World Academy of Science, Engineering and Technology

Authors: Charly Julien Nyobe, Eric Jacquelin, Denis Brizard, Alexy Mercier

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The performance of road side safety barriers depends largely on the dynamic interactions between post and soil. These interactions play a key role in the response of barriers to crash testing. In the literature, soil-post interaction is modeled in crash test simulations using three approaches. Many researchers have initially used the finite element approach, in which the post is embedded in a continuum soil modelled by solid finite elements. This method represents a more comprehensive and detailed approach, employing a mesh-based continuum to model the soil’s behavior and its interaction with the post. Although this method takes all soil properties into account, it is nevertheless very costly in terms of simulation time. In the second approach, all the points of the post located at a predefined depth are fixed. Although this approach reduces CPU computing time, it overestimates soil-post stiffness. The third approach involves modeling the post as a beam supported by a set of nonlinear springs in the horizontal directions. For support in the vertical direction, the posts were constrained at a node at ground level. This approach is less costly, but the literature does not provide a simple procedure to determine the constitutive law of the springs The aim of this study is to propose a simple and low-cost procedure to obtain the constitutive law of nonlinear springs that model the soil-post interaction. To achieve this objective, we will first present a procedure to obtain the constitutive law of nonlinear springs thanks to the simulation of a soil compression test. The test consists in compressing the soil contained in the tank by a rigid solid, up to a vertical displacement of 200 mm. The resultant force exerted by the ground on the rigid solid and its vertical displacement are extracted and, a force-displacement curve was determined. The proposed procedure for replacing the soil with springs must be tested against a reference model. The reference model consists of a wooden post embedded into the ground and impacted with an impactor. Two simplified models with springs are studied. In the first model, called Kh-Kv model, the springs are attached to the post in the horizontal and vertical directions. The second Kh model is the one described in the literature. The two simplified models are compared with the reference model according to several criteria: the displacement of a node located at the top of the post in vertical and horizontal directions; displacement of the post's center of rotation and impactor velocity. The results given by both simplified models are very close to the reference model results. It is noticeable that the Kh-Kv model is slightly better than the Kh model. Further, the former model is more interesting than the latter as it involves less arbitrary conditions. The simplified models also reduce the simulation time by a factor 4. The Kh-Kv model can therefore be used as a reliable tool to represent the soil-post interaction in a future research and development of road safety barriers.

Keywords: crash tests, nonlinear springs, soil-post interaction modeling, constitutive law

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Authors: Jean Felix Tuyisingize

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Speeding or inappropriate speed is a major problem worldwide, contributing to 10-15% of road crashes and 30% of fatal injury crashes. The consequences of speeding put the driver's life at risk and the lives of other road users like motorists, cyclists, and pedestrians. To control vehicle speeds, governments, and traffic authorities enforced speed regulations through speed cameras and speed section control, which monitor all vehicle speeds and detect plate numbers to levy penalties. However, speed limit violations are prevalent, even on motorways with speed cameras. The problem with speed cameras is that they alter driver behaviors, and their effect declines with increasing distance from the speed camera location. Drivers decelerate short distances before the camera and vigorously accelerate above the speed limit just after passing by the camera. The sudden decelerating near cameras causes the drivers to try to make up for lost time after passing it, and they do this by speeding up, resulting in a phenomenon known as the "Kangaroo jump" or "V-profile" around camera/ASSC areas. This study investigated the impact of speed enforcement devices, specifically Average Speed Section Control (ASSCs) and fixed cameras, on acceleration and deceleration events within their vicinity. The research employed advanced statistical and Geographic Information System (GIS) analysis on naturalistic driving data, to uncover speeding patterns near the speed enforcement systems. The study revealed a notable concentration of events within a 600-meter radius of enforcement devices, suggesting their influence on driver behaviors within a specific range. However, most of these events are of low severity, suggesting that drivers may not significantly alter their speed upon encountering these devices. This behavior could be attributed to several reasons, such as consistently maintaining safe speeds or using real-time in-vehicle intervention systems. The complexity of driver behavior is also highlighted, indicating the potential influence of factors like traffic density, road conditions, weather, time of day, and driver characteristics. Further, the study highlighted that high-severity events often occurred outside speed enforcement zones, particularly around intersections, indicating these as potential hotspots for drastic speed changes. These findings call for a broader perspective on traffic safety interventions beyond reliance on speed enforcement devices. However, the study acknowledges certain limitations, such as its reliance on a specific geographical focus, which may impact the broad applicability of the findings. Additionally, the severity of speed modification events was categorized into low, medium, and high, which could oversimplify the continuum of speed changes and potentially mask trends within each category. This research contributes valuable insights to traffic safety and driver behavior literature, illuminating the complexity of driver behavior and the potential influence of factors beyond the presence of speed enforcement devices. Future research directions may employ various categories of event severity. They may also explore the role of in-vehicle technologies, driver characteristics, and a broader set of environmental variables in driving behavior and traffic safety.

