Urban logistics face growing complexity as cities seek sustainable development pathways; one solution is integrating freight transportation with public transit. The purpose of this study is to evaluate current practices, identify gaps, and highlight opportunities for advancement in this field. Through a comprehensive literature review guided by four research questions, this study evaluates methodologies, vehicle choices, the application of intermodal containers, and the shared use of public transportation infrastructure for freight delivery. A meticulous search methodology was employed to select references, which were then analyzed and classified into two main tables. Findings reveal a progression from initial pilot projects and cost analyses to sophisticated planning and optimization challenges, with a focus on metro networks and buses. This study uncovers a predilection for certain research types, the utilization of varied transportation modes, underexplored intermodal container use, and an emerging emphasis on transshipment operations. The integration of freight and public transportation within urban settings is identified as a dynamic and diversifying field, with significant potential for contributing to sustainable urban development. We outline nine areas for future research, including the incorporation of external costs and congestion effects into optimization models, and the exploration of unmanned vehicles, thereby laying the groundwork for more inclusive and efficient urban logistics solutions.

Optimizing last-mile delivery operations is an essential component in making a modern city livable, particularly in the face of rapid urbanization, increasing e-commerce activity, and the growing demand for fast deliveries. These factors contribute significantly to traffic congestion and pollution, especially in densely populated urban centers like Casablanca. This paper presents an innovative approach to optimizing last-mile delivery by integrating public transportation into the logistics network to address these challenges. A custom-built environment is developed, utilizing public transportation nodes as transshipment nodes for standardized packets of goods, combined with a realistic simulation of traffic conditions through the integration of the travel time index (TTI) for Casablanca. The pickup and delivery operations are optimized with the proximal policy optimization algorithm within this environment, and experiments are conducted to assess the effectiveness of public transportation integration and three different exploration strategies. The experiments show that scenarios integrating public transportation yield significantly higher mean rewards—up to 1.49 million—and more stable policy convergence, compared to negative outcomes when public transportation is absent. The highest-performing configuration, combining PPO with segmented training and public transport integration, achieves the best value loss (0.0129) and learning stability, albeit with a trade-off in task completion. This research introduces a novel, scalable reinforcement learning framework to optimize pickup and delivery with time windows by exploiting both public transportation and traditional delivery vehicles.

Urban business-to-business distribution in Casablanca relies heavily on light commercial vehicles (LCVs) operating in a constrained street environment where loading/unloading access, intersection capacity, and recurring bottlenecks jointly shape performance and environmental impacts. However, high-resolution freight origin–destination (OD) observations and junction calibration data are limited, which complicates direct estimations of congestion and externalities attributable to commercial activity. This study develops a reproducible, large-scale modeling workflow that couples tour-based freight demand generation in order units with simulation-based traffic assignment (SBA) on a metropolitan network and translates network performance into emissions and monetary losses. Warehouses are modeled as primary producers and commercial activity zones as attractors via sector-tagged production and attraction functions; the resulting order distribution is converted to OD vehicle trips using the tour-based trip generation procedure with the mean targets-per-tour fixed to one to ensure numerical stability, yielding a direct-shipment approximation appropriate for stress–response analysis. Junction impedance is represented through turn-type volume–delay relationships and node-level impedance procedures, and congestion is evaluated using vehicle kilometers traveled/vehicle hours traveled (VKT/VHT)-based indicators, delay-intensity measures, and link/node bottleneck rankings. Across demand-scaling scenarios, VKT increases from 302,159 to 1,017,686 veh·km/day, while network delay rises nonlinearly from 392.5 to 2738.4 veh·h/day, indicating saturation-driven amplification of time losses. The Handbook of Emission Factors for Road Transport (HBEFA)-compatible emission estimates scale with activity: total carbon dioxide (CO₂) increases from 154.1 to 519.5 t/day, and nitrogen oxides (NOx) and particulate matter (PM_2.5) totals rise proportionally under fixed fleet assumptions. Monetizing delay with a purchasing-power-adjusted value-of-time range yields a congestion cost per trip that increases from approximately 0.20 to 0.41 Moroccan dirham, MAD/trip (at 60 MAD/veh·h), consistent with rising delay intensity. Bottleneck extraction shows welfare losses to be structurally concentrated on a small persistent corridor set, led by ‘Boulevard de la Résistance’, with recurrent hotspots including ‘Rue d’Arcachon’ and ‘Rue d’Ifni’. The framework supports policy-relevant reporting of congestion, emissions, and welfare impacts under data scarcity, with explicit sensitivity bounds.

Freight on public transportation offers promising solutions for transporting goods in cities. It utilizes existing infrastructure such as stations and stops, light rails, metro, or other modes like Bus Rapid Transit (BRT). Another method is to utilize the space within vehicles, known as shared passenger and parcel solutions. A well organized and implemented shared passenger and parcel solution can lead to more efficient and environmentally friendly transportation of goods and parcels within cities. The objective of this paper is to attempt to gauge the potential of inter-modal containers in urban freight transportation, a literature review was chosen as the means to achieve the stated objective, and so three research questions were formulated and 24 papers on freight using public transportation published between 2013 and 2023, were chosen, the review process involved the creation of a classification table, enabling the systematic organization and analysis of the selected papers. Our findings reveal that freight on public transportation research is a rich and diverse research field, multiple problem classes are solved including vehicle routing, transshipment between transportation modes has been considered repeatedly and inter-modal container is recognized as main field for future research.

Understanding traffic congestion in urban areas is crucial for ensuring mobility, especially in metropolitan cities of developing countries. This study presents new spatial and temporal data to analyze congestion in Casablanca. Spatial data, collected using QGIS, covers 22 ZIP code areas and includes built environment factors such as land use, road types, and public transport stations. Temporal data consists of 440 randomly generated trajectories per commune, with real-time travel data collected hourly over one week using the Waze Route Calculator. A Python script was used to compute the Travel Time Index (TTI) for each zone. To classify zones based on congestion patterns, we applied fuzzy c-means clustering, allowing for nuanced grouping and interpretation of overlapping characteristics. This dataset supports traffic modeling, simulation, and congestion analysis in developing urban contexts.