Pub Date : 2018-09-01DOI: 10.1109/ICVES.2018.8519492
V. Cañas, Eduardo Sánchez Morales, M. Botsch, Andrés García
The validation of driving functionalities for vehicles is a crucial step towards the implementation of mass production. This is especially true for autonomous functionalities. This paper presents the evaluation of a wireless communication system to aid in the validation of functionalities of full-scale autonomous vehicles in test tracks. The purpose of this system is to allow the analysis of the response of an autonomous function of a vehicle under different driving circumstances. This supports more realistic and relevant tests, since only full-scale vehicles participate in the circuits instead of dummies or crash targets. It also keeps humans out of harm’s way, since no occupants are needed inside the vehicles while the execution of the tests due to an autonomous maneuvering system that is controlling the pedals and the steering wheel. This wireless link complies with a series of constraints required for operation with full-scale vehicles. These are: real-time capabilities, connection stability and low packet loss rate. The compliance with these constraints is validated in a test track. For this, a series of tests are set up and performed under controlled conditions to provide specific evaluation parameters.
{"title":"Wireless Communication System for the Validation of Autonomous Driving Functions on Full-Scale Vehicles","authors":"V. Cañas, Eduardo Sánchez Morales, M. Botsch, Andrés García","doi":"10.1109/ICVES.2018.8519492","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519492","url":null,"abstract":"The validation of driving functionalities for vehicles is a crucial step towards the implementation of mass production. This is especially true for autonomous functionalities. This paper presents the evaluation of a wireless communication system to aid in the validation of functionalities of full-scale autonomous vehicles in test tracks. The purpose of this system is to allow the analysis of the response of an autonomous function of a vehicle under different driving circumstances. This supports more realistic and relevant tests, since only full-scale vehicles participate in the circuits instead of dummies or crash targets. It also keeps humans out of harm’s way, since no occupants are needed inside the vehicles while the execution of the tests due to an autonomous maneuvering system that is controlling the pedals and the steering wheel. This wireless link complies with a series of constraints required for operation with full-scale vehicles. These are: real-time capabilities, connection stability and low packet loss rate. The compliance with these constraints is validated in a test track. For this, a series of tests are set up and performed under controlled conditions to provide specific evaluation parameters.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133347276","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519511
Mohamed Nasr, Mostafa Ashraf, Mahmoud S. Hussein, A. M. Salem, Catherine M. Elias, Omar M. Shehata, E. I. Morgan
Autonomous navigation and localization of Aerial Vehicles in indoor environments is a major problem due to the difficulty of reliable control. Sliding Mode Control, Model Predictive Control, Back-stepping Control and Fuzzy Logic Control are proposed to stabilize and trajectory tracking for Unmanned Aerial Vehicles. Two trajectories were validated on the four controllers to determine the most efficient controller to maintain the optimal results.
{"title":"A comparitive study on the control of UAVs for Trajectory tracking by MPC, SMC, Backstepping, and Fuzzy Logic controllers","authors":"Mohamed Nasr, Mostafa Ashraf, Mahmoud S. Hussein, A. M. Salem, Catherine M. Elias, Omar M. Shehata, E. I. Morgan","doi":"10.1109/ICVES.2018.8519511","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519511","url":null,"abstract":"Autonomous navigation and localization of Aerial Vehicles in indoor environments is a major problem due to the difficulty of reliable control. Sliding Mode Control, Model Predictive Control, Back-stepping Control and Fuzzy Logic Control are proposed to stabilize and trajectory tracking for Unmanned Aerial Vehicles. Two trajectories were validated on the four controllers to determine the most efficient controller to maintain the optimal results.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130204599","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519585
Dauer Felix, D. Görges, A. Wienss
The popularity of pedelecs increases rapidly, which leads to a demand of new safety and comfort systems. An indepth analysis of sensor performance and boundary conditions is crucial since many of these systems rely on trustworthy inertial sensor data. This paper is focused on such an analysis and based on that, requirements for the sensors can be derived. Different sensor types are used to collect acceleration and angular rate measurement results during critical riding situations in different mounting positions with up to 50 kHz sampling frequency. Several critical environmental disturbances are taken into account, such as stone chipping, cobblestones and stairs. Based on these data, an evaluation for the use of inertial sensors, especially angular rate sensors, for eBike rider assistance systems is done. Overall, these investigations enable the selection of the most suitable sensors, sensor types and mounting positions for particular upcoming assistance systems.
