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The automotive industry is currently experiencing a revolution with the advent and deployment of autonomous vehicles. Several countries are conducting large-scale testing of autonomous vehicles on private and even public roads. It is important to examine the attitudes and potential concerns of end users towards autonomous cars before mass deployment. To facilitate the transition to autonomous vehicles, the automotive industry produces many videos on its products and technologies. The largest video sharing website, YouTube.com, hosts many videos on autonomous vehicle technology. Content analysis and text mining of the comments related to the videos with large numbers of views can provide insight about potential end-user feedback. This study examines two questions: first, how do people view autonomous vehicles? Second, what polarities exist regarding (a) content and (b) automation level? The researchers found 107 videos on YouTube using a related keyword search and examined comments on the 15 most-viewed videos, which had a total of 60.9 million views and around 25,000 comments. The videos were manually clustered based on their content and automation level. This study used two natural language processing (NLP) tools to perform knowledge discovery from a bag of approximately seven million words. The key issues in the comment threads were mostly associated with efficiency, performance, trust, comfort, and safety. The perception of safety and risk increased in the textual contents when videos presented full automation level. Sentiment analysis shows mixed sentiments towards autonomous vehicle technologies, however, the positive sentiments were higher than the negative.

Chapter 3 in the 2004 AASHTO high-occupancy-vehicle guidelines includes a prioritized trade-off table of various design options for high-occupancy-vehicle lanes (now known as managed lanes). The design trade-offs include the reduction of lane, shoulder, or buffer width. The key measure thought to be affected by lane, shoulder, and buffer width is lateral position. The presented study identified the relationship between operations and cross-section width, including the type of buffer design separating the managed lanes from the general-purpose lanes. This research study collected lateral position data on existing managed lane facilities with a range of geometric elements within both tangent and horizontal curves and identified potential relationships between the geometric design element values and the measure of effectiveness. The field studies included data collected at 28 sites with fixed video cameras and along 161 centerline miles with an instrumented vehicle that recorded data for the vehicle immediately in front of the instrumented vehicle. The study found that managed-lane drivers shifted away from the pylons placed in the buffer. Horizontal alignment (tangent or curve) and the direction of the horizontal curve (left or right) influenced lateral position. Left shoulder, lane, and buffer width affected lateral position. Modifying a 6.5-ft shoulder to a minimum shoulder (i.e., 1.5 ft) will result in drivers moving to the right about 0.5 ft; however, if an 18.5-ft shoulder is reduced by 5 ft, the impact in operations is negligible (drivers would shift only about 0.11 ft toward the right).

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Managed lanes typically are on or adjacent to freeways and are actively operated and managed to preserve operational performance—such as more optimal travel speeds—over comparable general-purpose traffic lanes. A study was conducted to evaluate speeds on existing buffer-separated managed lanes to identify variables that influence operating speed. Speed data from more than 130 unique sites in Los Angeles, California; Orange County, California; and Dallas, Texas, were used. All analyses showed that the managed lane volume and the speed in the general-purpose lanes were related to the speed in the managed lane (statistically significant). The Dallas analysis, which used speeds averaged by 1-min increments, showed that the factor with the most influence on uncongested managed lane speed was the managed lane’s geometry. The relationship between uncongested managed lane speed and the managed lane envelope (sum of left shoulder width, managed lane width, and buffer width) was found to be statistically significant. For each additional foot over a 16-ft envelope width, managed lane speed increased by approximately 3.2 mph. In contrast, the California analysis, which used speeds averaged by 1-h increments, showed that the variable having the most influence was the volume in the managed lane. The researchers theorized that the lack of a relationship between managed lane speed and geometry in California is related to those speeds being an average 1-h speed rather than the 1-min speeds available in Texas.