Pub Date : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294669
Kunxiong Ling, Nishant Shah, Jan Thiele
We introduce a novel method to generate customer vehicle usage profiles, representing driving, parking, and charging behavior. Synthesizing usage profiles is the key to support decision-making for customer-centric vehicle development. So far, current methods for vehicle development focus exclusively on driving cycles, whereas the representability of parking and charging behavior, which is essential for electromobility, remains neglected. In this paper, we perform vehicle usage profiling by (i) allocating time spans for driving and parking sections, (ii) optimally selecting driving sections from a trip library established from testing fleets, (iii) rearranging driving sections with parking sections into e.g. week profiles, and (iv) integrating the inferred charging behavior of the profiles together with simulation. Using a model of an exemplary plugin hybrid electric vehicle and given raw data from our testing fleets, we demonstrate that our method is capable of estimating the influence of driving, parking and charging behavior on vehicle loads.
{"title":"Customer-Centric Vehicle Usage Profiling Considering Driving, Parking, and Charging Behavior","authors":"Kunxiong Ling, Nishant Shah, Jan Thiele","doi":"10.1109/ITSC45102.2020.9294669","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294669","url":null,"abstract":"We introduce a novel method to generate customer vehicle usage profiles, representing driving, parking, and charging behavior. Synthesizing usage profiles is the key to support decision-making for customer-centric vehicle development. So far, current methods for vehicle development focus exclusively on driving cycles, whereas the representability of parking and charging behavior, which is essential for electromobility, remains neglected. In this paper, we perform vehicle usage profiling by (i) allocating time spans for driving and parking sections, (ii) optimally selecting driving sections from a trip library established from testing fleets, (iii) rearranging driving sections with parking sections into e.g. week profiles, and (iv) integrating the inferred charging behavior of the profiles together with simulation. Using a model of an exemplary plugin hybrid electric vehicle and given raw data from our testing fleets, we demonstrate that our method is capable of estimating the influence of driving, parking and charging behavior on vehicle loads.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123929404","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294223
M. Mues, Sebastian Gerard, Falk Howar
Machine learning components are becoming popular for the automotive industry. More and more data sets become available for training machine learning components. All of them provide ground truth labels for images. The labeling process is expensive and potentially error-prone. At the same time, label correctness defines the business value of a data set. In this paper, we use N-Version approach to assess the label quality in a data set. The approach combines N state-of-the-art neural networks and aggregates their results in a single verdict using majority voting. We analyze this majority vote against the ground truth label and compute the percentage of disagreeing pixels along with other metrics, enabling the automated and detailed analysis of label quality on data sets. We evaluate our methodology by classifying the BDD100K drivable area data set. The evaluation shows that the approach identifies misclassified scenes or inconsistencies between label semantics for similar scenes.
{"title":"Identification of Spurious Labels in Machine Learning Data Sets using N-Version Validation","authors":"M. Mues, Sebastian Gerard, Falk Howar","doi":"10.1109/ITSC45102.2020.9294223","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294223","url":null,"abstract":"Machine learning components are becoming popular for the automotive industry. More and more data sets become available for training machine learning components. All of them provide ground truth labels for images. The labeling process is expensive and potentially error-prone. At the same time, label correctness defines the business value of a data set. In this paper, we use N-Version approach to assess the label quality in a data set. The approach combines N state-of-the-art neural networks and aggregates their results in a single verdict using majority voting. We analyze this majority vote against the ground truth label and compute the percentage of disagreeing pixels along with other metrics, enabling the automated and detailed analysis of label quality on data sets. We evaluate our methodology by classifying the BDD100K drivable area data set. The evaluation shows that the approach identifies misclassified scenes or inconsistencies between label semantics for similar scenes.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125876017","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294621
Albrecht Michler, Paul Schwarzbach, Hagen Ußler, Paula Tauscher, O. Michler
Highly accurate localization technologies are a key enabler of future intelligent transport system applications including automated and cooperative driving as well as location based services. One major challenge is positioning in urban areas, where high buildings with reflecting surfaces lead to signal blockage, multipath effects and Non-Line-of-Sight (NLOS) reception. As a countermeasure, deterministic NLOS modelling approaches using 3D map aided GNSS (3DMA-GNSS) have been developed and show promising results in mitigating those effects. However, most prior studies focused on advancing the method itself, while the implementational aspects of such a system regarding real-world applications remain unsolved. Major challenges lie within the generation and dissemination of suitable 3D maps as well as the computational cost of the classification of measurements into LOS resp. NLOS behaviour. The aim of this paper is to connect the parts of highly precise GNSS based urban localization, digital maps, Vehicle-to-Everything (V2X) based cooperative positioning and data dissemination. A map dissemination scheme for precomputed sky occupancy masks using V2X communication technology is evolved and discussed. Furthermore, the data rate requirements are compared with the capability of the existing IEEE802.11p (ITS-G5) V2X standard in terms of data rate and the range of the communication link.
