Analysis of Goods Delivery Models in Urban Environments for Improving Logistics Activities: The Case of Rijeka City

Abstract

This paper analyzes models of goods delivery to city centers, with a specific focus on the city of Rijeka. Urban areas are increasingly facing problems such as traffic congestion, lack of delivery space, and negative environmental impacts. The aim of the research is to examine existing delivery models and propose sustainable solutions that include consolidation centers, alternative fuel vehicles, and smart technologies. The paper presents three main delivery models: using consolidation centers, environmentally friendly vehicles, and modular BentoBox systems. Based on traffic data analysis and surveys with carriers and business entities, it was found that most deliveries are carried out by large diesel vehicles, which often face difficulties due to the lack of designated unloading zones. Building on these findings, several improvement scenarios were developed, including the introduction of one or two consolidation centers and the use of eco-friendly vehicles. The results indicate that the proposed models have the potential to reduce the number of large freight vehicles in the city center, ease traffic congestion, and lower emissions. However, quantitative confirmation of these effects will require the development and application of simulation models. This study therefore serves as a foundation for such future research.

1. Introduction

Urban centers today represent key hubs of logistical activities, as they host a high concentration of economic, commercial, and service-oriented operations. This concentration results in increased demand for efficient and reliable delivery services, which must meet the needs of a large number of businesses and end users within a very limited space. At the same time, infrastructural constraints such as narrow streets, a lack of parking spaces, and traffic congestion further complicate the organization of distribution processes, placing pressure on logistics operators, public authorities, and city residents [1].

In parallel with these challenges, the development of modern technologies such as global positioning systems (GPS), cloud computing, the Internet of Things (IoT), and intelligent transport systems (ITS) enables more precise planning, tracking, and management of delivery vehicles and goods flows [2]. These technologies significantly enhance the efficiency and transparency of delivery operations, reduce delivery times, and allow for better adaptation of distribution to real-time traffic conditions [3]. In addition to technological advancements, increasing attention is being given to the sustainability of urban transport, with environmental friendliness becoming an imperative. Air pollution, noise, and CO₂ emissions negatively impact citizens’ health and quality of life in cities [4]. Therefore, the potential use of alternative fuels, electric vehicles, and consolidation centers is increasingly being viewed as a way to simultaneously improve logistical efficiency and reduce the environmental footprint of urban deliveries [5]. Recent developments in urban logistics emphasize the integration of advanced computational methods, such as deep reinforcement learning and multi-lane traffic flow models, to address last-mile delivery and urban traffic challenges. For example, El Amrani et al. [6] present a deep reinforcement learning framework for optimizing last-mile delivery by integrating public transport and real-time traffic data. Similarly, Zeng et al. [7] propose a multi-value cellular automata model for multi-lane traffic flow, which enables detailed simulation and analysis of urban congestion phenomena. Recent research in urban logistics highlights the importance of integrating public transportation into the logistics network and applying deep learning methods for optimizing last-mile delivery [6]. Such tools enable more efficient distribution of goods, reduction of emissions and costs, and better adaptation to real traffic conditions, directly addressing the challenges identified in this work.

These trends highlight the importance of redefining urban delivery models through the integration of smart and sustainable solutions in order to respond to contemporary challenges and achieve economic, traffic, and environmental sustainability goals [8].

