Managing all the mobility and transportation services with autonomous vehicles for users
of a smart city requires determining the assignment of the vehicles to the users and their
routing in conjunction with their speed. Such decisions must ensure low emission, efficiency,
and high service quality by also considering the impact on traffic congestion caused by other
vehicles in the transportation network.
In this paper, we first propose an abstract trilevel multi-objective formulation architecture
to model all vehicle routing problems with assignment, routing, and speed decision
variables and conflicting objective functions. Such an architecture guides the development
of subproblems, relaxations, and solution methods. We also propose a way of integrating
the various urban transportation services by introducing a constraint on the speed variables
that takes into account the traffic volume caused across the different services. Based on the
formulation architecture, we introduce a (bilevel) problem where assignment and routing are
at the upper level and speed is at the lower level. To address the challenge of dealing with
routing problems on urban road networks, we develop an algorithm that alternates between
the assignment-routing problem on an auxiliary complete graph and the speed optimization
problem on the original non-complete graph. The computational experiments show the effectiveness
of the proposed approach in determining approximate Pareto fronts among the
conflicting objectives.
Citation
T. Giovannelli and L. N. Vicente, An integrated assignment, routing, and speed model for roadway mobility and transportation with environmental, efficiency, and service goals Convergence rates of the stochastic alternating algorithm for bi-objective optimization, ISE Technical Report 22T-013, Lehigh University.