  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.