Keywords: acceleration, deceleration, speeding, inappropriate speed, speed enforcement cameras

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Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

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Crowdsourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowdsourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is the first to develop safety performance functions using crowdsourced data by adopting a negative binomial structure model and Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

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Authors: Hassan M. Al-Ahmadi, Hamad Bader Almobayedh

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Planning for urban transportation is essential for developing effective and sustainable transportation networks that meet the needs of various communities. Advanced modeling software is required for effective transportation planning, management, and optimization. This paper compares PTV VISUM, Aimsun, TransCAD, and Emme, four industry-leading software tools for transportation planning and modeling. Each software has strengths and limitations, and the project's needs, financial constraints, and level of technical expertise influence the choice of software. Transportation experts can design and improve urban transportation systems that are effective, sustainable, and meet the changing needs of their communities by utilizing these software tools.

Keywords: PTV VISUM, Aimsun, TransCAD, transportation modeling software

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Authors: Hassan M. Al-Ahmadi

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The fatality index (deaths/100 K population) due to road traffic accidents in the Kingdom of Saudi Arabia (KSA) is over 25, according to the World Health Organization Statistics (WHO) statistics, which is much higher than in the neighboring Arab regions. The KSA has implemented measures to mitigate traffic accidents by enforcing road safety regulations. As a result, there has been a slight decline in the frequency of road traffic accidents within the Kingdom. This study was based on the variations in the accidents for three provinces of KSA, i.e., Riyadh, Eastern Province (EP), & Qaseem, for 2016 and 2017 using ANOVA method. Data appropriateness for the ANOVA method was confirmed by the normality and the randomness of residuals. Additionally, the half-normal plot was used to identify the significant terms for the ANOVA analysis. The analysis revealed that the accidents in the EP were significantly higher than in the other two provinces during the analysis period. The monthly variation showed a spike in the accidents from month 7th to 9th month in the EP region and a slight drop in the accidents in the Qaseem and the Riyadh region during the same period, which was attributed to the increased leisure travels from the other regions to the EP. Furthermore, most of the accidents were found to occur in the age group of 18+ and 30+, and also the major reduction of accidents in 2017 as compared to 2016 was found to have occurred in the same group. These findings can be beneficial for developing strategies to further reduce the number of accidents.

Keywords: fatality index, emergency, road traffic accident, safety, leisure travels

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Authors: Faisal Mahroogi, Mahmoud Bady, Yaser H. Alahmadi, Ahmed Alsisi, Sunny Narayan, Muhammad Usman Kaisan

