Pub Date : 2018-12-01DOI: 10.1109/VNC.2018.8628432
Gokhan Gurbilek, M. Koca, B. Turan, S. Ergen
Vehicular visible light communication (V2LC) has recently gained popularity as a complementary technology to radio frequency (RF) based vehicular communication schemes due to light emitting diode (LED)s’ readily availability on vehicles with its secure and RF-interference free nature. However, vehicular visible light communication (V2LC) system performance mainly depends on LED characteristics. Investigating various LED bulbs for their frequency response and optical OFDM (O-OFDM) based modulation performances, it has been observed that LED and DC-bias voltage selection is key for the V2LC system modulation performance. Experimental results indicate that, on contrary to simulation results in the literature, asymmetrically clipped optical OFDM (ACO-OFDM) is observed to perform better than unipolar OFDM (U-OFDM) as it inherits lower peak-to-average power ratio (PAPR) with lower clipping noise which is crucial for LEDs under consideration with limited linear working region.
{"title":"Poster: Vehicular VLC Experimental Modulation Performance Comparison","authors":"Gokhan Gurbilek, M. Koca, B. Turan, S. Ergen","doi":"10.1109/VNC.2018.8628432","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628432","url":null,"abstract":"Vehicular visible light communication (V2LC) has recently gained popularity as a complementary technology to radio frequency (RF) based vehicular communication schemes due to light emitting diode (LED)s’ readily availability on vehicles with its secure and RF-interference free nature. However, vehicular visible light communication (V2LC) system performance mainly depends on LED characteristics. Investigating various LED bulbs for their frequency response and optical OFDM (O-OFDM) based modulation performances, it has been observed that LED and DC-bias voltage selection is key for the V2LC system modulation performance. Experimental results indicate that, on contrary to simulation results in the literature, asymmetrically clipped optical OFDM (ACO-OFDM) is observed to perform better than unipolar OFDM (U-OFDM) as it inherits lower peak-to-average power ratio (PAPR) with lower clipping noise which is crucial for LEDs under consideration with limited linear working region.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124862404","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628409
Qi Ye, Lanqing Yang, Guangtao Xue
Gesture recognition has a rapidly growing market size which is forcasted to increase from 14 billion in 2012 to 44 billion in 2020. Applying gesture recognition for vehicle infotainment system control is considered a promising alternative against traditional buttons, touch screens, or even speech-based control for its numerous advantages. However, existing gesture control solutions either depend on camera which imposes privacy concern and is sensitive to light condition or require users to wear a device on their hand which makes it inconvenient to use. Therefore, the work proposes to use the acoustic-based device-free hand tracking technology for gesture recognition. Because it only requires an ordinary speaker and microphone which are already available on vehicles or equipped in smart phones, it doesn’t cast additional hardware cost or installation. We implement the proposed gesture control in Android phones and show it’s feasibility for vehicle infotainment system control.
{"title":"Hand-free Gesture Recognition for Vehicle Infotainment System Control","authors":"Qi Ye, Lanqing Yang, Guangtao Xue","doi":"10.1109/VNC.2018.8628409","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628409","url":null,"abstract":"Gesture recognition has a rapidly growing market size which is forcasted to increase from 14 billion in 2012 to 44 billion in 2020. Applying gesture recognition for vehicle infotainment system control is considered a promising alternative against traditional buttons, touch screens, or even speech-based control for its numerous advantages. However, existing gesture control solutions either depend on camera which imposes privacy concern and is sensitive to light condition or require users to wear a device on their hand which makes it inconvenient to use. Therefore, the work proposes to use the acoustic-based device-free hand tracking technology for gesture recognition. Because it only requires an ordinary speaker and microphone which are already available on vehicles or equipped in smart phones, it doesn’t cast additional hardware cost or installation. We implement the proposed gesture control in Android phones and show it’s feasibility for vehicle infotainment system control.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127003110","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628350
Fabian Bronner, C. Sommer
Simulation is a key tool for studying new system designs, but its scalability is often limited by the complexity of underlying models. We investigate to what degree different channel models – in particular differently-complex signal representations and loss models – impact simulation performance. Measurements reveal that, if all effects relevant to typical vehicular network simulations are to be captured, use of a highly efficient signal representation that can exploit modern CPU features allows to cut its performance impact by an order of magnitude. Yet, measurements also reveal that in typical vehicular network simulations, runtime performance is dominated by that of loss modeling instead. To address this issue, we also present a universal approach that can speed up loss modeling. We show that this approach can improve the overall runtime performance of simulations by more than an order of magnitude with no loss in precision.
