Pub Date : 2017-07-19DOI: 10.1504/IJVS.2017.10006064
Shahab Amelian, A. Shojaei, Sayyed Mohammad Reza Davoodi
The present study seeks to investigate efficiency of roads in provinces in Iran. Considering the resource limitation, prioritisation of roads seems necessary for better allocation of resources. Since it is possible to investigate decision-making units (DMUs) where there are several inputs and outputs without considering any weight for them in data envelopment analysis, this method is very suitable for ranking. In order to analyse efficiency, BCC model with variable return to scale was used and given that a number of DMUs become efficient after solving the model, Anderson-Peterson method was employed to determine strong efficiency. Considering that one of the advantages of data envelopment analysis is the possibility of offering a progress model for inefficient DMUs, the essential changes in inputs and outputs of inefficient DMUs for being efficient have been mentioned.
{"title":"Road safety evaluation using data envelopment analysis case study: roads in provinces in Iran","authors":"Shahab Amelian, A. Shojaei, Sayyed Mohammad Reza Davoodi","doi":"10.1504/IJVS.2017.10006064","DOIUrl":"https://doi.org/10.1504/IJVS.2017.10006064","url":null,"abstract":"The present study seeks to investigate efficiency of roads in provinces in Iran. Considering the resource limitation, prioritisation of roads seems necessary for better allocation of resources. Since it is possible to investigate decision-making units (DMUs) where there are several inputs and outputs without considering any weight for them in data envelopment analysis, this method is very suitable for ranking. In order to analyse efficiency, BCC model with variable return to scale was used and given that a number of DMUs become efficient after solving the model, Anderson-Peterson method was employed to determine strong efficiency. Considering that one of the advantages of data envelopment analysis is the possibility of offering a progress model for inefficient DMUs, the essential changes in inputs and outputs of inefficient DMUs for being efficient have been mentioned.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"253-261"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42938156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-19DOI: 10.1504/IJVS.2017.10006056
Yuan-Lin Chen
This paper uses the driving behaviour to design a Forward Collision Probability Index (FCPI) for alerting and to assist the driver to keep a safety driving distance for avoiding the forward collision accident in highway driving. We use the time-to-collision (TTC) as a main factor for calculating the FCPI. The index of FCPI is easy understanding for the driver even those who have no professional knowledge in vehicle technology. A self-learning algorithm for reducing the wrong warnings is presented for obtaining a suitable FCPI for the driver, which means that calculating the FCPI could meet each driver's behaviour. For the value of FCPI, value 0 is indicating the 0% probability of forward collision, and values 0.5 and 1 are indicating the 50% and 100% probabilities of forward collision, respectively. The experimental results guaranteed that the self-learning algorithm could figure out an optimal FCPI index for each driver to meet his/her driving behaviour and could reduce the wrong warnings.
{"title":"Using the driving behaviour to design a forward collision probability index","authors":"Yuan-Lin Chen","doi":"10.1504/IJVS.2017.10006056","DOIUrl":"https://doi.org/10.1504/IJVS.2017.10006056","url":null,"abstract":"This paper uses the driving behaviour to design a Forward Collision Probability Index (FCPI) for alerting and to assist the driver to keep a safety driving distance for avoiding the forward collision accident in highway driving. We use the time-to-collision (TTC) as a main factor for calculating the FCPI. The index of FCPI is easy understanding for the driver even those who have no professional knowledge in vehicle technology. A self-learning algorithm for reducing the wrong warnings is presented for obtaining a suitable FCPI for the driver, which means that calculating the FCPI could meet each driver's behaviour. For the value of FCPI, value 0 is indicating the 0% probability of forward collision, and values 0.5 and 1 are indicating the 50% and 100% probabilities of forward collision, respectively. The experimental results guaranteed that the self-learning algorithm could figure out an optimal FCPI index for each driver to meet his/her driving behaviour and could reduce the wrong warnings.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"196-208"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44344948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-19DOI: 10.1504/IJVS.2017.10006058
M. Chitra, S. Sathya
Vehicular Ad Hoc Networks (VANETs) is a form of Intelligent Transportation System (ITS) to improve road safety and transport efficiency. During an emergency like accidents, traffic jams, etc., the vehicles in VANET are alerted with an Emergency Safety Message (ESM) through broadcasting. However, blind broadcasting of ESMs across VANETs leads to Broadcast Storm Problem (BSP) which would affect the QoS requirements of VANET. Hence, it is vital to suppress BSP to broadcast ESMs effectively. This paper proposes a Broadcast Storm Suppression Algorithm (BSSA) based on the concept of epidemic spreading, i.e. SEIR (Susceptible, Exposed, Infected and Removed) model. The broadcast storm is suppressed by finding the 'Farthest Infected Vehicle' (FIV) travelling in the direction of the ESM and recovering the other infected vehicles within the region to prevent from rebroadcasting the ESM. The SEIR model is simulated in NS-2.34 and found to outperform other popular broadcasting techniques.