{"title":"Experimental Analysis of Sensor Requirements for eBike Rider Assistance Systems","authors":"Dauer Felix, D. Görges, A. Wienss","doi":"10.1109/ICVES.2018.8519585","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519585","url":null,"abstract":"The popularity of pedelecs increases rapidly, which leads to a demand of new safety and comfort systems. An indepth analysis of sensor performance and boundary conditions is crucial since many of these systems rely on trustworthy inertial sensor data. This paper is focused on such an analysis and based on that, requirements for the sensors can be derived. Different sensor types are used to collect acceleration and angular rate measurement results during critical riding situations in different mounting positions with up to 50 kHz sampling frequency. Several critical environmental disturbances are taken into account, such as stone chipping, cobblestones and stairs. Based on these data, an evaluation for the use of inertial sensors, especially angular rate sensors, for eBike rider assistance systems is done. Overall, these investigations enable the selection of the most suitable sensors, sensor types and mounting positions for particular upcoming assistance systems.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131464938","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519524
Jonatan Pajares Redondo, Lisardo Prieto-González, Mat Max Montalvo Martínez, Javier García Guzmán, S. Sanchez, M. J. L. Boada, B. L. Boada
Vehicle dynamics studies are an indispensable characteristic to improve the vehicle stability and handling. To fulfil this requirement, control systems are included in commercial vehicles nowadays. These control systems consider variables such as lateral acceleration, roll rate and sideslip angle, that can be directly obtained from sensors or estimated from the collected data. With the objective of incorporating control systems without increasing the price of these vehicles, it is necessary to develop low-cost embedded systems, capable of acquiring data from a diversity of sensors to execute estimations and to perform control actions under real-time constraints. The increase of capabilities and features provided by smartphones enable them as data acquisition and processing devices. In this paper, an analysis in terms of reliability, accuracy and acquisition have been performed for two different smartphones in order to study the possibility to use this kind of devices as a low-cost sensing platform for vehicle dynamic applications. Each smartphone used in this study is classified into a different category (low-end or high-end device) depending on not only its price but also its specifications. Both yaw rate and lateral acceleration have been analyzed in order to quantify the performance of each smartphone. These variables have a direct influence on the vehicle lateral dynamics. Experimental tests have been carried out in a real scenario and the VBOX IMU connected with the VBOX 3i data logger of Racelogic has been used as the ground truth.
{"title":"VEHIOT: Evaluation of Smartphones as Data Acquisition Systems to Reduce Risk Situations in Commercial Vehicles","authors":"Jonatan Pajares Redondo, Lisardo Prieto-González, Mat Max Montalvo Martínez, Javier García Guzmán, S. Sanchez, M. J. L. Boada, B. L. Boada","doi":"10.1109/ICVES.2018.8519524","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519524","url":null,"abstract":"Vehicle dynamics studies are an indispensable characteristic to improve the vehicle stability and handling. To fulfil this requirement, control systems are included in commercial vehicles nowadays. These control systems consider variables such as lateral acceleration, roll rate and sideslip angle, that can be directly obtained from sensors or estimated from the collected data. With the objective of incorporating control systems without increasing the price of these vehicles, it is necessary to develop low-cost embedded systems, capable of acquiring data from a diversity of sensors to execute estimations and to perform control actions under real-time constraints. The increase of capabilities and features provided by smartphones enable them as data acquisition and processing devices. In this paper, an analysis in terms of reliability, accuracy and acquisition have been performed for two different smartphones in order to study the possibility to use this kind of devices as a low-cost sensing platform for vehicle dynamic applications. Each smartphone used in this study is classified into a different category (low-end or high-end device) depending on not only its price but also its specifications. Both yaw rate and lateral acceleration have been analyzed in order to quantify the performance of each smartphone. These variables have a direct influence on the vehicle lateral dynamics. Experimental tests have been carried out in a real scenario and the VBOX IMU connected with the VBOX 3i data logger of Racelogic has been used as the ground truth.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115984678","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519508
Hongxin Kong, Jun Cheng, K. Narayanan, Jiang Hu
Error handling and real-time are two fundamental needs for in-vehicle network communication. Traditionally, error detection code such as CRC (Cyclic Redundancy Check) is employed and a message is retransmitted if any error is detected. However, message retransmission can conflict with real-time constraints due to extra communication delay and uncertain waiting time. Conventional error correction code can avoid message retransmission, but entails long decoding time or expensive hardware cost. In some recent in-vehicle network protocols, such as FlexRay and Time-Triggered Ethernet, redundant communication channels are supported. We propose a fast yet lightweight error correction scheme that exploits this redundancy, called DUCER (DUal Crc Error coRrection). This scheme largely avoids message retransmission without changing the encoding of existing protocols and can correct 5-bit errors for 254-byte payload in less than 1 ms. Compared to Reed-Solomon code, DUCER is one order of magnitude faster in software decoding or reduces area cost by 89% in hardware implementation.
