scholarly journals Neural Networks Applied to Microsimulation: A Prediction Model for Pedestrian Crossing Time

2020 ◽  
Vol 12 (13) ◽  
pp. 5355
Author(s):  
Chiara Gruden ◽  
Irena Ištoka Otković ◽  
Matjaž Šraml
Keyword(s):  
Neural Networks ◽  
Original Form ◽  
Model Parameters ◽  
Pedestrian Behavior ◽  
Calibration Process ◽  
The Road ◽  
Crossing Time ◽  
The Difference ◽  
On The Road ◽  
Pedestrian Crossing

Walking is the original form of transportation, and pedestrians have always made up a significant share of transportation system users. In contrast to motorized traffic, which has to move on precisely defined lanes and follow strict rules, pedestrian traffic is not heavily regulated. Moreover, pedestrians have specific characteristics—in terms of size and protection—which make them much more vulnerable than drivers. In addition, the difference in speed between pedestrians and motorized vehicles increases their vulnerability. All these characteristics, together with the large number of pedestrians on the road, lead to many safety problems that professionals have to deal with. One way to tackle them is to model pedestrian behavior using microsimulation tools. Of course, modeling also raises questions of reliability, and this is also the focus of this paper. The aim of the present research is to contribute to improving the reliability of microsimulation models for pedestrians by testing the possibility of applying neural networks in the model calibration process. Pedestrian behavior is culturally conditioned and the adaptation of the model to local specifics in the calibration process is a prerequisite for realistic modeling results. A neural network is formulated, trained and validated in order to link not-directly measurable model parameters to pedestrian crossing time, which is given as output by the microsimulation tool. The crossing time of pedestrians passing the road on a roundabout entry leg has been both simulated and calculated by the network, and the results were compared. A correlation of 94% was achieved after both training and validation steps. Finally, tests were performed to identify the main parameters that influence the estimated crossing time.

Analysis of Pedestrian Movement on Delhi Roads by Using Naturalistic Observation Techniques

2017 ◽  
Vol 2634 (1) ◽  
pp. 95-100 ◽  
Author(s):  
Abhaya Jha ◽  
Geetam Tiwari ◽  
Dinesh Mohan ◽  
Sudipto Mukherjee ◽  
Subhashish Banerjee
Keyword(s):  
Rural Areas ◽  
Road Traffic ◽  
Pedestrian Behavior ◽  
Road Traffic Crashes ◽  
Large Cities ◽  
The Road ◽  
Road Space ◽  
On The Road ◽  
Pedestrian Crossing ◽  
Indian Cities

Pedestrian fatalities constitute about 30% of the deaths caused by road traffic crashes in India. The proportion of pedestrian fatalities in large cities (Delhi, Mumbai, etc.) varies from 50% to 60% and is about 20% to 30% on national and state highways. Pedestrians are present on all road categories in urban as well as rural areas. At least 20% to 40% of work trips are taken as pedestrian trips in most Indian cities. However, on pedestrian facilities such as footpaths, safe crossing facilities are not present in most Indian cities. Even when present, their poor maintenance and poor construction quality make them unusable. As a result, pedestrians are forced to share the road space with motorized vehicles and to cross the roads where there is no safe pedestrian crossing. This paper attempts to study pedestrian behavior—walking along the road and crossing the road—by detecting pedestrians with the use of a vehicle-mounted camera. The vehicle is driven on various categories of roads at different times. The data collected with this method are varied temporally as well as spatially. A smartphone–based GPS logging app was used to collect telemetry data, which were synced with the camera feed. The objective of this study was to understand pedestrian behavior—walking on the road versus a footpath in the presence of various road features, such as the number of lanes, presence of medians, and presence of footpaths. The influence of the presence of public transport stops, junctions, foot bridges, and grade-separated junctions (flyover) on pedestrian crossing behavior was studied.

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.

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.

scholarly journals Determination of the Dynamic Vehicle Model Parameters by Means of Computer Vision

2019 ◽  
Vol 21 (3) ◽  
pp. 28-34
Author(s):  
Daniil A. Loktev ◽  
Alexey A. Loktev ◽  
Alexandra V. Salnikova ◽  
Anna A. Shaforostova
Keyword(s):  
Computer Vision ◽  
Road Traffic ◽  
Deformable Body ◽  
Model Parameters ◽  
Vehicle Model ◽  
The Road ◽  
Complex Approach ◽  
On The Road ◽  
The Individual

This study is devoted to determining the geometric, kinematic and dynamic characteristics of a vehicle. To this purpose, it is proposed to use a complex approach applying the models of deformable body mechanics for describing the oscillatory movements of a vehicle and the computer vision algorithms for processing a series of object images to determine the state parameters of a vehicle on the road. The model of the vehicle vertical oscillations is produced by means of the viscoelastic elements and the dry friction element that fully enough represent the behavior of the sprung masses. The introduced algorithms and models can be used as a part of a complex system for monitoring and controlling the road traffic. In addition, they can determine both the speed of the car and its dynamic parameters and the driving behavior of the individual drivers.

