Average Operating Speed Research Articles

Study of the technical parameters dynamics influence on operational performance of hydraulic single-bucket excavators

Introduction. The development of automobile and road construction is a priority in the Russian economy. Timely putting construction projects in commission increases the requirements for planning of execution mechanized works. The operation of transport and technological machines in construction processes for a long time leads to a decrease in their potential capabilities, including operational productivity. The purpose of the proposed article is to improve the method of calculating the performance of a single-bucket hydraulic excavator (EO), taking into account the operating time.Methods and materials. The performance calculation method takes into account the dynamics of the working pressure in the hydraulic system of the working equipment (GRO), the speed of rotation of the crankshaft (PMVC) from the operating time, regression dependencies were used to describe them. The parameters of the law of distribution of the random value of the working pressure in the hydraulic drive and the rate of its fall for the ‘development and recruitment of soil’ operation were also obtained.Results. Processing of the results of production experiments enables to establish the dependence of changes in the working pressure in the hydraulic system during development and gathering soil, as well as for all technological operations of the working cycle, the rotational frequency of the crankshaft of a single-bucket excavator engine on the operating time. The influence of the working pressure in the hydraulic drive, the rotational speed of the crankshaft of the excavator engine on the supply and hydraulic power, the duration of technological operations is studied. The calculation of the operational productivity of a single-bucket excavator is carried out taking into account the dynamics of parameters reflecting its change over operating time.Discussion and conclusions. It has been established that with an increase in operating time, the operating pressure in the hydraulic drive decreases by an average of 12.7-13.0%, and the decrease in the average operating speed of the crankshaft is 4%. The estimated value of the drop in the average hourly operating performance of the EO, taking into account the deterioration of the technical condition, is 55% in the operating time range from 0 to 10,000 operating hours for the Japanese EO ZX 330 model.

Транспортная энергоэффективность и экономические принципы организации морского судоходства

Modern problems of ensuring energy efficiency and carbon intensity of marine vessels are considered, taking into account the achievement of profitability of flights. Since January 2023, such issues have been particularly acute for all maritime convention vessels engaged in international transport, taking into account the introduction of amendments to annex VI of the International Convention for the Prevention of Pollution from Ships (MARPOL), developed within the framework of the IMO short-term strategy until 2030 to reduce emissions greenhouse gases from ships. The composition of the world merchant fleet by ship types and deadweight was analyzed, the work of the tram freight market and the features of achieving optimal economic operational speed of the vessel were evaluated, taking into account operational and technical conventional restrictions on carbon intensity. The transport work of the universal vessel Singularity over the past three years has been analyzed, taking into account changes in operational speed and the level of freight rates. An adequate mathematical model has been proposed for assigning an optimal average operating speed to a ship according to a carbon intensity rating. The proposed methodological materials can be used by shipping companies in the commercial and technical operation of the fleet by assigning an operational speed in preparation for the voyage and when carrying out corrective energy efficiency measures to achieve an acceptable level of carbon intensity ratings for marine vessels.

Comprehensive Evaluation of Urban Road Network Capacity Using Fractal Theory in the Context of the Internet of Things

Abstract In order to make a good assessment of road traffic status, this paper proposes a comprehensive evaluation method of urban road network capacity based on soft computing under the background of Internet of Things. The focus of the research is to use a variety of soft computing technologies such as Hausdorff dimension simplification method, branch dimension measurement algorithm, multifractal method, etc., to analyze the overall traffic load and guide the traffic channelization in an optimal way, considering various factors comprehensively. The model helps to optimize infrastructure and reduce road traffic congestion. This avoids traffic congestion, ultimately reducing the carbon footprint and promoting a green environment. This method analyzes the network capacity, network load and corresponding conversion coefficient of all levels of highway. Based on the multi-component linear regression method, this paper evaluates the urban road network capacity, and constructs the urban road network capacity planning model according to the traffic volume constraints and travel time constraints. The test results show that under the application of this method, the road capacity of the planned route exceeds 4000 pcu. The pcu is a passenger vehicle unit that measures the extent to which different types of vehicles have an impact on road capacity. When the capacity of a planned road exceeds 4000 pcu, it means that the road can carry a large number of different types of vehicles at the same time, and the average operating speed of the line can reach 42.3 km/h. After 5 years of planning, the efficiency of road use is still above 75 %. It can be proved that this method can obtain the optimal traffic path through better route planning and avoid traffic congestion and pollution.

