| 000 | 08261nam a2200877 i 4500 | ||
|---|---|---|---|
| 001 | 6813756 | ||
| 003 | IEEE | ||
| 005 | 20200413152913.0 | ||
| 006 | m eo d | ||
| 007 | cr cn |||m|||a | ||
| 008 | 140113s2014 caua foab 000 0 eng d | ||
| 020 |
_a9781627052085 _qebook |
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| 020 |
_z9781627052078 _qpaperback |
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| 024 | 7 |
_a10.2200/S00553ED1V01Y201312AIM025 _2doi |
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| 035 | _a(CaBNVSL)swl00403031 | ||
| 035 | _a(OCoLC)867203780 | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aTE228.3 _b.B295 2014 |
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| 082 | 0 | 4 |
_a388.312 _223 |
| 090 |
_a _bMoCl _e201312AIM025 |
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| 100 | 1 |
_aBazzan, Ana L. C., _eauthor. |
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| 245 | 1 | 0 |
_aIntroduction to intelligent systems in traffic and transportation / _cAna L.C. Bazzan, Franziska Klügl. |
| 264 | 1 |
_aSan Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool, _c2014. |
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| 300 |
_a1 PDF (xvii, 119 pages) : _billustrations. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 |
_aSynthesis lectures on artificial intelligence and machine learning, _x1939-4616 ; _v# 25 |
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| 538 | _aMode of access: World Wide Web. | ||
| 538 | _aSystem requirements: Adobe Acrobat Reader. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 500 | _aSeries from website. | ||
| 504 | _aIncludes bibliographical references (pages 99-118). | ||
| 505 | 0 | _a1. Introduction -- 1.1 The importance of transportation -- 1.2 Transportation systems -- 1.3 Intelligent transportation systems -- | |
| 505 | 8 | _a2. Elements of supply -- 2.1 Traffic network structure -- 2.2 Traffic streams: macroscopic and microscopic parameters -- 2.3 Traffic flow theory -- 2.4 Traffic control measures -- 2.4.1 Signal timing and design -- 2.4.2 Progressive systems -- 2.5 To know more -- | |
| 505 | 8 | _a3. Elements of demand -- 3.1 Demand modeling -- 3.1.1 Representation of demand -- 3.1.2 Trip-based demand modeling -- 3.1.3 Activity-based demand modeling -- 3.2 Discrete choice modeling for travel demand -- 3.3 Travel demand management -- 3.4 To know more -- | |
| 505 | 8 | _a4. Traffic assignment: connecting supply and demand -- 4.1 Route computation -- 4.2 Basic trip assignment -- 4.2.1 Assignment on un-congested networks -- 4.2.2 Assignment under congestion and equilibrium -- 4.2.3 Dynamic traffic assignment -- 4.2.4 From user to system optimum -- 4.3 Changing the perspective: from trips to drivers -- 4.4 Evaluation of route assignment -- 4.5 To know more -- | |
| 505 | 8 | _a5. Getting data for demand estimation and traffic flow modeling -- 5.1 Data collection for estimation of demand and volume -- 5.2 Deriving parameters from data -- 5.3 Sources of public data about network topology and demand -- 5.3.1 OpenStreetMap -- 5.3.2 Transportation network test problems -- 5.4 To know more -- | |
| 505 | 8 | _a6. Modeling and simulation of advanced decision making -- 6.1 Systematics of traditional approaches -- 6.1.1 Sub-microscopic models -- 6.1.2 Microscopic traffic flow models -- 6.1.3 Macroscopic traffic flow simulation models -- 6.1.4 Mesoscopic traffic flow simulation -- 6.2 Human-like driving with advanced driver models -- 6.2.1 Anticipation -- 6.2.2 Behavior at crossings -- 6.2.3 Emotion and aggressiveness -- 6.2.4 Routing, planning and beyond -- 6.3 To know more -- | |
| 505 | 8 | _a7. Intelligent measures in control and management -- 7.1 Strategies for intelligent traffic signal control -- 7.1.1 From isolated to coordinated intersections -- 7.1.2 Approaches based on reinforcement learning -- 7.2 Beyond pure traffic signal control -- 7.2.1 Approaches explicitly addressing demand -- 7.2.2 Coordination of drivers' choices -- 7.2.3 Lightless and market-based approaches -- 7.2.4 System-level management -- 7.3 To know more -- | |