{"title":"SEIR epidemic spreading model to suppress broadcast storm in vehicular ad hoc networks","authors":"M. Chitra, S. Sathya","doi":"10.1504/IJVS.2017.10006058","DOIUrl":"https://doi.org/10.1504/IJVS.2017.10006058","url":null,"abstract":"Vehicular Ad Hoc Networks (VANETs) is a form of Intelligent Transportation System (ITS) to improve road safety and transport efficiency. During an emergency like accidents, traffic jams, etc., the vehicles in VANET are alerted with an Emergency Safety Message (ESM) through broadcasting. However, blind broadcasting of ESMs across VANETs leads to Broadcast Storm Problem (BSP) which would affect the QoS requirements of VANET. Hence, it is vital to suppress BSP to broadcast ESMs effectively. This paper proposes a Broadcast Storm Suppression Algorithm (BSSA) based on the concept of epidemic spreading, i.e. SEIR (Susceptible, Exposed, Infected and Removed) model. The broadcast storm is suppressed by finding the 'Farthest Infected Vehicle' (FIV) travelling in the direction of the ESM and recovering the other infected vehicles within the region to prevent from rebroadcasting the ESM. The SEIR model is simulated in NS-2.34 and found to outperform other popular broadcasting techniques.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"228-252"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48613111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-19DOI: 10.1504/IJVS.2017.10006028
J. K. Ooi, S. A. Ahmad, H. Harun, Y. Z. Chong, S. Ali
In year 2013, 777,817 out of 22,702,211 of registered vehicles were involved in road traffic crashes, with a damage cost of more than 9.3 billion ringgits in Malaysia. Automotive makers have deployed a wide range of active safety systems (traction control, auto cruise and braking, collision avoidance, and lane switching) in recent years. However, these systems failed to significantly reduce road crash statistics. The automotive network comprises the vehicle, road and driver. Huge effort had been placed on the vehicle and road, whereas the driver remains the feeblest part. Consequently, automotive makers should focus their attention on monitoring drivers' emotion, which influences their driving behaviour. This study aims to explore available technology that monitors driver behaviour, besides proposing accident-stimulating emotion that affects driving. Furthermore, a conceptual framework for recognising anger and stress emotion, which is a cause of road crash, is proposed.
{"title":"A conceptual emotion recognition framework: stress and anger analysis for car accidents","authors":"J. K. Ooi, S. A. Ahmad, H. Harun, Y. Z. Chong, S. Ali","doi":"10.1504/IJVS.2017.10006028","DOIUrl":"https://doi.org/10.1504/IJVS.2017.10006028","url":null,"abstract":"In year 2013, 777,817 out of 22,702,211 of registered vehicles were involved in road traffic crashes, with a damage cost of more than 9.3 billion ringgits in Malaysia. Automotive makers have deployed a wide range of active safety systems (traction control, auto cruise and braking, collision avoidance, and lane switching) in recent years. However, these systems failed to significantly reduce road crash statistics. The automotive network comprises the vehicle, road and driver. Huge effort had been placed on the vehicle and road, whereas the driver remains the feeblest part. Consequently, automotive makers should focus their attention on monitoring drivers' emotion, which influences their driving behaviour. This study aims to explore available technology that monitors driver behaviour, besides proposing accident-stimulating emotion that affects driving. Furthermore, a conceptual framework for recognising anger and stress emotion, which is a cause of road crash, is proposed.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"181-195"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44102632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper deals with the modelling and the optimisation of a rail vehicle system moving in curved tracks running at high speeds. Based on the structural characteristics of the rail vehicle and its curved motion, we present an improved analytical quasi-static model. This model has the advantage of considering the roll motion. The improved model is validated through simulations, using the software ADAMS. The obtained model is used for the optimisation of the rail vehicle design. The safety criterion is evaluated using the derailment angle. A critical speed optimisation as a function of the radius of curvature and the rail vehicle design parameters is performed using genetic algorithm. The outcome of this work could help the designer in the choice of the adequate design parameters yielding the best compromise between the critical speed and the radius of curvature.