Big Data Analysis for Travel Time Characterization in Public Transportation Systems

In this article, we introduces a model based on big data analysis to characterize the travel times of buses in public transportation systems. Travel time is a critical factor in evaluating the accessibility of opportunities and the overall quality of service of public transportation systems. The methodology applies data analysis to compute estimations of the travel time of public transportation buses by leveraging both open-source and private information sources. The approach is evaluated for the public transportation system in Montevideo, Uruguay using information about bus stop locations, bus routes, vehicle locations, ticket sales, and timetables. The estimated travel times from the proposed methodology are compared with the scheduled timetables, and relevant indicators are computed based on the findings. The most relevant quantitative results indicate a reasonably good level of punctuality in the public transportation system. Delays were between 10.5% and 13.9% during rush hours and between 8.5% and 13.7% during non-peak hours. Delays were similarly distributed for working days and weekends. In terms of speed, the results show that the average operational speed is close to 18 km/h, with short local lines exhibiting greater variability in their speed.

Assessing the Social Costs of Mixed Transport Systems with a Dominance of Motorcycles

When undertaking strategic planning to identify potential options for a detailed assessment, it is important to compare the total costs of existing mixed transport systems with the introduction of different new public transport (PT) modes. Hence, this study develops a social cost model for situation of mixed transport system which has a dominance of motorcycles where a new PT technology (e.g. Bus Rapid Transit - BRT, Monorail or elevated Metro) or an exclusive bus lane is being considered. The innovative aspects of this research are to develop equations to estimate the average operating speed of each mode and to the allocation of infrastructure costs to several transport modes sharing the facilities in motorcycle dominated mixed traffic environments. Based on a four-lane per direction mixed traffic corridor in Hanoi, Vietnam, the results show the lowest average social cost (ASC) mixed transport systems for different ranges of demand. Moreover, all mixed traffic options with BRT, Monorail, elevated Metro or exclusive bus lanes are better than the existing situation in terms of ASC and it is suggested that their feasibility is examined in a detailed assessment. The mixed transport social cost model can be modified to suit other local conditions where conventional bus, car and motorcycle share facilities and a new PT mode is operated. Additionally, transport planners and decision makers in such local situations, which are particularly common in South East Asia, can draw on the findings of this study.

Image Splicing Compression Algorithm Based on the Extended Kalman Filter for Unmanned Aerial Vehicles Communication

The technology of unmanned aerial vehicles (UAVs) is extensively utilized across various domains due to its exceptional mobility, cost-effectiveness, rapid deployment, and flexible configuration. However, its limited storage space and the contradiction between the large amount of image data returned and the limited bandwidth in emergency scenarios necessitate the development of a suitable UAVs image compression technology. In this research, we propose an image splicing compression algorithm based on the extended Kalman filter for UAV communication (SEKF-UC). Firstly, we introduce the concept of image splicing to enhance the compression ratio while ensuring image quality, leveraging the characteristics of deep learning-based compression, which are relatively unaffected by the size of the compressed data. Secondly, to address the issue of slow processing speed of deep neural networks (DNN) caused by the substantial volume of data involved in image splicing, we incorporate an extended Kalman filter module to expedite the process. Simulation experiments show that our proposed algorithm outperforms existing methods in multiple ways, achieving a significant compression ratio improvement, from 2:1 to 25:1, with a marginal reduction of 6.5% in structural similarity (SSIM) compared to the non-spliced approach. Moreover, for deep neural networks (DNN), our method incorporating the extended Kalman filter module achieves the same error level with only 30 iterations—a significant reduction compared to the traditional BP algorithm’s requirement of over 4000 iterations—while improving the average network operation speed by an impressive 89.76%. Additionally, our algorithm excels in image quality, with peak signal-to-noise ratio (PSNR) improving by 92.7% and SSIM by 42.1%, at most, compared to other algorithms. These results establish our algorithm as a highly efficient and effective solution, suitable for various image processing and data compression applications.

