Technical Report Documentation Page 1. Report No. 2 .
1. Report No.2. Government Accession No.Technical Report Documentation Page3. Recipient's Catalog No.SWUTC/00/167707-15. Report Date4. Title and SubtitleComprehensive Engineering Approach to Achieving Safe Neighborhoods September 20006. Performing Organization Code8. Performing Organization Report No.7. Author(s)James A. Bonneson, Angelia H. Parham and Karl Zimmerman9. Performing Organization Name and AddressResearch Report 167707-110. Work Unit No. (TRAIS)Texas Transportation InstituteTexas A&M University SystemCollege Station, Texas 77843-313511. Contract or Grant No.1072712. Sponsoring Agency Name and Address13. Type of Report and Period CoveredSouthwest Region University Transportation CenterTexas Transportation InstituteThe Texas A&M University SystemCollege Station, Texas 77843-313514. Sponsoring Agency Code15. Supplementary NotesSupported by general revenues from the State of Texas.16. AbstractSteady increases in travel demand coupled with minimal increases in arterial street capacity have led to an increase intraffic-related safety problems in residential neighborhoods. These problems stem from the significant number of motorists thatdivert from the arterial to the residential street system in an effort to avoid arterial-related delays. Diverted motorists add toneighborhood traffic volumes and increase crash exposure for pedestrians, bicyclists, and other vehicles. In addition, divertedmotorists often drive at excessive speed which increases both the potential for a crash and its severity.The objective of this research was to develop guidelines for the use of both neighborhood traffic management and corridortraffic management techniques for improving safety in residential neighborhoods. The focus of this research is on neighborhoodand corridor traffic management techniques that have the potential to reduce speed or cut-through volume on the local streetsystem. The approach taken to conduct this research was to develop as much of the guideline material through a synthesis of theliterature and to supplement this synthesis with some investigative research in areas where information was lacking.A model was developed for this research that can predict the percent of arterial drivers that cut-through the adjacentneighborhood streets. The data used to develop this model were obtained from extensive simulations of a typical city street systemthat includes arterial, collector, and local streets. The model variables include average arterial travel speed, signal density (insignals per mile), and the degree of saturation of the signalized intersections on the arterial. Percent cut-through traffic was foundto range from 0.0 to 30 percent of the arterial volume, with the higher percentage associated with oversaturated signalizedintersections.Several recommendations for future research in the area of traffic management techniques were developed.Fundamentally, it is recommended that additional research be conducted on the effectiveness of alternative traffic managementtechniques. For neighborhood traffic management techniques, before-and-after data are needed to assess technique effectiveness interms of volume reduction, speed reduction, and crash reduction. For corridor traffic management, further research efforts arenecessary to verify the accuracy of the cut-through traffic prediction model developed for this research.17. Key Words18. Distribution StatementTraffic Calming, Route Modification,Neighborhood Traffic Management, CorridorTraffic Management, Cut-Through Traffic, LivableStreetsNo Restrictions. This document is available to the public through NNational Technical Information Service5285 Port Royal RoadSpringfield, Virginia 2216119. Security Classif.(of this report)UnclassifiedForm DOT F 1700.7 (8-72)20. Security Classif.(of this page)21. No. of PagesUnclassified62Reproduction of completed page authorized22. Price
COMPREHENSIVE ENGINEERING APPROACH TOACHIEVING SAFE NEIGHBORHOODSFINAL REPORTforResearch Project No. 167707SOUTHWEST REGION UNIVERSITY TRANSPORTATION CENTERTEXAS TRANSPORTATION INSTITUTETHE TEXAS A&M UNIVERSITY SYSTEMbyJames A. Bonneson, Ph.D., P.E.Angelia H. Parham, P.E.Karl ZimmermanTexas Transportation InstituteTexas A&M UniversityCollege Station, Texas 77843-3135September 2000
ABSTRACTSteady increases in travel demand coupled with minimal increases in arterial streetcapacity have led to an increase in traffic-related safety problems in residentialneighborhoods. These problems stem from the significant number of motorists that divertfrom the arterial to the residential street system in an effort to avoid arterial-related delays.Diverted motorists add to neighborhood traffic volumes and increase crash exposure forpedestrians, bicyclists, and other vehicles. In addition, diverted motorists often drive atexcessive speed which increases both the potential for a crash and its severity.The objective of this research was to develop guidelines for the use of bothneighborhood traffic management and corridor traffic management techniques for improvingsafety in residential neighborhoods. The focus of this research is on neighborhood andcorridor traffic management techniques that have the potential to reduce speed or cut-throughvolume on the local street system. The approach taken to conduct this research was todevelop as much of the guideline material through a synthesis of the literature and tosupplement this synthesis with some investigative research in areas where information waslacking.A model was developed for this research that can predict the percent of arterialdrivers that cut-through the adjacent neighborhood streets. The data used to develop thismodel were obtained from extensive simulations of a typical city street system that includesarterial, collector, and local streets. The model variables include average arterial travelspeed, signal density (in signals per mile), and the degree of saturation of the signalizedintersections on the arterial. Percent cut-through traffic was found to range from 0.0 to 30percent of the arterial volume, with the higher percentage associated with oversaturatedsignalized intersections.Several recommendations for future research in the area of traffic managementtechniques were developed. Fundamentally, it is recommended that additional research beconducted on the effectiveness of alternative traffic management techniques.F o rneighborhood traffic management techniques, before-and-after data are needed to assesstechnique effectiveness in terms of volume reduction, speed reduction, and crash reduction.For corridor traffic management, further research efforts are necessary to verify the accuracyof the cut-through traffic prediction model developed for this research.ii
