Shaping E-roads Efficiency for Freight Automation

• Applicant: Professor Dr. Constantinos Antoniou
• Subject Area: City Planning, Spatial Planning, Transportation and Infrastructure Planning, Landscape Planning ; Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 551933463

1) Wider research context The necessity of reducing CO2 emissions is one of the main tasks on the global agenda. Guided by UE policy to neutral CO2 mobility and transportation the Austrian and German Governments initiated their road maps to reach that goal. In such situation the hybrid and electric trucks are considered one of the ways to reach zero CO2 freight transportation services. Automation of the transportation process is expected to contribute to the operation efficiency. Whilst the prospects are enormous, the expected operational efficiency evaluation, and the infrastructure facilities that should be provided within the system, still demand justification. 2) Objectives. The SEE-FAr project aims to evaluate the complex impact of freight vehicles automation and electrification distinguishing the charging options between e-roads and plug-in to promote decarbonized and cost- efficient freight transportation. The project has four objectives: (i) to identify the intercity freight delivery patterns distinguishing the tours and round trips with focus on regular and random routes; (ii) to justify the conditions of the plug-in and e-roads efficiency compared with fossil fuel-based freight deliveries; (iii) to enhance the state-of-the-art framework of the agent-based modeling for freight intercity deliveries regarding e-roads and plug-in charging options; (iv) to classify the expected impacts due to the freight vehicles automation and decarbonization. 3) Methods. Probability Theory and Mathematical Statistics to be used for the GPS data processing and evaluation of the current state delivery patterns for Bavaria and Austria regions. The Samling Theory will complement the mentioned theories to evaluate the representativeness of the formed samples. Analytical Models Analysis Theory to be utilized for the formalizing the cost-efficiency of the e-roads and plug-in technologies. To depict the energy consumption by the e-vehicles the Mixed-integer Nonlinear Programming will be used. The consideration of Transport Economics Theory will be taken into account to model the interaction between demand and supply subsystems in a case of deliveries decarbonization. 4) Level of originality. The first research question lies in the field of estimating the complex impact of freight deliveries due to their automation and electrification. The considered complex impact covers energy consumption for different charging options such as plug-in and e-roads, external cost evaluation based on emissions reduction, and cost efficiency with consideration of the energy market conditions. The study’s second research question arises – the freight delivery patterns to be revealed based on vehicles’ O-D matrices. The big data approach using the GPS data guarantees the necessary level of detail and robustness of the estimations. 5) Primary researchers involved The research will be led by Dr. Susilo and Dr. Antoniou who are experts in transport systems studies.

• DFG Programme: Research Grants
• International Connection: Austria
• Cooperation Partner: Professor Dr. Yusak Susilo