10 research outputs found
Application and Control Aware Communication Strategies for Transportation and Energy Cyber-Physical Systems
Cyber--Physical Systems (CPSs) are a generation of engineered systems in which computing, communication, and control components are tightly integrated. Some important application domains of CPS are transportation, energy, and medical systems. The dynamics of CPSs are complex, involving the stochastic nature of communication systems, discrete dynamics of computing systems, and continuous dynamics of control systems. The existence of communication between and among controllers of physical processes is one of the basic characteristics of CPSs. Under this situation, some fundamental questions are: 1) How does the network behavior (communication delay, packet loss, etc.) affect the stability of the system? 2) Under what conditions is a complex system stabilizable?;In cases where communication is a component of a control system, scalability of the system becomes a concern. Therefore, one of the first issues to consider is how information about a physical process should be communicated. For example, the timing for sampling and communication is one issue. The traditional approach is to sample the physical process periodically or at predetermined times. An alternative is to sample it when specific events occur. Event-based sampling requires continuous monitoring of the system to decide a sample needs to be communicated. The main contributions of this dissertation in energy cyber-physical system domain are designing and modeling of event-based (on-demand) communication mechanisms. We show that in the problem of tracking a dynamical system over a network, if message generation and communication have correlation with estimation error, the same performance as the periodic sampling and communication method can be reached using a significantly lower rate of data.;For more complex CPSs such as vehicle safety systems, additional considerations for the communication component are needed. Communication strategies that enable robust situational awareness are critical for the design of CPSs, in particular for transportation systems. In this dissertation, we utilize the recently introduced concept of model-based communication and propose a new communication strategy to address this need. Our approach to model behavior of remote vehicles mathematically is to describe the small-scale structure of the remote vehicle movement (e.g. braking, accelerating) by a set of dynamic models and represent the large-scale structure (e.g. free following, turning) by coupling these dynamic models together into a Markov chain. Assuming model-based communication approach, a novel stochastic model predictive method is proposed to achieve cruise control goals and investigate the effect of new methodology.;To evaluate the accuracy and robustness of a situational awareness methodology, it is essential to study the mutual effect of the components of a situational awareness subsystem, and their impact on the accuracy of situational awareness. The main components are estimation and networking processes. One possible approach in this task is to produce models that provide a clear view into the dynamics of these two components. These models should integrate continuous physical dynamics, expressed with ordinary differential equations, with the discrete behaviors of communication, expressed with finite automata or Markov chain. In this dissertation, a hybrid automata model is proposed to combine and model both networking and estimation components in a single framework and investigate their interactions.;In summary, contributions of this dissertation lie in designing and evaluating methods that utilize knowledge of the physical element of CPSs to optimize the behavior of communication subsystems. Employment of such methods yields significant overall system performance improvement without incurring additional communication deployment costs
Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application
While the development of Vehicle-to-Vehicle (V2V) safety applications based
on Dedicated Short-Range Communications (DSRC) has been extensively undergoing
standardization for more than a decade, such applications are extremely missing
for Vulnerable Road Users (VRUs). Nonexistence of collaborative systems between
VRUs and vehicles was the main reason for this lack of attention. Recent
developments in Wi-Fi Direct and DSRC-enabled smartphones are changing this
perspective. Leveraging the existing V2V platforms, we propose a new framework
using a DSRC-enabled smartphone to extend safety benefits to VRUs. The
interoperability of applications between vehicles and portable DSRC enabled
devices is achieved through the SAE J2735 Personal Safety Message (PSM).
However, considering the fact that VRU movement dynamics, response times, and
crash scenarios are fundamentally different from vehicles, a specific framework
should be designed for VRU safety applications to study their performance. In
this article, we first propose an end-to-end Vehicle-to-Pedestrian (V2P)
framework to provide situational awareness and hazard detection based on the
most common and injury-prone crash scenarios. The details of our VRU safety
module, including target classification and collision detection algorithms, are
explained next. Furthermore, we propose and evaluate a mitigating solution for
congestion and power consumption issues in such systems. Finally, the whole
system is implemented and analyzed for realistic crash scenarios
AROW: A V2X-based Automated Right-of-Way Algorithm for Distributed Cooperative Intersection Management
Safe and efficient intersection management is critical for an improved
driving experience. As per several studies, an increasing number of crashes and
fatalities occur every year at intersections. Most crashes are a consequence of
a lack of situational awareness and ambiguity over intersection crossing
priority. In this regard, research in Cooperative Intersection Management (CIM)
is considered highly significant since it can utilize Vehicle-to-Everything
(V2X) communication among Connected and Autonomous Vehicles (CAVs). CAVs can
transceive basic and/or advanced safety information, thereby improving
situational awareness at intersections. Although numerous studies have been
performed on CIM, most of them are reliant on the presence of a Road-Side Unit
(RSU) that can act as a centralized intersection manager and assign
intersection crossing priorities. In the absence of RSU, there are some
distributed CIM methods that only rely on communication among CAVs for
situational awareness, however, none of them are specifically focused towards
Stop Controlled-Intersection (SCI) with the aim of mitigating ambiguity among
CAVs. Thus, we propose an Automated Right-of-Way (AROW) algorithm based on
distributed CIM that is capable of reducing ambiguity and handling any level of
noncompliance by CAVs. The algorithm is validated with extensive experiments
for its functionality and robustness, and it outperforms the current solutions
DSRC Versus LTE-V2X: Empirical Performance Analysis of Direct Vehicular Communication Technologies
