| 000 | 03990nam a22005415i 4500 | ||
|---|---|---|---|
| 001 | 978-981-97-3597-6 | ||
| 003 | DE-He213 | ||
| 005 | 20251030112654.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 240727s2024 si | s |||| 0|eng d | ||
| 020 |
_a9789819735976 _9978-981-97-3597-6 |
||
| 024 | 7 |
_a10.1007/978-981-97-3597-6 _2doi |
|
| 050 | 4 | _aTA1001-1280 | |
| 050 | 4 | _aHE331-380 | |
| 072 | 7 |
_aTNH _2bicssc |
|
| 072 | 7 |
_aTEC009140 _2bisacsh |
|
| 072 | 7 |
_aTNH _2thema |
|
| 100 | 1 |
_aQi, HongSheng. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981410 |
|
| 245 | 1 | 0 |
_aStochastic Two-Dimensional Microscopic Traffic Model _h[electronic resource] : _bTheory and Applications / _cby HongSheng Qi. |
| 250 | _a1st ed. 2024. | ||
| 264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2024. |
|
| 300 |
_aXXII, 376 p. 221 illus., 212 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aLecture Notes in Intelligent Transportation and Infrastructure, _x2523-3459 |
|
| 505 | 0 | _aNoise reduction filtering and behavioral estimation for human driven vehicles -- Predictability analysis of driving behavior -- Two dimensional stochastic microscopic traffic model for human driven vehicles -- Two dimensional driving behavioral model considering vehicle dynamics -- Stochastic two dimensional microscopic driving model for intelligent vehicles -- Risky driving behavior with two dimensional jerk and wandering -- Capacity adjustment factor considering lateral influence for multi lane road -- Real time estimation of driving behaviors -- Stochastic lateral wandering of progressive autonomous vehicles flow -- Test scenario generation for autonomous vehicles considering the predictability. | |
| 520 | _aMicroscopic traffic model serves as the foundation of traffic flow theory and is the basis for applications such as traffic simulation, autonomous vehicle simulation, and digital twin technology. Conventional traffic models have primarily focused on the longitudinal dimension and have been deterministic in nature. However, vehicles' movements involve both longitudinal and lateral dimensions, and their dynamics are inherently stochastic. Therefore, a two-dimensional treatment is essential. This book explores the theory and application of stochastic two-dimensional microscopic traffic models, including the development of theory, establishment of methods, and applications to autonomous vehicles. The book is organized into three sections: data, theory, and application. In the data section, various open-source trajectory data are analyzed and noise reduction techniques are discussed. In the theory section, various two-dimensional traffic models are developed. In the application section, the potential applications of these models are discussed, including behavioral inferences and lateral wandering. This book will be a useful reference for students, researchers and engineers in the fields of vehicle engineering and traffic technology. | ||
| 650 | 0 |
_aTransportation engineering. _965686 |
|
| 650 | 0 |
_aTraffic engineering. _965687 |
|
| 650 | 0 |
_aVehicles. _966337 |
|
| 650 | 1 | 4 |
_aTransportation Technology and Traffic Engineering. _965691 |
| 650 | 2 | 4 |
_aVehicle Engineering. _966340 |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819735969 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819735983 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819735990 |
| 830 | 0 |
_aLecture Notes in Intelligent Transportation and Infrastructure, _x2523-3459 _971072 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-97-3597-6 |
| 912 | _aZDB-2-ENG | ||
| 912 | _aZDB-2-SXE | ||
| 999 |
_c61982 _d61982 |
||