{"title":"DUCER: a Fast and Lightweight Error Correction Scheme for In-Vehicle Network Communication","authors":"Hongxin Kong, Jun Cheng, K. Narayanan, Jiang Hu","doi":"10.1109/ICVES.2018.8519508","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519508","url":null,"abstract":"Error handling and real-time are two fundamental needs for in-vehicle network communication. Traditionally, error detection code such as CRC (Cyclic Redundancy Check) is employed and a message is retransmitted if any error is detected. However, message retransmission can conflict with real-time constraints due to extra communication delay and uncertain waiting time. Conventional error correction code can avoid message retransmission, but entails long decoding time or expensive hardware cost. In some recent in-vehicle network protocols, such as FlexRay and Time-Triggered Ethernet, redundant communication channels are supported. We propose a fast yet lightweight error correction scheme that exploits this redundancy, called DUCER (DUal Crc Error coRrection). This scheme largely avoids message retransmission without changing the encoding of existing protocols and can correct 5-bit errors for 254-byte payload in less than 1 ms. Compared to Reed-Solomon code, DUCER is one order of magnitude faster in software decoding or reduces area cost by 89% in hardware implementation.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129970435","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519483
Mingkang Li, Martin Stolz, Zhaofei Feng, M. Kunert, R. Henze, F. Küçükay
Novel automotive high resolution radar sensors can detect several thousands of reflection points from the surrounding environment, e.g., pedestrians, cyclists, vehicles and roadside infrastructure. For object classification and tracking, the detection points belonging to the same object shall be clustered into one group before further processing. This paper presents an adaptive clustering approach based on a range/angle/velocity-grid generated originally from the radar signal processing and angle estimation stage. In contrast to an x/y-approach, multiple reflection points will not be merged into one single grid cell at close ranges, but keep their individual information in different assigned grid cells. A time and storage efficient process with a clustering window according to grid indices is implemented to search for the points with similarity in all three dimensions. In order to eliminate the parameter dependency and the incorrect clustering due to uncertainties of real radar measurements, this approach is extended with a model-based clustering window depending on the tracked and estimated object contour. By validation with various measurement data, stable clustering results with almost perfect true positive rates are achieved independently of the prevailing parameters and object types.
{"title":"An Adaptive 3D Grid-Based Clustering Algorithm for Automotive High Resolution Radar Sensor","authors":"Mingkang Li, Martin Stolz, Zhaofei Feng, M. Kunert, R. Henze, F. Küçükay","doi":"10.1109/ICVES.2018.8519483","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519483","url":null,"abstract":"Novel automotive high resolution radar sensors can detect several thousands of reflection points from the surrounding environment, e.g., pedestrians, cyclists, vehicles and roadside infrastructure. For object classification and tracking, the detection points belonging to the same object shall be clustered into one group before further processing. This paper presents an adaptive clustering approach based on a range/angle/velocity-grid generated originally from the radar signal processing and angle estimation stage. In contrast to an x/y-approach, multiple reflection points will not be merged into one single grid cell at close ranges, but keep their individual information in different assigned grid cells. A time and storage efficient process with a clustering window according to grid indices is implemented to search for the points with similarity in all three dimensions. In order to eliminate the parameter dependency and the incorrect clustering due to uncertainties of real radar measurements, this approach is extended with a model-based clustering window depending on the tracked and estimated object contour. By validation with various measurement data, stable clustering results with almost perfect true positive rates are achieved independently of the prevailing parameters and object types.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128322850","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519521
J. Pimentel, Jennifer Bastiaan, M. Zadeh
Due to recent accidents, safety has surfaced as the number one concern for the acceptance and adoption of autonomous vehicles. The development of safety systems in selfdriving vehicles has some of the most complex requirements. How does one know when a self-driving vehicle is safe enough? And equally important, how do we measure the safety level of a given vehicle design? In this paper we present a mathematical model that is used to numerically evaluate the safety level of five different self-driving vehicle designs, in terms of important parameters related to the design process. The main results show that strict adherence to safety standards, and the use of faulttolerant techniques, particularly for the perception system, can considerably improve the safety level of a self-driving vehicle.
