Intelligent Mobility in Smart Cities
Smart Cities seek to optimize their systems by increasing integration through approaches such as increased interoperability, seamless system integration, and automation. Thus, they have the potential to deliver substantial efficiency gains and eliminate redundancy. To add to the complexity of the pr...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel
MDPI - Multidisciplinary Digital Publishing Institute
2022
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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245 | 1 | 0 | |a Intelligent Mobility in Smart Cities |
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520 | |a Smart Cities seek to optimize their systems by increasing integration through approaches such as increased interoperability, seamless system integration, and automation. Thus, they have the potential to deliver substantial efficiency gains and eliminate redundancy. To add to the complexity of the problem, the integration of systems for efficiency gains may compromise the resilience of an urban system. This all needs to be taken into consideration when thinking about Smart Cities. The transportation field must also apply the principles and concepts mentioned above. This cannot be understood without considering its links and effects on the other components of an urban system. New technologies allow for new means of travel to be built, and new business models allow for existing ones to be utilized. This Special Issue puts together papers with different focuses, but all of them tackle the topic of smart mobility. | ||
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546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
650 | 7 | |a History of engineering & technology |2 bicssc | |
653 | |a city logistics | ||
653 | |a cargo bike | ||
653 | |a cargo cycle | ||
653 | |a simulation | ||
653 | |a geometrical model | ||
653 | |a shopping mall | ||
653 | |a concentrated sets of delivery locations | ||
653 | |a bike delivery | ||
653 | |a big data | ||
653 | |a flow clustering | ||
653 | |a intelligent transportation systems | ||
653 | |a multi-source data analyses | ||
653 | |a spatio-temporal data analyses | ||
653 | |a user experience | ||
653 | |a multi-criteria decision-making | ||
653 | |a AHP/TOPSIS hybrid approach | ||
653 | |a optimal site selection | ||
653 | |a GeoSpatial data | ||
653 | |a smart cities | ||
653 | |a fire rescue service | ||
653 | |a housing estates | ||
653 | |a swept paths | ||
653 | |a digital model | ||
653 | |a cooperative systems | ||
653 | |a evaluation methodology | ||
653 | |a telematics | ||
653 | |a functional evaluation | ||
653 | |a impact assessment | ||
653 | |a user acceptance | ||
653 | |a traffic control | ||
653 | |a urban tunnel | ||
653 | |a integration | ||
653 | |a n/a | ||
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856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/91141 |7 0 |z DOAB: description of the publication |