Traffic Flow and Vehicle Speed Measurements using Anisotropic Magnetoresistive (AMR) Sensors

2018 ◽  
Author(s):  
Budi Santoso ◽  
Bo Yang ◽  
Chun Lian Ong ◽  
Zhimin Yuan
Keyword(s):  
Traffic Flow ◽  
Vehicle Speed

ENSURING THE PEDESTRIAN’S SAFETY DESIGN OF URBAN STREET CROSSWALKS

2019 ◽  
pp. 103-110
Author(s):  
Dmitriy Nemchinov
Keyword(s):  
Traffic Flow ◽  
Minimum Distance ◽  
Travel Speed ◽  
Vehicle Speed ◽  
Urban Street ◽  
Safety Design ◽  
Positive Practices ◽  
Time Required ◽  
Pedestrian Crossing ◽  
The City

The article presents an analysis of positive practices for ensuring the safety of pedestrians at the inter-section of the city streets carriageway, as well as a description of some innovations of regulatory and tech-nical documents, including an increased number of cases when a safety island can be arranged at a pedestri-an crossing. requirements for providing visibility at a pedestrian crossing to determine the minimum distance of visibility at a pedestrian crossing based on the time required pedestrians for crossing the roadway, recommended options for using ground unregulated pedestrian crossings on trapezoidal artificial irregularities according to GOST R 52605; traffic flow) and Z-shaped (also in the direction of the traffic flow), the requirements for the size of the securi-ty island have been established to allow put bicycle inside of safety island, a recommended set of measures to reduce the vehicle speed and describes the types of activities and describes a method of their application, describes methods zones device with reduced travel speed - residential and school zones, set requirements for turboroundabouts and methods of their design.

On kinematic waves II. A theory of traffic flow on long crowded roads

1955 ◽  
Vol 229 (1178) ◽  
pp. 317-345 ◽  
Keyword(s):  
Traffic Flow ◽  
Functional Relationship ◽  
Vehicle Speed ◽  
Main Road ◽  
The Road ◽  
Traffic Distribution ◽  
Kinematic Waves ◽  
The Subject ◽  
The Mean ◽  
Starting Flow

This paper uses the method of kinematic waves, developed in part I, but may be read independently. A functional relationship between flow and concentration for traffic on crowded arterial roads has been postulated for some time, and has experimental backing (§2). From this a theory of the propagation of changes in traffic distribution along these roads may be deduced (§§2, 3). The theory is applied (§4) to the problem of estimating how a ‘hump’, or region of increased concentration, will move along a crowded main road. It is suggested that it will move slightly slower than the mean vehicle speed, and that vehicles passing through it will have to reduce speed rather suddenly (at a ‘shock wave’) on entering it, but can increase speed again only very gradually as they leave it. The hump gradually spreads out along the road, and the time scale of this process is estimated. The behaviour of such a hump on entering a bottleneck, which is too narrow to admit the increased flow, is studied (§5), and methods are obtained for estimating the extent and duration of the resulting hold-up. The theory is applicable principally to traffic behaviour over a long stretch of road, but the paper concludes (§6) with a discussion of its relevance to problems of flow near junctions, including a discussion of the starting flow at a controlled junction. In the introductory sections 1 and 2, we have included some elementary material on the quantitative study of traffic flow for the benefit of scientific readers unfamiliar with the subject.

Prediction of Vehicular Traffic Flow using Levenberg-Marquardt Artificial Neural Network Model: Italy Road Transportation System

2022 ◽  
Vol 24 (2) ◽  
pp. E74-E86
Author(s):  
Isaac Oyeyemi Olayode ◽  
Alessandro Severino ◽  
Tiziana Campisi ◽  
Lagouge Kwanda Tartibu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Time Of Day ◽  
Vehicle Speed ◽  
Road Transportation ◽  
Artificial Neural

In the last decades, the Italian road transport system has been characterized by severe and consistent traffic congestion and in particular Rome is one of the Italian cities most affected by this problem. In this study, a LevenbergMarquardt (LM) artificial neural network heuristic model was used to predict the traffic flow of non-autonomous vehicles. Traffic datasets were collected using both inductive loop detectors and video cameras as acquisition systems and selecting some parameters including vehicle speed, time of day, traffic volume and number of vehicles. The model showed a training, test and regression value (R2) of 0.99892, 0.99615 and 0.99714 respectively. The results of this research add to the growing body of literature on traffic flow modelling and help urban planners and traffic managers in terms of the traffic control and the provision of convenient travel routes for pedestrians and motorists.