Analysis of distribution network planning with distributed power supply based on ELM algorithm

Abstract With the development of the social economy, the importance of energy and environmental issues is becoming more and more prominent. Distributed power sources (DG) have the advantages of low carbon and environmental protection, flexible control, and low investment cost, but their nodes in the grid are random, which will increase the complexity and uncertainty of grid operation after grid connection. In this paper, we study the planning path of DGs in distribution networks and the protection technologies involved. Firstly, we focus on the impact of DG access on the protection of distribution networks and the impact of different access capacities and access locations of DG on the protection of distribution networks. Second, after studying the current status of the application of traditional genetic algorithms in distribution network fault location, a two-layer planning model based on the modified extreme learning machine algorithm (MPSO-ELM) is proposed, with the load demand guaranteed by the first layer of power allocation and the fault location incorporated into the distribution network protection scheme in the second layer. Finally, simulations are performed to compare and demonstrate the advantages of this MPSO-ELM algorithm. The simulation results show that the MPSOELM algorithm converges faster than the traditional genetic algorithm by 7s, the average operating speed of power nodes is 3.61ms faster than the traditional genetic algorithm by 5.59ms, and the accuracy in fault location is improved by 23.14%. The simulation results verify the comprehensiveness, accuracy, and high efficiency of the ELM algorithm for double-layer planning of distribution networks containing distributed power supplies, which is important for improving the level of power grid construction and avoiding the risk of power grid construction.

Short-Duration Crash Modeling to Understand the Impact of Operating Speed on Freeway Crashes During COVID-19

Gaining an understanding of speed–crash relationships is a critical issue in highway safety research. Because of the ongoing pandemic (COVID-19) there has been a reduction in traffic volume, and some early studies explain that speeding in an environment with less traffic is associated with a high number of crashes, especially fatal and serious injury crashes. This study aims to quantify the impact of operating speed on traffic crash occurrences. The study conflated several databases (speed data, roadway inventory data, and crash data) that contain data from Dallas, Texas, spanning from 2018 to 2020, to examine the speed–crash association. Using the negative binomial Lindley regression model, this study showed that the trends of crash prediction models vary over the years (2018, 2019, and 2020) by different injury severity levels (i.e., fatal crashes, fatal and incapacitating injury crashes). The 2020 models show that operating speed measures (i.e., average operating speed) have a significant impact on crash frequencies. The magnitudes of the speed measures show variations across the models at different injury severity levels.

Comparison of Analytical and Simulation Results for One-Lane Operation on Low-Volume Two-Lane Highway

Work zones on two-lane highways with one lane closed require sharing the open lane with traffic from the closed directions. In such work zones, traffic control resembles operating a two-phase traffic signal and, in rare cases, a three-phase traffic signal. Temporary traffic signals (or flaggers) allow the open lane to be used in an alternating manner. Signal timing (green times and cycle length) of the temporary traffic lights directly affects the delay and queue in the work zones. Delay and queue computations must consider queue build up that often happens in oversaturated conditions. Another influential variable is the average operating speed of the work zone. The operating speed is affected by the work zone speed limit, work intensity, speed control technique, lane and shoulder widths, acceleration capability of vehicles, and work zone length. WorkZoneQ-Pro (WZQ-Pro) is developed with a new signal timing method that considers the above-mentioned factors. The procedure can handle multiple hours of analysis with two- or three-phase signal operations. Test scenarios are real-world work zone examples from three different U.S. states that were used to compute signal time variables and use them to compute queue and delay. These values were also computed using Highway Capacity Manual (HCM) 2016 procedures and are compared. In addition, the computed values were input into Vissim simulation software, and the results were compared. It showed that the WZQ-Pro results are reasonably close to Vissim simulation results, and that further validated that an acceptable agreement existed between the analytical and simulation results.

Нормативы скорости автомобиля в планировании перевозок с использованием электронных путевых листов

The development of digital technologies unveils prospects for paperless document management in road transport, which is confirmed by a pilot project on the use of an electronic shipping manifest and a bill of lading. It is important to use the shipping manifest not only as a digital document, but also as a specialized software tool for calculating planned and actual performance indicators of vehicles as part of the enterprise management information system. An algorithm is proposed for constructing the information system for managing transport activities using electronic waybills, which are used as software for calculating planned performance indicators of vehicles and summarizing the results of transportation. The established standards and legal documents regulating the transfer of document flow in the field of road freight transportation to electronic basis are given. The importance of reasonable standards of average technical speed and idle time of vehicles at loading and unloading points for scheduling the performance of freight trucks on routes is illustrated. The factors influencing the value of the average technical and operational speed of a vehicle during transportation are studied and systematized, recommendations on establishing of their regulatory standards are given, formulas for calculating quantitative values are provided. Based on the specified standard of average technical speed, the calculation of the radius of cargo delivery during the day in intercity communication is demonstrated.