Vehicle-to-Vehicle (V2V) communication systems have an eminence potential to improve road safety and optimize traffic flow by broadcasting Basic Safety Messages (BSMs). Dedicated Short-Range Communication (DSRC) and LTE Vehicle-to-Everything (V2X) are two candidate technologies to enable V2V communication. DSRC relies on the IEEE 802.11p standard for its PHY and MAC layer while LTE-V2X is based on 3GPP’s Release 14 and operates in a distributed manner in the absence of cellular infrastructure. There has been considerable debate over the relative advantages and disadvantages of DSRC and LTE-V2X, aiming to answer the fundamental question of which technology is most effective in real-world scenarios for various road safety and traffic efficiency applications. In this paper, we present a comprehensive survey of these two technologies (i.e., DSRC and LTE-V2X) and related works. More specifically, we study the PHY and MAC layer of both technologies in the survey study and compare the PHY layer performance using a variety of field tests. First, we provide a summary of each technology and highlight the limitations of each in supporting V2X applications. Then, we examine their performance based on different metrics
Task-aware Distributed Source Coding under Dynamic Bandwidth
Efficient compression of correlated data is essential to minimize
communication overload in multi-sensor networks. In such networks, each sensor
independently compresses the data and transmits them to a central node due to
limited communication bandwidth. A decoder at the central node decompresses and
passes the data to a pre-trained machine learning-based task to generate the
final output. Thus, it is important to compress the features that are relevant
to the task. Additionally, the final performance depends heavily on the total
available bandwidth. In practice, it is common to encounter varying
availability in bandwidth, and higher bandwidth results in better performance
of the task. We design a novel distributed compression framework composed of
independent encoders and a joint decoder, which we call neural distributed
principal component analysis (NDPCA). NDPCA flexibly compresses data from
multiple sources to any available bandwidth with a single model, reducing
computing and storage overhead. NDPCA achieves this by learning low-rank task
representations and efficiently distributing bandwidth among sensors, thus
providing a graceful trade-off between performance and bandwidth. Experiments
show that NDPCA improves the success rate of multi-view robotic arm
manipulation by 9% and the accuracy of object detection tasks on satellite
imagery by 14% compared to an autoencoder with uniform bandwidth allocation
Minimally Disruptive Cooperative Lane-change Maneuvers
A lane-change maneuver on a congested highway could be severely disruptive or
even infeasible without the cooperation of neighboring cars. However,
cooperation with other vehicles does not guarantee that the performed maneuver
will not have a negative impact on traffic flow unless it is explicitly
considered in the cooperative controller design. In this letter, we present a
socially compliant framework for cooperative lane-change maneuvers for an
arbitrary number of CAVs on highways that aims to interrupt traffic flow as
minimally as possible. Moreover, we explicitly impose feasibility constraints
in the optimization formulation by using reachability set theory, leading to a
unified design that removes the need for an iterative procedure used in prior
work. We quantitatively evaluate the effectiveness of our framework and compare
it against previously offered approaches in terms of maneuver time and incurred
throughput disruption.Comment: 6 pages, 2 figure
Automotive Collision Risk Estimation Under Cooperative Sensing
This paper offers a technique for estimating collision risk for
automated ground vehicles engaged in cooperative sensing. The
technique allows quantification of (i) risk reduced due to cooperation, and (ii) the increased accuracy of risk assessment due to cooperation. If either is significant, cooperation can be viewed as a
desirable practice for meeting the stringent risk budget of increasingly automated vehicles; if not, then cooperation—with its various
drawbacks—need not be pursued. Collision risk is evaluated over an
ego vehicle’s trajectory based on a dynamic probabilistic occupancy
map and a loss function that maps collision-relevant state information to a cost metric. The risk evaluation framework is demonstrated
using real data captured from two cooperating vehicles traversing an
urban intersection.Aerospace Engineering and Engineering Mechanic
Utilizing Model-Based Communication And Control For Cooperative Automated Vehicle Applications
Connected vehicle applications rely on wireless communication for achieving real-time situational awareness and enabling automated actions or driver warnings. Given the constraints of the communication systems, it is critical to employ communication strategies and approaches that allow robust situational awareness. In this work, we utilize the recently introduced concept of model-based communication and design a new strategy based on small- and large-scale modeling of vehicle movement dynamics. Our approach is to describe the small-scale structure of the remote vehicle movement (e.g., braking, accelerating) by a set of dynamic models (ARX models) and represent the large-scale structure (e.g., free following, turning) by coupling these ARX models together into a Markov chain. The effect of this design is investigated for the case of cooperative adaptive cruise control application. Assuming model-based communication approach is used with the coupled model, a novel stochastic model predictive method is proposed to achieve cruise control goals. We use actual highway driving maneuvers to compare the proposed methodology with the conventional design of cooperative adaptive cruise control
Design a Sustainable Micro-mobility Future: Trends and Challenges in the US and EU
Micro-mobility is promising to contribute to sustainable cities with its efficiency and low cost. To better design such a sustainable future, it is necessary to understand the trends and challenges. Thus, we examined people's opinions on micro-mobility in the US and the EU using Tweets. We used topic modeling based on advanced natural language processing techniques and categorized the data into seven topics: promotion and service, mobility, technical features, acceptance, recreation, infrastructure and regulations. Furthermore, using sentiment analysis, we investigated people's positive and negative attitudes towards specific aspects of these topics and compared the patterns of the trends and challenges in the US and the EU. We found that 1) promotion and service included the majority of Twitter discussions in the both regions, 2) the EU had more positive opinions than the US, 3) micro-mobility devices were more widely used for utilitarian mobility and recreational purposes in the EU than in the US, and 4) compared to the EU, people in the US had many more concerns related to infrastructure and regulation issues. These findings help us design and prioritize micro-mobility to improve their safety and experience across the two areas for designing a more sustainable micro-mobility future.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/175033/1/Micromobility.pdfDescription of Micromobility.pdf : Main articleSEL