{"title":"Efficient Multi-Channel Simulation of Wireless Communications","authors":"Fabian Bronner, C. Sommer","doi":"10.1109/VNC.2018.8628350","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628350","url":null,"abstract":"Simulation is a key tool for studying new system designs, but its scalability is often limited by the complexity of underlying models. We investigate to what degree different channel models – in particular differently-complex signal representations and loss models – impact simulation performance. Measurements reveal that, if all effects relevant to typical vehicular network simulations are to be captured, use of a highly efficient signal representation that can exploit modern CPU features allows to cut its performance impact by an order of magnitude. Yet, measurements also reveal that in typical vehicular network simulations, runtime performance is dominated by that of loss modeling instead. To address this issue, we also present a universal approach that can speed up loss modeling. We show that this approach can improve the overall runtime performance of simulations by more than an order of magnitude with no loss in precision.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115750009","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628348
Chung-Wei Lin
System integration has became more challenging than ever. In this poster, we propose to use a formal approach to verify the Quality of Service (QoS) compatibility of components connected by the Time-Sensitive Networking (TSN) [6]. We demonstrate that the formal approach, if realized, is applicable to various stages including specification definition of components to be developed, integration with existing components, runtime monitoring with adaptive components, and maintenance of components.
{"title":"Poster: Formal QoS Compatibility Verification for Components on Time-Sensitive Networking","authors":"Chung-Wei Lin","doi":"10.1109/VNC.2018.8628348","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628348","url":null,"abstract":"System integration has became more challenging than ever. In this poster, we propose to use a formal approach to verify the Quality of Service (QoS) compatibility of components connected by the Time-Sensitive Networking (TSN) [6]. We demonstrate that the formal approach, if realized, is applicable to various stages including specification definition of components to be developed, integration with existing components, runtime monitoring with adaptive components, and maintenance of components.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130970649","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628334
Chia-Cheng Yen, D. Ghosal, H. M. Zhang, C. Chuah, Hao Chen
In urban transportation, scheduling algorithms in traffic signal control (TSC) are important for achieving high throughput and low latency traffic flow, lowering accidents, and reducing emissions. As new scheduling algorithms are being developed particularly to leverage and accommodate connected and autonomous vehicles, there is increased potential for cyber-attacks on TSC that can undermine the benefits of new algorithms. Attackers can learn the behavior of scheduling algorithms and launch attacks to get scheduling priority and/or to create traffic panic and congestion. These attacks can compromise the system and significantly increase traffic delay and make TSC completely ineffective. In this paper, we compare the performance of different backpressure-based scheduling algorithms when they are under attack. We consider four different backpressure-based schemes, namely, delay-based, queue-based, sum-of-delay-based, and hybrid scheme that combines delay-based and queue-based schemes. We consider time spoofing attacks where individual vehicles arriving at an intersection can alter their arrival times. Through detailed simulation analysis we show that while the delay-based scheme has better fairness performance, it is more vulnerable to time spoofing attacks than the other schemes. We explore drawbacks of the delay-based scheme under different scenarios including non-homogeneous arrivals both for isolated intersection as well as multiple intersections. This study throws light on how to prevent time spoofing attacks on next generation TSC.
