Pub Date : 2018-09-01DOI: 10.1109/ICVES.2018.8519494
David Augustin, Marius Hofmann, U. Konigorski
Intelligent automated driving functions require a deep understanding about the current traffic situation and its likely evolution. For highly automated driving on highways, predicting trajectories of traffic participants is a crucial task for collision-free trajectory planning and risk-aware maneuver choice. For a prediction horizon of a few seconds the execution of those trajectories is fuzzy and highly dependent on the maneuver choice of the driver. This paper presents a new online-capable statistical approach for maneuver detection and uncertainty-aware trajectory prediction in highway scenarios based on detecting and clustering typical motion patterns in real highway footage and deriving prototypical trajectories for each cluster. The cluster prototypes are utilized for maneuver detection by evaluating their proximities to incomplete tra- jectory records while identifying for each prototype its most similar section. The remaining segment of the best fit is used as an estimate for the future motion of the traffic participant. Quantitative evaluation results demonstrate the potential of the proposed concept for maneuver detection and maneuver-based trajectory prediction.
{"title":"Motion Pattern Recognition for Maneuver Detection and Trajectory Prediction on Highways","authors":"David Augustin, Marius Hofmann, U. Konigorski","doi":"10.1109/ICVES.2018.8519494","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519494","url":null,"abstract":"Intelligent automated driving functions require a deep understanding about the current traffic situation and its likely evolution. For highly automated driving on highways, predicting trajectories of traffic participants is a crucial task for collision-free trajectory planning and risk-aware maneuver choice. For a prediction horizon of a few seconds the execution of those trajectories is fuzzy and highly dependent on the maneuver choice of the driver. This paper presents a new online-capable statistical approach for maneuver detection and uncertainty-aware trajectory prediction in highway scenarios based on detecting and clustering typical motion patterns in real highway footage and deriving prototypical trajectories for each cluster. The cluster prototypes are utilized for maneuver detection by evaluating their proximities to incomplete tra- jectory records while identifying for each prototype its most similar section. The remaining segment of the best fit is used as an estimate for the future motion of the traffic participant. Quantitative evaluation results demonstrate the potential of the proposed concept for maneuver detection and maneuver-based trajectory prediction.","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":"127013286","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.2018.8519591
Mingkang Li, Fabian Straub, M. Kunert, R. Henze, F. Küçükay
Nowadays, the automotive advanced driver assistance systems have the ability to detect surrounding objects, predict impending collisions and initiate automatic emergency braking. However, by a late detection of objects at higher speeds, the collision is hardly avoidable by braking only, hence an evasive steering maneuver shall be performed simultaneously to cure this deficiency. This paper presents a novel approach that utilizes a dedicated cost function to make the appropriate maneuver decision in an imminent collision avoidance situation. By taking into account the host vehicle and the collision target motions as well as other moving or stationary objects in the near vicinity, diverse aspects and criteria are analyzed and discussed to evaluate possible maneuver candidates. After that, the cost functions of different maneuvers are calculated by summarizing the results of all the evaluation criteria and aspects. In both simulated and measured critical situations, the cost function is validated and the maneuver with the best (i.e., lowest) cost is selected to avoid the impending collision and the endangerment of any other road users aside.
{"title":"A Novel Cost Function for Decision-Making Strategies in Automotive Collision Avoidance Systems","authors":"Mingkang Li, Fabian Straub, M. Kunert, R. Henze, F. Küçükay","doi":"10.1109/ICVES.2018.8519591","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519591","url":null,"abstract":"Nowadays, the automotive advanced driver assistance systems have the ability to detect surrounding objects, predict impending collisions and initiate automatic emergency braking. However, by a late detection of objects at higher speeds, the collision is hardly avoidable by braking only, hence an evasive steering maneuver shall be performed simultaneously to cure this deficiency. This paper presents a novel approach that utilizes a dedicated cost function to make the appropriate maneuver decision in an imminent collision avoidance situation. By taking into account the host vehicle and the collision target motions as well as other moving or stationary objects in the near vicinity, diverse aspects and criteria are analyzed and discussed to evaluate possible maneuver candidates. After that, the cost functions of different maneuvers are calculated by summarizing the results of all the evaluation criteria and aspects. In both simulated and measured critical situations, the cost function is validated and the maneuver with the best (i.e., lowest) cost is selected to avoid the impending collision and the endangerment of any other road users aside.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"17 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":"127826318","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.2018.8519490
Minchul Lee, Wonteak Lim, Seokwon Kim, M. Sunwoo
Recently, the intelligent Driver Assistant System (DAS) and an autonomous driving system have been widely studied. For those systems, a local route that represents the road shape is essential information for controlling a vehicle's behavior. When the local route is recognized by the perception sensors attached to the vehicle, the discontinuous information caused by the noise and detection failure worsens the driving comfort and stability. Since filtering methods in previous studies have caused time delays, the reaction of the vehicle control may be late when the curvature of the road changes. In this paper, the local route is temporary modeled into a mathematical form with several nodes to smooth the discontinuous information without delay problems. The node location of the temporal roadway geometry model is probabilistically updated by a Bayesian filtering scheme using the recognized local route. The proposed method was evaluated with a Mobileye camera and a real road. This method not only provided road shape information without a time delay but also interpolated the road shape information during the misdetection of sensor information and updating period.