{"title":"A V2X Based Data Dissemination Scheme for 3D Map Aided GNSS Positioning in Urban Environments","authors":"Albrecht Michler, Paul Schwarzbach, Hagen Ußler, Paula Tauscher, O. Michler","doi":"10.1109/ITSC45102.2020.9294621","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294621","url":null,"abstract":"Highly accurate localization technologies are a key enabler of future intelligent transport system applications including automated and cooperative driving as well as location based services. One major challenge is positioning in urban areas, where high buildings with reflecting surfaces lead to signal blockage, multipath effects and Non-Line-of-Sight (NLOS) reception. As a countermeasure, deterministic NLOS modelling approaches using 3D map aided GNSS (3DMA-GNSS) have been developed and show promising results in mitigating those effects. However, most prior studies focused on advancing the method itself, while the implementational aspects of such a system regarding real-world applications remain unsolved. Major challenges lie within the generation and dissemination of suitable 3D maps as well as the computational cost of the classification of measurements into LOS resp. NLOS behaviour. The aim of this paper is to connect the parts of highly precise GNSS based urban localization, digital maps, Vehicle-to-Everything (V2X) based cooperative positioning and data dissemination. A map dissemination scheme for precomputed sky occupancy masks using V2X communication technology is evolved and discussed. Furthermore, the data rate requirements are compared with the capability of the existing IEEE802.11p (ITS-G5) V2X standard in terms of data rate and the range of the communication link.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125941130","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294446
Toussaint Hoché, D. Barth, T. Mautor, W. Burghout
The electric vehicle market is booming. However, these vehicles need to be refilled more often and do so much more slowly than internal combustion engine (ICE) vehicles. The arrival of autonomous vehicles will enable both fully centralised systems for taxi fleet management and a 24/7 use of each taxi. Finally, the ride-sharing market is also booming. Thus, efficient future taxi fleets will have to provide efficient, integrated solutions for ride-sharing, charging and automation. In this paper, the problem focused on is a variation of the Dial-A-Ride-Problem (DARP) where charging as well as the availability of charging stations are taken into account: Given a fleet of autonomous and electric taxis, a charging infrastructure, and a set of trip requests, the objective is to assign trips and charges to taxis such that the total profit of the fleet is maximised. Our contribution consists in the development of a greedy method, and of a simulated annealing. Our methods are evaluated on large instances (10000 requests) based on taxi trip datasets in Porto. Our conclusions show that while high-capacity batteries are largely unneeded in normal circumstances, they are capital in case of disruption, and useful when the charging infrastructure is shared, with queueing time to access to a charger. Parking searches also represent a significant energy expense for autonomous taxis.
电动汽车市场正在蓬勃发展。然而，与内燃机(ICE)汽车相比，这些汽车需要更频繁地加油，而且速度要慢得多。自动驾驶汽车的到来将使出租车车队管理的完全集中系统和每辆出租车的24/7使用成为可能。最后，拼车市场也在蓬勃发展。因此，高效的未来出租车车队必须为拼车、收费和自动化提供高效、综合的解决方案。在本文中，重点关注的问题是dial - a - ride problem (DARP)的一个变体，其中考虑了充电和充电站的可用性:给定一组自动驾驶出租车和电动出租车，充电基础设施和一组行程请求，目标是为出租车分配行程和收费，从而使车队的总利润最大化。我们的贡献在于开发了贪心法和模拟退火法。我们的方法在基于波尔图出租车出行数据集的大型实例(10000个请求)上进行了评估。我们的结论表明，虽然大容量电池在正常情况下基本上是不需要的，但在中断的情况下，它们是资本，当充电基础设施是共享的，需要排队才能使用充电器时，它们是有用的。停车搜索对自动驾驶出租车来说也意味着巨大的能源消耗。
{"title":"Charging management of shared taxis: Neighbourhood search for the E-ADARP","authors":"Toussaint Hoché, D. Barth, T. Mautor, W. Burghout","doi":"10.1109/ITSC45102.2020.9294446","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294446","url":null,"abstract":"The electric vehicle market is booming. However, these vehicles need to be refilled more often and do so much more slowly than internal combustion engine (ICE) vehicles. The arrival of autonomous vehicles will enable both fully centralised systems for taxi fleet management and a 24/7 use of each taxi. Finally, the ride-sharing market is also booming. Thus, efficient future taxi fleets will have to provide efficient, integrated solutions for ride-sharing, charging and automation. In this paper, the problem focused on is a variation of the Dial-A-Ride-Problem (DARP) where charging as well as the