Vehicle Association and Tracking in Image Sequences Using Feature-Based Similarity Comparison

2014 ◽  
Vol 536-537 ◽  
pp. 176-179 ◽  
Author(s):  
Du Hyung Cho ◽  
M. Naushad Ali ◽  
Seok Ju Chun ◽  
Seok Lyong Lee
Keyword(s):  
Image Sequences ◽  
Similarity Comparison ◽  
Current Frame ◽  
The Road ◽  
Multiple Vehicles ◽  
Feature Based ◽  
The Difference ◽  
On The Road ◽  
Difference Operation ◽  
Object Association

Object association and tracking have attracted great attention in the computer vision. In this paper, we present an object association and tracking method for monitoring multiple vehicles on the road based on objects' visual features and the similarity comparison between them. First, we identify vehicles using the difference operation between the current frame in CCTV image sequences and the referential images that are stored in a database, and then extract various features from the vehicles identified. Finally, we associate the objects in the current frame with those in the next frames using similarity comparison, and track multiple objects over a sequence of CCTV image frames. Empirical study using CCTV images shows that our method has achieved the considerable effectiveness in tracking vehicles on the road.

Determination of Resistance to Abrasive Wear. VIII. Influence of Softeners in Tests with the Akron-Croydon and Du Pont Machines

1949 ◽  
Vol 22 (1) ◽  
pp. 259-262
Author(s):  
J. F. Morley
Keyword(s):  
Unit Area ◽  
Published Data ◽  
The Road ◽  
Abrasive Surface ◽  
Abrasive Power ◽  
The Difference ◽  
On The Road ◽  
The Right ◽  
Abrasion Testing

Abstract These experiments indicate that softeners can influence abrasion resistance, as measured by laboratory machines, in some manner other than by altering the stress-strain properties of the rubber. One possible explanation is that the softener acts as a lubricant to the abrasive surface. Since this surface, in laboratory abrasion-testing machines, is relatively small, and comes repeatedly into contact with the rubber under test, it seems possible that it may become coated with a thin layer of softener that reduces its abrasive power. It would be interesting in this connection to try an abrasive machine in which a long continuous strip of abrasive material was used, no part of it being used more than once, so as to eliminate or minimize this lubricating effect. The fact that the effect of the softener is more pronounced on the du Pont than on the Akron-Croydon machine lends support to the lubrication hypothesis, because on the former machine the rate of wear per unit area of abrasive is much greater. Thus in the present tests the volume of rubber abraded per hr. per sq. cm. of abrasive surface ranges from 0.03 to 0.11 cc. on the du Pont machine and from 0.0035 to 0.0045 cc. on the Akron-Croydon machine. On the other hand, if the softener acts as a lubricant, it would be expected to reduce considerably the friction between the abrasive and the rubber and hence the energy used in dragging the rubber over the abrasive surface. The energy figures given in the right-hand columns of Tables 1 and 3, however, show that there is relatively little variation between the different rubbers. As a test of the lubrication hypothesis, it would be of interest to vary the conditions of test so that approximately the same amount of rubber per unit area of abrasive is abraded in a given time on both machines; this should show whether the phenomena observed under the present test conditions are due solely to the difference in rate of wear or to an inherent difference in the type of wear on the two machines. This could most conveniently be done by considerably reducing the load on the du Pont machine. In the original work on this machine the load was standardized at 8 pounds, but no figures are quoted to show how abrasion loss varies with the load. As an addition to the present investigation, it is proposed to examine the effect of this variation with special reference to rubbers containing various amounts and types of softener. Published data on the influence of softeners on the road wear of tire rubbers do not indicate anything like such large effects as are shown by the du Pont machine. This throws some doubt on the value of this machine for testing tire tread rubbers, a conclusion which is confirmed by information obtained from other workers.

scholarly journals In Situ Measurement of Discomfort Curves for Seated Subjects in a Car on the Four-Post Rig

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
T. Ibicek ◽  
A. N. Thite
Keyword(s):  
Predictive Models ◽  
Dynamic Behaviour ◽  
Rate Of Change ◽  
Test Results ◽  
Vehicle Dynamic ◽  
The Road ◽  
Perceived Intensity ◽  
The Difference ◽  
On The Road

The aim of this study is to measure and quantify perceived intensity of discomfort due to vibration in a vehicle in situ considering complete vehicle dynamic behaviour. The shaker table based discomfort curves or the road test results may not accurately and universally indicate the true level of human discomfort in a vehicle. A new experimental method, using a seated human in a car on the four-post rig simulator, is proposed to quantify discomfort. The intensity of perception to vibration decreased with decreasing input and increasing frequency; the rate of change is different from the published literature; the difference is large for angular modes of inputs. Vehicle dynamic response is used to inform and analyse the results. The repeatability of the method and the fact that they are in situ measurements may eventually help reduce reliance on the road tests. Furthermore, discomfort curves obtained, subsequently, can be used in predictive models.

