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Estimates of annual average daily traffic volumes are important in the planning and operations of state highway departments. These estimates are used in the planning of new construction and improvement of existing facilities, and, in some cases, in the allocation of maintenance funds. It is, therefore, important that any method used in obtaining the estimates provide data of sufficient accuracy for the intended use. This importance of having reliable and current data on traffic volumes at hand is generally recognized, and over the years data collection programs have tended to expand. This expansion has led to huge amounts of money being spent annually for the collection and analysis of traffic data. Efforts are, however, now being made to reduce the annual expenditure on traffic counts while at the same time maintaining the desired level of accuracy. A study was, therefore, carried out by the Council to develop an optimal counting program for the state. Firstly, the study entailed breaking down all highways in the primary system into homogeneous links such that the traffic characteristics along any given link were constant. A total of 2,510 links were obtained. The links in each district were then grouped into clusters, such that the links within a given cluster had similar traffic volume characteristics. The McQueen's K-means Method was used in the grouping procedure. A total of 82 clusters were obtained. A counting procedure was then developed based on an accuracy level of ± 10% with 95% confidence. Counting stations were then randomly selected. The counting program developed requires 927 counting stations for the whole state compared with the 1,345 currently being used.
The methodology described in entry 55-14 was used with 1980 data for 16 continuous count stations to determine periods that were stable throughout the year for different short counts. It was found that stable periods for short counts occurred mainly on Mondays, Tuesdays, and Wednesdays, and expansion factors were then developed for short counts of different durations and different starting times for these days. The expansion factors were then used to estimate 1981 AADT's from short counts extracted from data obtained in 1981 continuous counts. The results indicated that relative errors of less than 10% were obtained for AADT's estimated from counts of 6-, 8-, 10-, and 12-hour durations on Mondays, Tuesdays, and Wednesdays. As described in entry 55-15, the overall study entailed breaking down all highways in the primary system into homogeneous links such that the traffic characteristics along any given link were constant. The links in each district were then grouped into clusters such that the links within a given cluster had similar traffic volume characteristics. A counting procedure was then developed based on an accuracy level of ± 10% with 95% confidence. Counting stations were then randomly selected. Entry 55-17 revised some of the data in the final report.
This book is focused on the discussion of the traffic assignment problem, the mathematical and practical meaning of variables, functions and basic principles. This work gives information about new approaches, methods and algorithms based on original methodological technique, developed by authors in their publications for the past several years, as well as corresponding prospective implementations. The book may be of interest to a wide range of readers, such as civil engineering students, traffic engineers, developers of traffic assignment algorithms etc. The obtained results here are to be used in both practice and theory. This book is devoted to the traffic assignment problem, formulated in a form of nonlinear optimization program. The most efficient solution algorithms related to the problem are based on its structural features and practical meaning rather than on standard nonlinear optimization techniques or approaches. The authors have carefully considered the meaning of the traffic assignment problem for efficient algorithms development.
Estimates of annual average daily traffic (AADT) volumes are important in the planning and operations of state highway departments. These estimates are used in the planning of new construction and improvements of existing facilities, and, in some cases, in the allocation of maintenance funds. It is, therefore, important that any method used in obtaining the estimates provide data of sufficient accuracy for the intended use. This importance of having reliable and current data on traffic volumes at hand is generally recognized, and over the years data collection programs have tended to expand. This expansion has ledto huge amounts of money being spent annually for the collection and analysis of traffic data. Renewed efforts are, however, now being made to reduce the annual expenditure on traffic counts while at the same time maintaining the desired level of accuracy. A study is, therefore, being carried out by the Council to develop an optimal counting program for the state. This interim report presents the results of that portion of the study in which the feasibility of estimating AADT volumes from short counts was established. The procedure was first to use 1980 data for 16 continuous count stations to determine periods that are stable throughout the year for different short counts. It was found that stable periods for short counts occurred mainly on Mondays, Tuesdays, and Wednesdays, and expansion factors were then developed for short counts of different durations and different starting times for these days. The expansion factors were then used to estimate 1981AADT's from short counts extracted from data obtained in 1981 continuous counts. The results indicate that relative errors of less than 10% were obtained for AADT's estimated from counts of 6-, 8-, 10-, and 12-hour durations on Mondays, Tuesdays, and Wednesdays-The results for Tuesdays and Wednesdays tended to be more accurate than those for Mondays, and counts taken between February and November tended to give more accurate results than those taken in January and December.
This book contains selected papers from the presentations given at the 7th EURO-Working Group Meeting on 'Iransportation, which took place at the Helsinki University of Technology (HUT), Finland, during August 2-4, 1999. Altogether 31 presentations were given and 14 full papers have been selected in this publication through a peer review process coordinated by the editors. The papers in this book cover a wide range of transportation problems from the simulation of railway traffic to optimum congestion tolling and mode choice modeling with stated preference data. In general, the variety of papers clearly demonstrates the wide areas of interest of people who are involved in the research of transportation systems and their operation. They as well demonstrate the importance and possibilities of modeling and theoretical approaches in the analysis of transportation systems and problem solving. Most of the papers are purely theoretical in nature, that is, they present a theoretical model with only a hypothetical example of applica tion. There are, however, some papers, which are closer to the practice or describe applications of and give interesting results of studies made by known methodologies. It is especially noteworthy, that half of the accepted papers deal with planning and operation of public transport.
This report summarizes the results of the National Signal Timing Organization Project initiated by the Federal Highway Administration as a fuel conservation effort. The objectives of this project are: 1) to establish credible data on the effectiveness of signal timing optimization; 2) to make signal timing optimization projects easier to do; and 3) to define the resources (cost, level of staff, computer, etc.) required to undertake a signal timing optimization project, so that traffic engineers and administrators can more effectively budget for this activity. The project consisted of the development of the TRANSYT-7F signal timing optimization program User's Manual, and training course, and application of the program in 11 cities nationwide to evaluate the effectiveness of the poptimized signal timing plans and to collect data on the needed resources.