Madhav Chitturi

METHODOLOGY FOR ESTIMATING OPERATING SPEED AND CAPACITY IN WORK ZONES

A new step-by-step methodology for estimation of operating speed and capacity in work zones on highways is presented and validated. The underlying principle of this methodology is that the operating factors in work zones, which include work intensity, lane width, lateral clearance, and other factors, cause motorists to reduce their speed. The reduced speed adversely affects the capacity of the work zones. Video data were collected for around 30 h from 11 work zones on Interstate highways in Illinois where one of the two lanes was closed. These work zones included eight long-term and three short-term ones. Work intensity in the work zone was quantified, and the relationship between work intensity and consequent speed reduction in construction zones was established. Speed reduction in a long-term work zone was established with field data, and the reduction in a short-term work zone was established with data from a driver survey. These relationships were used to compute the operating speed in the work zone. A speed-flow curve, which represents the operating conditions in work zones, was developed. The congested part of the curve was developed with the field data, corresponding to platooning vehicles, and the uncongested part was developed from information in the Highway Capacity Manual and the educated judgment of the authors. Once the operating speed is known, this curve can be used to obtain the capacity of the work zone. The developed methodology was used to predict the operating speed and capacity of work zones, and these predictions were compared with field data for validation.

Methodology for Computing Delay and User Costs in Work Zones

A step-by-step methodology for computing delays and user costs in highway work zones is presented in this paper. The methodology is based on the relationship between speed and capacity in work zones. Speed is adjusted to account for the adverse effects of roadway geometrics, work intensity, speed enforcement, and other work zone factors. Speed reductions for work intensity and narrow lane widths were determined previously by use of data from work zones. Values from the Highway Capacity Manual were used where data from work zones were not available. The fundamental difference between this methodology and previous approaches is that it accounts for the various work zone factors. Two applications of the methodology are presented, one with queuing and one without queuing, to real-world work zones. Results are compared with field data. For the nonqueuing site, the computed speed and capacity were 44.4 mph and 1,778 vehicles per hour per lane (vphpl), respectively, while the field speed and capacity were 44 mph and 1,708 vphpl, respectively. For the queuing site, computed capacity was 1,012 vphpl while the field capacity was 1,220 vphpl. Considering the assumptions made in the methodology for some of the parameters, these results build confidence in the methodology. Extensive validation of this methodology is strongly recommended.

Modeling Reservation-Based Autonomous Intersection Control in VISSIM

The use of autonomous vehicles is attracting more and more attention as a promising approach to improving both highway safety and efficiency. Most previous studies on autonomous intersection management relied heavily on custom-built simulation tools to implement and evaluate their control algorithms, but the use of nonstandard simulation platforms makes the comparison of systems almost impossible. Furthermore, without support from standard simulation platforms, reliable and trustworthy simulation results are hard to obtain. In this context, this paper explores a way to model autonomous intersections through the use of VISSIM, a standard microscopic simulation platform. A reservation-based intersection control system named autonomous control of urban traffic (ACUTA) was introduced and implemented in VISSIM through the use of VISSIMs external driver model. The operational and safety performance characteristics of ACUTA were evaluated with VISSIMs easy-to-use evaluation tools. In comparison with the results obtained with optimized signalized control, significantly reduced delays, along with a higher intersection capacity and lower volume-to-capacity ratios under various traffic demand conditions, resulted from the use of ACUTA. The safety performance of ACUTA was evaluated by use of the surrogate safety measure model, and few conflicts between vehicles within the intersection were detected. Moreover, the key steps and elements for implementation of ACUTA in VISSIM were introduced. These steps and elements can be useful for other researchers and practitioners implementing their autonomous intersection control algorithms in a standard simulation platform. By use of a standard simulation platform, the performance characteristics of autonomous intersection control algorithms can eventually be compared.

