set of pre-defined scenarios. These…

Predicting pedestrian crossing behavior is important for intelligent traffic systems to avoid pedestrian-vehicle collisions. Most existing pedestrian crossing behavior models are trained and evaluated on datasets collected from a single…

Illegal vehicle parking is a common urban problem faced by major cities in the world, as it incurs traffic jams, which lead to air pollution and traffic accidents. The government highly relies on active human efforts to detect illegal…

The effect of transport-related pollution on human health is fast becoming recognised as a major issue in cities worldwide. Cyclists, in particular, face great risks, as they typically are most exposed to tail-pipe emissions. Three avenues…

Learning socially-aware motion representations is at the core of recent advances in multi-agent problems, such as human motion forecasting and robot navigation in crowds. Despite promising progress, existing representations learned with…

Cyclists travelling in urban areas are particularly at risk of harm from particulate emissions due to their increased breathing rate and proximity to vehicles. In this paper we combine human respiratory models with models of particulate…

Overtaking on country roads with possible opposing traffic is a dangerous maneuver and many proposed assistant systems assume car-to-car communication and sensors currently unavailable in cars. To overcome this limitation, we develop an…

Understanding human driving behavior is crucial to develop autonomous vehicles' algorithms. However, most low level automation, such as the one in advanced driving assistance systems (ADAS), is based on objective safety measures, which are…

Safety is an essential component for deploying reinforcement learning (RL) algorithms in real-world scenarios, and is critical during the learning process itself. A natural first approach toward safe RL is to manually specify constraints on…

Conventional approaches for addressing road safety rely on manual interventions or immobile CCTV infrastructure. Such methods are expensive in enforcing compliance to traffic rules and do not scale to large road networks. This paper…

Social robot navigation is an evolving research field that aims to find efficient strategies to safely navigate dynamic environments populated by humans. A critical challenge in this domain is the accurate modeling of human motion, which…

Cycling is a green transportation mode, and is promoted by many governments to mitigate traffic congestion. However, studies concerning the traffic dynamics of bicycle flow are very limited. This study experimentally investigated bicycle…

Addressing public safety effectively requires incorporating diverse stakeholder perspectives, particularly those of the community, which are often underrepresented compared to other stakeholders. This study presents a comprehensive analysis…

Studying how social contexts shape technology interactions and how we experience them is hard. One challenge is that social contexts are very dynamic and shaped by the situated practices of everyone involved. As a result, the same…

The development of smart cities requires innovative sensing solutions for efficient and low-cost urban environment monitoring. Bike-sharing systems, with their wide coverage, flexible mobility, and dense urban distribution, present a…

Autonomous mobile robots need to perceive the environments with their onboard sensors (e.g., LiDARs and RGB cameras) and then make appropriate navigation decisions. In order to navigate human-inhabited public spaces, such a navigation task…

This proposal is for the creation and annotation of an egocentric video data set of hazardous cycling situations. The resulting data set will facilitate projects to improve the safety and experience of cyclists. Since cyclists are highly…

Suspicious behavior is likely to threaten security, assets, life, or freedom. This behavior has no particular pattern, which complicates the tasks to detect it and define it. Even for human observers, it is complex to spot suspicious…

The estimation of the amount of uncertainty featured by predictive machine learning models has acquired a great momentum in recent years. Uncertainty estimation provides the user with augmented information about the model's confidence in…

Recommender Systems have become crucial in the modern world, commonly guiding users towards relevant content or products, and having a large influence over the decisions of users and citizens. However, ensuring transparency and user trust…