Safety Aspects of Sophisticated In-Vehicle Information Displays and Controls

1986 ◽  
Vol 30 (3) ◽  
pp. 256-260 ◽  
Author(s):  
Helmut T. Zwahlen ◽  
David P. DeBald
Keyword(s):  
Standard Deviation ◽  
Occlusion Time ◽  
The Road ◽  
Safety Aspects ◽  
Eyes Closed ◽  
Starting Point ◽  
Reading Text ◽  
Standard Deviations ◽  
The Difference ◽  
On The Road

Two groups of six young and healthy subjects were used in this study to investigate the lateral path deviations when driving in a straight path with the eyes fixated on the road ahead, when driving while reading information inside of the automobile, and when driving with the eyes closed. Each group of subjects drove a typical large car and a typical small car at a fixed speed of 30 mph. An unused 2000 foot long and 75 foot wide, level, concrete airport runway was used to conduct the experiment. Each subject made three runs under each of the three conditions with the large car and with the small car (18 runs total). The lateral path deviations from the longitudinal centerline of the car to the centerline of the runway were measured every 15 feet for a distance of 705 feet. A device which dripped liquid dye was attached to the center of the rear bumper of the automobiles to indicate their paths. The results of this study show that the average lateral standard deviations for driving with the eyes fixated upon the road ahead were between 5.5″ and 11.3″. The difference in the lateral standard deviations for large and small automobiles was statistically not significant for distances between 100 and 500 feet from the starting point for the three conditions tested. The lateral standard deviation was smaller for reading text within the automobile than for driving with the eyes closed, and was statistically significant after an occlusion distance of 225 feet or an occlusion time of about 5 seconds. Using a constant of 0.041, the fundamental relationship between the lateral standard deviation, the speed, and the occlusion distance developed by Zwahlen and Balasubramanian (1974) fits the data for reading text inside of the automobile while driving fairly well. This constant is approximately one half of that which has been used for driving with the eyes closed (0.076) in this study. Based upon the results of this study, the development and introduction of sophisticated in-vehicle displays and/or touch panels should be halted and their safety aspects with regard to information aquisition, information processing, and driver control actions should be critically evaluated.

The Effects of Expectancy, Clothing Reflectance, and Detection Criterion on Nighttime Pedestrian Visibility

1985 ◽  
Vol 27 (3) ◽  
pp. 327-333 ◽  
Author(s):  
David Shinar
Keyword(s):  
Prior Knowledge ◽  
The Road ◽  
Detection Criterion ◽  
Visibility Distance ◽  
The Difference ◽  
On The Road

Nighttime pedestrian visibility was studied under various combinations of driver expectancy (to see a pedestrian on the road), pedestrian clothing characteristics (dark clothing, light clothing, and dark clothing with retroreflective tags), and the detection criterion (pedestrian versus retroreflective tag). It was found that visibility distance increases with expectancy, but the magnitude of the effect varies as a function of whether or not the pedestrian is wearing the tag. Furthermore, it was shown that when the pedestrian is unexpected, the usefulness of the tag is significant only if the driver can rely on it as a criterion for detection (by prior knowledge of the association between the tag and the pedestrian). The difference in visibility when the tag is not associated with the pedestrian may explain the less-than-expected effectiveness of retroreflective materials on accident reduction.

scholarly journals Impact of Automated Truck Platooning on the Performance of Freeway Mixed Traffic Flow

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Seolyoung Lee ◽  
Cheol Oh ◽  
Gunwoo Lee
Keyword(s):  
Traffic Flow ◽  
Energy Savings ◽  
Automated Driving ◽  
Average Speed ◽  
The Road ◽  
Mobility Performance ◽  
Vehicle Platooning ◽  
Negative Effect ◽  
The Difference ◽  
On The Road