Influence of Truck-Mounted Radar Speed Signs in Controlling Vehicle Speed for Mobile Maintenance Operations: Oregon Case Study

2017 ◽  
Vol 2617 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Ali Jafarnejad ◽  
John Gambatese ◽  
Salvador Hernandez
Keyword(s):  
Traffic Flow ◽  
T Test ◽  
Descriptive Statistics ◽  
Vehicle Speed ◽  
Work Zones ◽  
Speed Difference ◽  
Flow Speeds ◽  
Maintenance Work

Radar speed signs (RSSs) are a measure for reducing traffic flow speeds through work zones. The influence of truck-mounted RSSs on vehicle speed was evaluated for mobile maintenance operations in two multilane maintenance work zones in Oregon. In each case study, two periods of testing were conducted: one with the RSS display turned on (treatment) and one without the RSS display turned on (control), and vehicle speeds were recorded. Descriptive statistics were used to summarize collected data, and a two-sample t-test was applied to each case study to compare the speed difference between control and treatment cases. The findings indicate that vehicle speeds are typically lower and that there is less variation in speeds between adjacent vehicles with the RSS turned on. RSSs are thus promising devices for controlling vehicle speed and making work zones safer for motorists and workers.

CELLULAR AUTOMATON MODELS FOR MIXED TRAFFIC FLOW CONSIDERING PASSAGE WAY OF EMERGENCY VEHICLE

2013 ◽  
Vol 27 (08) ◽  
pp. 1350052 ◽  
Author(s):  
HAN-TAO ZHAO ◽  
HONG-YAN MAO ◽  
RUI-JIN HUANG
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Average Density ◽  
Vehicle Speed ◽  
Emergency Vehicle ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
The Road ◽  
Emergency Vehicles ◽  
Computer Numerical Simulation

Two kinds of cellular automaton models are proposed for mixed traffic flow with emphasis on emergency vehicles. By analyzing the characteristics of ordinary vehicles in giving way to emergency vehicles, the rules for changing lanes are modified. Computer numerical simulation results indicate that an emergency vehicle without changing lanes can enhance speed with density lower than 0.1, while its speed can be enhanced by changing lane with density greater than 0.1. Meanwhile, vehicle speed and density within a certain range around emergency vehicles are lower than the road section average velocity and average density. The passage way of emergency vehicle that facilitate lane change causes less interference than that of an emergency vehicle which is unable to change lane. The study found that the physical characteristics of traffic flow when there are emergency vehicles are significantly different from routine traffic flow. Emergency vehicles can facilitate their passage by changing lanes at a medium or high density.

USING VARIABLE SPEED LIMITS TO ELIMINATE WIDE MOVING JAMS: A STUDY BASED ON THREE-PHASE TRAFFIC THEORY

2012 ◽  
Vol 23 (09) ◽  
pp. 1250060 ◽  
Author(s):  
YIZHI WANG ◽  
YI ZHANG ◽  
JIANMING HU ◽  
LI LI
Keyword(s):  
Traffic Flow ◽  
Control Strategies ◽  
Vehicle Speed ◽  
Variable Speed ◽  
Speed Limits ◽  
Congested Traffic ◽  
Three Phase ◽  
Variable Speed Limits ◽  
Ca Model ◽  
Traffic Theory

One frequently observed congested traffic flow pattern is wide moving jam (WMJ), in which the average vehicle speed is very low and the density is very high. In some recent studies, variable speed limits (VSL) were proposed as effective measures to eliminate or abate the influence of jam waves. However, in most of these studies, the stochastic features of driving behaviors and the resulting uncertainty of traffic flow dynamics were not fully considered. In this paper, we use cellular automaton (CA) model-based simulations to test the performances of different VSL control strategies and apply the three-phase traffic theory to further analyze the obtained results. Based on the simulation results, we got two novel findings. Firstly, we observed seven, instead of the previously assumed six, states of traffic flow in the evolution process of WMJ, when VSL were applied. Secondly and more importantly, we found that inappropriate speed limit may induce new WMJ and exaggerate congestions in two ways: one way corresponds to an F → J transition and the other corresponds to an F → S → J transition. Based on these findings, the appropriate lower bound of VSL was finally discussed in this paper.