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The Kingdom of Saudi Arabia established Saudi Vision 2030, an initiative of the government with the goal of promoting more socioeconomic as well as cultural diversity. The kingdom, which is dedicated to sustainable development and clean energy, uses cutting-edge approaches to address energy-related issues, including the circular carbon economy (CCE) and a more varied energy mix. In order for Saudi Arabia to achieve its Vision 2030 goal of having a net zero future by 2060, sustainability is essential. By addressing the energy and climate issues of the modern world with responsibility and innovation, Vision 2030 is turning into a global role model for the transition to a sustainable future. As per the Ambitions of the National Environment Strategy of the Saudi Ministry of Environment, Agriculture, and Water (MEWA), raising environmental compliance across all sectors and reducing pollution and adverse environmental impacts are critical focus areas. As a result, the current study presents an experimental analysis of the performance and exhaust emissions of a diesel engine running mostly on waste cooking oil (WCO). A one-cylinder direct-injection diesel engine with constant speed and natural aspiration is the engine type utilized. Research was done on how the engine performed and emission parameters when fueled with a mixture of 10% butanol, 10% diesel, 10% WCO, and 10% diethyl ether (D70B10W10DD10). The study's findings demonstrated that engine emissions of nitrogen oxides (NOX) and carbon monoxide (CO) varied significantly depending on the load being applied. The brake thermal efficiency, cylinder pressure, and the brake power of the engine were all impacted by load change.

Keywords: ICE, waste cooking oil, fuel additives, butanol, combustion, emission characteristics

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Authors: Shravanth Vasisht M., Balachandra P., Dasappa S.

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Electric mobility (e-mob) is one of the significant actions proposed for sustainable urban transport in India. The current efforts are aimed at reducing the carbon-dioxide (CO2) emissions and environmental pollution through a smooth transition from fossil-fueled mobility (f-mob) to e-mob. The study summarizes the e-mob landscape in India, its roadmap, the expected challenges relevant to the consumer preferences and perceptions. In addition to the challenges of transition from f-mob to e-mob, the sustainability of e-mob is more crucial as it involves addressing challenges related to three dimensions, namely, environmental, economic, and social sustainability. The critical factors in each of these dimensions are analyzed. The recommendations for attaining sustainability are suggested to enable a successful transition from f-mob to e-mob. The specific objectives of the research include a detailed synthesis of urban mobility landscape, analyses of various stakeholders' behaviors, drivers, and barriers influencing the transition, measures to boost the drivers and mitigate the barriers. The study also aims to arrive at policy recommendations and strategies for a successful and sustainable transition from f-mob to e-mob, reducing the carbon footprint due to transportation.

Keywords: electricmobility, urbanmobility, transportation, consumerbehaviour, carbonemission

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Authors: Maz Muradvich

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The Federal Highway Administration's Everyday Counts (EDC) initiative is designed to identify and deploy innovations, enhancing the safety of our roadways. According to and as referenced in FHWA everyday counts (2) website, High friction surface treatment (HFST) is an emerging surface application that has been proven to reduce crashes. High Friction Surface Treatment involves the application of Calcined Bauxite, very high-quality aggregate to the pavement using a polymer binder to restore and maintain pavement friction at existing or potentially high crash areas. Bauxite is a byproduct of manufacturing aluminum resulting in very hard aggregate and is abrasion and polish resistant. HFST is an approach that has been recognized nationally and internationally and has provided considerable increases in friction for curves and intersections spot applications. Maricopa County qualified and received HSIP (Highway Safety Improvement Program) funding that was applied towards HFST application on 2 locations in Maricopa County. The project was successfully completed in December 2019. Four years later MCDOT continues to conduct wet and dry ABS and Non-ABS friction coefficient testing in pursuit of after studies evaluation of HFST application.

