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发表于 2005-10-5 20:44:53
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高自友,任华玲《城市动态交通流分配模型与算法》
这个话题可能太耗时. 简言之, 如果达到了DUE, 则, 同一OD之间同时出发的人应该同时到达目的地. 而DUO可以不这样, DSO更不这样.
Dynamic traffic assignment models which have important applications in being rapidly developed advanced traveler information systems and advanced traffic management systems, can be classified into two categories: the reactive assignment model and the predictive assignment model. The reactive assignment model assumes that each traveler chooses the shortest route to his destination according to present instantaneous traffic condition. As a result of the time-varying traffic condition, travelers between the same origin-destination (OD) pair departing at the same time may arrive at the destination differently if different routes have been chosen. The models proposed by Wie et al. (1990), Boyce et al. (1993), Lam and Huang (1995), Ran et al. (1993) and Kuwahara and Akamatsu (1997) can be classified as this category. In contrast, the predictive assignment model considers the impact of future traffic condition on route choice behavior, i.e., the shortest route is determined based on the actually experienced travel time or cost by a traveler leaving from a particular location at certain time. The models proposed by Bernstein et al. (1993), Friesz et al. (1993), Kuwahara and Akamatsu (1993), Smith (1993), Heydecker and Addison (1996), Smith and Wisten (1995), Wie et al. (1995), Ran and Boyce (1996), Chen and Hsueh (1998) can be put in this category.
Most of the predictive assignment models aim to satisfy the dynamic user-equilibrium (UE) condition which requires that at equilibrium, the actual travel time or cost experienced by travelers between the same OD pair departing at the same time is equal and minimal. In other words, if such an equilibrium state has arisen today, then there is no incentive for any route-inflow to change tomorrow. This definition about equilibrium can also be used in departure time choice, as well as simultaneous route and departure (SRD) time choices (Bernstein et al., 1993; Friesz et al., 1993; Wie et al., 1995). However, the predictive assignment problem is much more difficult than that of the reactive assignment due to the burdensome computational requirements and vague property of the actual route travel time (or cost) in general networks. Modeling and solving the dynamic SRD equilibrium problems become challenging from both theoretical and practical viewpoints.
Janson and Robles (1993) formulated a link-based bi-level program for dynamic user-equilibrium assignment in which departure times are affected by arrival time costs. Lam et al. (1999) also proposed a time-dependent assignment model for logit-based departure time and user-equilibrium route choices. However, for various reasons these models adopted much longer time intervals, for instance, ten or fifteen minutes in Janson and Robles (1993, 1995) and one hour in Lam et al. (1999), than other discrete-time dynamic assignment models that are generally regarded as their continuous-time counterparts. So, these models may be more applicable for long-term transportation planning, rather than instantaneous traffic analysis.
The approach of variational inequalities has been demonstrated to be quite useful for modeling the dynamic SRD equilibrium problem. Friesz et al. (1993) was the first to offer an infinite-dimensional variational inequality (VI) formulation for this problem. Wie et al. (1995) extended the model to a discrete-time dimension and presented a heuristic algorithm for obtaining an approximate solution. They employed a non-linear link exit function to describe the physical phenomenon of traffic congestion. This yields some difficulties in precisely computing the actual link travel times which is necessary for preserving the first-in-first-out queue discipline and correctly modeling the vehicle dynamics (or flow propagation).
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