7 research outputs found
Bounding the inefficiency of logit-based stochastic user equilibrium
Bounding the inefficiency of selfish routing has become an emerging research subject. A central result obtained in the literature is that the inefficiency of deterministic User Equilibrium (UE) is bounded and the bound is independent of network topology. This paper makes a contribution to the literature by bounding the inefficiency of the logit-based Stochastic User Equilibrium (SUE). In a stochastic environment there are two different definitions of system optimization: one is the traditional System Optimum (SO) which minimizes the total actual system travel time, and the other is the Stochastic System Optimum (SSO) which minimizes the total perceived travel time of all users. Thus there are two ways to define the inefficiency of SUE, i.e. to compare SUE with SO in terms of total actual system travel time, or to compare SUE with SSO in terms of total perceived travel time. We establish upper bounds on the inefficiency of SUE in both situations
Scholarship at UWindsor Annual Report: Nov 2012-2013
This is the first annual report for the Scholarship at UWindsor institutional Repository
Price of Anarchy for Non-atomic Congestion Games with Stochastic Demands
We generalize the notions of user equilibrium and system optimum to
non-atomic congestion games with stochastic demands. We establish upper bounds
on the price of anarchy for three different settings of link cost functions and
demand distributions, namely, (a) affine cost functions and general
distributions, (b) polynomial cost functions and general positive-valued
distributions, and (c) polynomial cost functions and the normal distributions.
All the upper bounds are tight in some special cases, including the case of
deterministic demands.Comment: 31 page
Efficiency Loss of Mixed Equilibrium Associated with Altruistic Users and Logit-based Stochastic Users in Transportation Network
The efficiency loss of mixed equilibrium associated with two categories of users is investigated in this paper. The first category of users are altruistic users (AU) who have the same altruism coefficient and try to minimize their own perceived cost that assumed to be a linear combination of selfish component and altruistic component. The second category of users are Logit-based stochastic users (LSU) who choose the route according to the Logit-based stochastic user equilibrium (SUE) principle. The variational inequality (VI) model is used to formulate the mixed route choice behaviours associated with AU and LSU. The efficiency loss caused by the two categories of users is analytically derived and the relations to some network parameters are discussed. The numerical tests validate our analytical results. Our result takes the results in the existing literature as its special cases
Capacity constrained stochastic static traffic assignment with residual point queues incorporating a proper node model
Static traffic assignment models are still widely applied for strategic transport planning purposes in spite of the fact that such models produce implausible traffic flows that exceed link capacities and predict incorrect congestion locations. There have been numerous attempts in the literature to add capacity constraints to obtain more realistic traffic flows and bottleneck locations, but so far there has not been a satisfactory model formulation. After reviewing the literature, we come to the conclusion that an important piece of the puzzle has been missing so far, namely the inclusion of a proper node model. In this paper we propose a novel path-based static traffic assignment model for finding a stochastic user equilibrium in which we include a first order node model that yields realistic turn capacities, which are then used to determine consistent traffic flows and residual point queues. The route choice part of the model is specified as a variational inequality problem, while the network loading part is formulated as a fixed point problem. Both problems are solved using existing techniques. We illustrate the model using hypothetical examples, and also demonstrate feasibility on large-scale networks
Bounding the inefficiency of logit-based stochastic user equilibrium
Bounding the inefficiency of selfish routing has become an emerging research subject. A central result obtained in the literature is that the inefficiency of deterministic User Equilibrium (UE) is bounded and the bound is independent of network topology. This paper makes a contribution to the literature by bounding the inefficiency of the logit-based Stochastic User Equilibrium (SUE). In a stochastic environment there are two different definitions of system optimization: one is the traditional System Optimum (SO) which minimizes the total actual system travel time, and the other is the Stochastic System Optimum (SSO) which minimizes the total perceived travel time of all users. Thus there are two ways to define the inefficiency of SUE, i.e. to compare SUE with SO in terms of total actual system travel time, or to compare SUE with SSO in terms of total perceived travel time. We establish upper bounds on the inefficiency of SUE in both situations.Transportation Selfish routing Inefficiency Stochastic user equilibrium