{"title":"Temporal local route modeling using the recognized lane for autonomous driving comfort","authors":"Minchul Lee, Wonteak Lim, Seokwon Kim, M. Sunwoo","doi":"10.1109/ICVES.2018.8519490","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519490","url":null,"abstract":"Recently, the intelligent Driver Assistant System (DAS) and an autonomous driving system have been widely studied. For those systems, a local route that represents the road shape is essential information for controlling a vehicle's behavior. When the local route is recognized by the perception sensors attached to the vehicle, the discontinuous information caused by the noise and detection failure worsens the driving comfort and stability. Since filtering methods in previous studies have caused time delays, the reaction of the vehicle control may be late when the curvature of the road changes. In this paper, the local route is temporary modeled into a mathematical form with several nodes to smooth the discontinuous information without delay problems. The node location of the temporal roadway geometry model is probabilistically updated by a Bayesian filtering scheme using the recognized local route. The proposed method was evaluated with a Mobileye camera and a real road. This method not only provided road shape information without a time delay but also interpolated the road shape information during the misdetection of sensor information and updating period.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"151 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":"131616113","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.2018.8519489
Bahae Abidi, Francisco Miguel Moreno, M. Haziti, A. Hussein, Abdulla Al-Kaff, David Martín Gómez
Technology advances in the field of intelligent transportation systems are rapidly increasing due to their crucial importance in saving millions of lives on the roads. One of the main elements to ensure that all road entities are connected is the design of stable and secure communication schemes, which is able to operate under different conditions and constraints. Accordingly, in this paper, a hybrid communication approach is proposed for Vehicle-to-Everything (V2X) communication schemes based on the use of WiFi and 4G connections. The objective is to ensure that the intelligent vehicles are able to maintain the vehicular communication using both connection methods in real-time, based on preadjusted configurations. The configurations include the networks availability, signal strength, and network security, among others. In order to validate the proposed work, several experiments were carriedout using automated vehicle in off-road environment scenario. The obtained results shows the performance of the proposed work to switch from a network to another aiming for the optimization of the shared data speed and steadiness.
{"title":"Hybrid V2X Communication Approach using WiFi and 4G Connections","authors":"Bahae Abidi, Francisco Miguel Moreno, M. Haziti, A. Hussein, Abdulla Al-Kaff, David Martín Gómez","doi":"10.1109/ICVES.2018.8519489","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519489","url":null,"abstract":"Technology advances in the field of intelligent transportation systems are rapidly increasing due to their crucial importance in saving millions of lives on the roads. One of the main elements to ensure that all road entities are connected is the design of stable and secure communication schemes, which is able to operate under different conditions and constraints. Accordingly, in this paper, a hybrid communication approach is proposed for Vehicle-to-Everything (V2X) communication schemes based on the use of WiFi and 4G connections. The objective is to ensure that the intelligent vehicles are able to maintain the vehicular communication using both connection methods in real-time, based on preadjusted configurations. The configurations include the networks availability, signal strength, and network security, among others. In order to validate the proposed work, several experiments were carriedout using automated vehicle in off-road environment scenario. The obtained results shows the performance of the proposed work to switch from a network to another aiming for the optimization of the shared data speed and steadiness.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"65 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":"115356007","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.2018.8519505
Efi Papatheocharous, E. Frécon, C. Kaiser, A. Festl, A. Stocker
Advances in the field of engineering have resulted in vehicles becoming a digitised source of data from which scenarios of Quantified Vehicles emerge. Even though the benefits and range of emerging services are ample, several challenges cap the extent of opportunities, such as determining the business benefits, as well as constructing and operating an independent, scalable, and flexible platform ensuring e.g., privacy, accountability. In our work in progress paper, we propose a conceptual architecture of a generic IoT platform for enabling such data-driven services for the vehicle domain, while considering important characteristics, such as data security and privacy, improved service operations, safety and value creation for end-users. We then describe how this platform can be demonstrated, including the vehicle gateway device (Vehicle Data Logger) capturing the vehicle data, to finally enable a set of useful and usable data-driven services for vehicle drivers and other stakeholders.
