Abstract

Safe travel for all road users is a prerequisite for ensuring sustainable and inclusive cities. Providing safe transport system is an objective for sustainable transport, because risk of injuries and deaths from traffic crashes has become a major public health concern worldwide (WHO, 2011). At the same time safety of pedestrians, bicyclists and public transport users also has an impact on the choice of these modes. Risk to pedestrians, bicyclists and public transport users can be reduced by appropriate street designs and neighbourhood environment. Safer pedestrian and bicycle infrastructure results in increased use of these environment friendly modes (Tiwari & Jain, 2012). Safe travel options for women in general and specifically low income women are important for addressing livelihood and poverty issues for a significant proportion of urban population in low income countries like India. In this paper we present data from two Indian cities- Vishakhapattanam( a city in south India with a population of 1.7 million persons) and Delhi the capital city of India having 16.4 million residents to compare the travel patterns of women and men. The household survey in Delhi focused on low income settlements since poverty adds another dimension to gender bias. The survey repeated after ten years shows that the travel patterns remain unchanged. Women travel shorter distances, are dependent on lower cost modes-walking and public transport and perform multi-purpose linked trips. In view of the sustainability requirements, lower mobility of women must be addressed by ensuring safe accessibility to employment opportunities by walking, bicycles and public transport. The paper concludes with possible interventions required to ensure safe and secure travel of women at land use planning level and street design level.

Abstract

In Germany, the data of the Open Street Map project has become available as an alternative to proprietary road networks in commercial business geomatics software, and their customers are wondering whether the quality may be sufficient. This paper describes an implemented methodology to compare OSM street data with those of Navteq for all populated roads in Germany. As a unique feature, the presented methodology is based on a matching between the street objects of OSM and Navteq, and all steps are fully automated so that they can be applied to updated versions of both data sets. While there are considerable qualitative differences between regions, towns, and street categories, at a national level the relative completeness of objects, their relative precision and the relative completeness of names are high enough for maps. However, other attributes, which are needed for the computation of catchment areas, are still relatively incomplete.