788 research outputs found
Existence of optima and equilibria for traffic flow on networks
This paper is concerned with a conservation law model of traffic flow on a
network of roads, where each driver chooses his own departure time in order to
minimize the sum of a departure cost and an arrival cost. The model includes
various groups of drivers, with different origins and destinations and having
different cost functions. Under a natural set of assumptions, two main results
are proved: (i) the existence of a globally optimal solution, minimizing the
sum of the costs to all drivers, and (ii) the existence of a Nash equilibrium
solution, where no driver can lower his own cost by changing his departure time
or the route taken to reach destination. In the case of Nash solutions, all
departure rates are uniformly bounded and have compact support.Comment: 22 pages, 5 figure
A destination-preserving model for simulating Wardrop equilibria in traffic flow on networks
In this paper we propose a LWR-like model for traffic flow on networks which
allows one to track several groups of drivers, each of them being characterized
only by their destination in the network. The path actually followed to reach
the destination is not assigned a priori, and can be chosen by the drivers
during the journey, taking decisions at junctions.
The model is then used to describe three possible behaviors of drivers,
associated to three different ways to solve the route choice problem: 1.
Drivers ignore the presence of the other vehicles; 2. Drivers react to the
current distribution of traffic, but they do not forecast what will happen at
later times; 3. Drivers take into account the current and future distribution
of vehicles. Notice that, in the latter case, we enter the field of
differential games, and, if a solution exists, it likely represents a global
equilibrium among drivers.
Numerical simulations highlight the differences between the three behaviors
and suggest the existence of multiple Wardrop equilibria
Continuity of the Effective Path Delay Operator for Networks Based on the Link Delay Model
This paper is concerned with a dynamic traffic network performance model,
known as dynamic network loading (DNL), that is frequently employed in the
modeling and computation of analytical dynamic user equilibrium (DUE). As a key
component of continuous-time DUE models, DNL aims at describing and predicting
the spatial-temporal evolution of traffic flows on a network that is consistent
with established route and departure time choices of travelers, by introducing
appropriate dynamics to flow propagation, flow conservation, and travel delays.
The DNL procedure gives rise to the path delay operator, which associates a
vector of path flows (path departure rates) with the corresponding path travel
costs. In this paper, we establish strong continuity of the path delay operator
for networks whose arc flows are described by the link delay model (Friesz et
al., 1993). Unlike result established in Zhu and Marcotte (2000), our
continuity proof is constructed without assuming a priori uniform boundedness
of the path flows. Such a more general continuity result has a few important
implications to the existence of simultaneous route-and-departure choice DUE
without a priori boundedness of path flows, and to any numerical algorithm that
allows convergence to be rigorously analyzed.Comment: 12 pages, 1 figur
Existence of simultaneous route and departure choice dynamic user equilibrium
This paper is concerned with the existence of the simultaneous
route-and-departure choice dynamic user equilibrium (SRDC-DUE) in continuous
time, first formulated as an infinite-dimensional variational inequality in
Friesz et al. (1993). In deriving our existence result, we employ the
generalized Vickrey model (GVM) introduced in and to formulate the underlying
network loading problem. As we explain, the GVM corresponds to a path delay
operator that is provably strongly continuous on the Hilbert space of interest.
Finally, we provide the desired SRDC-DUE existence result for general
constraints relating path flows to a table of fixed trip volumes without
invocation of a priori bounds on the path flows.Comment: 21 page
Unilateral Altruism in Network Routing Games with Atomic Players
We study a routing game in which one of the players unilaterally acts
altruistically by taking into consideration the latency cost of other players
as well as his own. By not playing selfishly, a player can not only improve the
other players' equilibrium utility but also improve his own equilibrium
utility. To quantify the effect, we define a metric called the Value of
Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the
altruistic user to the equilibrium utility he would have received in Nash
equilibrium if he were selfish. We show by example that the VoU, in a game with
nonlinear latency functions and atomic players, can be arbitrarily large. Since
the Nash equilibrium social welfare of this example is arbitrarily far from
social optimum, this example also has a Price of Anarchy (PoA) that is
unbounded. The example is driven by there being a small number of players since
the same example with non-atomic players yields a Nash equilibrium that is
fully efficient
Nash Equilibria, collusion in games and the coevolutionary particle swarm algorithm
In recent work, we presented a deterministic algorithm to investigate collusion between players in a game where the players’ payoff functions are subject to a variational inequality describing the equilibrium of a transportation system. In investigating the potential for collusion between players, the diagonalization algorithm returned a local optimum. In this paper, we apply a coevolutionary particle swarm optimization (PSO) algorithm developed in earlier research in an attempt to return the global maximum. A numerical experiment is used to verify the performance of the algorithm in overcoming local optimum
The Price of Anarchy in Transportation Networks: Efficiency and Optimality Control
Uncoordinated individuals in human society pursuing their personally optimal
strategies do not always achieve the social optimum, the most beneficial state
to the society as a whole. Instead, strategies form Nash equilibria which are
often socially suboptimal. Society, therefore, has to pay a price of anarchy
for the lack of coordination among its members. Here we assess this price of
anarchy by analyzing the travel times in road networks of several major cities.
Our simulation shows that uncoordinated drivers possibly waste a considerable
amount of their travel time. Counterintuitively,simply blocking certain streets
can partially improve the traffic conditions. We analyze various complex
networks and discuss the possibility of similar paradoxes in physics.Comment: major revisions with multicommodity; Phys. Rev. Lett., accepte
- …