{"title":"An improved modelling and optimisation of rail vehicle design based on safety criterion","authors":"Nejlaoui Mohamed, Houidi Ajmi, Affi Zouhaier, Romdhane Lotfi","doi":"10.1504/IJVS.2017.10006057","DOIUrl":"https://doi.org/10.1504/IJVS.2017.10006057","url":null,"abstract":"This paper deals with the modelling and the optimisation of a rail vehicle system moving in curved tracks running at high speeds. Based on the structural characteristics of the rail vehicle and its curved motion, we present an improved analytical quasi-static model. This model has the advantage of considering the roll motion. The improved model is validated through simulations, using the software ADAMS. The obtained model is used for the optimisation of the rail vehicle design. The safety criterion is evaluated using the derailment angle. A critical speed optimisation as a function of the radius of curvature and the rail vehicle design parameters is performed using genetic algorithm. The outcome of this work could help the designer in the choice of the adequate design parameters yielding the best compromise between the critical speed and the radius of curvature.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"209-209"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43926630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-19DOI: 10.1504/IJVS.2017.10006065
D. Suman, M. Malini, B. Ramreddy
Drowsiness detection plays a vital role in accidents avoidance systems, thereby saving many precious lives. According to the World Health Organization, drowsiness has been the radical contributor of road fatalities. Electroencephalogram (EEG) is a physiological signal which relays the functioning of brain and is widely used in the diagnosis of neurological disorders. This study extrapolates the EEG signal analysis to examine several cognitive tasks. In this report, the EEG signal is processed to detect the behavioural patterns of the brain and drowsiness state of the drivers while performing monotonous driving for long distances. An eight-channel EEG data acquisition system is used to acquire the EEG data from 13 male volunteers. The EEG signal is pre-processed and decomposed into various rhythms by applying digital filter in MATLAB 2007b (Mathworks, Inc., USA). Time-frequency domain analysis has been done to extract certain features, PSG and PRMSD, which are statistically significant (ρ < 0.05) in the detection of drowsiness. The driving profile is classified into active and drowsy by a threshold, and linear regression analysis has been performed on the features extracted. A drowsiness index is proposed stating a positive correlation (0.8-0.9) between the total mean and the drowsy mean of the subject.