{"title":"Numerical Evaluation of the Safety of Self-Driving Vehicles: Functionality Involving Vehicle Detection","authors":"J. Pimentel, Jennifer Bastiaan, M. Zadeh","doi":"10.1109/ICVES.2018.8519521","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519521","url":null,"abstract":"Due to recent accidents, safety has surfaced as the number one concern for the acceptance and adoption of autonomous vehicles. The development of safety systems in selfdriving vehicles has some of the most complex requirements. How does one know when a self-driving vehicle is safe enough? And equally important, how do we measure the safety level of a given vehicle design? In this paper we present a mathematical model that is used to numerically evaluate the safety level of five different self-driving vehicle designs, in terms of important parameters related to the design process. The main results show that strict adherence to safety standards, and the use of faulttolerant techniques, particularly for the perception system, can considerably improve the safety level of a self-driving vehicle.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130809622","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519520
Katharina Gillmeier, Tobias Schuettke, F. Diederichs, Gloriya Miteva, D. Spath
Driver intention detection holds high potential for adaptive driver assistance systems and automated driving functions. To develop a combined driver distraction and intention model as well as an intention detection algorithm a real driving study with 45 subjects performing 1260 braking and 1890 evasion maneuvers was conducted and analyzed. The driver‘s distraction level and hand position are varied to analyze their influence on driver intention. With a probabilistic approach, a sensitivity analysis of indicators for detecting driver intention was developed. The accelerator pedal and the longitudinal and lateral accelerations reveal to be most sensitive for evasion, while the longitudinal acceleration, the brake pressure and the accelerator pedal are most sensitive for braking. By using this sensitivities for algorithm design and combining them with information about whether drivers have recognized the object and their distraction level, evasion maneuvers can be detected correctly at least three seconds prior to passing the object in 91 % of all cases, braking maneuvers in 87 % of all cases. The driver‘s distraction level turned out to be relevant for intention recognition, as 87 % of drivers reduce their distraction at least three seconds prior to passing the object. We conclude that drivers cannot have a relevant intention and be highly distracted at the same time. Driver distraction detection hence contributes to the driver intention recognition. A three seconds prediction frame allow effective risk mitigation by warning and automated interventions.
{"title":"Combined Driver Distraction and Intention Algorithm for Maneuver Prediction and Collision Avoidance","authors":"Katharina Gillmeier, Tobias Schuettke, F. Diederichs, Gloriya Miteva, D. Spath","doi":"10.1109/ICVES.2018.8519520","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519520","url":null,"abstract":"Driver intention detection holds high potential for adaptive driver assistance systems and automated driving functions. To develop a combined driver distraction and intention model as well as an intention detection algorithm a real driving study with 45 subjects performing 1260 braking and 1890 evasion maneuvers was conducted and analyzed. The driver‘s distraction level and hand position are varied to analyze their influence on driver intention. With a probabilistic approach, a sensitivity analysis of indicators for detecting driver intention was developed. The accelerator pedal and the longitudinal and lateral accelerations reveal to be most sensitive for evasion, while the longitudinal acceleration, the brake pressure and the accelerator pedal are most sensitive for braking. By using this sensitivities for algorithm design and combining them with information about whether drivers have recognized the object and their distraction level, evasion maneuvers can be detected correctly at least three seconds prior to passing the object in 91 % of all cases, braking maneuvers in 87 % of all cases. The driver‘s distraction level turned out to be relevant for intention recognition, as 87 % of drivers reduce their distraction at least three seconds prior to passing the object. We conclude that drivers cannot have a relevant intention and be highly distracted at the same time. Driver distraction detection hence contributes to the driver intention recognition. A three seconds prediction frame allow effective risk mitigation by warning and automated interventions.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117237798","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519596
Mehmet Ali Silgu, Kenan Muderrisoglu, Ahmet Halit Unsal, H. B. Çelikoglu
The work summarized in this paper analyzes the hazardous emission effects created in the city centers due to heavy duty truck operations. Simulations related to road and vehicle are backed up with the real time data to give more realistic results. The vehicle is simulated under both the road and traffic conditions with the acceleration and deceleration data coming from the information collected in real time. The real time data is preprocessed with a low pass filter to clear off unwanted parts. Then simulations are carried out via VISSIM and TruckMaker software. Eventually this paper claims the city center air pollution created due to heavy duty truck can easily be eliminated by converting to full electric trucks since the electric vehicle produces 0 emission and the electric energy production phase does not affect the air pollution at the city center.
