Abstract

Highly automated transport systems play an important role in the transformation towards a digital society, and planning the optimal routes for a set of fleet vehicles has been proved useful for improving the delivered services. Traditionally, routes are planned beforehand. However, with the advent of autonomous urban transport systems (e.g. autonomous cars), possible obstructions of tracks due to traffic congestion or bad weather conditions need to be handled on the fly. In this paper we tackle the problem of dynamically computing routes of vehicles in urban lines in the presence of potential obstructions. The problem is formulated as an integer linear optimization problem. The proposed algorithm will assign routes to vehicles dynamically, considering the track segments that are no longer available and the positions of the vehicles in the urban area. The recomputed routes guarantee the minimal waiting time for passengers. Safety of the computed routes is also guaranteed.

Abstract

In this paper we study traffic engineering in Multiprotocol Label Switching (MPLS) networks. We consider off-line computation of disjoint working and restoration paths where path rerouting is used as the restoration scheme. We first compute maximum number of paths for each demand such that paths satisfy diversity requirements. Using the generated path set we study four different approaches for selecting working and restoration paths, and formulate each method as an Integer Linear Programming (ILP) problem. The first two methods treat working and restoration path design problems separately. We propose two new path design methods that jointly optimize the working and restoration paths. A traffic uncertainty model is developed in order to evaluate performances of these four approaches based on their robustness with respect to changing traffic patterns. We compare these design approaches based on the number of additional demands carried and the distribution of residual capacity over the network. It is shown through simulations that the weighted load balancing method proposed in this paper outperforms the other three methods in handling traffic demand uncertainty.