{"title":"Towards a Generic IoT Platform for Data-driven Vehicle Services","authors":"Efi Papatheocharous, E. Frécon, C. Kaiser, A. Festl, A. Stocker","doi":"10.1109/ICVES.2018.8519505","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519505","url":null,"abstract":"Advances in the field of engineering have resulted in vehicles becoming a digitised source of data from which scenarios of Quantified Vehicles emerge. Even though the benefits and range of emerging services are ample, several challenges cap the extent of opportunities, such as determining the business benefits, as well as constructing and operating an independent, scalable, and flexible platform ensuring e.g., privacy, accountability. In our work in progress paper, we propose a conceptual architecture of a generic IoT platform for enabling such data-driven services for the vehicle domain, while considering important characteristics, such as data security and privacy, improved service operations, safety and value creation for end-users. We then describe how this platform can be demonstrated, including the vehicle gateway device (Vehicle Data Logger) capturing the vehicle data, to finally enable a set of useful and usable data-driven services for vehicle drivers and other stakeholders.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"71 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":"127632075","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.2018.8519525
Wael Ben Messaoud, M. Basset, Jean-Philippe Lauffenburger, R. Orjuela
Obstacle avoidance and overtaking are important manoeuvres for autonomous driving. The collision avoidance with a vehicle, a pedestrian or any obstacle and the generation of a feasible continuous curvature trajectory represent the major problems faced by researchers to provide a safe path planning solution. This paper presents an algorithm able to avoid vehicles or obstacles by proposing a smooth local modified trajectory of a global path. The proposed method is based on the combination of a parameterized sigmoid function and a rolling horizon. The major advantage of this method is the reactivity to the obstacle motion and the generation of a smooth trajectory in a low execution time. The lateral and the longitudinal safety distances are easily parameterized when generating the avoidance trajectory. Simulation results show that the algorithm performs collision avoidance manoeuvres for static and dynamic obstacles in an effective way. The method is validated by applying the avoidance approach on real measured trajectory.
{"title":"Smooth Obstacle Avoidance Path Planning for Autonomous Vehicles","authors":"Wael Ben Messaoud, M. Basset, Jean-Philippe Lauffenburger, R. Orjuela","doi":"10.1109/ICVES.2018.8519525","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519525","url":null,"abstract":"Obstacle avoidance and overtaking are important manoeuvres for autonomous driving. The collision avoidance with a vehicle, a pedestrian or any obstacle and the generation of a feasible continuous curvature trajectory represent the major problems faced by researchers to provide a safe path planning solution. This paper presents an algorithm able to avoid vehicles or obstacles by proposing a smooth local modified trajectory of a global path. The proposed method is based on the combination of a parameterized sigmoid function and a rolling horizon. The major advantage of this method is the reactivity to the obstacle motion and the generation of a smooth trajectory in a low execution time. The lateral and the longitudinal safety distances are easily parameterized when generating the avoidance trajectory. Simulation results show that the algorithm performs collision avoidance manoeuvres for static and dynamic obstacles in an effective way. The method is validated by applying the avoidance approach on real measured trajectory.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"6 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":"121994636","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.2018.8519599
Andreas Lauber, Houssem Guissouma, E. Sax
The fast development of embedded automotive systems in form of connected Electronic Control Units (ECUs) has led to complex development processes. Especially for safetycritical functions, the testing activities are essential to check if the designed system complies with the requirements. Nowadays, the continuous development of mobile electronic devices through software updates is performed almost on a daily basis. This trend is now starting to be observed in cyber-physical systems with higher safety priorities. In the automotive field, the rising software portion in the vehicles and the shortening technology life-cycles are accentuating the need for Software Over The Air (SOTA) updates. Despite the opportunities offered by SOTA updates, the current test processes and methods must be adapted to manage the resulting complexity throughout the life-cycle of the vehicles. Especially the typical variants abundance in automotive product lines is considered as an important challenge, which cannot be solved only by ”classical” testing methods such as Hardware-In-the-Loop. In this paper, we present a testing method for variantrich systems, which can be applied for automotive software updates. It uses virtual platforms for automated delta testing to handle the abundance of system configurations. Virtual testing is introduced as a powerful tool to reduce the amount of real tests and allow efficient variants verification. As a proof of concept, an Adaptive Cruise Control (ACC) composed of two ECUs has been implemented both in real hardware and using a virtual platform. With this approach, virtual delta tests, i. e. specific test-benches targeting the differences to a basic variant, can be rapidly executed for various system configurations. To prove the feasibility of the presented test method in more complex systems, a scalability study has been conducted.