availability of charging stations are taken into account: Given a fleet of autonomous and electric taxis, a charging infrastructure, and a set of trip requests, the objective is to assign trips and charges to taxis such that the total profit of the fleet is maximised. Our contribution consists in the development of a greedy method, and of a simulated annealing. Our methods are evaluated on large instances (10000 requests) based on taxi trip datasets in Porto. Our conclusions show that while high-capacity batteries are largely unneeded in normal circumstances, they are capital in case of disruption, and useful when the charging infrastructure is shared, with queueing time to access to a charger. Parking searches also represent a significant energy expense for autonomous taxis.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124672837","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294458
Sercan Akti, Ismet Göksad Erdagi, Mehmet Ali Silgu, H. B. Çelikoglu
With the advances in communication technologies, a fully connected and automated traffic environment has become possible to be implemented. However, it is a fact that a road network that is ready to be operated in such a fashion needs several systems to handle different maneuvers in traffic flow. Therefore, in the study we summarize in the present paper, we propose an integrated system that is composed of three elements, which organizes longitudinal and lateral movements with the intention of mitigating shockwaves due to merging maneuvers. A car-following based (Cooperative Adaptive Cruise Control) CACC model is used for longitudinal motion modeling, while vehicles approaching to the merging zone are controlled using a speed harmonization algorithm and, in cases of zone conflicts, a merging strategy that is based on the game theory is applied for flow management. Simulation results from a single lane road segment show that the proposed approach outperforms the performance of the system in which cooperative merging is not adopted.
{"title":"A Game-Theoretical Approach for Lane-Changing Maneuvers on Freeway Merging Segments","authors":"Sercan Akti, Ismet Göksad Erdagi, Mehmet Ali Silgu, H. B. Çelikoglu","doi":"10.1109/ITSC45102.2020.9294458","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294458","url":null,"abstract":"With the advances in communication technologies, a fully connected and automated traffic environment has become possible to be implemented. However, it is a fact that a road network that is ready to be operated in such a fashion needs several systems to handle different maneuvers in traffic flow. Therefore, in the study we summarize in the present paper, we propose an integrated system that is composed of three elements, which organizes longitudinal and lateral movements with the intention of mitigating shockwaves due to merging maneuvers. A car-following based (Cooperative Adaptive Cruise Control) CACC model is used for longitudinal motion modeling, while vehicles approaching to the merging zone are controlled using a speed harmonization algorithm and, in cases of zone conflicts, a merging strategy that is based on the game theory is applied for flow management. Simulation results from a single lane road segment show that the proposed approach outperforms the performance of the system in which cooperative merging is not adopted.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129870234","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294596
G. Aifadopoulou, G. Tsaples, Josep Maria Salanova Grau, Panagiotis Tzenos
To accommodate the increasing intensity of port operations, the introduction of automated straddle carriers (ASCs) is considered an innovative direction in the management of ports. However, ASCs rely on satellite navigation systems for positioning, which is accompanied by limitations. The purpose of this paper is to present an algorithmic approach to fleet management, routing and collision avoidance and use the algorithm to study the effects of GNSS limitations to its results. The designed algorithm provides information on assignment, routing and speed profiles for the Automated Straddle Carriers with the purpose of avoiding collisions. Five different scenarios were simulated with experimental data. The results indicated that when noise is introduced to more than one places, then more time is necessary to complete the tasks. Finally, differences in the results may appear insignificant, however, in an automated environment they could increase the volatility and create cascading effects that increase the risk.
