Follow-up study: floating glass beads for traffic stripes. Final report.

Mode of access: Internet.

Signing and delineation for special usage lanes.

Authors: Richard F. Pain et al.

Investigation of exposure based pedestrian accident areas : crosswalks, sidewalks, local streets and major arterials /

"September 1988."

Thermoplastic striping with improved durability and snowplow resistance : executive summary and draft specifications /

Mode of access: Internet.

Epoxy striping for improved durability /

Mode of access: Internet.

Usage guide for rapid-set epoxy adhesive (118-AF) for traffic marker /

Mode of access: Internet.

Epoxy thermoplastic pavement marking material : specification and testing.

Mode of access: Internet.

Nontoxic yellow traffic striping /

Mode of access: Internet.

Glass beads for highway paint stripes /

Bibliography: p. 10.

Integrated motorist information system (IMIS) feasibility and design study : phase 1 : feasibility /

Mode of access: Internet.

Night visibility of highway pavement surfaces; paint durability tests.

Cover title.

Modeling geometric rules in object based models:an XML / GML approach

Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

Configuring retroreflective markings to enhance the night-time conspicuity of road workers

This study investigated whether the night-time conspicuity of road workers can be enhanced by positioning retroreflective strips on the moveable joints in patterns that convey varying degrees of biological motion. Participants were 24 visually normal adults (12 young M = 26.8 years; 12 older M = 72.9 years). Visual acuity, contrast sensitivity and glare sensitivity were recorded for each participant. Experimenters acting as road workers walked in place on a closed road circuit within simulated road work sites, facing either the oncoming driver or the roadway (presenting sideways to the driver) and wearing one of four clothing conditions: (i) standard road worker vest; (ii) standard vest plus thigh-mounted retroreflective strips; (iii) standard vest plus retroreflective strips on ankles and knees; (iv) standard vest plus retroreflective strips positioned on the extremities in a configuration that conveyed biological motion (“biomotion”). As they drove along the closed road participants were instructed to press a button to indicate when they first recognized that a road worker was present. The results demonstrated that regardless of the direction of walking, road workers wearing biomotion clothing were recognized at significantly (p < 0.05) longer distances (3×), relative to the standard vest alone. Response distances were significantly shorter for the older drivers. Contrast sensitivity was a better predictor of the ability to recognize road workers than was visual acuity or glare sensitivity. We conclude that adding retroreflective strips in the biomotion configuration can significantly improve road worker conspicuity regardless of the road worker's orientation and the age of the driver.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.