Automated Speed Photo Enforcement Effects on Speeds in Work Zones

Automated speed enforcement in construction zones has the potential to increase compliance with the speed limit and improve safety. The effectiveness of speed photo enforcement (SPE) (by radar) in reducing speeds and increasing speed limit compliance in work zones was evaluated for the first time in the United States, at Illinois work zones. Details are presented on SPE implementation and its effectiveness at the point it was stationed and at a downstream location in a work zone. Speed data were collected at the location of SPE and at a location 1.5 mi downstream in the work zone to determine the point and spatial effects of SPE. Speeds were measured for free-flowing and platooned cars and heavy vehicles in shoulder and median lanes. Results showed that SPE is effective in reducing the average speed and increasing compliance with work zone speed limit. The SPE reduced speed in the median lane more than in the shoulder lane, as expected. In addition, the speed of free-flowing vehicles was reduced more than for platooned vehicles. The reduction of the mean speed varied from 3.2 to 7.3 mph. The percentage of vehicles exceeding the speed limit near SPE was reduced from about 40% to 8% for free-flowing cars and from 17% to 4% for free-flowing heavy vehicles. Near the SPE van, none of the cars exceeded the speed limit by more than 10 mph, and none of the heavy vehicles exceeded it by more than 5 mph. The data also showed a mixed spatial effect for SPE. At the downstream location, the speed reduction for cars was not significant, while it varied from 0.9 to 2.5 mph for heavy vehicles.

Effect of Lane Width on Speeds of Cars and Heavy Vehicles in Work Zones

Traffic data were collected from 11 work zones on Interstate highways in Illinois in which one of the two lanes was open. The reductions in free-flow speed (FFS) due to narrow lanes and lateral clearances in work zones were studied. It was found that the reductions in FFSs of vehicles in work zones because of narrow lanes were higher than the reductions given in the Highway Capacity Manual for basic freeway sections. The data also showed that the narrower the lane was, the greater the speed reduction was. The data showed that the FFSs of heavy vehicles were statistically lower than the FFSs of passenger cars, even though the speed limit was the same for both types of vehicles. In addition, the reduction in the FFSs of heavy vehicles was greater than the reduction in the FFSs of passenger cars. This greater reduction in the speed of heavy vehicles affected the performance of the traffic stream in work zones. Thus, it should be considered in the computation of the passenger car equivalence for heavy vehicle...

Automated Identification and Extraction of Horizontal Curve Information from Geographic Information System Roadway Maps

Roadway horizontal alignment has long been recognized as one of the most significant contributing factors to lane departure crashes. Knowledge of the location and geometric information of horizontal curves can greatly facilitate the development of appropriate countermeasures. When curve information is unavailable, obtaining curve data in a cost-effective way is of great interest to practitioners and researchers. To date, many approaches have been developed to extract curve information from commercial satellite imagery, Global Positioning System survey data, laser-scanning data, and AutoCAD digital maps. As geographic information system (GIS) roadway maps become more accessible and more widely used, they become another cost-effective source for extraction of curve data. This paper presents a fully automated method for the extraction of horizontal curve data from GIS roadway maps. A specific curve data–extraction algorithm was developed and implemented as a customized add-in tool in ArcMap. With this tool, horizontal curves could be automatically identified from GIS roadway maps. The length, radius, and central angle of the curves were also computed automatically. The only input parameter of the proposed algorithm was calibrated to have the least curve identification errors. Finally, algorithm validation was conducted through a comparison of the algorithm-extracted curve data with the ground truth curve data for 76 curves that were obtained from Bing aerial maps. The validation results indicated that the proposed algorithm was very effective and that it identified completely 96.7% of curves and computed accurately their geometric information.

Downstream effects of speed photo-radar enforcement and other speed reduction treatments on work zones

The effects of automated speed photo–radar enforcement (SPE) and traditional speed reduction treatments (speed feedback trailer, presence of police vehicles with emergency lights on and off, and combinations of the speed feedback trailer and police presence) on speed were studied at a location 1.5 mi downstream of the actual treatment (spatial effects). Three data sets from two Interstate highway work zones were used. Field data consistently showed significant spatial (downstream) effects for SPE. The combination of speed feedback trailer and police vehicle with emergency lights off had downstream effects in some cases but to a lesser degree than SPE. Other treatments showed no significant downstream effects. For free-flowing traffic, SPE reduced the average downstream speed by 2 to 3.8 mph for cars and by 0.8 to 5.3 mph for trucks. Also, SPE reduced speeding cars by 7.1% to 23.4% (except for cars in median in Data Set 1), and speeding trucks by 4.2% to 48.3% (except for trucks in shoulder in Data Set 3). For the general traffic stream, SPE reduced the average downstream speed by 1.1 to 2.9 mph on cars and by 0.9 to 3.3 mph on trucks. When SPE was used, the percentage of speeding cars and trucks in the general traffic stream was reduced by 2.9% to 28.6%, and by 7.5% to 36.1%, respectively. SPE also reduced the percentage of cars in the general traffic stream exceeding the speed limit by more than 10 mph in virtually all cases, and eliminated such trucks in all but one case.