In addition to presenting current delivery challenges and existing models in urban centers, this study aims to highlight the essential data requirements for conducting detailed simulations using specialized software tools. These simulations are critical for accurately assessing and comparing the effectiveness of various delivery scenarios. However, even without engaging in complex simulation processes, significant improvement in delivery activities can be achieved through enhanced organization and coordination among all stakeholders involved in the urban delivery ecosystem. By fostering collaboration among carriers, recipients, residents, and policymakers, the efficiency and sustainability of city center logistics can be considerably improved. This approach aligns with the findings of recent studies, including the paper by Jardas et al. [9], which employs a multi-actor multi-criteria analysis (MAMCA) to evaluate delivery flows and stakeholder priorities in urban settings. Their conclusions underscore the importance of stakeholder engagement and the integration of technical, economic, social, and organizational criteria in optimizing urban logistics without reliance solely on simulation models. Jardas et al. [9] have demonstrated the usefulness of simulation models in evaluating delivery scenarios and quantifying their potential impacts on emissions, traffic congestion, and costs. However, such approaches require a wide range of detailed input data that is often not readily available, especially in small- and medium-sized European cities. This limitation creates a research gap: before reliable simulations can be carried out, it is necessary to establish what types of data, methodological frameworks, and stakeholder insights are essential for credible modeling. Unlike studies that focus directly on simulation, this paper investigates the prerequisites for conducting such analyses. By analyzing traffic data, conducting surveys with carriers and business entities, and developing scenario-based delivery models, this study identifies the critical data requirements and organizational aspects needed to support advanced simulations in the future. In doing so, it not only addresses the specific case of the city of Rijeka but also provides a methodological foundation that can be adapted to other urban contexts, thereby complementing existing simulation-based research.

The research problem arises from the need for better organization of goods transport within urban areas, with particular emphasis on reducing traffic congestion, harmful emissions, and the rationalization of logistical processes. Numerous delivery activities, inconsistent use of entry/exit points, and high resource consumption place pressure on the city’s traffic system, environment, and economy. A particular challenge is the implementation of sustainable delivery models, considering the high costs of acquiring eco-friendly vehicles and the need for infrastructure such as electric charging stations. The aim of this research is to thoroughly analyze existing models of urban delivery logistics, using the city of Rijeka as a case study. As part of this, the research will assess traffic load and the spatial distribution of delivery activities in order to identify key congestion points and opportunities for optimization. Additionally, special emphasis is placed on evaluating the potential for implementing consolidation centers and environmentally friendly vehicles, with the goal of enhancing the sustainability of urban logistics processes. Based on the analysis, the research aims to propose a sustainable urban delivery solution that will simultaneously reduce costs, emissions, and traffic congestion, while contributing to the improvement of citizens’ quality of life and the city’s business environment.

2. Models of Goods Delivery to City Centers

Logistics distribution towards urban centers is essential, but the transport capacity within cities is high as demand increases. Global positioning systems and similar technologies streamline deliveries. Different delivery organization models are direct delivery, transit point, supply to customer distribution, and self-pickup. Advancements in IoT, cloud computing, and intelligent transport systems are critical for an efficient delivery management. Thus, the authors note that implementing sustainable regulations like banning diesel vehicles, electric vehicle incentives, or electric charging stations reduces emissions and improves city air quality.

2.1. Distribution Model Using a Consolidation Center

Urban distribution centers are vital for the organization and connection of goods within city areas, particularly in growing urban agglomerations [10]. These centers allow for the consolidation of shipments to facilitate more efficient distribution tailored to delivery times, cargo type, and distribution routes [11]. The goal is to reorganize smaller shipments into larger units to reduce transport and storage costs and optimize goods positioning relative to suppliers [12]. Freight consolidation reduces the need for large freight vehicles in city centers, decreases transportation costs, the number of deliveries, and delivery times, and improves delivery efficiency. Encouraging the use of smaller delivery vehicles results in savings for transportation companies and better service for businesses [13]. Beyond economic benefits, consolidation centers reduce emissions and traffic congestion in urban areas. Integrating sustainable delivery approaches maximizes vehicle capacity and brings economic and environmental advantages [13]. Additional consolidation centers may be required due to the specific configuration of metropolitan areas or a large customer base, confirming the importance of this approach, as explained in Figure 1.

The collaboration between recipients and freight carriers forms the foundation for the future development of consolidation centers, from which the following operational models may emerge [14]:

a

Consolidated delivery to all stores of the same customers with multiple suppliers, such as supermarkets.

b

Consolidated delivery to individual businesses located within the same geographic area.

Each delivery model from a consolidation center leverages the full capacity of vehicles, reducing the number of trips and enabling users to concentrate on core activities. A primary challenge is the efficient communication between users and suppliers to minimize delivery times [12]. Key to this model is collaboration on aligning delivery schedules, packaging, and handling sensitive products. Deliveries from consolidation centers frequently employ eco-friendly vehicles, optimizing distribution from remote areas [15]. This model also facilitates product returns, recycling, and the management of waste and packaging.