scholarly journals Molecular Dynamics Characteristics and Model of Vehicle-Following Behavior

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yanfeng Jia ◽  
Dayi Qu ◽  
Xiaolong Ma ◽  
Lu Lin ◽  
Jiale Hong
Keyword(s):  
Molecular Dynamics ◽  
Adaptive Cruise Control ◽  
Dynamic Balance ◽  
Model Parameters ◽  
Cruise Control ◽  
Long Distance ◽  
The Road ◽  
Preceding Vehicle ◽  
Acceleration And Deceleration ◽  
On The Road

The vehicle-following behavior is a self-organizing behavior that restores dynamic balance under the stimulation of external environmental factors. In fact, there are asymmetric problems in the process of acceleration and deceleration of drivers. The existing traditional models ignored the differences between acceleration and deceleration of vehicles. In order to solve this problem, the vehicles driving on the road are compared to interacting molecules. Vehicle-following characteristics are studied, and the molecular following model is established based on molecular dynamics. The model parameters under different conditions are calibrated considering the required safety distance by the vehicle and the reaction time of the driver. With the help of the vehicle running track graphs, speed, and acceleration graphs, the numerical simulations of the molecular following model and the classical optimal speed vehicle-following model are carried out. The results of the comparative analysis show that the acceleration in the process of acceleration and deceleration is not constant but more sensitive to the deceleration of the preceding vehicle than to the acceleration and more sensitive to the acceleration/deceleration of the short-distance vehicle than to the acceleration/deceleration of the long-distance vehicle. Therefore, the molecular following model can better describe the vehicle-following behavior, and the research results can provide a theoretical basis and a technical reference for the analysis of traffic flow dynamic characteristics and adaptive cruise control technology.

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.

scholarly journals Pruning of Deep Spiking Neural Networks through Gradient Rewiring

2021 ◽  
Author(s):  
Yanqi Chen ◽  
Zhaofei Yu ◽  
Wei Fang ◽  
Tiejun Huang ◽  
Yonghong Tian
Keyword(s):  
Neural Networks ◽  
Learning Algorithm ◽  
High Energy ◽  
Neural System ◽  
Spiking Neural Networks ◽  
Synapse Elimination ◽  
Joint Learning ◽  
The Road ◽  
Key Innovation ◽  
The Difference

Spiking Neural Networks (SNNs) have been attached great importance due to their biological plausibility and high energy-efficiency on neuromorphic chips. As these chips are usually resource-constrained, the compression of SNNs is thus crucial along the road of practical use of SNNs. Most existing methods directly apply pruning approaches in artificial neural networks (ANNs) to SNNs, which ignore the difference between ANNs and SNNs, thus limiting the performance of the pruned SNNs. Besides, these methods are only suitable for shallow SNNs. In this paper, inspired by synaptogenesis and synapse elimination in the neural system, we propose gradient rewiring (Grad R), a joint learning algorithm of connectivity and weight for SNNs, that enables us to seamlessly optimize network structure without retraining. Our key innovation is to redefine the gradient to a new synaptic parameter, allowing better exploration of network structures by taking full advantage of the competition between pruning and regrowth of connections. The experimental results show that the proposed method achieves minimal loss of SNNs' performance on MNIST and CIFAR-10 datasets so far. Moreover, it reaches a ~3.5% accuracy loss under unprecedented 0.73% connectivity, which reveals remarkable structure refining capability in SNNs. Our work suggests that there exists extremely high redundancy in deep SNNs. Our codes are available at https://github.com/Yanqi-Chen/Gradient-Rewiring.

Study of Highway Crack Diagnosis Based on Cellular Neural Network

2013 ◽  
Vol 427-429 ◽  
pp. 2013-2017
Author(s):  
Sheng Zhuo Yao ◽  
Guo Dong Li ◽  
Fu Xin Zhang ◽  
Lin Ge
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Cellular Neural Network ◽  
Cellular Neural Networks ◽  
Quality Information ◽  
Image Detection ◽  
The Road ◽  
Standard Level ◽  
On The Road

Road quality information detect system is an important component in architecture quality detect system, also is the basement of successfully working of other related project for the whole country. The study of detecting the road crack is the key to insure the security of accurately detect the road quality in transportation system. In this paper, we come up with a fixed way of road undersized rift image detection by using cellular neural networks. By image processing, building rift networks and details networks and adding the model of similarity undersized rift networks. It can avoid the problem that can not accurately detect undersized crack by only taking the crack feature value. The experiment proved that fixed crack detect computing is easy to do, more accurate to detect the undersized cracks on the road and can reach the standard level of current detect technique.

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.

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