{"title":"Virtual Test Method for Complex and Variant-Rich Automotive Systems","authors":"Andreas Lauber, Houssem Guissouma, E. Sax","doi":"10.1109/ICVES.2018.8519599","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519599","url":null,"abstract":"The fast development of embedded automotive systems in form of connected Electronic Control Units (ECUs) has led to complex development processes. Especially for safetycritical functions, the testing activities are essential to check if the designed system complies with the requirements. Nowadays, the continuous development of mobile electronic devices through software updates is performed almost on a daily basis. This trend is now starting to be observed in cyber-physical systems with higher safety priorities. In the automotive field, the rising software portion in the vehicles and the shortening technology life-cycles are accentuating the need for Software Over The Air (SOTA) updates. Despite the opportunities offered by SOTA updates, the current test processes and methods must be adapted to manage the resulting complexity throughout the life-cycle of the vehicles. Especially the typical variants abundance in automotive product lines is considered as an important challenge, which cannot be solved only by ”classical” testing methods such as Hardware-In-the-Loop. In this paper, we present a testing method for variantrich systems, which can be applied for automotive software updates. It uses virtual platforms for automated delta testing to handle the abundance of system configurations. Virtual testing is introduced as a powerful tool to reduce the amount of real tests and allow efficient variants verification. As a proof of concept, an Adaptive Cruise Control (ACC) composed of two ECUs has been implemented both in real hardware and using a virtual platform. With this approach, virtual delta tests, i. e. specific test-benches targeting the differences to a basic variant, can be rapidly executed for various system configurations. To prove the feasibility of the presented test method in more complex systems, a scalability study has been conducted.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"76 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":"129981672","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.2018.8519507
Shota Imai, Y. Kamiya
Vital sensing using a Doppler sensor is attractive since it does not need to put electrodes or sensors on a human body. It must be suitable for the monitoring of car drivers due to its easy use. By using this sensor, we can think about an alarm system for sudden illness of car drivers preventing them from causing accidents. However, the problem is body movements of car drivers and the vibration of the car. The Doppler sensor observes the variation of the distance between the sensor and the human body because the distance variation is yielded by the respiration and the heartbeats. Thus, the body movements of the driver are destructive for the measurement as well as the car vibration. Obviously, they cause false alarms, so the measurement must be robust against the body movement.In this paper, we propose a new signal processing method suitable for vitalsensing using a Doppler sensor. It is robust against disturbances caused by the body movement or the car vibrations. However, if these disturbances are serious, the proposed method automatically recognize the situation in order to avoid the false alarm for the car drivers’ monitoring. In addition, the proposed method is applicable to multiple persons. The performance of the proposed method is investigated through computer simulations.