The functions of these centers include reducing freight traffic, enhancing operational efficiency, and minimizing environmental impact through the use of smaller vehicles, thereby improving customer service. They provide services such as consolidation, cross-docking, short-term storage, replenishment, and additional services like quality control and returns management. Consolidation centers enable high-quality delivery without extensive warehouse requirements, which is especially beneficial for seasonal sales [3]. Information and communication technologies increase visibility across the supply chain, reduce inventory losses, and enhance competitiveness [16]. The sustainability of these centers depends on public sector support, including funding, subsidies, and environmental initiatives. Proximity to logistics hubs is essential for efficient and timely deliveries.

2.2. Delivery Model Using Environmentally Friendly Vehicles

Large cities face challenges of air pollution and CO₂ emissions due to the concentration of vehicle traffic. Trucks often cause illegal parking during deliveries. Eco-friendly vehicles reduce negative environmental impacts, such as noise and emissions, by using alternative fuels such as liquefied and compressed natural gas, biofuels, electricity, and hydrogen [17].

The introduction of eco-friendly vehicles faces high initial costs, lack of charging stations, low battery reliability, and reduced productivity. Public sector support is essential for their implementation through tax breaks, subsidies, special loading zones and bus lanes, and financing of alternative fuel infrastructure [18]. This can encourage the wider use of eco-friendly technologies and reduce the advantage of conventional vehicles. Some cities use small electric vehicles for distribution from remote warehouses on the outskirts of the city to the center [19]. The distribution of goods from consolidation centers will be key for the future, significantly improving the quality of life by reducing pollution and noise [20].

2.3. Modular Bento Box Model

The Modular BentoBox is a delivery system designed for smaller packages in urban centers. Customers use a card and PIN to access a designated compartment. Delivery notifications are sent via SMS or email, and parcels can be collected within five working days. Each package is labeled with a barcode before being placed in the compartment.

The Modular BentoBox model offers several advantages [21]:

• Separation of customer orders from logistics operators’ deliveries.
• Reduction in the number of trips, as goods are unloaded at a single location rather than door-to-door.
• Each customer is assigned a unique code, preventing delivery errors.
• Operators can consolidate undelivered packages into a single compartment, freeing up space for new shipments and ensuring uninterrupted station operation.
• Simultaneous use by multiple carriers, with a specific number of modules allocated to each carrier.
• Any delivery vehicle can replenish the compartments, enabling multiple sections of the BentoBox to be serviced in a single trip.

These systems are centrally managed through mobile devices equipped with barcodes and RFID technology for tracking deliveries. The Modular BentoBox reduces delivery costs, stimulates consumption, and provides economic benefits [22]. Remote monitoring from a central warehouse ensures security and keeps customers informed about their shipments. Active tags enable logistical control, including delivery tracking [23]. Active tags are electronic devices equipped with their own power source (usually a battery) that emit a signal at regular intervals. These tags send data such as the location or movement of goods to a receiver, enabling real-time tracking and monitoring throughout the delivery process. BentoBox simplifies delivery processes, enhances customer service through online communication, and facilitates nighttime deliveries as well as the use of bicycles or small electric vehicles [21]. Customers can retrieve their shipments independently with prior delivery notifications. Before implementation, it is necessary to analyze the financial feasibility, operational, and technical feasibility of the BentoBox system in practice [24].

3. Input Data Required for Traffic Analysis and Analysis of Delivery Activities Within the City Center

This research paper focuses on the evaluation of the valuation model of goods delivery in urban centers, with Rijeka as an example. Rijeka is an important economic, cultural and transport center with a population between 100,000 and 250,000 inhabitants. According to energy analyses, the share of CO₂ from the transport sector amounts to 175,224 tCO₂, or 46% of total emissions [25]. The city has committed to reducing greenhouse gas emissions and energy consumption by 20% by 2030, with the transport sector contributing 46% of total CO₂ emissions. The analysis will focus on the narrower center of Rijeka, from Piramida to Cambierie Street, collecting detailed data on traffic, business entities and vehicles entering the city center (Figure 2).

