Deep Learning and YOLOv3 Systems for Automatic Traffic Data Measurement by Moving Car Observer Technique

Macroscopic traffic flow variables estimation is of fundamental interest in the planning, designing and controlling of highway facilities. This article presents a novel automatic traffic data acquirement method, called MOM-DL, based on the moving observer method (MOM), deep learning and YOLOv3 algorithm. The proposed method is able to automatically detect vehicles in a traffic stream and estimate the traffic variables flow q, space mean speed vs. and vehicle density k for highways in stationary and homogeneous traffic conditions. The first application of the MOM-DL technique concerns a segment of an Italian highway. In the experiments, a survey vehicle equipped with a camera has been used. Using deep learning and YOLOv3 the vehicles detection and the counting processes have been carried out for the analyzed highway segment. The traffic flow variables have been calculated by the Wardrop relationships. The first results demonstrate that the MOM and MOM-DL methods are in good agreement with each other despite some errors arising with MOM-DL during the vehicle detection step due to a variety of reasons. However, the values of macroscopic traffic variables estimated by means of the Drakes’ traffic flow model together with the proposed method (MOM-DL) are very close to those obtained by the traditional one (MOM), being the maximum percentage variation less than 3%.

Traffic Operations on Rural Two-Lane Highways: A Review on Performance Measures and Indicators

Two- lane highways constitute a large proportion of the highway system in the United States, particularly in rural areas. Performance evaluation on those highways is the basis for planning, upgrade, and improvement programs. Such evaluations are conducted using performance measures that should ideally be correlated to performance determinants on those highways. Unlike other highway facilities, two-lane highway performance is notably affected by the platooning phenomenon, which is believed to be a function of traffic level and passing opportunities. Over the last couple of decades, several studies have addressed performance measures on two-lane highways, and are mainly driven by the reported limitations of the current measures used by the Highway Capacity Manual (HCM). This review aims to summarize the performance measures that have been published in the literature or used in practice both in the United States and abroad. The review starts with an historical overview of the HCM performance measures since its inception in 1950. It then discusses the most important criteria for measures to be more effective in describing performance, before presenting the review results for measures that have been proposed in literature or reported as being used in practice. Finally, a subjective assessment of all performance measures against the set of criteria outlined in the article is presented. The review presented in this paper provides information that is valuable for practitioners and researchers in understating the alternative measures for assessing performance on two-lane highways, and the limitations and merits associated with those measures.

Using Congestion-Priced Road User Charges to Restore Metropolitan Mobility and Fund Highways

The purpose of this paper is to introduce and evaluate a congestion-pricing strategy that could be used in metropolitan areas to supplement revenue generation mechanisms such as mileage-based user fees and fuel taxes. Congestion charges would be applied with transponder-based technology only on limited access metropolitan highway facilities to pay for the costs of their reconstruction and maintenance. Since most of the worst congestion in metropolitan and state roadways occurs on limited access facilities, this strategy would address the goal of restoring mobility without raising the kinds of privacy concerns that appear with regard to other types of more comprehensive road user charging systems that use location-based technology, such as mileage-based user fees. Proceeds from congestion charges could be used to pay for new low-cost, part-time (dynamic) shoulder travel lane capacity and transit and carpooling enhancements. This approach can increase public acceptability by providing multimodal travel alternatives. The paper discusses the strategy in the context of the reconstruction of the freeway system in a hypothetical metropolitan area, with an availability payment public–private partnership project delivery model to design, finance, build, operate, and maintain the improved freeway network. The analysis presented in the paper suggests that the approach could be financially viable and more economically efficient than conventional transportation funding approaches.