Study on Identification and Prevention of Traffic Congestion Zones Considering Resilience-Vulnerability of Urban Transportation Systems

In order to solve the problem of urban short-term traffic congestion and temporal and spatial heterogeneity, it is important to scientifically delineate urban traffic congestion response areas to alleviate regional traffic congestion and improve road network efficiency. Previous urban traffic congestion zoning is mostly divided by urban administrative divisions, which is difficult to reflect the difference of congestion degree within administrative divisions or traffic congestion zoning. In this paper, we introduce the Self-Organizing Feature Mapping (SOFM) model, construct the urban traffic congestion zoning index system based on the resilience and vulnerability of urban traffic systems, and establish the urban traffic congestion zoning model, which is divided into four, five, six, and seven according to the different structures of competition layer topology. The four vulnerability damage capacity indicators of traffic volume, severe congestion mileage, delay time and average operating speed, and two resilience supply capacity indicators of traffic systems, namely, road condition and number of lanes, are used as model input vectors; the data of Guiyang city from January to June 2021 are used as data sets to input four SOFM models for training and testing and the best SOFM model with six competitive topologies is constructed. Finally, the Support Vector Machine (SVM) is used to identify the optimal partition boundary line for traffic congestion. The results show that the four models predict the urban traffic congestion zoning level correctly over 95% on the test set, each traffic congestion zoning evaluation index in the urban area shows different obvious spatial clustering characteristics, the urban traffic congestion area is divided into six categories, and the city is divided into 16 zoning areas considering the urban traffic congestion control types (prevention zone, control zone, closure control zone). The spatial boundary is clear and credible, which helps to improve the spatial accuracy when predicting urban traffic congestion zoning and provides a new methodological approach for urban traffic congestion zoning and zoning boundary delineation.

Characteristics of Light Rail Travel Time: Examples from France

The total journey time of Light Rail Vehicles (LRVs) is made up of running time, dwell time (station stops for passenger boarding and alighting), and signal delay (delay of LRVs being stopped by the regular traffic signals). Data from operational surveys of six modern light rail systems in France has shown that LRV running time was 65-71 percent of the total journey time and dwell time was 22-27 percent, while signal delay was 7 to 8 percent of the total journey time. The average operating speed of the Light Rail Transit (LRT) ranged from 17.7 to 22.8 km/h and has an approximate linear relationship to passenger stop frequency (stops/km).Light rail dwell time has been found to follow a log-normal distribution, although the values differed significantly between different LRT systems. The means of the dwell time distribution have the range of 16 to 31 seconds in off-peak periods and 21 to 37 seconds in peak periods. Factors that influence light rail dwell time include the number of passengers at the stops, the number of standees in the vehicles, vehicle design (number of doors, door size, low floor or high floor vehicle, etc.), fare collection system, and the location of LRT stops.The findings in this paper could be used by LRT planners and operators directly in developing and assessing operating and service changes and in providing input to long-range planning procedures. The results can also be used in microscopic simulation modeling studies of LRT in an urban network, such as the TRGMSM model.

One-Coil Long-Stroke Permanent Magnetic Actuator Design Applied to Load Breaker Switch for Railway

This paper proposes a design for a one-coil long-stroke permanent magnet actuator (PMA) applied to a load breaker switch with a novel mechanism applicable to railways. As a new load breaker switch applicable to railway overhead lines has a double-insulation structure of the vacuum interrupter (VI) and a disconnect switch (DS) for higher insulation, the actuator to control the switch requires a very long stroke. While the traditional mechanism of the PMA implements a stroke of 10 to 30 mm, the load breaker switch with a double-insulation structure requires a stroke of 120 mm. To do so, we used the finite element method (FEM) and designed a novel one-coil long-stroke PMA. Then, values from FEM analysis were compared with measured holding force data, and a simplified prototype test-jig was used to confirm the actuator’s operating characteristics. In addition, the electromagnetic force, plunger rotation, and part weight ratio, which affect operating performance, were adapted in its design. By doing so, we confirmed the operating performance required for the one-coil long-stroke PMA for a new load breaker switch with a double-insulation structure with a VI average opening speed of 1.4 m/s and an average closing speed of 0.9 m/s at 1/2 of full stroke.