{"title":"Falsified Data Attack on Backpressure-based Traffic Signal Control Algorithms","authors":"Chia-Cheng Yen, D. Ghosal, H. M. Zhang, C. Chuah, Hao Chen","doi":"10.1109/VNC.2018.8628334","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628334","url":null,"abstract":"In urban transportation, scheduling algorithms in traffic signal control (TSC) are important for achieving high throughput and low latency traffic flow, lowering accidents, and reducing emissions. As new scheduling algorithms are being developed particularly to leverage and accommodate connected and autonomous vehicles, there is increased potential for cyber-attacks on TSC that can undermine the benefits of new algorithms. Attackers can learn the behavior of scheduling algorithms and launch attacks to get scheduling priority and/or to create traffic panic and congestion. These attacks can compromise the system and significantly increase traffic delay and make TSC completely ineffective. In this paper, we compare the performance of different backpressure-based scheduling algorithms when they are under attack. We consider four different backpressure-based schemes, namely, delay-based, queue-based, sum-of-delay-based, and hybrid scheme that combines delay-based and queue-based schemes. We consider time spoofing attacks where individual vehicles arriving at an intersection can alter their arrival times. Through detailed simulation analysis we show that while the delay-based scheme has better fairness performance, it is more vulnerable to time spoofing attacks than the other schemes. We explore drawbacks of the delay-based scheme under different scenarios including non-homogeneous arrivals both for isolated intersection as well as multiple intersections. This study throws light on how to prevent time spoofing attacks on next generation TSC.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123320481","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628345
Wen-Ping Lai, Kuan-Chun Chiu
Network functions virtualization (NFV) based service chaining is one of the key enablers to speed up innovations of 5G networks for differential service needs in terms of network slicing. In this demonstration, we showcase automatic deployment of a service chain or slice (i.e., a load-balanced web-database system with memory cache), consisting of 4 different virtual network functions (VNFs) connected with proper mutual relations, on a x86-PC bare metal server running with Linux. Dynamic scaling-up of such a service chain without service interruption is also demonstrated by adding one more web server, during the run time, based on the fact that its relations with the others can be automatically copied and established. Our stress tests show the load*duration responses with the stress level before and after the scaling-up, and their difference becomes dramatically amplified as the stress level gets high.
{"title":"Demo: Automatic Deployment and Dynamic Scaling of NFV Service Chaining on Bare Metal (SCBM)","authors":"Wen-Ping Lai, Kuan-Chun Chiu","doi":"10.1109/VNC.2018.8628345","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628345","url":null,"abstract":"Network functions virtualization (NFV) based service chaining is one of the key enablers to speed up innovations of 5G networks for differential service needs in terms of network slicing. In this demonstration, we showcase automatic deployment of a service chain or slice (i.e., a load-balanced web-database system with memory cache), consisting of 4 different virtual network functions (VNFs) connected with proper mutual relations, on a x86-PC bare metal server running with Linux. Dynamic scaling-up of such a service chain without service interruption is also demonstrated by adding one more web server, during the run time, based on the fact that its relations with the others can be automatically copied and established. Our stress tests show the load*duration responses with the stress level before and after the scaling-up, and their difference becomes dramatically amplified as the stress level gets high.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129314079","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628352
P. Carnelli, M. Sooriyabandara, R. E. Wilson
Wireless vehicular ad-hoc networks comprised solely of city taxis are investigated for their ability to deliver data across an urban environment. Openly available taxi trace datasets for Rome (Italy) and San Francisco (USA) are combined with respective building footprint and road network topology data from OpenStreetMap, to generate a realistic systems level model of a taxi V2V network. Analysis of LOS and NOLOS constraints on wireless transmission range suggests a minimum threshold of 50m is applicable to ensure LOS in over 90% of cases. Variations in taxi location sampling frequency and filtering techniques for the taxi trace datasets are also investigated. Overall vehicular network performance is computed for an all-to-one transmission scenario for both cities with varying taxi fleet size. Results suggest a non-linear relationship between increases in taxi fleet sizes and the reduction of end-to-end delay; doubling taxi fleet size (using a randomised data folding technique) reduces end-to-end delay by a factor of 0.6–0.7. However, doubling the fleet does not increase the fraction of delivered source messages, which saturates at 0.67–0.71 in most simulations. Finally it appears that taxi networks for delivering messages across urban environments are limited more by their routing than by the number of possible V2V exchanges. In a simulated one-to-all continuous V2V broadcast scenario, over 90% of the taxis within the fleet receive the source message within one hour of the original taxi passing the source node.