{"title":"A new signal processing method for vital sensing using a Doppler sensor aiming at reliable sensingunder body movement","authors":"Shota Imai, Y. Kamiya","doi":"10.1109/ICVES.2018.8519507","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519507","url":null,"abstract":"Vital sensing using a Doppler sensor is attractive since it does not need to put electrodes or sensors on a human body. It must be suitable for the monitoring of car drivers due to its easy use. By using this sensor, we can think about an alarm system for sudden illness of car drivers preventing them from causing accidents. However, the problem is body movements of car drivers and the vibration of the car. The Doppler sensor observes the variation of the distance between the sensor and the human body because the distance variation is yielded by the respiration and the heartbeats. Thus, the body movements of the driver are destructive for the measurement as well as the car vibration. Obviously, they cause false alarms, so the measurement must be robust against the body movement.In this paper, we propose a new signal processing method suitable for vitalsensing using a Doppler sensor. It is robust against disturbances caused by the body movement or the car vibrations. However, if these disturbances are serious, the proposed method automatically recognize the situation in order to avoid the false alarm for the car drivers’ monitoring. In addition, the proposed method is applicable to multiple persons. The performance of the proposed method is investigated through computer simulations.","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":"128879381","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.2018.8519504
S. K. Maurya, Ayesha Choudhary
In this paper, we propose a camera based novel, realtime framework for detection and tracking of vulnerable road users, such as pedestrians and cyclists. Our framework also gives a measure of the degree of vulnerability based on the direction of movement and distance from the vulnerable region. Pedestrians and cyclists are the most vulnerable road users and it is necessary to develop automated systems that can detect them and ensure their safety by alerting the driver. In our framework, we apply deep learning based method for 2D pose detection for detecting the pedestrians and cyclists in the view of the outside looking camera mounted on the dashboard of a vehicle. As the vehicle moves, the pedestrians and cyclists are detected and tracked across frames, their degree of vulnerability is measured and the driver is alerted in case of high vulnerability score. Experimental results show that the our framework is able to accurately detect vulnerable road users and measure their degree of vulnerability.
{"title":"Deep Learning based Vulnerable Road User Detection and Collision Avoidance","authors":"S. K. Maurya, Ayesha Choudhary","doi":"10.1109/ICVES.2018.8519504","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519504","url":null,"abstract":"In this paper, we propose a camera based novel, realtime framework for detection and tracking of vulnerable road users, such as pedestrians and cyclists. Our framework also gives a measure of the degree of vulnerability based on the direction of movement and distance from the vulnerable region. Pedestrians and cyclists are the most vulnerable road users and it is necessary to develop automated systems that can detect them and ensure their safety by alerting the driver. In our framework, we apply deep learning based method for 2D pose detection for detecting the pedestrians and cyclists in the view of the outside looking camera mounted on the dashboard of a vehicle. As the vehicle moves, the pedestrians and cyclists are detected and tracked across frames, their degree of vulnerability is measured and the driver is alerted in case of high vulnerability score. Experimental results show that the our framework is able to accurately detect vulnerable road users and measure their degree of vulnerability.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"42 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":"125086269","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.2018.8519601
Y. Liu, Juntao Gao, Minoru Ito
Back-pressure algorithm has been shown to be effective in reducing traffic congestion. However, available works on back-pressure based traffic control usually ignore the fact that vehicles need time to travel across roads, resulting in inconsistency between controllers' viewpoint of traffic congestion situation and real traffic situation and thus misleading controllers. In this paper, we propose back-pressure based adaptive traffic signal control and vehicle routing with real-time control information update such that controllers always have consistent viewpoint of traffic congestion with real traffic situation and make wise signal control and vehicle routing decisions. As verified by simulations, our algorithm significantly reduces traffic congestion. For example, it reduces average vehicle travelling time by percentage ranging from 71% to 87% under high vehicle arrival rates when compared to other three algorithms.
{"title":"Back-Pressure Based Adaptive Traffic Signal Control and Vehicle Routing with Real-Time Control Information Update","authors":"Y. Liu, Juntao Gao, Minoru Ito","doi":"10.1109/ICVES.2018.8519601","DOIUrl":"https://doi.org/10.1109/ICVES.2018.8519601","url":null,"abstract":"Back-pressure algorithm has been shown to be effective in reducing traffic congestion. However, available works on back-pressure based traffic control usually ignore the fact that vehicles need time to travel across roads, resulting in inconsistency between controllers' viewpoint of traffic congestion situation and real traffic situation and thus misleading controllers. In this paper, we propose back-pressure based adaptive traffic signal control and vehicle routing with real-time control information update such that controllers always have consistent viewpoint of traffic congestion with real traffic situation and make wise signal control and vehicle routing decisions. As verified by simulations, our algorithm significantly reduces traffic congestion. For example, it reduces average vehicle travelling time by percentage ranging from 71% to 87% under high vehicle arrival rates when compared to other three algorithms.","PeriodicalId":203807,"journal":{"name":"2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"29 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":"121479334","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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