Urban freight is growing fast, and its adverse effects bring consequences for the residents, the environment, and the liveability of cities. Although understanding its dynamics has become a priority for governments, the multiplicity of actors with conflicting objectives makes it a significant urban planning challenge.
A study by Juan E. Muriel et al. focuses on one type of on-street parking infrastructure for urban freight: loading zones. Although they are considered one of the most important parking strategies (loading zones) to control freight traffic, increasing pressure for more pedestrian space, public transport, sustainable mobility, and the surge in urban deliveries have reduced their size, quantity, and availability. These factors have increased the externalities generated by delivery vehicles (congestion, accidents, noise, pollution, and visual intrusion), reduced the liveability of urban areas, and increased the difficulty for cities to improve urban traffic.
To address this problem, the researchers developed a simulation-optimization framework to evaluate urban logistics strategies that balance the courier’s (walking and cruising time) and the city’s (traffic flow variability) objectives. The methodology considers the decision-making processes of the road users, their interaction, and the variability of stochastic parameters (traffic conditions, competition, cruising, and illegal parking). To optimize the routes of delivery vehicles, we developed an evolutionary algorithm that minimizes the trucking and walking distances and used commercial software to re-optimize mid-route decisions.
The model is applied to represent the Melbourne central business district (CBD), a common network structure among many cities, simulating realistic conditions. Results show that is possible to devise win-win solutions that favor all parties in the transport network. The analysis showed that understanding the complexity of urban freight transport makes it possible to design and manage better logistic strategies that can significantly reduce transport-related externalities.
Source:
Juan E. Muriel, Lele Zhang, Jan C. Fransoo, Roberto Perez-Franco, Assessing the impacts of last mile delivery strategies on delivery vehicles and traffic network performance, Transportation Research Part C: Emerging Technologies, Volume 144, 2022, 103915, ISSN 0968-090X,
https://doi.org/10.1016/j.trc.2022.103915.