Investigation on anode modes of vacuum arc under different contact opening speeds

This paper aims to investigate the anode modes of vacuum arc at different opening speeds, especially at a high opening speed that exceeds 3 m/s. The butt contacts made of CuCr30 and CuCr50 with a diameter of 15 mm are used. Experiments are conducted at the current of 3.3, 4.4, 5.5, and 6.3 kA with a frequency of 50 Hz. An electromagnetic repulsion actuator provides the average opening speed from 1.7 to 3 m/s. The experimental results show that the number of droplets splashing into electrodes increases as the arc current increases, while a higher opening speed decreases the droplets. A higher opening speed will reduce the transferred charge before the anode spot type 2, and a higher Cr content increases the transferred charge before the anode spot type 2. Increasing opening speed will decrease the starting time of anode spot type 2, but it increases the gap distance when anode spot type 2 appears. Meanwhile, the increase in Cr content delays the formation of anode spot type 2.

Did Operating Speeds During COVID-19 Result in More Fatal and Injury Crashes on Urban Freeways?

Impacts of the COVID-19 pandemic in the transportation arena included less traffic, higher speeds, and higher fatal and injury crash frequencies. Many news media reported on speeding and its impact. However, the majority of these reporting are based on partial or incomplete information. The current study aims to understand the association between speed and crash on the freeways of Dallas (Texas) by collecting data from the National Performance Management Research Dataset, the Texas Department of Transportation’s (TxDOT’s) roadway inventory, and TxDOT’s crash database for 2018–2020. The results show decreasing traffic volume, increasing average operating speed, and increasing fatal and severe crash frequencies per 100 million vehicle miles traveled during 2020 (April–November). This study developed 8-month- and daily-level safety prediction models for fatal and injury crashes. The 8-month-level dataset contains speed measures as an aggregate for the 8-month period. The daily-level database includes operating speeds and fatal and injury crashes at the daily level where segments experiencing fatal and injury crashes were temporally matched with the same segment with the same day of the week and with no fatal and injury crash occurrences. For the 8-month models, average operating speed and speed variability are positively associated with fatal and injury crash frequencies during the COVID period. This association was also found for daily-level models. The findings of this study can help transportation agencies in developing strategies (for example, posted speed limit reconsideration, additional enforcement at specific locations) for crash reduction.

Impact of operating speed measures on traffic crashes: Annual and daily level models for rural two-lane and rural multilane roadways

A significant association between crash severity and operating speed is known to exist. However, the findings related to the speed-crash association are inconclusive. Some studies found that higher speed is associated with a higher number of crashes, whereas other studies found the opposite result. Some of the critical issues in this research problem result from study design, the definition of operating speed measures, types and granularity of operating speed measures, spatial correlation, and design standards of different roadway facilities. The road safety profession will benefit greatly from informative research on the impact of vehicle operating speed, roadway design elements, and traffic volume on crash outcomes. This study investigated the speed-crash association in both annual and daily level datasets to determine how roadway characteristics interact with various speed measures to impact the likelihood of crash occurrences on both annual and daily levels. For annual models, the average operating speed is positively associated with both fatal and injury and property damage only (PDO) crashes. However, for daily models, this association is mostly negative and insignificant. The standard deviation of operating speed is positively associated with crash occurrences for both daily and annual models. The findings of this study can provide additional insights into the speed-crash association literature.

The Mathematical Model of Marine Engine Room Equipment Based on Machine Learning

This study is aimed at reducing the occurrence of oil spill accidents in the engine room of ships and carries out risk prevention for the equipment of the port ships, thereby reducing pollution to the marine ecological environment. Firstly, the concepts and principles of cluster analysis and ship automatic identification system are expounded. Secondly, the data information collected by the ship’s automatic identification system (AIS) is combined with density-based cluster analysis. The accident area and extent at different stages of the ship’s engine room equipment are classified. Finally, cluster analysis is used to evaluate the risk of equipment of the port ship engine room. The results show that there are 43000 ship operation information points in port a, the average operating speed of ships is 9 kilometers, and the fastest operation speed is 16.9 kilometers. In addition, many ship routes in port a need to take risk prevention measures to minimize the impact between ships and reduce the risk of oil leakage in the engine room. The proposed cabin model can easily and quickly analyze the orientation information of the ship and classify all the data into different types according to the surrounding information points. AIS can realize the information transfer between ships and between ship and shore. Information such as the position, speed, and direction of the ship needs to be accurately known to ensure safety at sea. These data need to relate to some terminals and networks to form a maritime monitoring network. The ship AIS based on cluster analysis can cluster the areas where the ship’s speed and direction change significantly in the port area, effectively preventing accidents. Scientific risk prevention measures can effectively reduce the oil leakage risk of ship engine room equipment, improve the working efficiency of marine engines, and provide a strong foundation for the entire marine ecological environment protection.