Keywords: roadway departure, sever crashes, coefficient of friction, break meter technology

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Authors: Jonathan Matyenyika

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In recent years, automobile manufacturers have increasingly produced vehicles equipped with cutting-edge automotive electronic technology to match the fast-paced digital world of today; this has brought about various benefits in different business sectors that make use of these vehicles as a means of turning over a profit. In the logistics industry, vehicles equipped with this technology have proved to be very utilitarian; this paper focuses on the benefits automobile electronic equipped vehicles have in the logistics industry. Automotive vehicle manufacturers have introduced new technological electronic features to their vehicles to enhance and improve the overall performance, efficiency, safety and driver comfort. Some of these features have proved to be beneficial to logistics operators. To start with the introduction of adaptive cruise control in long-distance haulage vehicles, to see how this system benefits the drivers, we carried out research in the form of interviews with long-distance truck drivers with the main question being, what major difference have they experienced since they started to operate vehicles equipped with this technology to which most stated they had noticed that they are less tired and are able to drive longer distances as compared to when they used vehicles not equipped with this system. As a result, they can deliver faster and take on the next assignment, thus improving efficiency and bringing in more monetary return for the logistics company. Secondly, the introduction of electric hybrid technology, this system allows the vehicle to be propelled by electric power stored in batteries located in the vehicle instead of fossil fuel. Consequently, this benefits the logistic company as vehicles become cheaper to run as electricity is more affordable as compared to fossil fuel. The merging of electronic systems in vehicles has proved to be of great benefit, as my research proves that this can benefit the logistics industry in plenty of ways.

Keywords: logistics, manufacturing, hybrid technology, haulage vehicles

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Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Jollen Dai, Truman You, Xinyun Du, Katrina Liu

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Transportation is one of the leading sources of greenhouse gas emissions (GHG). Thus, to meet the Paris Agreement 2015, all countries must adopt a different and more sustainable transportation system. From bikes to Maglev, the world is slowly shifting to sustainable transportation. To develop a utility public transit system, a sustainable web of buses must be implemented. As of now, only a handful of cities have adopted a detailed plan to implement a full fleet of e-buses by the 2030s, with Shenzhen in the lead. Every change requires a detailed plan and a focused analysis of the impacts of the change. In this report, the economic implications and financial implications have been taken into consideration to develop a well-rounded 10-year plan for New York City. We also apply the same financial model to the other cities, LA and Chicago. We picked NYC, Chicago, and LA to conduct the comparative NPB analysis since they are all big metropolitan cities and have complex transportation systems. All three cities have started an action plan to achieve a full fleet of e-bus in the decades. Plus, their energy carbon footprint and their energy price are very different, which are the key factors to the benefits of electric buses. Using TCO (Total Cost Ownership) financial analysis, we developed a model to calculate NPB (Net Present Benefit) /and compare EBS (electric buses) to DBS (diesel buses). We have considered all essential aspects in our model: initial investment, including the cost of a bus, charger, and installation, government fund (federal, state, local), labor cost, energy (electricity or diesel) cost, maintenance cost, insurance cost, health and environment benefit, and V2G (vehicle to grid) benefit. We see about $1,400,000 in benefits for a 12-year lifetime of an EBS compared to DBS provided the government fund to offset 50% of EBS purchase cost. With the government subsidy, an EBS starts to make positive cash flow in 5th year and can pay back its investment in 5 years. Please remember that in our model, we consider environmental and health benefits, and every year, $50,000 is counted as health benefits per bus. Besides health benefits, the significant benefits come from the energy cost savings and maintenance savings, which are about $600,000 and $200,000 in 12-year life cycle. Using linear regression, given certain budget limitations, we then designed an optimal three-phase process to replace all NYC electric buses in 10 years, i.e., by 2033. The linear regression process is to minimize the total cost over the years and have the lowest environmental cost. The overall benefits to replace all DBS with EBS for NYC is over $2.1 billion by the year of 2033. For LA, and Chicago, the benefits for electrification of the current bus fleet are $1.04 billion and $634 million by 2033. All NPB analyses and the algorithm to optimize the electrification phase process are implemented in Python code and can be shared.