{"title":"Autonomous port vehicles fleet management: analyzing the effect of GNSS limitations","authors":"G. Aifadopoulou, G. Tsaples, Josep Maria Salanova Grau, Panagiotis Tzenos","doi":"10.1109/ITSC45102.2020.9294596","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294596","url":null,"abstract":"To accommodate the increasing intensity of port operations, the introduction of automated straddle carriers (ASCs) is considered an innovative direction in the management of ports. However, ASCs rely on satellite navigation systems for positioning, which is accompanied by limitations. The purpose of this paper is to present an algorithmic approach to fleet management, routing and collision avoidance and use the algorithm to study the effects of GNSS limitations to its results. The designed algorithm provides information on assignment, routing and speed profiles for the Automated Straddle Carriers with the purpose of avoiding collisions. Five different scenarios were simulated with experimental data. The results indicated that when noise is introduced to more than one places, then more time is necessary to complete the tasks. Finally, differences in the results may appear insignificant, however, in an automated environment they could increase the volatility and create cascading effects that increase the risk.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128343197","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294250
Niklas Stannartz, Mario Theers, Adalberto Llarena, Marc Sons, Markus Kuhn, T. Bertram
High-precision maps provide essential and detailed information for automated vehicles, especially about the individual lanes of a road. Here, the memory efficiency of curve representations is a critical aspect to limit the amount of data to store and process. There are many specific approaches in literature that generate spline-based maps from sensor data, however only a few evaluate the memory requirement. Furthermore, different algorithms are developed for each specific spline type. In this contribution, a generic optimization-based framework for the generation of spline curves with arbitrary degree and continuity is proposed by adapting an algorithm from the field of computer aided design. Here, the continuity of the spline is explicitly optimized which enhances the approximation capabilities. The method is evaluated for two datasets with a total length of 34.22 km. Comparative approaches are outperformed in terms of memory efficiency and robustness while the proposed method yields an average memory requirement of less than 3 byte/m.
{"title":"Comparison of Curve Representations for Memory-Efficient and High-Precision Map Generation","authors":"Niklas Stannartz, Mario Theers, Adalberto Llarena, Marc Sons, Markus Kuhn, T. Bertram","doi":"10.1109/ITSC45102.2020.9294250","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294250","url":null,"abstract":"High-precision maps provide essential and detailed information for automated vehicles, especially about the individual lanes of a road. Here, the memory efficiency of curve representations is a critical aspect to limit the amount of data to store and process. There are many specific approaches in literature that generate spline-based maps from sensor data, however only a few evaluate the memory requirement. Furthermore, different algorithms are developed for each specific spline type. In this contribution, a generic optimization-based framework for the generation of spline curves with arbitrary degree and continuity is proposed by adapting an algorithm from the field of computer aided design. Here, the continuity of the spline is explicitly optimized which enhances the approximation capabilities. The method is evaluated for two datasets with a total length of 34.22 km. Comparative approaches are outperformed in terms of memory efficiency and robustness while the proposed method yields an average memory requirement of less than 3 byte/m.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128363466","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294291
Lingguang Wang, Zhenkang Wu, Jiakang Li, C. Stiller
A reliable autonomous driving system should be capable of performing safe stop when proceeding the normal driving becomes impossible. It is essential for safe stop planning to be able to provide a trajectory that leads the vehicle to a specific stopped goal in real-time. With this as a main challenge and distinction, the safe stop planning should still be able to avoid collision with static and dynamic obstacles like normal motion planning. To guarantee a meaningful solution and be real-time capable, we propose to utilize path-velocity decomposition, which provides a non-globally optimal solution but reduces the computational burden. Firstly, by sampling piecewise quintic polynomials that connect a series of sampled points from the current location to the goal, a set of path candidates in Frenét frame are generated. The path that meets kinematic constraints, maximizes comfort, and avoids static obstacles is selected. Afterward, we generate the length-time (ST) graph by projecting the dynamic obstacles on our driving corridor along the chosen path in space and time domain. The velocity planning is performed on the ST-graph with an extended multidimensional Hybrid A-Star $(mathrm{A}^{*})$ Algorithm. Finally, our approach is evaluated in several simulation scenarios and also in CoInCar-Simulation framework, which shows a real-time capability and promising driving behaviors.
