Communication and Positioning Uncertainties in Cooperative Intelligent Transportation Systems
Doctoral thesis, 2019
The current road transport system has problems with both safety and efficiency. Future intelligent transportation systems (ITS) are envisioned to alleviate these problems. In particular, cooperative ITS, where vehicles are connected to each other and the cloud, will allow vehicles to collaborate and share both sensor and control information. This will significantly expand the possibilities of optimizing traffic flow and increasing safety. However, as both communication and sensing are unreliable, a key challenge in cooperative ITS is how to accommodate for communication and sensing impairments. This requires an understanding of what the limitations of communication and sensing systems are, and how their uncertainties affect the control and coordination task. The contribution of this thesis lies on the intersection of the fields of communication, sensing, and control, and can be summarized as follows.
First of all, through the use of stochastic geometry, we analyze the impact of interference in vehicular networks, and propose a general procedure to analytically determine key performance metrics such as packet reception probabilities and throughput. Along with this procedure, we provide a model repository that can be used to adapt to both rural and urban propagation characteristics, and different medium access control protocols. The procedure can be used to gain fundamental insights about the performance of vehicular communication systems in a variety of scenarios of practical relevance.
Secondly, when it comes to sensing uncertainties, we use Fisher information theory to provide bounds on the achievable performance of cooperative positioning solutions. We thereby characterize how the composition of the vehicle fleet, and the penetration rate of vehicles with extensive sensing capabilities affects positioning and mapping performance. While the analysis is generally applicable, we present simulation results from a multi-lane freeway scenario, which indicate that introducing a small fraction of cooperating vehicles with high-end sensors significantly improves the positioning quality of the entire fleet, but may not be enough to meet the stringent demands posed by safety-critical applications.
Finally, we study how communication and sensing uncertainties impact cooperative intersection coordination. We show that the requirements on control, communication and sensing are stringent if they are treated separately and that they could be relaxed if the individual systems are made aware of each other. This awareness is explored in two ways: we provide a communication system analysis for a centralized intersection coordination scheme using stochastic geometry, which can be used to provide guidelines on how to design the communication system to guarantee a control-dependent communication quality. We also propose a collision aware resource allocation strategy, which proactively reduces channel congestion by only assigning communication resources to vehicles that are in critical configurations, i.e., when there is a risk for future collisions.
This thesis, through the use of several mathematical tools, thus sheds new insights into the communication, sensing and control performance of cooperative ITS.
First of all, through the use of stochastic geometry, we analyze the impact of interference in vehicular networks, and propose a general procedure to analytically determine key performance metrics such as packet reception probabilities and throughput. Along with this procedure, we provide a model repository that can be used to adapt to both rural and urban propagation characteristics, and different medium access control protocols. The procedure can be used to gain fundamental insights about the performance of vehicular communication systems in a variety of scenarios of practical relevance.
Secondly, when it comes to sensing uncertainties, we use Fisher information theory to provide bounds on the achievable performance of cooperative positioning solutions. We thereby characterize how the composition of the vehicle fleet, and the penetration rate of vehicles with extensive sensing capabilities affects positioning and mapping performance. While the analysis is generally applicable, we present simulation results from a multi-lane freeway scenario, which indicate that introducing a small fraction of cooperating vehicles with high-end sensors significantly improves the positioning quality of the entire fleet, but may not be enough to meet the stringent demands posed by safety-critical applications.
Finally, we study how communication and sensing uncertainties impact cooperative intersection coordination. We show that the requirements on control, communication and sensing are stringent if they are treated separately and that they could be relaxed if the individual systems are made aware of each other. This awareness is explored in two ways: we provide a communication system analysis for a centralized intersection coordination scheme using stochastic geometry, which can be used to provide guidelines on how to design the communication system to guarantee a control-dependent communication quality. We also propose a collision aware resource allocation strategy, which proactively reduces channel congestion by only assigning communication resources to vehicles that are in critical configurations, i.e., when there is a risk for future collisions.