{"title":"Large-Scale VANET Simulations and Performance Analysis using Real Taxi Trace and City Map Data","authors":"P. Carnelli, M. Sooriyabandara, R. E. Wilson","doi":"10.1109/VNC.2018.8628352","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628352","url":null,"abstract":"Wireless vehicular ad-hoc networks comprised solely of city taxis are investigated for their ability to deliver data across an urban environment. Openly available taxi trace datasets for Rome (Italy) and San Francisco (USA) are combined with respective building footprint and road network topology data from OpenStreetMap, to generate a realistic systems level model of a taxi V2V network. Analysis of LOS and NOLOS constraints on wireless transmission range suggests a minimum threshold of 50m is applicable to ensure LOS in over 90% of cases. Variations in taxi location sampling frequency and filtering techniques for the taxi trace datasets are also investigated. Overall vehicular network performance is computed for an all-to-one transmission scenario for both cities with varying taxi fleet size. Results suggest a non-linear relationship between increases in taxi fleet sizes and the reduction of end-to-end delay; doubling taxi fleet size (using a randomised data folding technique) reduces end-to-end delay by a factor of 0.6–0.7. However, doubling the fleet does not increase the fraction of delivered source messages, which saturates at 0.67–0.71 in most simulations. Finally it appears that taxi networks for delivering messages across urban environments are limited more by their routing than by the number of possible V2V exchanges. In a simulated one-to-all continuous V2V broadcast scenario, over 90% of the taxis within the fleet receive the source message within one hour of the original taxi passing the source node.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121531808","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628453
Yuhui Sun, Yongzhao Zhang, Guangtao Xue
Vehicles are providing increasing number of functions for drivers than they were designed, including streaming music from the Internet, answering calls, showing the latest news from drivers’ social networks, advising drivers the route and road condition, and etc. Traditionally, drivers use buttons and switches on control panel or a touch screen to access all the functions. However, a flat design may turn a car into a button-fest which may confuse even daily drivers. On the other hand, hierarchical UI requires drivers to click buttons or screens several times to navigate the menus is time intensive and may take drivers’ eyes from the road. To address these problems, we propose SmartWheelTag. SmartWheelTag is a RFID tag on a slap bracelet so drivers can easily attach and disattach it onto a steering wheel. When drivers touch the different part of the SmartWheelTag, different phases are detected. We further develop an Android APP so drivers can pre-define gestures to map their actions on SmartWheelTag to vehicle functions. Since SmartWheelTag can be installed at the most comfortable place and provide customized functions, drivers can easily access the desired vehicle functions quickly while concentrating on the roads.
{"title":"SmartWheelTag: Flexible and Battery-less User Interface for Drivers","authors":"Yuhui Sun, Yongzhao Zhang, Guangtao Xue","doi":"10.1109/VNC.2018.8628453","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628453","url":null,"abstract":"Vehicles are providing increasing number of functions for drivers than they were designed, including streaming music from the Internet, answering calls, showing the latest news from drivers’ social networks, advising drivers the route and road condition, and etc. Traditionally, drivers use buttons and switches on control panel or a touch screen to access all the functions. However, a flat design may turn a car into a button-fest which may confuse even daily drivers. On the other hand, hierarchical UI requires drivers to click buttons or screens several times to navigate the menus is time intensive and may take drivers’ eyes from the road. To address these problems, we propose SmartWheelTag. SmartWheelTag is a RFID tag on a slap bracelet so drivers can easily attach and disattach it onto a steering wheel. When drivers touch the different part of the SmartWheelTag, different phases are detected. We further develop an Android APP so drivers can pre-define gestures to map their actions on SmartWheelTag to vehicle functions. Since SmartWheelTag can be installed at the most comfortable place and provide customized functions, drivers can easily access the desired vehicle functions quickly while concentrating on the roads.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121773493","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628362
Wei Liu, Y. Shoji
Sensing data gathering and dissemination is one of the most challenging tasks in smart city construction, and vehicles moving around a city have been widely considered as a good candidate to deliver data efficiently and economically. Hence, this paper proposes a deep recurrent neural network-based algorithm to predict vehicle mobility and facilitate vehicle-based sensing data delivery. Extensive evaluations have been conducted by using a large-scale taxi mobility dataset that is obtained from a smart city testbed deployed in Tokyo, Japan. The results have validated that, compared with the most state-of-art algorithms, our proposal can improve the F1-Score of vehicle mobility prediction by a range of 18.3% ~24.6%.
