Prediction of level crossings for normal processes containing deterministic components

1979 ◽  
Vol 11 (1) ◽  
pp. 93-117 ◽  
Author(s):  
Georg Lindgren
Keyword(s):  
False Alarm ◽  
Water Level ◽  
Sufficient Accuracy ◽  
Sufficient Time ◽  
Level Crossing ◽  
Level Crossings ◽  
Specific Process ◽  
Predetermined Level ◽  
Natural Criterion ◽  
Deterministic Components

A level crossing predictor is a predictor process Y(t) which can be used to predict whether a specific process X(t) will cross a predetermined level or not. A natural criterion of how good a predictor is can be the probability that a crossing is detected a sufficient time ahead, and the number of times the predictor makes a false alarm.Suppose the process X(t) consists of a deterministic part A(t) which can be calculated with sufficient accuracy, and a stochastic part Xe(t) which can be predicted by some statistically based predictor An example of this is the prediction of water level near a coast, when A(t) is a sum of known tide components.The paper develops a tool to handle the detection properties of such predictor processes when used to predict level crossings for the case when A(t) is periodic or is a sum of such functions.

Prediction of level crossings for normal processes containing deterministic components

1979 ◽  
Vol 11 (01) ◽  
pp. 93-117 ◽  
Author(s):  
Georg Lindgren
Keyword(s):  
False Alarm ◽  
Water Level ◽  
Sufficient Accuracy ◽  
Sufficient Time ◽  
Level Crossing ◽  
Level Crossings ◽  
Specific Process ◽  
Predetermined Level ◽  
Natural Criterion ◽  
Deterministic Components

A level crossing predictor is a predictor process Y(t) which can be used to predict whether a specific process X(t) will cross a predetermined level or not. A natural criterion of how good a predictor is can be the probability that a crossing is detected a sufficient time ahead, and the number of times the predictor makes a false alarm. Suppose the process X(t) consists of a deterministic part A(t) which can be calculated with sufficient accuracy, and a stochastic part Xe (t) which can be predicted by some statistically based predictor An example of this is the prediction of water level near a coast, when A(t) is a sum of known tide components. The paper develops a tool to handle the detection properties of such predictor processes when used to predict level crossings for the case when A(t) is periodic or is a sum of such functions.

scholarly journals Survey-based Impact of Influencing Parameters on Level Crossings Safety

2016 ◽  
Vol 28 (6) ◽  
pp. 639-649 ◽  
Author(s):  
Martin Starčević ◽  
Danijela Barić ◽  
Hrvoje Pilko
Keyword(s):  
Survey Questionnaire ◽  
Level Crossing ◽  
Level Crossings ◽  
Policy Makers ◽  
Railway Traffic ◽  
Research Activities ◽  
On Line ◽  
Line Survey ◽  
First Time ◽  
Influential Parameters

Level crossing (LC) accidents are a significant safety challenge worldwide and for that reason they have been subject of numerous research activities. Joint conclusion is that human behaviour is the main cause of accidents. This study examines how and to which extent certain influential parameters cause accident mechanisms on level crossings. To gain the necessary data we used an on-line survey questionnaire that was sent internationally to key experts in the field of road and railway safety. A total of 185 experts were asked to rank how much certain parameters influence level crossings accident mechanisms and what are the best countermeasures for diminishing accidents at level crossings. To our knowledge, this is the first time that an international survey among key experts was used to gain necessary data about influential parameters regarding level crossings safety. The results of this study could be used by road and railway traffic engineers and policy makers for further enhancement of LC’s safety.

scholarly journals Study of Drivers’ Behaviour at a Passive Railway Crossing

1970 ◽  
Vol 24 (3) ◽  
pp. 193-201 ◽  
Author(s):  
Sandra Kasalica ◽  
Radisav Vukadinović ◽  
Vojkan Lučanin
Keyword(s):  
Observational Study ◽  
Road Traffic ◽  
Level Crossing ◽  
Level Crossings ◽  
Road Vehicle ◽  
Railway Crossing ◽  
Limited Visibility ◽  
Risky Decisions

