Mind the gap: Developments in autonomous driving research and the sustainability challenge

Time-Optimal Trajectory Planning and Tracking for Autonomous Vehicles

This article presents a hierarchical control framework for autonomous vehicle trajectory planning and tracking, addressing the challenge of accurately following high-speed, at-limit maneuvers. The proposed time-optimal trajectory planning and tracking (TOTPT) framework utilizes a hierarchical control structure, with an offline trajectory optimization (TRO) module and an online nonlinear model predictive control (NMPC) module. The TRO layer generates minimum-lap-time trajectories using a direct collocation method, which optimizes the vehicle's path, velocity, and control inputs to achieve the fastest possible lap time, while respecting the vehicle dynamics and track constraints. The NMPC layer is responsible for precisely tracking the reference trajectories generated by the TRO in real time. The NMPC also incorporates a preview algorithm that utilizes the predicted future travel distance to estimate the optimal reference speed and curvature for the next time step, thereby improving the overall tracking performance. Simulation results on the Catalunya circuit demonstrated the framework's capability to accurately follow the time-optimal raceline at an average speed of 116 km/h, with a maximum lateral error of 0.32 m. The NMPC module uses an acados solver with a real-time iteration (RTI) scheme, to achieve a millisecond-level computation time, making it possible to implement it in real time in autonomous vehicles.

Inclusive Environments: Home, Work, Public Spaces, Technology, and Specialty Environments within Occupational Therapy Practice

This position statement describes the role and importance of occupational therapy practitioners in integrating inclusive environments into their professional services and into their underlying science. Primary documents that define the occupational therapy profession clearly support its role in creating and ensuring inclusive environments.

Understanding online behavior towards community water user participation: A perspective of a developing country

The social network is a network of virtual relationships that can facilitate the development of a new society in which everyone can use online communication effectively. This article investigates and identifies the fundamental influences on the social network system, as well as the online behavior of the community users. This study was designed by any social network to help improve efficiency and offer people with services that match the needs of their communities. Furthermore, it increases participation in the equitable distribution of social benefits. This study investigates the critical factors that impact a community's view of community water user participation. The researcher sent a questionnaire on a five-point Likert scale to 1,000 community water customers and collected 627 valid replies. Data from 14 villages were sampled using a simple random sampling strategy to acquire the data. Subsequently, descriptive statistics are used to describe the data (frequency distributions, percentages, averages, medians, and standard deviation). Furthermore, PLS-SEM was used to examine the relationships between factors and to launch the conceptual model using PLS route modeling. This study reveals that digital technologies are crucial to increasing the expectations and happiness of the community through social networks. Multiple causes contribute to its expansion. In addition, this research provides an outstanding case study technique based on TAM and ECT to assess people's social networking and community participation habits. Additionally, community water providers participate in social networks by certifying that their expectations are met.

Designing Interactions With Shared AVs in Complex Urban Mobility Scenarios

In this article, we report on the design and evaluation of an external human-machine interface (eHMI) for a real autonomous vehicle (AV), developed to operate as a shared transport pod in a pedestrianized urban space. We present insights about our human-centered design process, which included testing initial concepts through a tangible toolkit and evaluating 360-degree recordings of a staged pick-up scenario in virtual reality. Our results indicate that in complex mobility scenarios, participants filter for critical eHMI messages; further, we found that implicit cues (i.e., pick-up manoeuvre and proximity to the rider) influence participants' experience and trust, while at the same time more explicit interaction modes are desired. This highlights the importance of considering interactions with shared AVs as a service more holistically, in order to develop knowledge about AV-pedestrian interactions in complex mobility scenarios that complements more targeted eHMI evaluations.

Take It to the Curb: Scalable Communication Between Autonomous Cars and Vulnerable Road Users Through Curbstone Displays

Automated driving will require new approaches to the communication between vehicles and vulnerable road users (VRUs) such as pedestrians, e.g., through external human–machine interfaces (eHMIs). However, the majority of eHMI concepts are neither scalable (i.e., take into account complex traffic scenarios with multiple vehicles and VRUs), nor do they optimize traffic flow. Speculating on the upgrade of traffic infrastructure in the automated city, we propose Smart Curbs, a scalable communication concept integrated into the curbstone. Using a combination of immersive and non-immersive prototypes, we evaluated the suitability of our concept for complex urban environments in a user study (N = 18). Comparing the approach to a projection-based eHMI, our findings reveal that Smart Curbs are safer to use, as our participants spent less time on the road when crossing. Based on our findings, we discuss the potential of Smart Curbs to mitigate the scalability problem in AV-pedestrian communication and simultaneously enhance traffic flow.

