Search results for "Digital image processing technique"
showing 3 items of 3 documents
Traffic Flow Variables Estimation: An Automated Procedure Based on Moving Observer Method. Potential Application for Autonomous Vehicles
2019
Abstract The estimation of traffic flow variables (flow, space mean speed and density) plays a fundamental role in highways planning and designing, as well as in traffic control strategies. Moving Observer Method (MOM) allows traffic surveys in a road, or in a road network. This paper proposes a novel automated procedure, called MOM-AP based on Moving Observer Method and Digital Image Processing (DIP) Technique able to automatically detect (without human observers) and calculate flow q, space mean speed vs and density k in case of stationary and homogeneous traffic conditions. In order to evaluate how reliable is the MOM-AP, an experiment has been carried out in a segment of one two-lane si…
Analysis of Kinematic Parameters and Driver Behavior at Turbo Roundabouts
2018
This study focuses on both vehicle kinematic parameters (speed and acceleration) and behavior parameters (critical interval and follow-up time) of drivers at turbo-roundabouts. Empirical evaluations of such parameters can be helpful in calibrating traffic microsimulation models or assigning behavior parameters to closed-form capacity models in turbo-roundabouts (gap-acceptance capacity models) and are also related to evaluation of vehicles pollutant emissions. The research was based on traffic process observed in the first turbo-roundabout implemented in the city of Maribor in Slovenia. In 2016 a great number of traffic samples were taken with high-frame-rate video recordings [>50 frames pe…
Automated Railway Signs Detection. Preliminary Results
2019
Abstract Nowadays safety in railways is mostly achieved by automated system technologies such as ERTMS/ETCS. Nevertheless, on local railways (suburban and regional lines) several tasks still depend on the choices and actions of a human crew. With the aim to improve safety in such type of railways, this research proposes a system for the automatic detection and recognition of railway signs by means of the digital image processing technique. First field applications, carried out on the Italian railway network, show that the proposed system is very accurate (the percentage of correctly detected railway signs is about 97%), even at high train speeds.