According to the 2021 census, Rijeka has a population of 107,964, while the area observed in the study represents slightly more than 10% of the city’s total surface, with approximately 12,000 residents. Urban traffic is managed by the company Rijeka plus d.d., which is responsible for maintaining unclassified roads, public traffic areas, and traffic signaling. Vehicle entry into the city center is monitored using counters located at key access points.

Figure 3 illustrates the locations where vehicle entry into the city center is monitored. The red dots indicate the following locations: Krešimirova Street (R6), Vukovarska Street (R38), Street 1. Maja (R40-41), Laginjina Street (R46-47), Street Franje Račkog (R24-25), Strossmayerova and Križanićeva Streets (R20-21), and D404 Road (R89).

Data was processed to display the hourly vehicle counts for the week of 5–9 February 2025. The average number of vehicles entering and exiting on a working day is presented in the following table.

Table 1. Average number of vehicles in a working day by entrances and exits. Source: Created by authors based on data obtained from Rijeka plus d.d.

Time	R6 KREŠIMIROVA	R38 VUKOVARSKA	R40-41 1. MAJA	R24-25 F. RAČKOG	R89 D404	R20-21 Strossmayerova-Križanićeva
0–1	56	56	30	21	5	92
1–2	44	25	23	10	5	58
2–3	17	19	15	9	2	33
3–4	20	26	19	6	4	42
4–5	58	42	35	18	9	91
5–6	217	160	111	69	48	317
6–7	462	548	312	260	218	877
7–8	1035	784	488	570	515	1373
8–9	735	772	380	319	312	1216
9–10	539	572	396	254	242	1117
10–11	539	630	406	215	197	1176
11–12	604	644	405	231	173	1089
12–13	590	625	380	259	205	1202
13–14	603	664	434	268	178	1164
14–15	565	572	369	271	187	1199
15–16	660	691	410	309	211	1261
16–17	606	587	397	328	226	1242
17–18	533	616	327	260	170	1101
18–19	472	593	359	217	171	1001
19–20	444	479	289	150	114	931
20–21	301	326	195	97	66	787
21–22	273	216	127	71	38	499
22–23	171	138	112	65	30	419
23–24	111	95	50	25	12	214
TOTAL	9653	9880	6069	4302	3338	18,501

shows the average daily number of vehicles per hour at the R6 entry point: Krešimirova Street. The highest number of vehicles enters between 7:00 and 9:00 a.m. accounting for nearly 18% of the total daily traffic or 30% of the working hours. During working hours, from 7:00 a.m. to 5:00 p.m., 66% of vehicles enter the city center. Due to a malfunction in the exit lane vehicle counter, a comparison of outbound traffic is not possible.

Furthermore, Table 1 presents the average daily number of vehicles per hour at the R38 entry point: Vukovarska Street. The highest number of vehicles enters between 7:00 and 9:00 AM, making up nearly 16% of the daily traffic or 24% of the total working hours. During working hours, from 7:00 a.m. to 5:00 p.m., 66% of vehicles enter the city center.

The table also shows a consistent daily flow of vehicles at the R40-41 entry point: Ulica 1. Maja, with peak activity occurring between 7:00 and 8:00 a.m., during which the highest number of entries is recorded. Between 7:00 AM and 5:00 p.m., 59% of vehicles enter the city center.

Additionally, the average daily number of vehicles per hour at the R40-41 exit point: Ulica 1. Maja highlights that the largest number of vehicles leave the city center between 3:00 and 6:00 p.m., coinciding with the end of the workday and increased commuting.

It is noted that the highest number of vehicles enters the city center at the R24-25 entry point: Ulica Franje Račkog between 7:00 and 9:00 a.m., accounting for nearly 20% of the total traffic during that time frame or 28% of the working hours. Within working hours, from 7:00 a.m. to 5:00 p.m., 70% of vehicles enter the city center, while the largest number of vehicles exit between 3:00 and 5:00 p.m., representing nearly 20% of the total daily traffic.

