Speed Management Research: A Summary Comparison of Literature Between High-Income and Low and Middle-Income Countries

Low- and middle-income countries (LMICs) have been experiencing growth in vehicle travel and mobility but have not yet realized road safety gains experienced by high-income countries (HICs). Excessive and inappropriate speed is known to be a major cause of road crashes, injuries and deaths. Thus, speed management is considered a key initiative for improving road safety outcomes worldwide and has been applied successfully in most HICs. Proven interventions do not necessarily have the same impacts in LMICs, or may not be feasible to apply, due significant differences in traffic mix, road user behavior, road design and vehicle standards. This document summarizes current available knowledge about speed, its effects on safety, mobility and emissions, along with potential safety effectiveness of speed management initiatives in the LMIC context. Knowledge gaps for LMICs are clearly referenced for further consideration. Relationship between speed and safety outcomes. All road users are at increased risk of crashes, injuries and death when travelling at higher speeds. Vulnerable road users experience very high risk of death at vehicle impact speeds as low as 30 km/h. Empirical models relate change in mean traffic speed to changes in fatal and serious injuries and could be used to estimate effectiveness of many speed management initiatives. LMIC-specific models are not available especially for the vulnerable road users such as powered two- and three-wheelers (a knowledge gap). In the interim, the HIC models are likely to provide a general conservative estimate. Global Road Safety Facility (GRSF) provided a practitioner tool to assist in estimating safety benefits via its Speed Management Hub. Speed and emissions relationship. There is ample evidence that high speeds and stop-start urban traffic result in increased emission and pollution. Reviewed studies point to reductions in emissions and pollutants when speeds are reduced from high to moderate. There is emerging evidence that reducing urban speeds via traffic calming and introduction of 30 km/h speed limits would also reduce emissions via smoother traffic flow and modal changes away from driving. There was a general lack of knowledge and emission rate models applicable to the diverse traffic scenarios found in LMICs. Speed variance and crashes. Higher traffic speed variation is associated with increased crash and injury risk. The nature of this relationship with mean speed is not simple and poorly understood outside of LMIC high-speed road networks. Safety effects of speed differences between different driver / vehicle types need to be understood (e.g. two-wheelers and trucks). Traffic mix and speeds of different road users. Research recognized that LMIC traffic has more diverse vehicle and road user types than found in most HICs. This results in greater variance around mean traffic speeds, speeds of different vehicle types and in complex interactions between them. There is a need to better understand how these affect crash injury risk for different road users, and effectiveness of speed management initiatives in LMICs. Speed limits and travel time (mobility). Speed limit reductions have been used as a low-cost measure to reduce crashes and injuries. Research demonstrates that drivers have a bias to overestimate time lost when speed limits are reduced, leading to frequent opposition. In urban areas, actual travel time impacts were negligible due to delays at intersections and other traffic disruptions. Rural trip times were minimally longer at reduced speed limits, with practical impacts dependent on the overall trip length. Variable speed limits used on motorways were found to reduce travel times through predictive application of temporary reductions in speed limits. LMIC There was little LMIC research on the effects of speed limits on travel time. Cultural differences affecting attitudes to speed. Cultural differences may influence attitudes toward speed selection and speeding with factors including personal, social, situational, legal and travel time (economic) pressures. Reviewed studies found speeding was more acceptable or likely in LMICs due to attitudes and behavioral norms. Still, speed attitudes are significantly different amongst LMICs and need to be understood in individual country context. There was a need to provide a standardized framework for understanding the complex factors affecting speeding in each country. Speed data collection methods. The review highlighted the need to select fit-for-purpose traffic speed Key Performance Indicators (KPIs) before undertaking any speed data surveys. Leading speed data collection methods were summarized and compared, including conventional roadside and recent floating-car data (FCD) sampling approaches. The lack of guidance on selection of speed KPIs and methods was noted in the LMIC context of more mixed traffic. The knowledge summary provides a useful reference for practitioners wishing to inform themselves about traffic speeds, their selection and impacts on safety outcomes, mobility and emissions. The LMIC knowledge gaps will be useful in considering future research and data priorities.