一个可靠的自动驾驶系统应该能够在无法进行正常驾驶的情况下进行安全停车。对于安全停车计划来说，能够提供一个实时的轨迹来引导车辆到达特定的停车目标是至关重要的。以此为主要挑战和区别，安全停车规划仍应像正常运动规划一样，能够避免与静态和动态障碍物的碰撞。为了保证有意义的解和实时性，我们提出利用路径速度分解，它提供了一个非全局最优解，但减少了计算负担。首先，通过将当前位置的一系列采样点与目标点连接起来的分段五次多项式进行采样，生成一组frensamt帧内的候选路径;选择满足运动学约束、舒适性最大化、避开静态障碍物的路径。然后，我们通过在空间和时间域上沿选定路径投影驾驶走廊上的动态障碍物来生成长时间(ST)图。采用扩展的多维混合A- star $( mathm {A}^{*})$算法对st图进行速度规划。最后，我们的方法在几个仿真场景和corecar - simulation框架中进行了评估，显示出实时能力和有前景的驾驶行为。
{"title":"Real-Time Safe Stop Trajectory Planning via Multidimensional Hybrid A*-Algorithm","authors":"Lingguang Wang, Zhenkang Wu, Jiakang Li, C. Stiller","doi":"10.1109/ITSC45102.2020.9294291","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294291","url":null,"abstract":"A reliable autonomous driving system should be capable of performing safe stop when proceeding the normal driving becomes impossible. It is essential for safe stop planning to be able to provide a trajectory that leads the vehicle to a specific stopped goal in real-time. With this as a main challenge and distinction, the safe stop planning should still be able to avoid collision with static and dynamic obstacles like normal motion planning. To guarantee a meaningful solution and be real-time capable, we propose to utilize path-velocity decomposition, which provides a non-globally optimal solution but reduces the computational burden. Firstly, by sampling piecewise quintic polynomials that connect a series of sampled points from the current location to the goal, a set of path candidates in Frenét frame are generated. The path that meets kinematic constraints, maximizes comfort, and avoids static obstacles is selected. Afterward, we generate the length-time (ST) graph by projecting the dynamic obstacles on our driving corridor along the chosen path in space and time domain. The velocity planning is performed on the ST-graph with an extended multidimensional Hybrid A-Star $(mathrm{A}^{*})$ Algorithm. Finally, our approach is evaluated in several simulation scenarios and also in CoInCar-Simulation framework, which shows a real-time capability and promising driving behaviors.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128451998","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294183
Christoph Maget, Sebastian Gutmann, K. Bogenberger
In this paper we present a decision support system for essential planning processes of innovative transportation systems. We enhance an existing transportation model to analyze how passenger drones and autonomous cars can interact optimally to enable mobility and reduce congestion. The resulting transportation model covers 70,550 square kilometers as well as 12.6 million citizens and extends passenger drone services beyond urban use cases. Building upon this customization, we first identify a set of potential intermodal vertihub locations for vertical take-off and landing (VTOL). Second, a mathematical model is developed to decide at which locations vertihubs should be built to enable access to the new mode for a maximum number of citizens. Third, we connect the vertihubs through a fine-meshed flight route network using Delaunay triangulation. We finally apply the model to perform specific analyses concerning the interactions of these future modes of transport: With optimized vertihub locations and 30 min autonomous feeder service, more than 70% of the population could have access to passenger drones. Moreover, we perform sensitivity analyses for feeder time parameters and a possible substitution of public transport (PT) by drones. Finally, we identify a master vertihub location with a minimal flight distance to all other vertihubs.
{"title":"Model-based Evaluations Combining Autonomous Cars and a Large-scale Passenger Drone Service: The Bavarian Case Study","authors":"Christoph Maget, Sebastian Gutmann, K. Bogenberger","doi":"10.1109/ITSC45102.2020.9294183","DOIUrl":"https://doi.org/10.1109/ITSC45102.2020.9294183","url":null,"abstract":"In this paper we present a decision support system for essential planning processes of innovative transportation systems. We enhance an existing transportation model to analyze how passenger drones and autonomous cars can interact optimally to enable mobility and reduce congestion. The resulting transportation model covers 70,550 square kilometers as well as 12.6 million citizens and extends passenger drone services beyond urban use cases. Building upon this customization, we first identify a set of potential intermodal vertihub locations for vertical take-off and landing (VTOL). Second, a mathematical model is developed to decide at which locations vertihubs should be built to enable access to the new mode for a maximum number of citizens. Third, we connect the vertihubs through a fine-meshed flight route network using Delaunay triangulation. We finally apply the model to perform specific analyses concerning the interactions of these future modes of transport: With optimized vertihub locations and 30 min autonomous feeder service, more than 70% of the population could have access to passenger drones. Moreover, we perform sensitivity analyses for feeder time parameters and a possible substitution of public transport (PT) by drones. Finally, we identify a master vertihub location with a minimal flight distance to all other vertihubs.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128245850","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 : 2020-09-20DOI: 10.1109/ITSC45102.2020.9294438
Martin Butz, Christian Heinzemann, M. Herrmann, Jens Oehlerking, Michael Rittel, Nadja Schalm, D. Ziegenbein
Highly automated driving systems need to master a highly complex environment and are required to show meaningful behavior in any situation occurring in mixed traffic with humans. Deriving a sufficiently complete and consistent set of system-level requirements capturing all possible traffic situations is a significant problem that has not been solved in existing literature. In this paper, we propose a new method called SOCA addressing this problem by introducing a novel abstraction of traffic situations, called zone graph, and using this abstraction in a morphological behavior analysis. The morphological behavior analysis enables us to derive a set of system-level requirements with guarantees on completeness and consistency. We illustrate our method on a slice-of-reality example from the automated driving domain.
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