This paper summarizes and synthesizes the existing literature relevant to pedestrian receptivity toward Fully Automated Vehicles (FAVs). Objectives of this review are to identify research gaps that need to be filled and to propose a roadmap for future research. Since FAVs are operated by software and hardware, with no human driver required, interactions between other road users and FAVs must be understood, and potential risks must be addressed. This is especially true for pedestrians, who often exhibit unpredictable behavior and are one of the most vulnerable road-user groups. A comprehensive review was conducted of 1) different aspects of pedestrian interaction with forthcoming fully automated vehicles, and 2) the existing research approaches (surveys and simulator studies) for investigating risky pedestrian behavior as well as public acceptance of fully automated vehicles. The review identified three major gaps in pedestrian research: 1) lack of a pedestrian behavior questionnaire for FAV research, 2) lack of a validated pedestrian simulator for FAV research, and 3) lack of research investigating pedestrian design suggestions for FAVs. A future research roadmap to facilitate investigating pedestrian receptivity toward FAVs was designed. Achieving pedestrian acceptance of FAVs will require investigation of pedestrian risks and needs by transportation researchers and communication of the results to vehicle manufacturers and regulatory agencies. This review will be useful to transportation researchers and automated vehicle manufacturers to help guide planning for future design and production of FAVs in order to ensure their successful implementation.

This study investigates the effectiveness of Reverse 911 warning systems compared with other evacuation warning sources. This study also investigates the impact of individual differences on evacuation behavior, and presents a regression model of evacuation behavior on the basis of empirical data. A 57 question survey was administered by telephone to people who had been affected by the 2007 San Diego wildfires, with 1020 usable responses (8.4% response rate). By signal detection theory, Reverse 911 warnings had the best performance compared with other evacuation warning sources, as indicated by the high influence rating (0.66) and hit rate (1.00). People who received the Reverse 911 warning also had a significantly higher rate of evacuation (0.80), as did those who received warnings from more than one source (0.78). Regression analysis shows that the Reverse 911 warning was critical in predicting whether an individual evacuated. Demographic factors, including knowledge and experience with previous wildfire...