{"title":"Applying Deep Recurrent Neural Network to Predict Vehicle Mobility","authors":"Wei Liu, Y. Shoji","doi":"10.1109/VNC.2018.8628362","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628362","url":null,"abstract":"Sensing data gathering and dissemination is one of the most challenging tasks in smart city construction, and vehicles moving around a city have been widely considered as a good candidate to deliver data efficiently and economically. Hence, this paper proposes a deep recurrent neural network-based algorithm to predict vehicle mobility and facilitate vehicle-based sensing data delivery. Extensive evaluations have been conducted by using a large-scale taxi mobility dataset that is obtained from a smart city testbed deployed in Tokyo, Japan. The results have validated that, compared with the most state-of-art algorithms, our proposal can improve the F1-Score of vehicle mobility prediction by a range of 18.3% ~24.6%.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124004342","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 : 2018-12-01DOI: 10.1109/VNC.2018.8628425
Wen-Hsuan Shen, Po-Wen Chen, Hsin-Mu Tsai
State-of-the-art vehicular visible light communication (V2LC) systems utilize either a photodiode or a camera as the receiver, while both have their drawbacks. A photodiode-based receiver lacks the capability to separate signals from sources transmitting at the same time and is more vulnerable to interference. On the other hand, a camera-based receiver suffers from low system throughput, resulting from the low image frame rate of commodity cameras. In this paper, we investigate a solution which attempts to combine the best of both, and mitigate their drawbacks.We propose to use a new type of CMOS vision sensor: a dynamic vision sensor (DVS). Instead of recording still frames, a DVS only generates outputs when it senses a significant change of brightness in a pixel. The output of a DVS is a stream of events on the pixel basis with 1 μs resolution, which greatly increase the bandwidth. We investigate the key requirements of the modulation wave form when using a DVS camera-based receiver, and propose a new pulse wave form that maintains the same average luminance level while extending the operational range of the system. Preliminary experimental results show that the proposed wave form nearly triples the range to 8 m, compared to the range of 3 m when using the conventional inverse pulse position modulation wave form.
{"title":"Vehicular Visible Light Communication with Dynamic Vision Sensor: A Preliminary Study","authors":"Wen-Hsuan Shen, Po-Wen Chen, Hsin-Mu Tsai","doi":"10.1109/VNC.2018.8628425","DOIUrl":"https://doi.org/10.1109/VNC.2018.8628425","url":null,"abstract":"State-of-the-art vehicular visible light communication (V2LC) systems utilize either a photodiode or a camera as the receiver, while both have their drawbacks. A photodiode-based receiver lacks the capability to separate signals from sources transmitting at the same time and is more vulnerable to interference. On the other hand, a camera-based receiver suffers from low system throughput, resulting from the low image frame rate of commodity cameras. In this paper, we investigate a solution which attempts to combine the best of both, and mitigate their drawbacks.We propose to use a new type of CMOS vision sensor: a dynamic vision sensor (DVS). Instead of recording still frames, a DVS only generates outputs when it senses a significant change of brightness in a pixel. The output of a DVS is a stream of events on the pixel basis with 1 μs resolution, which greatly increase the bandwidth. We investigate the key requirements of the modulation wave form when using a DVS camera-based receiver, and propose a new pulse wave form that maintains the same average luminance level while extending the operational range of the system. Preliminary experimental results show that the proposed wave form nearly triples the range to 8 m, compared to the range of 3 m when using the conventional inverse pulse position modulation wave form.","PeriodicalId":335017,"journal":{"name":"2018 IEEE Vehicular Networking Conference (VNC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122479181","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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