{"title":"Approximation Of Emission For Heavy Duty Trucks In City Traffic","authors":"Mehmet Ali Silgu, Kenan Muderrisoglu, Ahmet Halit Unsal, H. B. Çelikoglu","doi":"10.1109/ICVES.2018.8519596","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519596","url":null,"abstract":"The work summarized in this paper analyzes the hazardous emission effects created in the city centers due to heavy duty truck operations. Simulations related to road and vehicle are backed up with the real time data to give more realistic results. The vehicle is simulated under both the road and traffic conditions with the acceleration and deceleration data coming from the information collected in real time. The real time data is preprocessed with a low pass filter to clear off unwanted parts. Then simulations are carried out via VISSIM and TruckMaker software. Eventually this paper claims the city center air pollution created due to heavy duty truck can easily be eliminated by converting to full electric trucks since the electric vehicle produces 0 emission and the electric energy production phase does not affect the air pollution at the city center.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123297211","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 : 2018-09-01DOI: 10.1109/ICVES.2018.8519512
A. M. Nascimento, P. Cugnasca, L. Vismari, J. B. C. Junior, J. R. Almeida
Sonar distance sensors are commonly used for obstacle detection and distance measurement, providing input information for different applications, such as collision avoidance algorithms and vehicle parking assistants. However, they have a wide range of quality and accuracy, resulting in prices ranging from $0.55 to over $100 per unit. As it is often necessary to use a few units in parking assistants and those are deployed on a largescale vehicle production, the unit price is a critical factor. However, the simple choice of the lowest price sensors directly impacts on the measurements reliability, since they have high levels of noise in the values of their measurements. Therefore, this presents the results of the experiments using the Bayesian Recursive Estimation technique – also known as Bayesian Filtering – to increase the accuracy and reliability of low-cost sonar sensor measurements. A prototype is implemented and evaluated in simulated and real (physical) experimental environments. Using this approach, a significant accuracy improvement on distance measurements was observed compared to the raw data obtained from sensors. The results suggest this approach can be an alternative to be considered to reduce costs when equipping vehicles with parking assistants.
{"title":"Enhancing the Accuracy of Parking Assistant Sensors with Bayesian Filter","authors":"A. M. Nascimento, P. Cugnasca, L. Vismari, J. B. C. Junior, J. R. Almeida","doi":"10.1109/ICVES.2018.8519512","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519512","url":null,"abstract":"Sonar distance sensors are commonly used for obstacle detection and distance measurement, providing input information for different applications, such as collision avoidance algorithms and vehicle parking assistants. However, they have a wide range of quality and accuracy, resulting in prices ranging from $0.55 to over $100 per unit. As it is often necessary to use a few units in parking assistants and those are deployed on a largescale vehicle production, the unit price is a critical factor. However, the simple choice of the lowest price sensors directly impacts on the measurements reliability, since they have high levels of noise in the values of their measurements. Therefore, this presents the results of the experiments using the Bayesian Recursive Estimation technique – also known as Bayesian Filtering – to increase the accuracy and reliability of low-cost sonar sensor measurements. A prototype is implemented and evaluated in simulated and real (physical) experimental environments. Using this approach, a significant accuracy improvement on distance measurements was observed compared to the raw data obtained from sensors. The results suggest this approach can be an alternative to be considered to reduce costs when equipping vehicles with parking assistants.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129270519","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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