U.S. pedestrian fatalities have risen recently, even as vehicles are equipped with increasingly sophisticated safety and crash avoidance technology. Many experts expect that advances in automated vehicle technology will reduce pedestrian fatalities substantially through eliminating crashes caused by human error. This paper investigates automated vehicles' potential for reducing pedestrian fatalities by analyzing nearly 5,000 pedestrian fatalities recorded in 2015 in the Fatality Analysis Reporting System, virtually reconstructing them under a hypothetical scenario that replaces involved vehicles with automated versions equipped with state-of-the-art (as of December 2017) sensor technology. This research involved the following activities: (1) establish functional ranges of state-of-the-art pedestrian sensor technologies, (2) use data from the Fatality Analysis Reporting System to identify pedestrian fatalities recorded in each state in the U.S. and District of Columbia in 2015, and (3) assess the maximum numbers of pedestrian fatalities that could have been avoided had involved vehicles been replaced with autonomous versions equipped with the described sensors. The research was conducted from July to December 2017. Sensors' abilities to detect pedestrians in advance of fatal collisions vary from 90% of fatalities. Combining sensor technologies offers the greatest potential for eliminating fatalities, but may be unrealistically expensive. Furthermore, whereas initial deployment of automated vehicles will likely be restricted to freeways and select urban areas, non-freeway streets and rural settings account for a substantial share of pedestrian fatalities. Although technologies are being developed for automated vehicles to successfully detect pedestrians in advance of most fatal collisions, the current costs and operating conditions of those technologies substantially decrease the potential for automated vehicles to radically reduce pedestrian fatalities in the short term.

Problem, research strategy, and findings: Land use planning is key to mitigating natural hazards and the effects of climate change. Communities adopt multiple plans that directly and indirectly address hazard mitigation; the integration of local plans can significantly affect future community vulnerability to hazards. We develop a resilience scorecard to assess the degree to which the network of local plans targets areas most prone to hazards and then evaluate the coordination of local plans and test it in Washington (NC), a community vulnerable to coastal floods and projected sea-level rise. We find that local plans are not fully consistent and do not always address the areas in a community most vulnerable to floods or sea level risks; moreover, some plans actually increase physical and social vulnerability to hazards. While these results indicate the validity of a resiliency scorecard, we were forced to use a narrow range of vulnerability indicators; better data would improve the process. Takeaway for practice: Planners can assume a crucial role in improving planning for hazards by using the scorecard to identify conflicts among local plans, assessing whether local plans target areas most vulnerable to specific hazards. Planners can inform the public and decision makers about missed opportunities to improve local hazard mitigation planning. To support such important efforts, the U.S. Federal -Emergency Management Agency and other federal agencies should consider developing additional databases that are widely applicable and available.