A relatively steady number of vehicles is observed at the R20-21 entry point (Strossmayerova and Križanićeva Streets) throughout the day, with peak activity occurring between 7:00 and 8:00 a.m., when the highest influx of vehicles is recorded. During working hours, from 7:00 a.m. to 5:00 p.m, 65% of the total daily traffic enters the city center via this entry point.

The highest influx of vehicles into the city center at the R89 entry point (D404) is observed between 7:00 and 9:00 a.m., accounting for approximately 22% of the total daily traffic or 30% of the working hours. During working hours, from 7:00 a.m. to 5:00 p.m., up to 73% of vehicles enter the city center through this entry point.

Chart 1 shows the proportion of entries into the city center relative to the total number of vehicles, which averages 53,746 per day. Data for the R46-47 entry point: Laginjina Street is unavailable by the hour. The most frequented are the eastern entry points, such as R20-21: Strossmayerova and Križanićeva Streets (36%), as well as R89: D404 and R24-25: Ulica Franje Račkog (48%). Western entry points, such as R6: Krešimirova Street, R38: Vukovarska Street, and R40-41: Ulica 1. Maja, account for 46% of the total entries. There are approximately 80 delivery locations with over 200 spots in total, as shown in Figure 4.

4. Analysis of Delivery Activities

The analysis of the current state of delivery activities in Rijeka (Status Quo model) included a survey of carriers and business entities. Carriers who deliver to the center of Rijeka have their headquarters and warehouses at three key locations: the Kukuljanovo industrial zone, Osječka Street, and Tome Strižića Street. These locations serve as the starting points for deliveries to the city center, as shown in Figure 5.

A total of 11 surveys were conducted, covering 50% of the carriers delivering to the city center. Collectively, they operate 358 delivery vehicles. Other contacted carriers did not participate, as their deliveries depend on specific orders. Apart from two carriers who provide delivery services across the entirety of Croatia, all carriers surveyed deliver to the city center of Rijeka. As shown in Chart 2, the survey results indicate that carriers use all entry points to the city center nearly equally.

There are over a thousand commercial premises in the studied area (according to data from the Department of Municipal Services). After excluding entities such as sports clubs, associations, and embassies, 524 business entities remain. Of these, 361 use delivery services, representing nearly 70%, as shown in Chart 3.

All streets in the city center were covered by the survey. A total of 61 business entities from each street were surveyed. The only entity not surveyed was Robna Kuća Ri (Riva 6), as they have their own delivery points and independently organize the time and method of delivery.

In the observed area, 361 business entities utilize delivery services. A total of 113 entities were surveyed, representing 31%. The remaining entities were either unwilling to complete the survey or declined to participate in the research.

From Figure 6, it can be concluded that the largest number of entities is located in zone 2,4 (50), which represents 34% of the total surveyed. It should also be emphasized that the highest number of deliveries takes place in this zone. Chart 4 shows the distribution by zones.

Carriers make deliveries every working day. The analysis of the survey shows that the delivery is evenly distributed during the working days of the week, which is shown in Chart 5.

Economic entities answered the same question, and Chart 6 shows that the results are practically the same as the responses of the transport company.

During normal business hours between 7 a.m. and 5 p.m., deliveries are made in 95% of cases, as shown in Chart 7.

The same question was asked to economic entities and the results are identical to those in Chart 7. The average time from the point of departure to the delivery point is 10–20 min for 90% of carriers, and the vehicle’s stay at the delivery point also lasts the same amount of time, as can be seen in Chart 8.

Regarding the type of goods, food and frozen goods are most often delivered, as shown in Chart 9. Delivering mostly food and frozen goods has specific logistics implications. These products require temperature-controlled transport and storage to maintain quality and safety. Frozen goods need refrigerated vehicles, careful handling, and timely delivery to prevent spoilage. This also affects route planning, inventory management, and operational costs.

Goods are unloaded manually or using handcarts, with forklifts occasionally employed. This indicates predominantly smaller quantities of goods being unloaded. Carriers deliver goods to city centers exclusively using large delivery vehicles or heavy freight vehicles, such as trucks and semitrailers. Chart 10 clearly shows that 60% of deliveries are carried out with such vehicles.

All vehicles use diesel fuel. The survey included carriers operating a total of 358 delivery vehicles.

