Driver behavior and performances on in-vehicle display based speed compliance.

Traffic safety, and the inherent risks associated with speeding, continue to remain a national priority. Advances in both roadway and vehicle technology have created potential mechanisms to mitigate speeding behaviors. This driving simulator study evaluated the effects of alternative ways to increase driver safety by investigating the characteristics of specific driving cues and drivers' response rates to those cues. The study builds upon existing approaches to symbolically deliver Traffic Control Devices (TCDs), specifically speed alerts, at different locations within the vehicle to reduce cognitive distraction and prevent visual crowding so that drivers can properly select their speed and focus upon the roadway environment. Twenty-three participants received five visual treatments (e.g., combinations of speed alert style, presentation, and location) in a simulated environment. Participants also responded to a set of survey questions following the simulated drive. Participants were evaluated on various response factors to each visual treatment. Results showed that younger participants of the age group 18-23 responded to the visual treatment and stayed within speed limits as compared to other older and more experienced participants. Results also showed that alerts falling in the mid-peripheral visual region and alerts that flashed received an increased response rate for observing speed limits.

The role of protected intersections in improving bicycle safety and driver right-turning behavior.

Protected or separated bike lanes or cycle tracks, are increasing in popularity in North America and Europe. However, despite their documented benefits, there are concerns about potential conflicts between bicycles and vehicles when they merge back together at an intersection. The concern is that following a period of separation, drivers are less likely to anticipate and scan for the presence of bicyclists. This research examines how transitions from fully separated to mixed-traffic environments and vice versa affect driver behavior. The goal is to assess whether certain segment-intersection treatment combinations can alert drivers of the presence of bicyclists and thus, encourage them to scan for bicyclists prior to a right turn, reducing potential right-hook conflicts. Driving simulation is utilized and driver performance for right-turning vehicles is recorded under the presence of various bicycle infrastructure treatments along segments and at intersections. The experimental design includes conventional and protected bike lanes and intersections with either intersection crossing markings or protected intersections. The results show that the presence of protected bike lanes motivates fewer glances towards bicyclists traveling on those bike lanes, therefore, reducing drivers' ability to detect and in turn, perceive bicyclists. Drivers developed slightly lower speeds while driving next to protected versus conventional bike lanes. It was also found that protected intersections result in a higher rate of right glances at the intersection prior to a right turn. Drivers glancing at the intersection were also found to have lower speeds, indicating a correlation between the presence of protected intersection elements and speed selection. This research can be used to guide decisions on bicycle infrastructure implementation for safer multimodal operations.

Accounting for drivers' bicycling frequency and familiarity with bicycle infrastructure treatments when evaluating safety.

Municipalities in the United States often encourage bicycling for the health, economic, and environmental benefits by implementing new and innovative bicycle infrastructure treatments. Unfortunately, many treatments are unfamiliar to or misunderstood by drivers, especially when lacking explicit rules (e.g., shared lanes). To date, research has largely investigated bicycle infrastructure from a bicyclist's perspective, but with little research from the driver's perspective. The objective of this research is to utilize a driving simulator to investigate driver behavior towards different bicycle infrastructure treatments when driver behavior is not provoked by an interaction with bicyclists. More specifically, this research intends to investigate the impact of bicycling frequency and treatment familiarity, as well as the combined effect of the two, on driver behavior at each treatment type. The treatments investigated are shared lane markings called "sharrows", standard bike lanes, bike boxes, and merge lanes. The results show that bicycling frequency significantly affects the proportion of drivers making eye glances at treatments. In addition, drivers more familiar with bike boxes stopped significantly further back from bike boxes, and drivers more familiar with merge lanes performed the merge maneuver significantly earlier. Furthermore, driver speed and lane positioning at bike lanes was significantly affected by the combination of bike lane familiarity and bicycling frequency, but not individually. This research is a first step towards understanding driver behavior and expectation of bicyclists; an essential understanding for infrastructure treatments that do not provide physical barriers between bicycles and automobiles, and instead rely on driver behavior for safety.

A mixed methods investigation of bicycle exposure in crash rates.

Crash rates are an essential tool enabling researchers and practitioners to assess whether a location is truly more dangerous, or simply serves a higher volume of vehicles. Unfortunately, this simple crash rate is far more difficult to calculate for bicycles due to data challenges and the fact that they are uniquely exposed to both bicycle and automobile volumes on shared roadways. Bicycle count data, though increasingly more available, still represents a fraction of the available count data for automobiles. Further compounding on this, bicycle demand estimation methods often require more data than automobiles to account for the high variability that bicycle demand is subject to. This paper uses a combination of mixed methods to overcome these challenges and to perform an investigation of crash rates and exposure to different traffic volumes.