Dependence of design hourly volume on the function and nature of traffic demand of rural roads

In the first phases of study and design documentation of rural roads, one of the key parameters to determine in the analyses is the Design Hourly Volume (DHV). The required level of service and the feasibility of the project depend to a large extent on a properly established DHV. Essentially, the problem is to determine the value of the K-factor for a certain nth highest hour of the year. This paper points to the need for additional analysis of existing databases of long-term automatic traffic counting, from which the necessary guidance for planners and designers can be derived, enabling them to understand and apply the K-factors in a clearer and more detailed way. Using specific data examples, characteristic sections of rural roads with different functions and types (seasonal variations) of traffic demand were selected to show significant differences in the values of the K-factors for the same selected nth highest hour of the year. Several guidelines (BiH, Slovenia, Croatia, Italy, Serbia) were analysed beforehand to get a better understanding of how the K-factor or DHV is explained and used in different countries. The main objective of the article is to show that, on the basis of the existing databases of continuous automatic counting in these countries, with additional analyses presented in this paper or in a similar form, significant regularities in determining the DHV can be achieved, eliminating difficulties of application in engineering practice. As all guidelines practically recommend the use of HCM in capacity analyses, specific examples are selected to show the difference between the definition of HCM for a route with dominant recreational traffic and our route with dominant tourist traffic (recreational versus tourist).

Prediction of Design Hourly Volume on Rural Roads

Design hourly volume (DHV) represents one of the most significant parameters in the procedures of developing and evaluating road designs. DHV values can be accurately and precisely calculated only on the road sections with the implemented automatic traffic counters (ATCs) which constantly monitor the traffic volume. Unfortunately, many road sections do not contain ATCs primarily because of the implementation costs. Consequently, for many years, the DHV values have been defined on the basis of occasional counting and the factors related to traffic flow variability over time. However, it has been determined that this approach has significant limitations and that the predicted values considerably deviate from the actual values. Therefore, the main objective of this paper is to develop a model which will enable DHV prediction on rural roads in cases of insufficient data. The suggested model is based on the correlation between DHVs and the parameters defining the characteristics of traffic flows, that is, the relationship between the traffic volumes on design working days and non-working days, and annual average daily traffic. The results of the conducted research indicate that the application of the proposed model enables the prediction of DHV values with a significant level of data accuracy and reliability. The coefficient of determination (R2) shows that more than 98% of the variance of the calculated DHVs was explained by the observed DHV values, while the mean error ranged from 4.86% to 7.84% depending on the number of hours for which DHV was predicted.

Methodology For Determining Reliable Traffic Parameters For Current Analysis Of Performance Of Motorways And Expressways

In this paper, the results of analyses concerning selected traffic characteristics typical for Polish motorways and expressways are presented. The input data were collected automatically by stations located on various highways. In the first place, with the use of the coefficient of variability, periods with the lowest traffic volume variability in the year and the day were determined. On this basis, the most favourable time scope of random measurements was determined to allow reliable estimation of traffic parameters for road performance analyses. Then, based on model relationships between the characteristics of traffic volume variability over time and constant volume (regression relationships, a model of Artificial Neural Networks), correction factors were developed enabling direct conversion of the obtained measurement results into Design Hourly Volume. In addition, the rules for determining the share of heavy vehicles meeting the conditions at peak hours of the year were developed. The presented approach is in line with the current research trend on a global scale and allows for improving the accuracy of estimating Design Hourly Volume by 20 per cent concerning the method currently recommended in Poland.

Factors Determining Seasonal Variations in Traffic Volumes

The characteristics of seasonal variations in traffic volumes are used for a variety of purposes, for example to determine the basic parameters describing annual average daily traffic – AADT, and design hourly volume – DHV, analyses of road network reliability, and traffic management. Via these analyses proper classification of road sections into appropriate seasonal factor groups (SFGs) has a decisive influence on results. This article, on the basis of computational experiments (models of artificial neural networks, discriminatory analysis), aims to identify which factors have the greatest impact on the allocation of a section of road to the corresponding SFG, based on short-term measurements. These factors are presented as qualitative data: the Polish region, spatial relationships, functions of road, cross-sections, technical class; and quantitative data: rush hour traffic volume.