Problem: The number of killed and injured persons in incidents at railway level crossings is generally increasing on the Serbian Railways, particularly at passive crossings. In this paper we researched the direct behaviour of road traffic participants at a conventional railway passive crossing. Method: Direct observational study of drivers’ behaviour at a level crossing. Results: Sixty-one road vehicle drivers were observed in the moments of train approach. The probability of crossing varies depending on the train distance and the time the driver has to cross the crossing. The drivers who have limited visibility cannot estimate the speed of the approaching train well and make more risky decisions. Conclusion: This study shows that the number of “risky crossings” is worrying as the result of such crossings is a large number of accidents with fatal consequences at the passive crossings in Serbia.

scholarly journals Experimental tests of vehicle body accelerations at selected road and rail crossings

2019 ◽  
Vol 254 ◽  
pp. 04002 ◽  
Author(s):  
Konrad J. Waluś ◽  
Jakub Polasik ◽  
Janusz Mielniczuk ◽  
Łukasz Warguła
Keyword(s):  
Cross Section ◽  
Experimental Tests ◽  
The Body ◽  
Geometric Parameters ◽  
Vehicle Body ◽  
Delivery Vehicle ◽  
Dynamic Reaction ◽  
Level Crossing ◽  
Level Crossings ◽  
Section Structure

Vehicles moving across the railway are exposed to the dynamic reaction of unevenness of surface on those level crossing. This significantly influences on the increase of the acceleration as well as forces values transferred to the body of the car. These values depend to extent on the geometric parameters of level crossing as well as on the characteristics of the car tires and suspension. The paper presents the results of experimental tests of a small delivery vehicle crossing selected level crossings with a diversified geometric cross-section structure.

scholarly journals A Fourier Approach for the Level Crossings of Shot Noise Processes with Jumps

2012 ◽  
Vol 49 (01) ◽  
pp. 100-113 ◽  
Author(s):  
Hermine Biermé ◽  
Agnès Desolneux
Keyword(s):  
Shot Noise ◽  
Poisson Point Process ◽  
Functions Of Bounded Variation ◽  
Level Crossing ◽  
Level Crossings ◽  
Variable Formula ◽  
Shot Noise Process ◽  
Change Of Variable ◽  
The Mean ◽  
The Fourier Transform

We use a change-of-variable formula in the framework of functions of bounded variation to derive an explicit formula for the Fourier transform of the level crossing function of shot noise processes with jumps. We illustrate the result in some examples and give some applications. In particular, it allows us to study the asymptotic behavior of the mean number of level crossings as the intensity of the Poisson point process of the shot noise process goes to infinity.

scholarly journals Automatic Railway Level Crossing System with Embedded Precision Solar Panel using IoT

2019 ◽  
Vol 8 (2) ◽  
pp. 6211-6216
Keyword(s):  
Internet Of Things ◽  
Public Transportation ◽  
Research Work ◽  
Solar Panel ◽  
Level Crossing ◽  
Level Crossings ◽  
The Public ◽  
Road Users ◽  
Transportation Modes ◽  
Human Interventions

Indian Railways is one of the public transportation modes in the country. It is the largest interconnected rail routes which carry many numbers of people from one end to another end. In this, various level crossings are operated on the rail routes and some of the level crossing gates are operated manually. This process is carried out by getting the information from the previous station once the train left the station. In this process, lots of mishaps are occurring due to human interventions and also there is no safety for road users. This issue can be overcome by making the same process in an automated manner. Hence, in this research work, a new automated level crossing model is proposed using the technology “Internet of Things” (IoT). This model will provide

scholarly journals Model for Risk Calculation and Reliability Comparison of Level Crossings

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1230
Author(s):  
Pamela Ercegovac ◽  
Gordan Stojić ◽  
Miloš Kopić ◽  
Željko Stević ◽  
Feta Sinani ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Road Traffic ◽  
Operating Mode ◽  
Level Crossing ◽  
Level Crossings ◽  
Risk Calculation ◽  
Real Risk ◽  
The World ◽  
The Republic ◽  
Basic Input

There is not a single country in the world that is so rich that it can remove all level crossings or provide their denivelation in order to absolutely avoid the possibility of accidents at the intersections of railways and road traffic. In the Republic of Serbia alone, the largest number of accidents occur at passive crossings, which make up three-quarters of the total number of crossings. Therefore, it is necessary to constantly find solutions to the problem of priorities when choosing level crossings where it is necessary to raise the level of security, primarily by analyzing the risk and reliability at all level crossings. This paper presents a model that enables this. The calculation of the maximal risk of a level crossing is achieved under the conditions of generating the maximum entropy in the virtual operating mode. The basis of the model is a heterogeneous queuing system. Maximum entropy is based on the mandatory application of an exponential distribution. The system is Markovian and is solved by a standard analytical concept. The basic input parameters for the calculation of the maximal risk are the geometric characteristics of the level crossing and the intensities and structure of the flows of road and railway vehicles. The real risk is based on statistical records of accidents and flow intensities. The exact reliability of the level crossing is calculated from the ratio of real and maximal risk, which enables their further comparison in order to raise the level of safety, and that is the basic idea of this paper.