Vehicle platooning service through wireless communication and automated driving technology has become a reality. Vehicle platooning means that several vehicles travel like a train on the road with a minimum safety distance, which leads to the enhancement of safety, mobility, and energy savings. This study proposed a framework for exploring traffic mobility and safety performance due to the market penetration rate (MPR) of truck platoons based on microscopic traffic simulations. A platoon formation algorithm was developed and run on the VISSIM platform to simulate automated truck maneuvering. As a result of the mobility analysis, it was found that the difference in network mobility performance was not significant up to MPR 80%. Regarding the mobility performance of the truck-designated lane, it was found that the average speed was lower than in other lanes. In the truck-designated lane of the on-ramp section, the average speed was identified to be approximately 33% lower. From the viewpoint of network safety, increasing the MPR of the truck platoon has a positive effect on longitudinal safety but has a negative effect on lateral safety. The safety analysis of the truck-designated lane indicated that the speed difference by lane of MPR 100% is 2.5 times higher than that of MPR 0%. This study is meaningful in that it explores traffic flow performance on mobility and safety in the process of platoon formation. The outcomes of this study are expected to be utilized as fundamentals to support the novel traffic operation strategy in platooning environments.

scholarly journals PSYCHOMOTOR AND COGNITIVE SKILLS THAT MAKE A DIFFERENCE IN TENNIS PLAYERS AT NATIONAL LEVEL

2020 ◽  
pp. 390-404
Keyword(s):  
Reaction Time ◽  
Cognitive Skills ◽  
National Level ◽  
Cognitive Model ◽  
Tennis Players ◽  
Sports Clubs ◽  
The Road ◽  
The Difference ◽  
On The Road ◽  
Materials Used

Tennis has become an extremely complex sport, with tennis players needing a team of specialists to maximise their sports performance. Performance tennis has proven that the difference between the players, in the conditions of similar technical-tactical performances, is made by the physical and mental training. Our paper aimed to investigate the subjective reality of junior tennis players in order to optimise their actions and activities by identifying a psychomotor and cognitive model of athletes ranked in the top area nationally. The research involved 75 tennis players - 40 boys and 35 girls aged between 14 and 16 years. The materials used were represented by the PSISELTEVA psychological testing system developed by the RQ Plus Company and calibrated to the Romanian population, which contains: levers, desk with buttons, pedals. The tests belonging to the computerised battery used in the research are: TRS (simple reaction time), TRD (discrimination reaction time), RCMV (intersegmental coordination), TUD (eye-hand coordination), ANALOGIE (analogical transfer), TAC (attention concentration), MT (topographical memory) and RNE (resistance to mental fatigue). Through the Mann-Whitney (U) test, significant differences were identified between the first tennis players in the national ranking and the players placed in the middle or final zone of the ranking, in terms of different psychomotor and cognitive coordinates (investigated in various environmental conditions). The results obtained are useful both for specialists working in the field of tennis (coaches, sports psychologists, physical trainers), athletes (boys and girls) aspiring on the road to great performance, but also for sports clubs.

The Influence of Driver Expectation when Recognizing Lighted Targets at Nighttime

2016 ◽  
Vol 60 (1) ◽  
pp. 489-493 ◽  
Author(s):  
Jeffrey W. Muttart ◽  
Swaroop Dinakar ◽  
Gregory Vandenberg ◽  
Michael Yosko
Keyword(s):  
Information Theory ◽  
Light Source ◽  
Search Model ◽  
Theory Approach ◽  
Night Time ◽  
The Road ◽  
Driving Scenario ◽  
The Difference ◽  
On The Road

Over the years, in a night time driving scenario, expectancy has been linked with faster night time recognition. This study tries to evaluate the ability of observers to identify illuminated objects on the road in the absence of an associative pattern. In this study 47 of 60 participants did not respond to a light source that was in the drivers’ travel lane ahead. Of those who did not respond to the light when directly ahead, 64% indicated that had seen it beforehand. When the light was 2 meters to the drivers’ right, 33% that saw the light failed to respond. All of the drivers who saw the light before striking it claimed that they thought it was off the road until too late. When the drivers did not know what the light source was, they could not decipher where the light was. However, once aware of the presence of the light the average recognition distance improved 192 meters (632 feet) with 100% recognition. These results fit well with the SEEV search model and an Information Theory approach to driver expectancy. Previous claims that the difference between expected and unexpected driver responses is a 2 to 1 ratio was not supported by this research.