EXECUTIVE SUMMARYSteady increases in travel demand coupled with minimal increases in arterial streetcapacity have led to an increase in traffic-related safety problems in residentialneighborhoods. These problems stem from the significant number of motorists that divertfrom the arterial to the residential street system in an effort to avoid arterial-related delays.Diverted motorists add to neighborhood traffic volumes and increase crash exposure forpedestrians, bicyclists, and other vehicles. In addition, diverted motorists often drive atexcessive speed which increases both the potential for a crash and its severity.The objective of this research was to develop guidelines for the use of bothneighborhood traffic management and corridor traffic management techniques for improvingsafety in residential neighborhoods. The guidelines would provide a framework forevaluating the effectiveness of a traffic management plan developed for a specifiedneighborhood and associated street system. This framework would allow for an evaluationof alternative techniques on a consistent basis.The focus of this research is on neighborhood and corridor traffic managementtechniques that have the potential to reduce speed or cut-through volume on the local streetsystem. The techniques considered for neighborhood traffic management are limited to thosecommonly deployed on residential streets by city agencies. Such techniques include: streetclosures, speed humps, traffic circles, and roadway narrowings. Techniques considered forcorridor traffic management are limited to those that increase arterial travel speed. Suchtechniques include: signalization improvements, geometric improvements, and accessmanagement.The approach taken to conduct this research was to develop as much of the guidelinematerial through a synthesis of the literature and to supplement this synthesis with someinvestigative research in areas where information was lacking. Some information was foundin the literature for the more common neighborhood traffic management devices. However,no information was found that described the effect of arterial operations on the number ofdrivers that might divert from the arterial through the adjacent neighborhood. Based on thisfinding, research was conducted to develop a relationship between arterial travel speed andthe percent of drivers that cut-through adjacent neighborhoods.The synthesis of neighborhood traffic management techniques focused on threemeasures of effectiveness: volume reduction, speed reduction, and crash reduction. Averagereductions (expressed as a percentage) were obtained from two sources that reflect conditionson several hundred city streets. Three management techniques that had been used most, asreported in these studies, include speed humps, traffic circles, and speed tables. Thesedevices were found to reduce street volumes from 5 to 25 percent. The reduced speeds from15 to 20 percent and crash rates from 4 to 15 percent, depending on the device.A model was developed for this research that can predict the percent of arterialdrivers that cut-through the adjacent neighborhood streets. The data used to develop thismodel were obtained from extensive simulations of a typical city street system that includesiii
arterial, collector, and local streets. The model variables include average arterial travelspeed, signal density (in signals per mile), and the degree of saturation of the signalizedintersections on the arterial. Percent cut-through traffic was found to range from 0.0 to 30percent of the arterial volume, with the higher percentage associated with oversaturatedsignalized intersections.A sensitivity analysis using this model indicated that the percent cut-through trafficdecreased rapidly with increasing arterial travel speed. The percentage of cut-through trafficalso decreased with an increase in signal density. This latter trend may appearcounterintuitive; however, further analysis indicated that it actually reflected an increase indelay on a “per signal” basis. Hence, it was concluded that percentage of cut-through trafficincreases with an increase in delay per signal.The sensitivity analysis also revealed that there is the possibility of a thresholdarterial travel speed associated with no cut-through traffic. If arterial travel speed could bemaintained at this threshold (or higher), cut-through traffic would essentially disappear. Thisthreshold was found to equate to an average arterial travel speed that is about 50 percent ofthe free-flow speed. Thus, when average speeds are one-half of the free-flow speed or less,drivers will likely cut-through the neighborhood adjacent to the arterial.Several recommendations for future research in the area of traffic managementtechniques were developed. Fundamentally, it is recommended that additional research beconducted on the effectiveness of alternative traffic management techniques. The existingbody of knowledge is based on informal studies conducted by agency staff for the purposeof assessing the effect at a given street location. Such studies rarely record all of the relevantdata or control for area-wide influences. The result is considerable variability in the reportedeffectiveness of any given technique.For neighborhood traffic management techniques, before-and-after data are