Assessing the Effect of Drivers’ Gender on Their Intention to Use Fully Automated Vehicles

Although fully automated vehicles (SAE level 5) are expected to acquire a major relevance for transportation dynamics by the next few years, the number of studies addressing their perceived benefits from the perspective of human factors remains substantially limited. This study aimed, firstly, to assess the relationships among drivers’ demographic factors, their assessment of five key features of automated vehicles (i.e., increased connectivity, reduced driving demands, fuel and trip-related efficiency, and safety improvements), and their intention to use them, and secondly, to test the predictive role of the feature’ valuations over usage intention, focusing on gender as a key differentiating factor. For this cross-sectional research, the data gathered from a sample of 856 licensed drivers (49.4% females, 50.6% males; M = 40.05 years), responding to an electronic survey, was analyzed. Demographic, driving-related data, and attitudinal factors were comparatively analyzed through robust tests and a bias-corrected Multi-Group Structural Equation Modeling (MGSEM) approach. Findings from this work suggest that drivers’ assessment of these AV features keep a significant set of multivariate relationships to their usage intention in the future. Additionally, and even though there are some few structural similarities, drivers’ intention to use an AV can be differentially explained according to their gender. So far, this research constitutes a first approximation to the intention of using AVs from a MGSEM gender-based approach, being these results of potential interest for researchers and practitioners from different fields, including automotive design, transport planning and road safety.

Not everything is as it seems: Digital technology affordance, pandemic control, and the mediating role of sociomaterial arrangements

An overly favorable narrative has developed around the role played by digital technologies in containing Covid-19, which oversimplifies the complexity of technology adoption. This narrative takes sociomaterial arrangements for granted and conceptualizes technology affordance - the problem-solving capability of a technology - as a standard built-in feature that automatically activates during technology deployment, leading to undiversified and predetermined collective benefits. This paper demonstrates that not everything is as it seems; implementing a technology is a necessary but insufficient condition for triggering its potential problem-solving capability. The potential affordance and effects of a technology are mediated by the sociomaterial arrangements that users assemble to connect their goals to the materiality of technological artifacts and socio-organizational context in which technology deployment takes place. To substantiate this argument and illustrate the mediating role of sociomaterial arrangements, we build on sociomateriality and technology affordance theory, and we present the results of a systematic review of Covid-19 literature in which 2187 documents are examined. The review combines text data mining, co-occurrence pattern recognition, and inductive coding, and it focuses on four digital technologies that public authorities have deployed as virus containment measures: infrared temperature-sensing devices; ICT-based surveillance and contact-tracing systems; bioinformatic tools and applications for laboratory testing; and electronic mass communications media. Reporting on our findings, we add nuances to the academic debate on sociomateriality, technology affordance, and the governance of technology in public health crises. In addition, we provide public authorities with practical recommendations on how to strengthen their approach to digital technology deployment for pandemic control.

Smart and Resilient Urban Futures for Sustainability in the Post COVID-19 Era: A Review of Policy Responses on Urban Mobility

The COVID-19 pandemic has put lifestyles in question, changed daily routines, and limited citizen freedoms that seemed inalienable before. A human activity that has been greatly affected since the beginning of the health crisis is mobility. Focusing on mobility, we aim to discuss the transformational impact that the pandemic brought to this specific urban domain, especially with regards to the promotion of sustainability, the smart growth agenda, and the acceleration towards the smart city paradigm. We collect 60 initial policy responses related to urban mobility from cities around the world and analyze them based on the challenge they aim to address, the exact principles of smart growth and sustainable mobility that they encapsulate, as well as the level of ICT penetration. Our findings suggest that emerging strategies, although mainly temporary, are transformational, in line with the principles of smart growth and sustainable development. Most policy responses adopted during the first months of the pandemic, however, fail to leverage advancements made in the field of smart cities, and to adopt off-the-shelf solutions such as monitoring, alerting, and operations management.