Design and short‐circuit current breaking test verification of a 72.5 kV single‐break fast vacuum circuit breaker

Fast clearing of a short-circuit fault is vital to increase the transmission capacity of power grid transmission lines and improve the transient stability of a power system. A fast vacuum circuit breaker (FVCB) is a good candidate to realize quick elimination of a short-circuit fault. The original contribution of this paper is to present the design of a 72.5 kV single-break FVCB and its verification of short-circuit breaking performance. A specially designed 72.5 kV vacuum interrupter, with floating shields and reduced mass of moving components, was developed. An electromagnetic repulsion actuator was used to provide a high initial opening speed, V1, of 5 m/s over half of the full-contact gap and a relatively low average opening speed, V2, of 1.59 m/s in the full contact gap of 30 mm. The high-designed V1 and low-designed V2 were achieved with the aid of a deliberately designed oil buffer. The opening and closing time of the designed 72.5 kV FVCB was 1.2 ± 0.04 ms and 18 ± 0.20 ms respectively. The terminal fault test duty of T100s(b), carried out on the 72.5 kV FVCB, demonstrated both the 40 kArms and 80 kArms short-circuit current breaking performance. The short-circuit current breaking arcing time windows of FVCB, including the minimum arcing time, the maximum arcing time, and the middle arcing time, was verified to fulfill the requirement of the international standard, IEC 62271-100 2017, and the Chinese standard, GB/T 1984–2014, both for the 40 kArms and 80 kArms switching cases, respectively. Further development of the 72.5 kV single-break FVCB would benefit the development of ultra- or extra-high voltage FVCBs by reducing essential numbers of series-connected breaking units.

An Efficient FIR Filter Based on Hardware Sharing Architecture Using CSD Coefficient Grouping for Wireless Application

FIR filter is an essential part of digital signal processing that is extensively used in many areas such as wireless applications and digital processing system. The FIR filter design is inherently stable and has a linear phase characteristic under symmetric conditions, but its implementation often involves complexity and a large filter length to achieve specific design requirements. In this paper, the complexity of the FIR filter is reduced by eliminating the repeated subexpression in a canonic signed digit (CSD) number system based filter operation. A new grouping method has been proposed for the CSD number system-based filter coefficient to minimize the number of unpaired nonzero bits in the filter coefficient. The statistical analysis of the proposed grouping method is performed and compared with other existing schemes. The number of unpaired nonzero bits in the proposed grouping scheme is reduced by an average of 24.11\(\%\) as compared to other existing schemes. Further, an efficient FIR filter with hardware sharing architecture is designed and implemented to achieve a 14.65\(\%\) reduction in average power consumption, and the average operation speed is increased by 10.1\(\%\) compared to the other existing filter structures.

Comparative Analysis of the Environmental Performance of Delivery Routes in the City Center and Peri-Urban Area of Madrid

Cities are experiencing a process of suburbanization and last-mile delivery has grown, worsening traffic congestion, pollutant emissions, and citizens’ quality of life. Based on a real-life case study, this research compares the environmental performance of different delivery routes carried out by Diesel Light-Duty Vehicles (LDV) according to delivery area, city center or peri-urban. Some 242 delivery routes performed by thirteen drivers were recorded for one month, including instantaneous GPS position, speed, and other parameters (7262 km travelled). Four different delivery routes typologies were compared, and the drag function of the vehicles was characterized. It enabled calibration and modelling dynamics to calculate fuel consumption and pollutant emissions according to delivery routes. The results show that pedestrian crossings, traffic lights, and traffic congestion reduce the average operating speed by up to 57% in the city center and consequently overall energy efficiency. Our results highlight the urgency of replacing diesel LDV for deliveries in the city center with no-motorized transport modes and of implementing intermodality to cover deliveries in residential peri-urban areas. Due to low speeds and frequent start-stops, the efficiency of vehicles in these areas is reduced to a minimum and pollutant emissions increase. The outputs set a basis for recommendations for using LDV only for delivery routes with less traffic interruptions and foster intermodal solutions.