Incorporating Vertical Acceleration for Defining Driving Behaviour

2019 ◽  
Vol 9 (2) ◽  
pp. 38-48
Author(s):  
Laura Eboli ◽  
Gabriella Mazzulla ◽  
Giuseppe Pungillo
Keyword(s):  
Road Safety ◽  
Weather Condition ◽  
Relevant Parameter ◽  
Vertical Acceleration ◽  
The Road ◽  
Driving Behaviour ◽  
Road Pavement ◽  
Driving Conditions ◽  
The Difference ◽  
On The Road

Acceleration of a vehicle is composed of three components: longitudinal, lateral, and vertical acceleration. Longitudinal and lateral accelerations have been frequently considered as components for investigating driving behaviour, with the aim of improving road safety. But in particular situations during the motion of the vehicle, also vertical acceleration is relevant. In this paper, the authors want to demonstrate that vertical acceleration is also a relevant parameter to be considered in terms of road safety. The authors focus on the difference registered by considering only lateral and longitudinal acceleration and by considering also vertical acceleration in the analysis of driving behaviour through real tests on the road. All the parameters were registered through a global positioning system (GPS) device and a tri-axial accelerometer, which allow the geo-referenced kinematic parameters of the vehicle to be detected. For this purpose, over 110 tests covering about 600 kilometers were completed. All the experimental surveys were conducted in a good weather condition, under dry road pavement conditions, on weekdays, during day time and out-of-peak hours, in order to have no influence from the traffic flow. Each path was repeatedly run by the driver in order to collect the instantaneous speed and acceleration along the pattern. During the tests, about 40,000 instantaneous values of vehicle position have been registered. The survey interested a segment of the Italian National road n.107 (S.S. 107), in Southern Italy. The authors found that by considering vertical together with longitudinal and lateral accelerations, a higher number of unsafe driving conditions can be identified. More specifically, the proposed methodology allows 20% extra of dangerous driving conditions to be registered. For this reason, the authors retain that also vertical acceleration should be considered in the definition of the safety domain, because it determines the intensity of the exchange forces between the tires and road pavement, and in some cases, it leads to a loss of friction. Definitively, the authors retain that vertical acceleration is not only useful as indicator of comfort on board, but it has an important role also in terms of road safety.

scholarly journals Multi-Vehicle Planning using RRT-Connect*

2011 ◽  
Vol 2 (3) ◽  
Author(s):  
Rahul Kala ◽  
Kevin Warwick
Keyword(s):  
Optimization Algorithm ◽  
Relative Position ◽  
Autonomous Vehicles ◽  
Random Trees ◽  
Effective Algorithm ◽  
The Road ◽  
Travel Plan ◽  
Multiple Vehicles ◽  
Planning Algorithm ◽  
On The Road

AbstractThe problem of planning multiple vehicles deals with the design of an effective algorithm that can cause multiple autonomous vehicles on the road to communicate and generate a collaborative optimal travel plan. Our modelling of the problem considers vehicles to vary greatly in terms of both size and speed, which makes it sub-optimal to have a faster vehicle follow a slower vehicle or for vehicles to drive with predefined speed lanes. It is essential to have a fast planning algorithm whilst still being probabilistically complete. The Rapidly Exploring Random Trees (RRT) algorithm developed and reported on here uses a problem specific coordination axis, a local optimization algorithm, priority based coordination, and a module for deciding travel speeds. Vehicles are assumed to remain in their current relative position laterally on the road unless otherwise instructed. Experimental results presented here show regular driving behaviours, namely vehicle following, overtaking, and complex obstacle avoidance. The ability to showcase complex behaviours in the absence of speed lanes is characteristic of the solution developed.

scholarly journals Traffic Analysis Using Artificial Neural Network

2021 ◽  
pp. 359-365
Author(s):  
Mounica B ◽  
Nithya B S ◽  
Rakshitha N ◽  
Sirisha M
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Processing ◽  
Artificial Neural Network ◽  
Conventional Method ◽  
Image Sequences ◽  
Testing Model ◽  
Traffic Jam ◽  
The Road ◽  
On The Road

The vehicle traffic on the road is increasing progressively and managing such traffic on the roads are not stable by conventional method. To remove this traffic issue, we develop a project using machine learning in which we train the testing model as well as trained model of extracted traffic features. Extracted information from image sequences of testing model can give us real information to create the database which is the captured images like accident, foggy places, collision of the vehicles, traffic signal, no traffic jam, treefall etc. Choose any traffic image from the testing model, process and analyze the traffic image and the traffic image which was taken from the testing model is compared with the trained model of traffic images to determine the cause of the traffic. Image processing will be done to determine the cause of the traffic. This project is utilizing image processing methods designed to analyze and determine the cause of the traffic with the accuracy of the traffic caused. Thus, by using this project we can avoid the traffic and the time being wasted.

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