PRR Project

Summary

1. TASKS TO BE ASSIGNED TO THE PROSPECTIVE EMPLOYEEThe prospective employee will be responsible for conducting advanced research studies concerning multimodal transport planning, that may include the following:Use combined network science and data science tools to identify current and emerging trends on transport for individual and collective modes, technology options and other determinants that shape future passenger and freight transport, addressing different contexts.Analyse and process data of various types (e.g., structured, and unstructured data) from heterogeneous sources to solve transport engineering problems at the strategic, tactical and operational levels and use machine learning methods to detect patterns in the data, to identify inefficiencies and bottlenecks in the operation of transport systems.Explore use of combined behavioural modelling approaches and AI-based methods to analyse ex ante transport solutions, including new mobility services and multimodal/intermodal transport, exploring trade-offs between socioeconomic, environmental and energy related criteria.Contribute to co-develop, test and validate transport solutions sensitive to the mobility and accessibility needs of people and the transport of goods in different geographies.Investigate performance measures to assess transport systems paying special attention on metrics to achieve sustainability in transport and logistics.Assess the impacts of integrated solutions for passenger and freight transport at the national, regional, and local levels, using quantitative and qualitative approaches, supported by a well-defined system of key performance indicators.Apply alternative methods to optimise multimodal transport networks and traffic management, for efficient door-to-door mobility of passengers and freight (from producers to last mile deliveries), to achieve carbon neutrality.Contribute to validated systems for an accurate detection of bottlenecks in transport networks, in order to improve its resilience and performance, enabling pro-active mobility management.Develop predictive and prescriptive transport models for sustainable transport and mobility planning, along with tailored-based solutions to improve the performance of the transport system in specific contexts (e.g., cities).Contribute to enhance policy and performance monitoring of transport programs, plans and projects, along with knowledge dissemination.2. SCIENTIFIC PROFILE REQUIREDTo accomplish the above planned research, LNEC requires a researcher with background and experience in applying data science and AI methods in transportation systems.The researcher should demonstrate a strong interest both on multimodal transport planning, network science and AI methods. She/he should demonstrate interest to work in multidisciplinary teams of research and innovation projects aiming to solve complex problems, in cooperation with other research institutes, while accounting for the research needs of the wide ecosystem of stakeholders that relate to the transportation field.3. RATIONALE TO HIRE FOR THE SCIENTIFIC AREATransport planning needs to respond to the emergence of sustainability and of integration of available (and prospective) transport modes for efficiency purposes. Hence, the use of transportation planning approaches need to rely less on a single (unimodal) perspective and focus more on multimodality/intermodality, e.g. aiming to address an efficient and sustainable combination of different modes along supply chains or low/zero emissions origin-destination routes.The proposed scientific area is aligned with the “Climate Change”, “Circular Economy” and “Industry 4.0” challenges outlined with LNEC’s Research and Innovation (R&I) Strategy 2021-2027, and focuses in the Transportation Department’s R&I priority “Sustainable mobility, transport and new mobility services”.The proposed position is central to ensure continuity of knowledge  in transport planning at LNEC, which counts with only one senior researcher specialized in the field.4. RELEVANCE OF THE SCIENTIFIC PROFILE OF THE PROPOSED POSITION IN THE CONTEXT OF THE STATE-OF-THE-ARTThe transport system is not yet sustainable, and advanced multimodal transport planning tools need to be further explored to support integrated policies for ensuring quality of life of people and enabling the competitiveness of economies.Transport systems are complex networks that are increasingly driven by sustainability goals that require accomplishing multiple long-term targets, while accounting for the spatial and temporal dynamics of the system.Several trends and patterns can be discovered across modes using data science tools, helping to detect opportunities to reduce CO2e emissions, travel delays and improve energy efficiency. New technologies are emerging and expected to change mobility, offering joint business opportunities for the logistics supply chains and integration of services.