One of the main issues in delivery activities is the lack of available designated delivery locations. According to the survey, 73% of carriers frequently encounter the unavailability of suitable delivery spots, as shown in Chart 11.

Carriers manage to find an available designated delivery parking spot in only a quarter of cases. Consequently, they are often forced to violate traffic regulations to complete deliveries, as illustrated in Chart 12.

Chart 11 and Chart 12 indicate that traffic congestion in the observed area is largely caused by poorly organized delivery activities, which contribute to increased emissions of harmful gases and elevated noise levels.

Interestingly, when carriers were asked about the possibility of making deliveries at different times, only 27% of respondents answered positively, as clearly shown in Chart 13.

In contrast, business entities showed a willingness to accept delivery services at different times of the day, with as many as 76% expressing readiness for deliveries during later hours, as shown in Chart 14.

The analysis of working hours for carriers and business entities in the city reveals significant differences. Most carriers operate under indefinite contracts from 7:00 a.m. to 5:00 p.m., while business entities often work until 8:00 p.m., particularly hospitality establishments, shops, and service providers. Carriers face challenges when delivering to the city center, including a lack of designated delivery spots, issues with parking freight vehicles, simultaneous deliveries causing congestion, and the absence of penalties for parking in delivery areas. These problems often result in traffic violations, such as blocking bus stops or vehicles, leading to delays and dissatisfaction among all traffic participants.

5. Proposal of a Model to Improve Delivery Activities Within the City of Rijeka

This chapter analyzes several delivery activity scenarios in the city center, based on the previous chapter. The scenarios include: the current delivery model, a model with a single consolidation center near the city center, a model with two consolidation centers near the city center, delivery using eco-friendly vehicles from a single consolidation center (according to scenario 2 in

Table 2. Possible scenarios for developing delivery activities in the city center. Source: Created by the authors.

Scenarios
Abbreviation	Description
Scenario 1	Status quo
Scenario 2	Delivery from one consolidation left near the city left
Scenario 3	Delivery from two consolidation lefts near the city left
Scenario 4	Delivery using eco-friendly vehicles from one consolidation left (scenario 2)
Scenario 5	Livability model

), and the livability model [9].

A consolidation center is a facility located near the city center or retail outlets where shipments are grouped for further distribution. The location is often selected based on the gravity center method, which can serve as a basic approximation in more complex models, although it does not take into account infrastructure systems, labor costs, inventory, and other key factors. When selecting the optimal location, it is important to use methods that align mathematical advantages with practical operational challenges [5].

It is necessary to define appropriate input data when using the aforementioned method, such as [1]:

• X and Y coordinates
• Volume of goods being transported
• Unit transport cost per kilometer distance.

The distances $d_i$ from individual carriers to the gravity center and each boundary point can be expressed using the Pythagorean theorem. The formula for calculating the distance is as follows:

$$d_i=K·{\left[{\left(\overline{X}-X_i\right)}^2+{\left(\overline{Y}-Y_i\right)}^2\right]}^{{\displaystyle \frac{1}{2}}},$$

(1)

where

d_i—distance from the point to the gravity center

X, Y—coordinates of the gravity center

X_i, Y_i—coordinates of the point

K—unit value in the coordinate system.

The method used aims to determine the location of the distribution center, with an emphasis on minimizing total delivery costs, which is the primary goal. The total costs for the selected distribution center location are calculated using the following formula:

$$\min TC=\sum _{i=1}^N{V}_i·R_i·d_i,$$

(2)

where

TC—total transportation cost

N—number of points (units of economic activity)

V_i—volume/quantity of goods

R_i—unit transportation cost

d_i—distance from the point to the gravity center.

The city of Rijeka has participated in European projects focused on urban mobility. The SMILE project (SMart Green Innovative Urban Logistics for Energy-Efficient Mediterranean Cities) promoted energy efficiency in Mediterranean cities through modeling, measurement, and evaluation of delivery systems. SUPLITER (Sustainable Planning of Urban Logistics to Enhance Regional Freight Transport) focused on improving the planning of urban logistics solutions to reduce harmful gas emissions in urban environments. Rijeka Promet d.d., which manages traffic and coordinates public city transport, participated in these projects. The location of the consolidation center, shown in Figure 7, is near the Kukuljanovo Industrial Zone, a central point for most carriers, and is in close proximity to the city center.