| 505 | 8 | _a8. Driver support and guidance -- 8.1 (Advanced) driver assistance systems -- 8.1.1 Elements of a driver assistance system -- 8.1.2 New technology for cooperative assistance systems -- 8.2 In-vehicle route guidance -- 8.2.1 Basic localization -- 8.2.2 Map-matching -- 8.2.3 Shortest path algorithms -- 8.2.4 Using route guidance -- 8.2.5 Cooperative route guidance -- 8.3 From route guidance to travel recommender systems -- 8.3.1 Extended routing -- 8.3.2 Mobile recommender systems -- 8.4 To know more -- | |
| 505 | 8 | _a9. Trends and new technologies -- 9.1 Interconnected automobiles -- 9.2 Some projects around autonomous vehicles and personal transit -- 9.3 Future of traffic management -- 9.3.1 Participatory traffic management -- 9.3.2 Autonomic traffic management -- 9.3.3 Crowd sensing -- 9.4 To know more -- | |
| 505 | 8 | _aBibliography -- Authors' biographies. | |
| 506 | 1 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | |
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | 3 | _aUrban mobility is not only one of the pillars of modern economic systems, but also a key issue in the quest for equality of opportunity, once it can improve access to other services. Currently, however, there are a number of negative issues related to traffic, especially in mega-cities, such as economical issues (cost of opportunity caused by delays), environmental (externalities related to emissions of pollutants), and social (traffic accidents). Solutions to these issues are more and more closely tied to information and communication technology. Indeed, a search in the technical literature (using the keyword "urban traffic" to filter out articles on data network traffic) retrieved the following number of articles (as of December 3, 2013): 9,443 (ACM Digital Library), 26,054 (Scopus), and 1,730,000 (Google Scholar). Moreover, articles listed in the ACM query relate to conferences as diverse as MobiCom, CHI, PADS, and AAMAS. This means that there is a big and diverse community of computer scientists and computer engineers who tackle research that is connected to the development of intelligent traffic and transportation systems. It is also possible to see that this community is growing, and that research projects are getting more and more interdisciplinary. To foster the cooperation among the involved communities, this book aims at giving a broad introduction into the basic but relevant concepts related to transportation systems, targeting researchers and practitioners from computer science and information technology. In addition, the second part of the book gives a panorama of some of the most exciting and newest technologies, originating in computer science and computer engineering, that are now being employed in projects related to car-to-car communication, interconnected vehicles, car navigation, platooning, crowd sensing and sensor networks, among others. This material will also be of interest to engineers and researchers from the traffic and transportation community. | |
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF title page (viewed on January 13, 2014). | ||
| 650 | 0 | _aIntelligent transportation systems. | |
| 653 | _aintelligent transportation systems | ||
| 653 | _atraffic modeling | ||
| 653 | _atraffic simulation | ||
| 653 | _aadvanced traveler information systems | ||
| 653 | _atraffic control | ||
| 653 | _atraffic assignment | ||
| 653 | _atraffic management | ||
| 653 | _aroute choice | ||
| 653 | _arouting | ||
| 653 | _aroute guidance | ||
| 653 | _adriver assistance systems | ||
| 653 | _acar to car communication | ||
| 653 | _aartificial intelligence | ||
| 653 | _amachine learning | ||
| 653 | _areinforcement learning | ||
| 653 | _aswarm intelligence | ||
| 653 | _amultiagent systems | ||
| 700 | 1 |
_aKlügl, Franziska., _eauthor. |
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| 776 | 0 | 8 |
_iPrint version: _z9781627052078 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on artificial intelligence and machine learning ; _v# 25. _x1939-4616 |
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| 856 | 4 | 2 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6813756 |
| 856 | 4 | 0 |
_3Abstract with links to full text _uhttp://dx.doi.org/10.2200/S00553ED1V01Y201312AIM025 |
| 999 |
_c562048 _d562048 |
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