Transformative commercial urban delivery solutions
This research aims to identify and evaluate new solutions for commercial urban deliveries to meet the demand of last-mile and surging e-commerce markets.
Traffic simulation models will be developed using real-world freight demands. Solutions modelled and evaluated will include electric vehicles for night-time deliveries, urban consolidation centres, load pooling, route optimisation, active mode deliveries, autonomous ground vehicles and drones.
The successful completion of this research will result in a number of practical deliverables which can be of direct benefit to commercial urban delivery providers, government agencies and the community at large.
Participants
Project background
The movement of goods in urban areas is an essential part of Australia’s economic activities. Commercial vehicles account for a substantial share of the vehicle fleet and contribute to traffic congestion and emissions particularly in inner city suburbs and areas.
With more people moving into cities, accompanied with surging online, last-mile deliveries and other commerce activities, freight volumes are projected to grow over the next decade. This will result in more commercial vehicles on the road further exasperating congestion and worsening air quality.
Finding new solutions to accommodate the growth of urban freight delivery will be essential to ensuring the quality of urban life in our growing cities.
This research aims to address this problem by identifying, modelling and evaluating a number of solutions that can provide effective, efficient and affordable delivery options that can promote sustainable transport principles, reduce congestion and emissions. The research will identify solutions that will be applicable to all Australian cities.
To demonstrate the feasibility of these new urban delivery solutions, the research will develop a traffic simulation model for Melbourne that can be used as a case study to showcase how these solutions would work and what their impacts will be. Various scenarios will be applied representing different city growth and freight demand patterns, a range of population growth scenarios, fleet composition, and a number of forecast horizons (e.g. short-term to 2025 and long-term up to 2050).
Once calibrated and validated, the model will be used to test the effectiveness and impacts of the proposed solutions in terms of reducing congestion, emissions, delivery times, and cost. Combinations of solutions will also be tested and evaluated as it is expected that converging these solutions would amplify the benefits.
Project objectives
The research aims to identify, model and evaluate a number of solutions that can provide effective, efficient and affordable urban delivery options that can promote sustainable transport principles, reduce congestion and emissions.
The research will identify solutions that are applicable to all Australian cities and jurisdictions with a focused case study for Melbourne. To achieve this, the project will have the following objectives:
- Establish current situation. Develop a good understanding of the current situation of urban freight deliveries in Australian cities with a focus on last-mile deliveries in Melbourne.
- Establish current urban freight demand. Develop a baseline (2020) urban freight demand matrices that show the origins and destinations of urban freight activities and deliveries.
- Identify new urban delivery solutions and interventions. Identify current and emerging trends in urban freight deliveries through desktop studies and stakeholder consultations.
- Develop traffic simulation models. Develop a suitable hierarchy of traffic simulation models for Melbourne for testing and evaluating a range of solutions and interventions.
- Test and evaluate impacts. Apply the simulation models to test the potential interventions and evaluate their impacts using a comprehensive set of key performance measures such as congestion and emissions.
- Disseminate findings and obtain feedback. Develop comprehensive reporting and engagement with stakeholder to obtain feedback and improve research outcomes.
Profile of researcher, Yijie Su
Find out more about this project’s researcher, including what questions the research will answer, a video presentation of the work, the obstacles Yijie has overcome, and what comes next after her PhD. Also hear from her supervisor, Professor Hussein Dia. Read the profile at: Yijie Su – iMOVE PhD student.
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