Vehicle Detection System with Statistical Functions Based on 3-Axis Anisotropic Magnetoresistive Using Wireless Communication Technology

2020 ◽  
Vol 17 (7) ◽  
pp. 2876-2881
Author(s):  
Xingguo Cheng ◽  
Chaomeng Chen
Keyword(s):  
Traffic Flow ◽  
Detection System ◽  
Experimental Result ◽  
Control Technique ◽  
Vehicle Speed ◽  
Single Chip ◽  
Novel Approach ◽  
Novel Method ◽  
Flow Detection ◽  
Statistical Functions

In terms of current issues that the sensor’s output signal drifts along with the surrounding strong magnetic field by using the single or dual-axis analog anisotropic magnetoresistive (AMR) sensor in the traffic flow detection, a traffic flow detection system based on ZigBee wireless sensor network is developed and a novel approach by exercising the new digital three-axis AMR sensor to detect the traffic flow is proposed to solve these issues as mentioned above. Using Single Chip Microcomputer (SCM) control technique and utilizing wireless transmitting, an effective algorithm is designed. The algorithm makes it possible to classify vehicle, calculate vehicle speed and count vehicle, in the meantime it provides a reliable and efficient method to collect intelligent transportation data. Even more important, the algorithm has a statistical functions based on MATLAB. The experimental result shows that the novel method has much better measurement accuracy, reliability and redundancy than single or dual-axis method.

scholarly journals An Analytical Framework for Accurate Traffic Flow Parameter Calculation from UAV Aerial Videos

2020 ◽  
Vol 12 (22) ◽  
pp. 3844
Author(s):  
Ivan Brkić ◽  
Mario Miler ◽  
Marko Ševrović ◽  
Damir Medak
Keyword(s):  
Traffic Flow ◽  
Low Cost ◽  
Vehicle Detection ◽  
Analytical Framework ◽  
Satellite System ◽  
Percentage Error ◽  
Vehicle Speed ◽  
Dual Frequency ◽  
Flow Parameters

Unmanned Aerial Vehicles (UAVs) represent easy, affordable, and simple solutions for many tasks, including the collection of traffic data. The main aim of this study is to propose a new, low-cost framework for the determination of highly accurate traffic flow parameters. The proposed framework consists of four segments: terrain survey, image processing, vehicle detection, and collection of traffic flow parameters. The testing phase of the framework was done on the Zagreb bypass motorway. A significant part of this study is the integration of the state-of-the-art pre-trained Faster Region-based Convolutional Neural Network (Faster R-CNN) for vehicle detection. Moreover, the study includes detailed explanations about vehicle speed estimation based on the calculation of the Mean Absolute Percentage Error (MAPE). Faster R-CNN was pre-trained on Common Objects in COntext (COCO) images dataset, fine-tuned on 160 images, and tested on 40 images. A dual-frequency Global Navigation Satellite System (GNSS) receiver was used for the determination of spatial resolution. This approach to data collection enables extraction of trajectories for an individual vehicle, which consequently provides a method for microscopic traffic flow parameters in detail analysis. As an example, the trajectories of two vehicles were extracted and the comparison of the driver’s behavior was given by speed—time, speed—space, and space—time diagrams.

scholarly journals Velocity Prediction Based on Vehicle Lateral Risk Assessment and Traffic Flow: A Brief Review and Application Examples

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3431
Author(s):  
Lin Li ◽  
Serdar Coskun ◽  
Jiaze Wang ◽  
Youming Fan ◽  
Fengqi Zhang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Transportation Systems ◽  
Vehicle Speed ◽  
Extensive Discussion ◽  
Lateral Dynamics ◽  
Speed Prediction ◽  
Velocity Prediction ◽  
Vehicle Lateral Dynamics

Forecasting future driving conditions such as acceleration, velocity, and driver behaviors can greatly contribute to safety, mobility, and sustainability issues in the development of new energy vehicles (NEVs). In this brief, a review of existing velocity prediction techniques is studied from the perspective of traffic flow and vehicle lateral dynamics for the first time. A classification framework for velocity prediction in NEVs is presented where various state-of-the-art approaches are put forward. Firstly, we investigate road traffic flow models, under which a driving-scenario-based assessment is introduced. Secondly, vehicle speed prediction methods for NEVs are given where an extensive discussion on traffic flow model classification based on traffic big data and artificial intelligence is carried out. Thirdly, the influence of vehicle lateral dynamics and correlation control methods for vehicle speed prediction are reviewed. Suitable applications of each approach are presented according to their characteristics. Future trends and questions in the development of NEVs from different angles are discussed. Finally, different from existing review papers, we introduce application examples, demonstrating the potential applications of the highlighted concepts in next-generation intelligent transportation systems. To sum up, this review not only gives the first comprehensive analysis and review of road traffic network, vehicle handling stability, and velocity prediction strategies, but also indicates possible applications of each method to prospective designers, where researchers and scholars can better choose the right method on velocity prediction in the development of NEVs.

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