neededto assess technique effectiveness in terms of volume reduction, speed reduction, and crashreduction. Studies that quantify the level of volume reduction should also report the“connectivity” (i.e., number of street segments per intersection or cul-de-sac) or a similarmeasure that provides some indication of the availability of alternate routes. Studies thatquantify speed reductions should also report: (1) the location of the measurement relativeto the location of the technique, (2) the distance to other techniques, and (3) the geometryof the device, if a device is used. Studies that quantify crash reduction should include trafficvolume so that crash rate reduction can be computed. Crash rate is defined as the numberof crashes per million vehicles. It was shown in this research that crash rate reduction is amuch more accurate method of evaluating a technique’s ability to improve safety.For corridor traffic management, further research efforts are necessary to verify theaccuracy of the cut-through traffic prediction model developed for this research and thefindings associated with a sensitivity analysis of this model. Specifically, additional researchis needed to:iv
1. Verify the existence of a threshold travel speed above which there would be no cutthrough traffic,2. Expand the model to include sensitivities to a wider range of factors (e.g., size of theneighborhood, density and connectivity of the local street system, and application ofspecific route modification and calming devices), and3. Validate the model using real-world data.v
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TABLE OF CONTENTSpageTechnical Report Documentation Page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiExecutive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viAcknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viiDisclaimer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viiChapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Objective and Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Concepts and Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1155Chapter 2. Neighborhood Traffic Management Techniques . . . . . . . . . . . . . . . . . . . . . . . 7Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Technique Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12Chapter 3. Corridor Traffic Management Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Technique Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Chapter 4. Development of a Cut-Through Traffic Prediction Model . . . . . . . . . . . . . .Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Traffic Simulation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Data Analysis and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23232330Chapter 5. Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47vii
LIST OF ageIllustration of speed management techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3Example of alternative routes that lead to cut-through traffic . . . . . . . . . . . . . . . . . 16Signalization and geometric improvements that reduces cut-through volume . . . . . 19Effect of volume, capacity, signal spacing, and speed limit on average travel speed 22Simulated traffic network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26Distribution of trip origins by zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28Impedance values for each origin-destination pair . . . . . . . . . . . . . . . . . . . . . . . . . . 28Sample origin-destination matrix for a lane volume of 175 veh/h/ln . . . . . . . . . . . . 29Network operational and geometric factors investigated . . . . . . . . . . . . . . . . . . . . . 30Average travel speed as a function of lane volume and diagonal percentage . . . . . 31Average travel speed as a function of lane volume and signal density . . . . . . . . . . 31Cut-through percentage compared to average lane volume for base condition . . . . 32Percent cut-through traffic compared to average arterial travel speed . . . . . . . . . . . 33Predicted cut-through traffic percentage as a function of speed and signal density 34Predicted cut-through traffic percentage for undersaturated operating conditions . 36Predicted cut-through traffic percentage for oversaturated operating conditions . . 36Street network and traffic volumes for Examples 1 and 2 . . . . . . . . . . . . . . . . . . . . 37LIST OF son of crash rates by roadway classification in urban areas . . . . . . . . . . . . . 1List of neighborhood traffic management techniques . . . . . . . . . . . . . . . . . . . . . . . . 8Typical procedures and issues considered in developing a neighborhood trafficmanagement program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Emergency vehicle delays due to selected traffic calming devices . . . . . . . . . . . . . 11Effectiveness of selected neighborhood traffic management techniques . . . . . . . . . 12Effect of alternate route availability on volume change . . . . . . . . . . . . . . . . . . . . . . 13Effectiveness of three traffic calming devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Acceptable levels of local street traffic volume . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Relationship between free flow speed and level of service . . . . . . . . . . . . . . . . . . . 20Effectiveness of signal coordination and signal timing adjustment . . . . . . . . . . . . . 20Factors related to cut-through volume on local streets . . . . . . . . . . . . . . . . . . . . . . . 25Traffic control at intersections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Adjustments to Equation 2 to account for selected factors . . .
Technical Report Documentation Page 1. Report No. SWUTC/00/167707-1 2. Government Accession No. 3. Recipient's Catalog No. 4. Title and Subtitle Comprehensive Engineering Approach to Achieving Safe Neighborhoods 5. Report Date September 2000 6. Performing Organization Code 7. Author(s) James A. Bonneson, Angelia H. Parham and Karl Zimmerman 8.
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