Evaluation of Electronic Speed Limit Signs on US 30, September, 2011

This study documents the speed reduction impacts of two dynamic, electronic school zone speed limit signs at United Community Schools between Ames and Boone, Iowa. The school facility is situated along US Highway 30, a rural four-lane divided expressway. Due to concerns about high speeds in the area, the Iowa Department of Transportation (DOT) decided to replace the original static school zone speed limit signs, which had flashing beacons during school start and dismissal times (Figure 1), with electronic speed signs that only display the reduced school speed limit of 55 mph during school arrival and dismissal times (Figure 2). The Center for Transportation Research and Education (CTRE) at Iowa State University (ISU) conducted a speed evaluation study one week before and 1 month, 7 months, and 14 or 15 months after the new signs were installed. Overall, the new dynamic school zone speed limit signs were more effective in reducing speeds than the original static signs with flashing beacons in the 1 month after period. During the 7 and 14 month after period, speeds increased slightly for the eastbound direction of traffic. However, the increases were consistent with overall speed increases that occurred independent of the signs. The dynamic, electronic signs were effective for the westbound direction of traffic for all time periods and for both start and dismissal times. Even though only modest changes in mean and 85th percentile speeds occurred, with the speed decreases, the number of vehicles exceeding the school speed limit decreased significantly, indicating the signs had a significant impact on high-end speeders.

Effectiveness of speed control signs in rural school zones and small communities. Final report.

Federal Highway Administration, Office of Research, Washington, D.C.

Evaluation of speed control signs for small rural towns. Final report.

Federal Highway Administration, Washington, D.C.

Koala mortality on roads in south-east Queensland: the koala speed-zone trial

In 1995, the Queensland Parks and Wildlife Service, the Queensland Department of Main Roads and Redland Shire Council initiated the Koala Speed Zone Trial in the Koala Coast, south-east Queensland. The aim of the trial was to assess the effect of differential speed signs on the number of koalas ( Phascolarctos cinereus) hit by vehicles in the Koala Coast from 1995 to 1999. On the basis of information collected by the Queensland Parks and Wildlife Service 1407 koalas were hit by vehicles in the Koala Coast during the five-year study ( mean 281 koalas per year, range 251 - 315). Monitoring of vehicle speeds by the Queensland Department of Main Roads suggested that there was no significant reduction in vehicle speed during the trial period from August to December. Consequently, there was no evidence to suggest that a reduction in the number of koalas hit by vehicles occurred during the trial. Approximately 70% of koalas were hit on arterial and sub-arterial roads and approximately 83% did not survive. The location of each koala hit was recorded and the signed speed limit of the road was noted. Most koalas that were hit by vehicles were young healthy males. Pooling of data on koala collisions and road speed limits suggested that the proportion of koalas that survived being hit by vehicles was slightly higher on roads with lower speed limits. However, vehicle speed was not the only factor that affected the number of koalas hit by vehicles. It is suggested that habitat destruction, koala density and traffic volume also contribute to road-associated koala mortality in the Koala Coast.

Benchmark Evaluation of HOG Descriptors as Features for Classification of Traffic Signs

The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

Speed control on high speed roads. Final report.

Federal Highway Administration, Traffic Systems Division, Washington, D.C.

Speed zoning and control. Final report.

Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

An evaluation of warning and regulatory signs for curves on rural roads. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Video enforcement for HOV lanes: field test results for the I-30 HOV lane in Dallas.

Texas Department of Transportation, Austin

Dynamic Speed Feedback Signs, 2014

Dynamic speed feedback sign (DSFS) systems are traffic control devices that are programmed to provide a message to drivers exceeding a certain speed thresh¬old. A DSFS system typically consists of a speed-measuring device, which may be loop detectors or radar, and a message sign that displays feedback to drivers who exceed a predetermined speed threshold. The feedback may be the driver’s actual speed, a message like “SLOW DOWN,” or activation of a warning device such as beacons or a curve warning sign. For more on this topic by these authors, see also "Evaluation of Dynamic Speed Feedback Signs on Curves: A National Demonstration Project": http://www.trb.org/main/blurbs/172092.aspx

The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Driver response in active advanced warning signs at high-speed signalized intersections. Final report.

Federal Highway Administration, Washington, D.C.

Speed Management Toolbox for Rural Communities, TR-630, 2012

The primary objective of this toolbox is to summarize various known traffic-calming treatments and their effectiveness. This toolbox focuses on roadway-based treatments for speed management, particularly for rural communities with transition zones. Education, enforcement, and policy strategies should also be considered, but are not the focus of this toolbox. The research team identified treatments based on their own research, a review of the literature, and discussion with other professionals. This toolbox describes each treatment and summarizes placement, advantages, disadvantages, effectiveness, appropriateness, and cost for each treatment. The categories of treatments covered in this toolbox are as follows: horizontal physical displacement, vertical physical displacement, narrowing, surroundings, pavement markings, traffic control signs, and other strategies. Separate 3- to 4-page Tech Briefs for various aspects of this toolbox are attached to this record: Center Islands with Raised Curbing for Rural Traffic Calming, Colored Entrance Treatments for Rural Traffic Calming, Dynamic Speed Feedback Signs for Rural Traffic Calming, Transverse Speed Bars for Rural Traffic Calming. This toolbox and the tech briefs are related to the report Evaluation of Low Cost Traffic Calming for Rural Communities – Phase II, which is also included in this record or can be found at http://publications.iowa.gov/id/eprint/14769

Perception and Interpretation of Advance Warning Signs on County Roads, HR-256, 1984

This research consisted of five laboratory experiments designed to address the following two objectives in an integrated analysis: (1) To discriminate between the symbol Stop Ahead warning sign and a small set of other signs (which included the word-legend Stop Ahead sign); and (2) To analyze sign detection, recognizability, and processing characteristics by drivers. A set of 16 signs was used in each of three experiments. A tachistoscope was used to display each sign image to a respondent for a brief interval in a controlled viewing experiment. The first experiment was designed to test detection of a sign in the driver's visual field; the second experiment was designed to test the driver's ability to recognize a given sign in the visual field; and the third experiment was designed to test the speed and accuracy of a driver's response to each sign as a command to perform a driving action. A fourth experiment tested the meanings drivers associated with an eight-sign subset of the 16 signs used in the first three experiments. A fifth experiment required all persons to select which (if any) signs they considered to be appropriate for use on two scale model county road intersections. The conclusions are that word-legend Stop Ahead signs are more effective driver communication devices than symbol stop-ahead signs; that it is helpful to drivers to have a word plate supplementing the symbol sign if a symbol sign is used; and that the guidance in the Manual on Uniform Traffic Control Devices on the placement of advance warning signs should not supplant engineering judgment in providing proper sign communication at an intersection.