睡意检测在事故避免系统中起着至关重要的作用，从而挽救了许多宝贵的生命。根据世界卫生组织(World Health Organization)的数据，困倦一直是导致交通事故死亡的根本原因。脑电图是一种反映大脑功能的生理信号，在神经系统疾病的诊断中有着广泛的应用。本研究外推脑电图信号分析来检查几个认知任务。在本报告中，对脑电图信号进行处理，以检测驾驶员在进行单调的长途驾驶时大脑的行为模式和困倦状态。采用八通道脑电数据采集系统对13名男性志愿者进行脑电数据采集。在MATLAB 2007b (Mathworks, Inc.， USA)中应用数字滤波器对EEG信号进行预处理并分解成各种节律。通过时频域分析提取出某些特征，PSG和PRMSD在检测嗜睡方面有统计学意义(ρ < 0.05)。通过阈值将driving profile分为active和sleepy，并对提取的特征进行线性回归分析。提出了一个困倦指数，表明总平均值与受试者的困倦平均值呈正相关(0.8-0.9)。
{"title":"Joint time-frequency analysis of EEG for the drowsiness detection: a study of cognitive behavioural patterns of the brain","authors":"D. Suman, M. Malini, B. Ramreddy","doi":"10.1504/IJVS.2017.10006065","DOIUrl":"https://doi.org/10.1504/IJVS.2017.10006065","url":null,"abstract":"Drowsiness detection plays a vital role in accidents avoidance systems, thereby saving many precious lives. According to the World Health Organization, drowsiness has been the radical contributor of road fatalities. Electroencephalogram (EEG) is a physiological signal which relays the functioning of brain and is widely used in the diagnosis of neurological disorders. This study extrapolates the EEG signal analysis to examine several cognitive tasks. In this report, the EEG signal is processed to detect the behavioural patterns of the brain and drowsiness state of the drivers while performing monotonous driving for long distances. An eight-channel EEG data acquisition system is used to acquire the EEG data from 13 male volunteers. The EEG signal is pre-processed and decomposed into various rhythms by applying digital filter in MATLAB 2007b (Mathworks, Inc., USA). Time-frequency domain analysis has been done to extract certain features, PSG and PRMSD, which are statistically significant (ρ < 0.05) in the detection of drowsiness. The driving profile is classified into active and drowsy by a threshold, and linear regression analysis has been performed on the features extracted. A drowsiness index is proposed stating a positive correlation (0.8-0.9) between the total mean and the drowsy mean of the subject.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"262-277"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42794780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-10DOI: 10.1504/IJVS.2016.079654
Yingjie Liu, Junsheng Jiang
The paper describes a method for inverse dynamics of vehicle minimum time manoeuvre for collision avoidance problem. Based on this purpose, the vehicle minimum time manoeuvre for collision avoidance, which is treated as an optimal control problem, is firstly converted into a nonlinear programming problem by Gauss pseudospectral method (GPM) and is then solved with sequential quadratic programming (SQP). Finally, a real vehicle test was executed to verify the rationality of the proposed model and methodology. The results show that the simulation values are in good agreement with the real vehicle test values. The algorithm is not only precise, but can also shorten the evaluation period of vehicle handling stability and reduce the tremendous cost for real vehicle testing. The study can more truly simulate the emergency collision avoidance quality including the varying of minimum avoidable distance with different initial velocity.
{"title":"Inverse dynamics of vehicle minimum time manoeuvre for collision avoidance problem","authors":"Yingjie Liu, Junsheng Jiang","doi":"10.1504/IJVS.2016.079654","DOIUrl":"https://doi.org/10.1504/IJVS.2016.079654","url":null,"abstract":"The paper describes a method for inverse dynamics of vehicle minimum time manoeuvre for collision avoidance problem. Based on this purpose, the vehicle minimum time manoeuvre for collision avoidance, which is treated as an optimal control problem, is firstly converted into a nonlinear programming problem by Gauss pseudospectral method (GPM) and is then solved with sequential quadratic programming (SQP). Finally, a real vehicle test was executed to verify the rationality of the proposed model and methodology. The results show that the simulation values are in good agreement with the real vehicle test values. The algorithm is not only precise, but can also shorten the evaluation period of vehicle handling stability and reduce the tremendous cost for real vehicle testing. The study can more truly simulate the emergency collision avoidance quality including the varying of minimum avoidable distance with different initial velocity.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"64 1","pages":"120"},"PeriodicalIF":0.0,"publicationDate":"2016-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJVS.2016.079654","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66693838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-10DOI: 10.1504/IJVS.2016.079656
K. Alkhulaifi, M. Alardhi, J. Alrajhi, Y. Alhouli, A. Abed
Automotive rear-end collisions cause neck injuries. This has become a major problem in traffic safety over the last two decades. The situation calls for more research in the field. The damping seat slide is one area of interest which is used for reducing neck injury. To reduce neck injury (whiplash), based upon new biomechanical research, the motion between head and torso should be reduced. In case of a rear-end impact, a new seat will slide backwards during the impact, which allows the motion to damp. Working Model software was used first to simulate and analyse the behaviour of the new system. Also, a test rig was developed for experimental purposes. The results show occupant protection increases with the new damping seat slide by reducing the neck injury criterion by 35%.
