1,548 research outputs found
The State-of-the-art of Coordinated Ramp Control with Mixed Traffic Conditions
Ramp metering, a traditional traffic control strategy for conventional
vehicles, has been widely deployed around the world since the 1960s. On the
other hand, the last decade has witnessed significant advances in connected and
automated vehicle (CAV) technology and its great potential for improving
safety, mobility and environmental sustainability. Therefore, a large amount of
research has been conducted on cooperative ramp merging for CAVs only. However,
it is expected that the phase of mixed traffic, namely the coexistence of both
human-driven vehicles and CAVs, would last for a long time. Since there is
little research on the system-wide ramp control with mixed traffic conditions,
the paper aims to close this gap by proposing an innovative system architecture
and reviewing the state-of-the-art studies on the key components of the
proposed system. These components include traffic state estimation, ramp
metering, driving behavior modeling, and coordination of CAVs. All reviewed
literature plot an extensive landscape for the proposed system-wide coordinated
ramp control with mixed traffic conditions.Comment: 8 pages, 1 figure, IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE
- ITSC 201
Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network
Accurate lane localization and lane change detection are crucial in advanced
driver assistance systems and autonomous driving systems for safer and more
efficient trajectory planning. Conventional localization devices such as Global
Positioning System only provide road-level resolution for car navigation, which
is incompetent to assist in lane-level decision making. The state of art
technique for lane localization is to use Light Detection and Ranging sensors
to correct the global localization error and achieve centimeter-level accuracy,
but the real-time implementation and popularization for LiDAR is still limited
by its computational burden and current cost. As a cost-effective alternative,
vision-based lane change detection has been highly regarded for affordable
autonomous vehicles to support lane-level localization. A deep learning-based
computer vision system is developed to detect the lane change behavior using
the images captured by a front-view camera mounted on the vehicle and data from
the inertial measurement unit for highway driving. Testing results on
real-world driving data have shown that the proposed method is robust with
real-time working ability and could achieve around 87% lane change detection
accuracy. Compared to the average human reaction to visual stimuli, the
proposed computer vision system works 9 times faster, which makes it capable of
helping make life-saving decisions in time
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
Decentralized Multi-Floor Exploration by a Swarm of Miniature Robots Teaming with Wall-Climbing Units
In this paper, we consider the problem of collectively exploring unknown and
dynamic environments with a decentralized heterogeneous multi-robot system
consisting of multiple units of two variants of a miniature robot. The first
variant-a wheeled ground unit-is at the core of a swarm of floor-mapping robots
exhibiting scalability, robustness and flexibility. These properties are
systematically tested and quantitatively evaluated in unstructured and dynamic
environments, in the absence of any supporting infrastructure. The results of
repeated sets of experiments show a consistent performance for all three
features, as well as the possibility to inject units into the system while it
is operating. Several units of the second variant-a wheg-based wall-climbing
unit-are used to support the swarm of mapping robots when simultaneously
exploring multiple floors by expanding the distributed communication channel
necessary for the coordinated behavior among platforms. Although the
occupancy-grid maps obtained can be large, they are fully distributed. Not a
single robotic unit possesses the overall map, which is not required by our
cooperative path-planning strategy.Comment: Accepted for publication in IEEE-MRS 2019, Rutgers University, New
Brunswick (NJ), US
Emergent Incident Response for Unmanned Warehouses with Multi-agent Systems*
Unmanned warehouses are an important part of logistics, and improving their
operational efficiency can effectively enhance service efficiency. However, due
to the complexity of unmanned warehouse systems and their susceptibility to
errors, incidents may occur during their operation, most often in inbound and
outbound operations, which can decrease operational efficiency. Hence it is
crucial to to improve the response to such incidents. This paper proposes a
collaborative optimization algorithm for emergent incident response based on
Safe-MADDPG. To meet safety requirements during emergent incident response, we
investigated the intrinsic hidden relationships between various factors. By
obtaining constraint information of agents during the emergent incident
response process and of the dynamic environment of unmanned warehouses on
agents, the algorithm reduces safety risks and avoids the occurrence of chain
accidents; this enables an unmanned system to complete emergent incident
response tasks and achieve its optimization objectives: (1) minimizing the
losses caused by emergent incidents; and (2) maximizing the operational
efficiency of inbound and outbound operations during the response process. A
series of experiments conducted in a simulated unmanned warehouse scenario
demonstrate the effectiveness of the proposed method.Comment: 13 pages, 7 figure
The Covert Life of Hospital Architecture
The Covert Life of Hospital Architecture addresses hospital architecture as a set of interlocked, overlapping spatial and social conditions. It identifies ways that planned-for and latent functions of hospital spaces work jointly to produce desired outcomes such as greater patient safety, increased scope for care provider communication and more intelligible corridors.
By advancing space syntax theory and methods, the volume brings together emerging research on hospital environments. Opening with a description of hospital architecture that emphasizes everyday relations, the sequence of chapters takes an unusually comprehensive view that pairs spaces and occupants in hospitals: the patient room and its intervisibility with adjacent spaces, care teams and on-ward support for their work and the intelligibility of public circulation spaces for visitors. The final chapter moves outside the hospital to describe the current healthcare crisis of the global pandemic as it reveals how healthcare institutions must evolve to be adaptable in entirely new ways. Reflective essays by practicing designers follow each chapter, bringing perspectives from professional practice into the discussion.
The Covert Life of Hospital Architecture makes the case that latent dimensions of space as experienced have a surprisingly strong link to measurable outcomes, providing new insights into how to better design hospitals through principles that have been tested empirically. It will become a reference for healthcare planners, designers, architects and administrators, as well as for readers from sociology, psychology and other areas of the social sciences
- …