Deliveries to the city center should exclusively be conducted from the consolidation center. This approach enables deliveries using smaller vehicles at full capacity, in contrast to the current practice of using larger vehicles with underutilized capacity.

5.1. Delivery Model from Two Consolidation Centers near the City Center

An analysis of vehicle entries into the city center revealed balanced use of entry points on the eastern and western sides of the city. The scenario of delivery from two consolidation centers is supported by the similar distribution of entry usage by carriers. The first consolidation center is planned near entry point R89: D404, while the second is planned in the western part of the city (Mlaka Industrial Zone, as shown in Figure 8) with access via R6: Krešimirova Street.

The selection of locations is based on traffic data from Rijeka plus d.d. and the potential of road D403 to facilitate freight vehicle flow to the new container terminal on Zagrebačka Obala. Deliveries from two consolidation centers would allow shorter routes for carriers to delivery points, reduce the number of vehicles, accelerate deliveries, eliminate bottlenecks, and lower emissions. However, this model requires significant financial investment and a thorough analysis of the need for two centers, taking into account the city’s size and the requirements of delivery service users.

5.2. Delivery Model Using Eco-Friendly Vehicles from a Single Consolidation Center

European cities are increasingly transitioning to eco-friendly delivery vehicles to reduce pollution, improve citizens’ quality of life, and lower health risks such as respiratory and cardiovascular diseases. The implementation of these vehicles is essential for the sustainable development of urban areas but faces challenges, including high acquisition costs, uncertainty regarding vehicle reliability, and high maintenance expenses. Public administration also encounters difficulties in investing in charging infrastructure, which further burdens the urban grid.

5.3. Livability Model

The concept of the livability model promotes reducing traffic in city centers to preserve the social and economic vitality of cities. An example is Ljubljana, which established a 10-hectare traffic-calmed zone in the city center, with special access for delivery vehicles between 6:00 a.m. and 10:00 a.m. [21]. The city of Rijeka also plans to transform streets like Riva into two-way streets, while Adamićeva Street would remain essential for public transportation, deliveries, and taxi services.

This plan requires significant investment in traffic infrastructure, including changes in signaling and adjustments for two-way traffic flows. Technical constraints currently make it difficult to simulate the closure of Adamićeva Street [22]. The proposed restriction on delivery vehicle access to Riva could reduce traffic in the city center but may increase congestion in the northern parts (see Figure 9).

6. Conclusions

The analysis of the current state of delivery logistics in the city center of Rijeka has shown that a large number of economic entities generate a significant level of daily deliveries, with traffic congestion peaking during the morning hours between 7 and 9 a.m. The equal usage of both eastern and western city entrances suggests a balanced distribution load on the traffic network, but also reveals potential congestion points that must be considered when planning optimized delivery scenarios.

Special attention in this analysis needs to be given to the organizational level of delivery implementation, particularly due to the fact that many existing delivery zones are improperly occupied. This directly affects the functionality of the transport infrastructure, slows down delivery processes, and creates additional congestion. Effective management of delivery spaces—through improved regulation, monitoring, and the potential digitalization of a reservation system—represents a key factor in implementing any sustainable logistics solution.

Proposed models that include consolidation centers and environmentally friendly vehicles have the potential to significantly reduce traffic load, CO₂ emissions, and overall transport costs. However, their effectiveness must be verified through simulations that incorporate all relevant input parameters, from traffic intensity and vehicle types to the locational characteristics of distribution points.

Accordingly, this study serves as a foundation for the development of a simulation model to test five proposed distribution scenarios in the city center. Through quantitative analysis of the expected impacts on the traffic system, environment, and costs, it is possible to provide informed guidelines for future transport policies, spatial planning, and infrastructural interventions. In the long term, such models offer a realistic framework for the development of efficient, technologically advanced, and sustainable urban logistics tailored to the specific needs of the city of Rijeka.