scholarly journals Object Detection at Level Crossing Using Deep Learning

Micromachines ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1055
Author(s):  
Muhammad Asad Bilal Fayyaz ◽  
Christopher Johnson
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Vision System ◽  
Significant Risk ◽  
Sufficient Information ◽  
Level Crossing ◽  
Level Crossings ◽  
Sensing System ◽  
Sensing Systems ◽  
Single Sensor

Multiple projects within the rail industry across different regions have been initiated to address the issue of over-population. These expansion plans and upgrade of technologies increases the number of intersections, junctions, and level crossings. A level crossing is where a railway line is crossed by a road or right of way on the level without the use of a tunnel or bridge. Level crossings still pose a significant risk to the public, which often leads to serious accidents between rail, road, and footpath users and the risk is dependent on their unpredictable behavior. For Great Britain, there were three fatalities and 385 near misses at level crossings in 2015–2016. Furthermore, in its annual safety report, the Rail Safety and Standards Board (RSSB) highlighted the risk of incidents at level crossings during 2016/17 with a further six fatalities at level crossings including four pedestrians and two road vehicles. The relevant authorities have suggested an upgrade of the existing sensing system and the integration of new novel technology at level crossings. The present work addresses this key issue and discusses the current sensing systems along with the relevant algorithms used for post-processing the information. The given information is adequate for a manual operator to make a decision or start an automated operational cycle. Traditional sensors have certain limitations and are often installed as a “single sensor”. The single sensor does not provide sufficient information; hence another sensor is required. The algorithms integrated with these sensing systems rely on the traditional approach, where background pixels are compared with new pixels. Such an approach is not effective in a dynamic and complex environment. The proposed model integrates deep learning technology with the current Vision system (e.g., CCTV to detect and localize an object at a level crossing). The proposed sensing system should be able to detect and localize particular objects (e.g., pedestrians, bicycles, and vehicles at level crossing areas.) The radar system is also discussed for a “two out of two” logic interlocking system in case of fail-mechanism. Different techniques to train a deep learning model are discussed along with their respective results. The model achieved an accuracy of about 88% from the MobileNet model for classification and a loss metric of 0.092 for object detection. Some related future work is also discussed.

scholarly journals The Effect of Takeover Lead Time on Driver Workload

2019 ◽  
Vol 63 (1) ◽  
pp. 1872-1873
Author(s):  
Yongdeok Yun ◽  
Hyungseok Oh ◽  
Rohae Myung
Keyword(s):  
False Alarm ◽  
Lead Time ◽  
Driving Simulator ◽  
Autonomous Driving ◽  
Physiological Signals ◽  
Sufficient Time ◽  
Subjective Workload ◽  
Driver Workload ◽  
Level 3 ◽  
Driving Task

