TY - BOOK ID - 125284261 TI - Intelligent Transportation Related Complex Systems and Sensors AU - Kyamakya, Kyandoghere AU - Al-Machot, Fadi AU - Mosa, Ahmad Haj AU - Chedjou, Jean Chamberlain AU - Bagula, Antoine PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Technology: general issues KW - image dehazing KW - traffic video dehazing KW - dark channel prior KW - spatial-temporal correlation KW - contrast enhancement KW - traffic signal control KW - game theory KW - decentralized control KW - large-scale network control KW - railway intrusion detection KW - scene segmentation KW - scene recognition KW - adaptive feature extractor KW - convolutional neural networks KW - in-cylinder pressure identification KW - speed iteration model KW - EKF KW - frequency modulation KW - amplitude modulation KW - sensor synchronization KW - microscopic traffic data KW - trajectory reconstruction KW - expectation maximization KW - vehicle matching KW - artificial neural networks KW - metro KW - transportation KW - user flow forecast KW - matrix inversion KW - time-varying matrix KW - noise problem in time-varying matrix inversion KW - recurrent neural network (RNN) KW - RNN-based solver KW - real-time fast computing KW - real-time estimation KW - probe vehicle KW - traffic density KW - neural network KW - level of market penetration rate KW - deep neural network KW - neural artistic extraction KW - objectification KW - ride comfort KW - subjective evaluation KW - road surface recognition KW - Gaussian background model KW - abnormal road surface KW - acceleration sensor KW - traffic state prediction KW - spatio-temporal traffic modeling KW - simulation KW - machine learning KW - hyper parameter optimization KW - ITS KW - crash risk modeling KW - hazardous materials KW - highway safety KW - operations research KW - prescriptive analytics KW - shortest path problem KW - trucking KW - vehicle routing problem KW - data visualization KW - descriptive analytics KW - predictive analytics KW - urban rail transit interior noise KW - smartphone sensing KW - XGBoost classifier KW - railway maintenance KW - vehicle trajectory prediction KW - license plate data KW - trip chain KW - turning state transit KW - route choice behavior KW - real world experiment KW - Intelligent Transportation Systems (ITS) KW - advanced traveler information systems (ATIS) KW - connected vehicles KW - particle filter KW - Kalman filter KW - road safety KW - travel time information system KW - safety performance function KW - bicycle sharing systems KW - public transport systems KW - data-driven classification of trips KW - BSS underlying network KW - trip index KW - automatic rail-surface-scratch recognition and computation KW - triangulation algorithm KW - complete closed mesh model KW - online rail-repair KW - autonomous vehicle KW - obstacle avoidance KW - artificial potential field KW - model predictive control KW - human-like KW - variable speed limits KW - intelligent transportation systems KW - ITS services KW - driving simulator studies KW - traffic modelling KW - surrogate safety measures KW - driving safety KW - driving emotions KW - driving stress KW - lifestyle KW - sensors KW - heart rate KW - plate scanning KW - low-cost sensor KW - sensor location problem KW - traffic flow estimation KW - n/a UR - https://www.unicat.be/uniCat?func=search&query=sysid:125284261 AB - Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data. ER -