Application of Traffic Conflict Techniques as Surrogate Safety Measures: A Sustainable Solution for Developing Countries

Abstract

Social, economic and infrastructure losses due to road traffic accidents and their consequences are very significant all over the world, particularly in developing countries. The evaluation of causative factors of accidents and the selection of remedial measures continues to be based mainly on traditional approaches. Whereas, accident statistics are frequently questioned due to large underreporting of accidents, injuries and property damages, coupled with incomplete and inconsistent recording of information on reported accidents. Poor timelines, ethical issues, biasness and human error are also critical issues. This paper present a comprehensive assessment of the data quality of reported accident databases, in terms of the degree and diversity of the reporting and recording inconsistency, using a case study from Bangladesh. For a more rigorous and sustainable form of safety analysis there is a need for robust methods that may yield targeted safety measures without the need to use accident data. Application of traffic conflict techniques for the diagnosis of accidents has gained research interest as a proactive surrogate approach. However, this has been developed and tested primarily based on lane based homogeneous traffic conditions prevailing in developed countries. Development of advanced image processing systems, as well as video analysis techniques for automatic discrimination of conflicts, has open new prospects. Traffic safety micro-simulation modeling using surrogate indicators is also a promising advancement in this context. This paper provides a framework for safety evaluation beyond the traditional approaches with the integration of recent advancement in surrogate safety evaluation for non-lane based traffic environments. Finally, future research directions, designed to achieve sustainable road safety objectives in developing counties, are outlined.