Effects of fog, snow, and rain on video detection systems at intersections

Abstract The flexibility and adaptability of video detection systems (VDS) make them attractive for vehicle detection at signalized intersections. However, the VDS performance could be affected by illumination and weather factors. This paper presents an evaluation of three commercial VDS under six adverse weather conditions including snow, fog, and rain, during daytime and/or nighttime. The systems were installed side-by-side at a signalized intersection, and evaluated at stop bar and advance zones based on four detection errors: false calls, missed calls, stuck-on calls (detections that are not terminated soon after vehicles depart), and dropped calls. Activation and deactivation timestamps were initially screened using a computer algorithm, and finally all errors were manually verified using video images. Results showed significant changes in the VDS performance under the different weather conditions. False activations increased in most scenarios but to a greater extent in snow conditions during both daytime and nighttime (typically to more than 50%, and up to 90%). Missed calls also increased in snow conditions and during dense fog (typically to more than 10%, and up to 50%) mostly at the advance zones. Stuck-on calls increased mostly in nighttime rain (less than 10%), while in general dropped calls were rare. Detailed quantification of the errors in each detection zone, and their potential causes are presented.

Safety Evaluation of Horizontal Curves on Rural Undivided Roads

The objective of this research was to develop prediction models for total crashes and fatal or injury crashes for rural horizontal curves on undivided roads, with a focus on three distinct aspects. The first was an emphasis on assembling a large, high-quality data set. Crash prediction models were developed by using a data set of 11,427 rural horizontal curves on Wisconsin state trunk network roads with more than 13 parameters and four distinct types of crash data sets. The second focus area was to use regression tree analysis in creating a simple model of horizontal curve safety aimed at practitioners of systemic road safety management and creating subsets of data that warranted further analysis. Regression tree results identified the curve radius of approximately 2,500 ft as a significant point below which there is a marked increase in crashes on horizontal curves. The third focus area was to research the effect on horizontal curve crash prediction models of different selection criteria to assemble the crash data set. Models (total and fatal or injury) based on a crash data set with and without crashes in the proximity of intersections were compared. The results show that when crashes on horizontal curves are selected where crash report forms indicate the presence of a horizontal curve, crashes that occur in the proximity of intersections do not affect model results significantly; therefore, the inclusion of such crashes would increase the size of the data set and benefit model development.

Speed Photo-Radar Enforcement and Its Effects on Speed in Work Zones

Automated speed photo–radar enforcement (SPE) in work zones was implemented for the first time in the United States in Illinois. This paper presents the results of the effectiveness of SPE on the basis of three data sets collected in two work zones. SPE was effective in reducing the average speed and increasing compliance with the work zone speed limit in all three data sets. In almost all cases in which SPE was implemented, the average speeds were significantly lower than the work zone speed limit. The average free-flowing speed of cars was reduced by 4.2 to 7.9 mph, and that of trucks by 3.4 to 6.9 mph. SPE reduced the percentage of cars and heavy vehicles exceeding the speed limit significantly. The percentages of free-flowing cars exceeding the speed limit were reduced from 39.8% to 8.3% in Data Set 1, from 30.4% to 4.2% in Data Set 2, and from 93.2% to 45.5% in Data Set 3. The percentages of free-flowing heavy vehicles exceeding the speed limit were reduced from 17.3% to 4.2% in Data Set 1; from 6.1% to 1.2% in Data Set 2; and from 69.2% to 13.9% in Data Set 3. Trucks did not exceed the speed limit by more than 10 mph in any of the data sets when SPE was implemented. In two data sets no cars exceeded the speed limit by more than 10 mph, while in the third data set only 2.5% did. Field data were also collected after the SPE van left the work zone to examine the halo (temporal) effects of SPE. SPE had a halo effect of 1.8∼2.7 mph on free-flowing trucks in one work zone but none in the other work zone. The halo effect of SPE on free-flowing cars was a limited 1.2 mph on the shoulder lane in only one data set.