This thesis, through the use of several mathematical tools, thus sheds new insights into the communication, sensing and control performance of cooperative ITS.
cooperative positioning
resource allocation
cooperative intelligent transportation systems
packet reliability
vehicular communication
Room EC, 5th floor, Hörsalsvägen 11
Opponent: Dr. Stephan Sand, German Aerospace Center, Oberpfaffenhofen, Germany
Author
Erik M Steinmetz
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
WiP abstract: Reception probability model for vehicular ad-hoc networks in the vicinity of intersections
2014 ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2014,;(2014)p. 223-
Paper in proceeding
Communication analysis for centralized intersection crossing coordination
Proc. 11th International Symposium on Wireless Communications Systems,;(2014)p. 813-818
Paper in proceeding
A Stochastic Geometry Model for Vehicular Communication near Intersections
IEEE Globecom Workshops,;(2015)
Paper in proceeding
E. Steinmetz, M. Wildemeersch, T. Q. S. Quek, and H.Wymeersch, “Packet Reception Probabilities in Vehicular Communications Close to Intersections,” submitted to IEEE Transactions on Intelligent Transportation Systems.
Coordination of Cooperative Autonomous Vehicles: Toward safer and more efficient road transportation
IEEE Signal Processing Magazine,;Vol. 33(2016)p. 74-84
Journal article
Collision-Aware Communication for Intersection Management of Automated Vehicles
IEEE Access,;Vol. 6(2018)p. 77359-77371
Journal article
Theoretical Limits on Cooperative Positioning in Mixed Traffic
IEEE Access,;Vol. 7(2019)p. 49712-49725
Journal article
Automated or so-called driverless cars and trucks will soon take over our streets. They are not only envisioned to change the way we get around, but also to make road transport more safe and efficient. This means that instead of spending your morning stuck in traffic, you will be able to rest or prepare for a meeting while your car takes you to work, and then goes and drops your kids off at school.
To be able realize this vision, driverless cars will rely heavily on on-board sensors to determine where they and other road users are. For instance, they will be equipped with Global Positing System (GPS) receivers that provide information about where on the road the car is, as well as radars and laser scanners to detect vehicles and pedestrian in the surrounding environment. However, as these sensors can only see as far as a traditional driver can, vehicles are also expected to “talk” to each other using wireless communication to increase their knowledge of the traffic scenario. By sharing what they see and what their intentions are, vehicles can determine where pedestrians and cyclists are and anticipate where they are going to be in the near future. The fact that they can talk to each other will also make it possible for vehicles to coordinate their actions. For instance, imagine a street intersection without traffic lights where two high-speed streams of vehicles merge and continue to drive without ever slowing down.
The wireless communication used for sharing of both sensor and control information is, unfortunately, not perfect. In fact, when information is exchanged between vehicles data packets can be lost or delayed. On top of this, even if the vehicles collaborate and share information to draw a common picture of where everyone is, the information is limited by the quality and range of the used sensors. To be able to guarantee safe operation, it is thus important to understand what the limitations are regarding communication and sensing, and how they impact the control and coordination task.
This thesis thus studies limitations of communication and sensing systems in future road transport systems, including how communication and sensing behave with more and more vehicles on the road, and how to adapt the communication for coordination tasks. A technical abstract of this thesis can be found on page i.
To be able realize this vision, driverless cars will rely heavily on on-board sensors to determine where they and other road users are. For instance, they will be equipped with Global Positing System (GPS) receivers that provide information about where on the road the car is, as well as radars and laser scanners to detect vehicles and pedestrian in the surrounding environment. However, as these sensors can only see as far as a traditional driver can, vehicles are also expected to “talk” to each other using wireless communication to increase their knowledge of the traffic scenario. By sharing what they see and what their intentions are, vehicles can determine where pedestrians and cyclists are and anticipate where they are going to be in the near future. The fact that they can talk to each other will also make it possible for vehicles to coordinate their actions. For instance, imagine a street intersection without traffic lights where two high-speed streams of vehicles merge and continue to drive without ever slowing down.
The wireless communication used for sharing of both sensor and control information is, unfortunately, not perfect. In fact, when information is exchanged between vehicles data packets can be lost or delayed. On top of this, even if the vehicles collaborate and share information to draw a common picture of where everyone is, the information is limited by the quality and range of the used sensors. To be able to guarantee safe operation, it is thus important to understand what the limitations are regarding communication and sensing, and how they impact the control and coordination task.
This thesis thus studies limitations of communication and sensing systems in future road transport systems, including how communication and sensing behave with more and more vehicles on the road, and how to adapt the communication for coordination tasks. A technical abstract of this thesis can be found on page i.
Subject Categories
Computer Engineering
Telecommunications
Communication Systems
Driving Forces
Sustainable development
Areas of Advance
Transport
ISBN
978-91-7905-111-2
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4578
Publisher
Chalmers
Room EC, 5th floor, Hörsalsvägen 11
Opponent: Dr. Stephan Sand, German Aerospace Center, Oberpfaffenhofen, Germany