Road Traffic Crashes and Road Configuration; A Space Syntax Application

Abstract

Transport provides a range of benefits to society in terms of mobility, access and economic growth. However, there are negative impacts of transport, not least in terms of environmental degradation, damage to property, traffic accidents and loss of life. In Sri Lanka, Road Traffic Crashes (RTCs) are responsible for a substantial fraction of morbidity and mortality and are responsible for more years of life loss than most of human diseases. Taking its cues, this paper focuses on RTCs, the reduction of which is an important aim of suitable transport policy worldwide. In this study, the authors have tried to delineate road specific factors that collectively represent the principal cause of three (people, vehicle and road) out of RTCs and which is less concerned in Sri Lankan transport researchers. In that context, the primary objective of this paper is to identify a series of relationships between RTCs and wad pattern focusing road configuration by using space syntax. Road Network Configuration is examined based on four different road configuration parameters that is (i) Choice, (ii.) Connectivity, (Hi.) integration and (iv.) Line length in two levels (Local O'5 Global) using Space Syntax. The RTCs data along the A1 road (from Peliyagoda to Kegalle, Sri Lankan) was collected from the Traffic division of Sri Lanka Police and entered in to Geographic Information System (GIS) database. Then statistical analysis have been conducted to identify the relationship between RTCs and Road Configuration Parameters. The results show notable! noticeable relationship between RTCs and Local level variance of integration values (r — 0.874, p < .01); Connectivity (r — 0.768, p < .01) and Global Level Choice (r = 0.759, p < .01). Further regression analysis indicated that combination those three variables have more than 90% of impact for RTCs. With that notable relationship between RTCs and wad configuration, this study highlights the need for preventive efforts that incorporate wad pattern specific strategies in wad network planning and design to create sustainable built environment rather than focusing only on human factors.