Xiong, Hui

A flashing LED stop sign is essentially a normal octagonal stop sign with light emitted diodes (LED) on the stop sign's corners. A hierarchical Bayes observational before/after study found an estimated reduction of about 41.5% in right-angle crashes, but with 95% confidence this reduction could be anywhere between 0% and 70.8%. In a field study, portable video equipment was used to record vehicle approaches at an intersection before and after installation of flashing LED stop signs. After installing the flashing stop signs, there was no change in the relative proportion of clear stops to clear non-stops when minor approach drivers did not face opposing traffic, but the relative proportion of clear stops increased for drivers who did encounter opposing traffic.

Report #10 in the series: Access to Destinations Study. The objectives of this project were to (a) produce historic estimates of travel times on Twin-Cities arterials for 1995 and 2005, and (b) develop an initial architecture and database that could, in the future, produce timely estimates of arterial traffic volumes and travel times. Our Phase I field study indicated that on arterial links where both the demand traffic volume and the signal timing are known, model-based estimates of travel time that are on average within 10% of measured values can be obtained. Phase II of this project then focused on applying this approach to the entire Twin Cities arterial system. The Phase II effort divided into three main subtasks: (1) updating estimates of demand traffic volume obtained from a transportation planning model to make them consistent with available volume measurements, (2) collecting information on traffic signal locations in the Twin Cities and compiling this into a geographic database, and (3) combining the updated traffic volumes and signal information to produce link-by-link peak-period travel time estimates. The traffic volume update took as inputs the predicted volumes generated by a traffic assignment model and measured average annual daily traffic from automatic traffic recorders, and gave as output updated estimates of the traffic volumes for links lacking automatic traffic recorders. A request to state, county and municipal agencies in the seven-county metro area produced Information on approximately 2,900 traffic signals. Estimated arterial travel times for the morning and afternoon peak periods for 1995 and 2005 were then computed and sent to other components of the Access to Destinations effort.

The primary objective of this project was to identify and evaluate parametric models for making default estimates of travel times on arterial links. A review of the literature revealed several candidate models, including the Bureau of Public Roads (BPR) function, Spiess's conical volume delay function, the Singapore model, the Skabardonis- Dowling model, and the Highway Capacity Manual's model. A license plate method was applied to a sample of 50 arterial links located in the Twin Cities seven county metropolitan area, to obtain measurements of average travel time. Also obtained were the lengths of each link, measurements of traffic volume, and signal timing information. Default values for model parameters were obtained from the Twin Cities planning model's database. Using network default parameters, we found that the BPR and conical volume-delay models produced mean average percent errors (MAPE) of about 25%, while the Singapore and Skabardonis-Dowling models, using maximal site-specific information, produced MAPE values of around 6.5%. As site-specific information was replaced by default information the performance of the latter two models deteriorated, but even under conditions of minimal information the models produced MAPE values of around 20%. A cross-validation study of the Skabardonis-Dowling model showed essentially similar performance when predicting travel times on links not used to estimate default parameter values.