Development of a Methodology for Estimating the Availability of ADAS-Dependent Road Infrastructure

Advanced driver assist systems are being promoted with the expectation that enhanced driver support will mitigate road trauma. While these technologies are optimised for certain road and traffic conditions, not all roads across Australasia are equipped with ADAS-supportive infrastructure. This study developed a desk-top methodology for using road classes (disaggregated by remoteness levels) to estimate the presence of quality roads, road delineation and speed signage in Victoria, Australia. Aerial imagery and mapping data were used to assess a number of random locations based on a developed protocol. The methodology demonstrated that in Victoria, major and arterial roads across all remoteness levels had high-quality sealed surfaces but 42% of all remote roads were unsealed. Delineation (crucial for lane support systems) were absent across 73% of sub-arterial roads independent of remoteness, and absent across 96% of sub-arterial roads in regional and remote areas. Speed sign availability across remote and regional areas was sparse, with only 65% of all roads assessed having signage. Results are reflective of Victoria’s road funding model and consistent with on-road audits conducted by other researchers. This methodology enables the proportion ADAS-ready roads to be estimated so the benefits of ADAS technologies can be quantified and investments into ADAS-supportive infrastructure be readily allocated.

Employing Emerging Technologies to Develop and Evaluate In-Vehicle Intelligent Systems for Driver Support: Infotainment AR HUD Case Study

The plurality of current infotainment devices within the in-vehicle space produces an unprecedented volume of incoming data that overwhelm the typical driver, leading to higher collision probability. This work presents an investigation to an alternative option which aims to manage the incoming information while offering an uncluttered and timely manner of presenting and interacting with the incoming data safely. The latter is achieved through the use of an augmented reality (AR) head-up display (HUD) system, which projects the information within the driver’s field of view. An uncluttered gesture recognition interface provides the interaction with the AR visuals. For the assessment of the system’s effectiveness, we developed a full-scale virtual reality driving simulator which immerses the drivers in challenging, collision-prone, scenarios. The scenarios unfold within a digital twin model of the surrounding motorways of the city of Glasgow. The proposed system was evaluated in contrast to a typical head-down display (HDD) interface system by 30 users, showing promising results that are discussed in detail.