A novel technology in freight transportation for improvement of the environmental impact

New technological innovations of eco-friendly vehicles combined with the usage of renewable energy sources showed significant results in mitigating emissions. In this thesis, we consider the eHighway system, a recent technology based on electrified roads. It is designed to supply new hybrid trucks, i.e. electric overhead catenary (OC) trucks, which are connected to overhead power lines through a pantograph positioned at the top of the vehicle. The eHighway implementation can result in lower emission vehicles’ rate since the vehicles are operating with electric mode. Therefore, in this thesis, we present a single-level multi-objective network design model and a bi-level multi-objective network design model considering a novel technology, the eHighway system. The proposed models investigate the opportunities of adopting eHighways and evaluating its environmental benefits considering limited budget resources for infrastructure electrification. Additionally, the models could be considered as useful tools for decision-makers in eHighway network planning and design. For developing both models, a simulation model presented in the literature was used to calculate the number of traction substations needed for arc electrification according to hybrid trucks flows. As a first approach, in the case of the single-level multi-objective network design model, we propose a formulation including three objectives: minimisation of infrastructure and environmental costs, maximisation of average traffic density of OC hybrid trucks on electrified arcs. The Pareto optimisation approach is considered for a comprehensive analysis of all possible solutions according to different criteria weights. This model served as a basis to construct a bi-level multi-objective network design model that also considers the possibility of increasing the capacity of electrified arcs to improve overall network performances. Thus, in the case of the bi-level network design model we considered four objectives in the upper level related to the minimisation of the total Overhead Catenary (OC) hybrid trucks’ travel time, infrastructure and environmental costs and maximisation of average traffic density of OC hybrid trucks on electrified arcs. The decision of the upper level depends on the output of the lower level which is formulated as a Stochastic Users Equilibrium traffic assignment based on a fixed-point problem. Moreover, the proposed bi-level network design model deals not only with finding the set of the arcs to be electrified but also with the capacity expansion of the electrified arcs for improving the performance of the overall system. Additionally, genetic algorithms were used as a solution approach, which demonstrated the effectiveness in finding the near-optimal results in a reasonable computation time. The proposed models have been tested on a medium-sized network and the Sioux-Falls network. In particular, we analysed the Pareto front obtained from the single-level model, where non-dominant solutions are identified according to the three considered criteria. Moreover, a sensitivity analysis is carried out for the bi-level problem in terms of criteria weights and the percentage of hybrid vehicles using the eHighway system. Numerical results quantified the environmental improvement we can obtain by using the eHighway system in both models, which can be a basis for making decisions regarding the adoption of this new technology.