Autonomous driving has been one of the most interesting technologies in recent years with expectation of solving accidents, pollution, and traffic jams (Jo, Lee, & Kim, 2013; Schrank, Eisele, & Lomax, 2012; Singh, 2018). However, current autonomous vehicles cannot handle all driving situations. Therefore, drivers must intervene in certain situations. SAE international defined these levels of autonomous driving as partial (level 2) and conditional (level 3) autonomous driving (SAE international, 2016). In level 3 autonomous driving, drivers are not required to monitor the driving situations and they may perform non-driving related tasks (NDRTs). However, drivers must pay attention to driving situations and make an appropriate reaction when takeover request (TOR) occurs. Takeover request (TOR) is one of the major issues in autonomous driving. A human driver must be ready to transfer the control of the vehicle when TOR is given. Therefore, how and when to request the driver to transfer the control is important. In this regard, takeover lead time (TORlt) has received great attention and there are many existing scholarly works on the effect of TORlt on takeover performance (Gold et al., 2013; Gold et al., 2017; Mok, Johns, Lee, Ive et al., 2015; Mok Johns Lee, Miller et al., 2015; Payre et al., 2016; Van den Beukel & Van der Voort, 2013; Wan & Wu, 2018; Zhang et al., 2018). Besides its impact on takeover performance, TORlt also has an effect on driver workload (Eriksson & Stanton, 2017; Wan & Wu, 2018). Inappropriate TORlt makes driver overload or underload and the abnormal workload deteriorates driver performance in takeover situation (De Winter et al., 2014; Eriksson & Stanton, 2017; Hajek et al., 2013; Wan & Wu, 2018). However, these studies either did not investigate workload induced by TOR or measure driver workload in a subjective method. This study focused on workload induced by TOR. Wan & Wu (2018) stated that takeover request without sufficient time budget may increase driver workload and generate erratic driver's response. However, many researches have focused on workload while performing NDRT alone. Additionally, a few research that assessed workload induced by TOR used subjective methods. The objective of this study is to investigate the effects of TORlt on driver workload in takeover situation. This study hypothesizes that workload would increase when TORlt is too short or too long. To investigate the hypothesis, an experiment was conducted with driving simulator and workload was measured by subjective and objective methods. The experiment with driving simulator was conducted with 28 participants to investigate the effect of TORlt on the driver workload. TORlt was controlled in 7 levels (3s, 7s, 10s, 15s, 30s, 45s, 60s). Each session of the experiment was dealt with one TORlt level and was conducted in random sequence. At the beginning of the session, participants had to perform the NDRT during autonomous driving. Then, they are required to identify an obstacle in ego-lane and make a lane change to avoid the collision when TOR occurs. The dependent variables in this experiment include workload measured by subjective and physiological methods. Driving Activity Load Index (DALI; Pauzie, 2008) was conducted to measure subjective workload and physiological measures including respiration rate (RSP), heart rate (HR), and galvanic skin reponse (GSR) were conducted to evaluate objective workload. The results of this study showed that TORlt had a significant effect on subjective workload. Subjective workload was increased in short TORlt as expected. Drivers, who were given the TOR with short lead time, did not have sufficient time to perceive and comprehend the driving situation nor make an appropriate decision. As a result, drivers could not cope with the takeover situation and their workload increased. However, driver workload was not increased in excessively long TORlt. Long TORlt was expected to increase driver workload because driver could assume long TORlt to be a false alarm or feel distraction (Wan & Wu, 2018). This might be because participants did not consider that 60s of TORlt was long or there was no false alarm in the experiment. There was no significant effect of TORlt on mean RSP and mean HR. This is because each participant behaved differently or regarded driving situation after the takeover as a simple driving task. In contrast to RSP and HR, TORlt had a significant effect on mean GSR. According to Kramer (1991), Physiological signals are sensitive to different resource demands (Kramer, 1991; Ryu & Myung, 2005). In this study, excessive temporal demand because of short TORlt and distraction caused by long TORlt were demands imposed on the participants. Hence, GSR which is sensitive to emotion and frustration (Kramer, 1991) was influenced by TORlt. In conclusion, the results of the study were different from the hypothesis which expected excessive workload with too short or long TORlt. Even though subjective workload and GSR partially support the hypothesis, more complicated and controlled experiment is needed to confirm the hypothesis. In the future research, experiment including complex driving task and false alarm should be conducted and it is necessary to measure physiological signals while controlling various resource demand to investigate the effect of TORlt on physiological signals.

The caulfield to Dandenong Level Crossing Removal Project – An innovative, sustainable, congestion busting success.

2021 ◽  
Author(s):  
Adam McManus ◽  
Daniel Tofful
Keyword(s):  
Urban Renewal ◽  
Urban Design ◽  
Urban Infrastructure ◽  
Ground Level ◽  
Level Crossing ◽  
Level Crossings ◽  
Design Integration ◽  
Design And Construction

<p>A case study of the Caulfield to Dandenong Level Crossing Removal Project in Melbourne Australia focusing on Design and Sustainability outcomes in urban infrastructure congestion. The Project completed in 2018 increased corridor capacity by 42% on Melbourne’s busiest rail corridor whilst removing nine level crossings and building five new stations. The Project has achieved an Excellent Rating with Infrastructure Sustainability Council Australia on the back of several key initiatives, not least being the bold decision to adopt an innovative elevated span by span design and construction solution for the critical 6 km of rail viaducts that kept the rail corridor open without any long-term rail closures. The completed Project now sets a new standard in urban design integration in form of structure and urban renewal, activation and re-use of the rail corridor at ground level.</p>

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