Dynamic system-optimal traffic assignment using a state space model
dc.contributor.author | Lafortune, Stéphane | en_US |
dc.contributor.author | Sengupta, Raja | en_US |
dc.contributor.author | Kaufman, David E. | en_US |
dc.contributor.author | Smith, Robert L. | en_US |
dc.date.accessioned | 2006-04-10T15:29:23Z | |
dc.date.available | 2006-04-10T15:29:23Z | |
dc.date.issued | 1993-12 | en_US |
dc.identifier.citation | Lafortune, Stephane, Sengupta, Raja, Kaufman, David E., Smith, Robert L. (1993/12)."Dynamic system-optimal traffic assignment using a state space model." Transportation Research Part B: Methodological 27(6): 451-472. <http://hdl.handle.net/2027.42/30420> | en_US |
dc.identifier.uri | http://www.sciencedirect.com/science/article/B6V99-466CFMV-93/2/f834f0507021c79d9fcbde0a648cf761 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/30420 | |
dc.description.abstract | We propose a new mathematical formulation for the problem of optimal traffic assignment in dynamic networks with multiple origins and destinations. This problem is motivated by route guidance issues that arise in an Intelligent Vehicle-Highway Systems (IVHS) environment. We assume that the network is subject to known time-varying demands for travel between its origins and destinations during a given time horizon. The objective is to assign the vehicles to links over time so as to minimize the total travel time experienced by all the vehicles using the network. We model the traffic network over the time horizon as a discrete-time dynamical system. The system state at each time instant is defined in a way that, without loss of optimality, avoids complete microscopic detail by grouping vehicles into platoons irrespective of origin node and time of entry to network. Moreover, the formulation contains no explicit path enumeration. The state transition function can model link travel times by either impedance functions, link outflow functions, or by a combination of both. Two versions (with different boundary conditions) of the problem of optimal traffic assignment are studied in the context of this model. These optimization problems are optimal control problems for nonlinear discrete-time dynamical systems, and thus they are amenable to algorithmic solutions based on dynamic programming. The computational challenges associated with the exact solution of these problems are discussed and some heuristics are proposed. | en_US |
dc.format.extent | 1599037 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | en_US |
dc.title | Dynamic system-optimal traffic assignment using a state space model | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Mechanical Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, U.S.A. | en_US |
dc.contributor.affiliationum | Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, U.S.A. | en_US |
dc.contributor.affiliationum | Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, U.S.A. | en_US |
dc.contributor.affiliationum | Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, U.S.A. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/30420/1/0000041.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/0191-2615(93)90017-5 | en_US |
dc.identifier.source | Transportation Research Part B: Methodological | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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