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• 1. [Article] Towards Effective Design Treatment for Right Turns at Intersections with Bicycle Traffic

  The overall goal of this research was to quantify the safety performance of alternative traffic control strategies to mitigate right-turning-vehicle/bicycle collisions, often called "right-hook" crashes, ...

  Citation × Citation Citation Abstract Copy Title: Towards Effective Design Treatment for Right Turns at Intersections with Bicycle Traffic Author: Hurwitz, David, Monsere, Christopher Year: 2016 The overall goal of this research was to quantify the safety performance of alternative traffic control strategies to mitigate right-turning-vehicle/bicycle collisions, often called "right-hook" crashes, at signalized intersections in Oregon. A two stage experiment was developed in the OSU high-fidelity driving simulator to investigate the causal factors of right-hook crashes at signalized intersections with a striped bike lane and no right-turn lane, and to then identify and evaluate alternative design treatments that could mitigate the occurrence of right-hook crashes. Experiment 1 investigated motorist and environmental related causal factors of right-hook crashes, using three different motorist performance measures: (1) visual attention, (2) situational awareness (SA) and (3) crash avoidance behavior. Data was collected from 51 participants (30 male and 21 female) turning right 820 times in 21 different experimental scenarios. It was determined that the worst case right-hook scenario occurred when a bicycle was approaching the intersection at a higher speed (16 mph) and positioned in the blind zone of the motorist. In crash and near crash situations (measured by time-to-collision) the most common cause was a failure of the driver to actively search for the adjacent bicyclist (situational awareness level 1), although failures were also determined to occur due to failures of projection (i.e. incorrectly assuming that the bicycle would yield or that there was enough time to turn in front of the bicycle). Elements of driver performance and gap acceptance collected in the first stage simulator experiment were field validated based on 144 hrs of video to provide additional confidence in the findings. Title: Towards Effective Design Treatment for Right Turns at Intersections with Bicycle Traffic Author: Hurwitz, David, Monsere, Christopher Year: 2016 The overall goal of this research was to quantify the safety performance of alternative traffic control strategies to mitigate right-turning-vehicle/bicycle collisions, often called "right-hook" crashes, at signalized intersections in Oregon. A two stage experiment was developed in the OSU high-fidelity driving simulator to investigate the causal factors of right-hook crashes at signalized intersections with a striped bike lane and no right-turn lane, and to then identify and evaluate alternative design treatments that could mitigate the occurrence of right-hook crashes. Experiment 1 investigated motorist and environmental related causal factors of right-hook crashes, using three different motorist performance measures: (1) visual attention, (2) situational awareness (SA) and (3) crash avoidance behavior. Data was collected from 51 participants (30 male and 21 female) turning right 820 times in 21 different experimental scenarios. It was determined that the worst case right-hook scenario occurred when a bicycle was approaching the intersection at a higher speed (16 mph) and positioned in the blind zone of the motorist. In crash and near crash situations (measured by time-to-collision) the most common cause was a failure of the driver to actively search for the adjacent bicyclist (situational awareness level 1), although failures were also determined to occur due to failures of projection (i.e. incorrectly assuming that the bicycle would yield or that there was enough time to turn in front of the bicycle). Elements of driver performance and gap acceptance collected in the first stage simulator experiment were field validated based on 144 hrs of video to provide additional confidence in the findings. Close

• 2. [Article] Addressing Data Challenges for Bicycle Crash Analysis

  Although an increasing number of separated bicycle facilities have been appearing across the US over the last few years, the majority of bicyclists are still traveling on roadways shared with motorized ...

  Citation × Citation Citation Abstract Copy Title: Addressing Data Challenges for Bicycle Crash Analysis Author: Christofa, Eleni Year: 2017 Although an increasing number of separated bicycle facilities have been appearing across the US over the last few years, the majority of bicyclists are still traveling on roadways shared with motorized vehicles. As a result, bicycles are essentially double exposed to safety risk, due to their interactions with both motorized vehicles and other bicycles. In addition to this double exposure, data challenges–such as a lack of continuous counts and bicycle crash data—complicate the assessment of bicycle safety further. This research presents a bicycle crash analysis framework for estimating bicycle crash rates accounting for both bicycle and motorized vehicle exposure as well as overcoming the lack of bicycle count data. First, a novel seasonal bicycle demand model is presented that is capable of estimating monthly average daily bicyclists (MADB) and annual average daily bicyclists (AADB) using an area-specific calibration factor. This factor can be estimated using a minimum of two short-term counts or one full year of a continuous count. The proposed sinusoidal model has been developed and validated using bicycle count data from a total of 47 permanent bicycle counters in six cities and four bike-sharing systems in North America. Next, a corridor-based crash and AADB assignment is performed to relate crash with volume data. These data are then used in parallel with motorized vehicle counts in a crash rate equation that accounts for exposure of bicyclists to both vehicles and other bicyclists. Results show that the proposed “double exposure” crash rate for bicyclists unveils high risk locations for bicyclists that would have been obscured by the high vehicle volumes if the typical crash rate per AADT or AADB were used. Title: Addressing Data Challenges for Bicycle Crash Analysis Author: Christofa, Eleni Year: 2017 Although an increasing number of separated bicycle facilities have been appearing across the US over the last few years, the majority of bicyclists are still traveling on roadways shared with motorized vehicles. As a result, bicycles are essentially double exposed to safety risk, due to their interactions with both motorized vehicles and other bicycles. In addition to this double exposure, data challenges–such as a lack of continuous counts and bicycle crash data—complicate the assessment of bicycle safety further. This research presents a bicycle crash analysis framework for estimating bicycle crash rates accounting for both bicycle and motorized vehicle exposure as well as overcoming the lack of bicycle count data. First, a novel seasonal bicycle demand model is presented that is capable of estimating monthly average daily bicyclists (MADB) and annual average daily bicyclists (AADB) using an area-specific calibration factor. This factor can be estimated using a minimum of two short-term counts or one full year of a continuous count. The proposed sinusoidal model has been developed and validated using bicycle count data from a total of 47 permanent bicycle counters in six cities and four bike-sharing systems in North America. Next, a corridor-based crash and AADB assignment is performed to relate crash with volume data. These data are then used in parallel with motorized vehicle counts in a crash rate equation that accounts for exposure of bicyclists to both vehicles and other bicyclists. Results show that the proposed “double exposure” crash rate for bicyclists unveils high risk locations for bicyclists that would have been obscured by the high vehicle volumes if the typical crash rate per AADT or AADB were used. Close