{"title":"Reduction of whiplash injury in rear-end automotive collision using linear damping seat","authors":"K. Alkhulaifi, M. Alardhi, J. Alrajhi, Y. Alhouli, A. Abed","doi":"10.1504/IJVS.2016.079656","DOIUrl":"https://doi.org/10.1504/IJVS.2016.079656","url":null,"abstract":"Automotive rear-end collisions cause neck injuries. This has become a major problem in traffic safety over the last two decades. The situation calls for more research in the field. The damping seat slide is one area of interest which is used for reducing neck injury. To reduce neck injury (whiplash), based upon new biomechanical research, the motion between head and torso should be reduced. In case of a rear-end impact, a new seat will slide backwards during the impact, which allows the motion to damp. Working Model software was used first to simulate and analyse the behaviour of the new system. Also, a test rig was developed for experimental purposes. The results show occupant protection increases with the new damping seat slide by reducing the neck injury criterion by 35%.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"159-165"},"PeriodicalIF":0.0,"publicationDate":"2016-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJVS.2016.079656","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66693880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-10DOI: 10.1504/IJVS.2016.079657
S. Babesse, D. Ameddah
In this paper, a neuronal network is used to improve a Linear-Quadratic Regulator (LQR) active anti-roll control applied to a single-unit heavy vehicle suspension with linear and non-linear side force model. First, to keep the normalised rollovers between front and rear axles, equal to or below unity, the LQR control is proposed. After that, the training data collected from this controller are used as a training basis of a neuronal regulator. The artificial neuronal network controller is thereafter applied for the non-linear side force model, and it gives more satisfactory results than the LQR.
{"title":"Improvement of LQR active anti-roll control of a single-unit heavy vehicle by means of a trained artificial neuronal network","authors":"S. Babesse, D. Ameddah","doi":"10.1504/IJVS.2016.079657","DOIUrl":"https://doi.org/10.1504/IJVS.2016.079657","url":null,"abstract":"In this paper, a neuronal network is used to improve a Linear-Quadratic Regulator (LQR) active anti-roll control applied to a single-unit heavy vehicle suspension with linear and non-linear side force model. First, to keep the normalised rollovers between front and rear axles, equal to or below unity, the LQR control is proposed. After that, the training data collected from this controller are used as a training basis of a neuronal regulator. The artificial neuronal network controller is thereafter applied for the non-linear side force model, and it gives more satisfactory results than the LQR.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"166-179"},"PeriodicalIF":0.0,"publicationDate":"2016-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJVS.2016.079657","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66693901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-10DOI: 10.1504/IJVS.2016.079653
Dong Haibin, Shen Yanfeng, Hong Qingquan, Ma Jianqin, L. Lianxi, Yang Zhenming, Xian Xuelei
This paper analyses the features and positions of fires occurring in a bus engine compartment by many fire accidents, then develops a fire pre-alarm system used in bus engine compartment based on difference and fixed temperature control method by collecting and analysing the temperature data from the real bus engine compartment and simulated testing apparatus fire, and finally validates the accuracy and reliability of this system by relative tests, that provides a reliable solution for early fire detection and warning in bus engine compartment.
{"title":"Research on the fire pre-alarm system of bus engine compartment based on difference and fixed temperature control method","authors":"Dong Haibin, Shen Yanfeng, Hong Qingquan, Ma Jianqin, L. Lianxi, Yang Zhenming, Xian Xuelei","doi":"10.1504/IJVS.2016.079653","DOIUrl":"https://doi.org/10.1504/IJVS.2016.079653","url":null,"abstract":"This paper analyses the features and positions of fires occurring in a bus engine compartment by many fire accidents, then develops a fire pre-alarm system used in bus engine compartment based on difference and fixed temperature control method by collecting and analysing the temperature data from the real bus engine compartment and simulated testing apparatus fire, and finally validates the accuracy and reliability of this system by relative tests, that provides a reliable solution for early fire detection and warning in bus engine compartment.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"101-119"},"PeriodicalIF":0.0,"publicationDate":"2016-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJVS.2016.079653","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66693821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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