Keywords: financial modeling, total cost ownership, net present benefits, electric bus, diesel bus, NYC, LA, Chicago

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Authors: Ismail Rahama Adam Hamid

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This paper presents the development of a thermal model for a flat, double-sided linear generator designed for use in free-piston engines. The study conducted in this paper examines the influence of temperature on the performance of the permeant magnet linear generator, an integral and pivotal component within the system. This research places particular emphasis on the Neodymium Iron Boron (NdFeB) permanent magnet, which serves as a source of magnetic field for the linear generator. In this study, an internal combustion engine that tends to produce heat is connected to a generator. Considering the temperatures rise from both the combustion process and the thermal contributions of current-carrying conductors and frictional forces. Utilizing Computational Fluid Dynamics (CFD) method, a thermal model of the (NdFeB) magnet within the linear generator is constructed and analyzed. Furthermore, the temperature field is examined to ensure that the linear generator operates under stable conditions without the risk of demagnetization.

Keywords: free piston engine, permanent magnet, linear generator, demagnetization, simulation

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Authors: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

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In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

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Authors: Samuel Nderitu Muchiri, Tracy Wangechi Maina

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Truck drivers face a myriad of challenges in their profession. Enhancements in logistics effectiveness can be pivotal in propelling economic developments. The specific objective of the study was to assess the influence of driver distraction on crash risk. The study is significant as it elucidates best practices that truck drivers can embrace in an effort to enhance road safety. These include amalgamating behaviors that enable drivers to fruitfully execute multifaceted functions such as finding and following routes, evading collisions, monitoring speed, adhering to road regulations, and evaluating vehicle systems’ conditions. The analysis involved an empirical review of ten previous studies related to the research topic. The articles revealed that driver distraction plays a substantial role in road accidents and other crucial road security incidents across the globe. Africa depends immensely on the freight transport sector to facilitate supply chain operations. Several studies indicate that drivers who operate primarily on rural roads, such as those found in Sub-Saharan Africa, have an increased propensity to engage in distracted activities such as cell phone usage while driving. The findings also identified the need for digitalization in truck driving operations, including carrier management techniques such as fatigue management, artificial intelligence, and automating functions like cell phone usage controls. The recommendations can aid policymakers and commercial truck carriers in deepening their understanding of driver distraction and enforcing mitigations to foster road safety.

Keywords: truck drivers, distraction, digitalization, crash risk, road safety

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Authors: Jiaqi Zhang, Zhi Dong, Pan Xing

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With the continuous development of urban agglomerations, higher demands are placed on intercity public transport travel services. To improve these services, it is necessary to comprehensively understand the views and evaluations of travelers. Taking the Guanzhong Plain urban agglomeration in China as the object, this study explores subjective attitude indicators from self-administrated survey data and examines the relationship among perceived accessibility, preference, and satisfaction for intercity public transport using a structural equation model. The results show that perceived service quality has a direct positive impact on perceived accessibility and satisfaction. Perceived accessibility and preference significantly affect satisfaction. In addition, perceived accessibility mediates the effect of service quality on satisfaction. This study provides valuable insights from a policy perspective to improve the subjective evaluation of intercity public transport travelers while emphasizing the importance of subjective variables in transport system evaluation and advocates for their subdivision to more comprehensively improve the travel experience.

Keywords: intercity public transport, perceived accessibility, satisfaction, structural equation model

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Authors: Jaejeogn Kim, Jeongmin Hong, Jungin Lee

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The Hydrogen Storage System Management Unit (HMU) is a controller that manages hydrogen charging and storage. It detects hydrogen leaks and tank pressure and temperature, calculates the charging concentration and remaining amount, and controls the opening and closing of the hydrogen tank valve. Since this role is an important part of the vehicle behavior and stability of Fuel Cell Electric Vehicles (FCEV), verifying the HMU controller is an essential part. To perform verification under various conditions, it is necessary to increase time efficiency based on an automated verification environment and increase the reliability of the controller by applying numerous test cases. To this end, we introduce the HMU controller automation verification method by applying the HILS environment and an automation test program with the ASAM XIL standard.

Keywords: HILS, ASAM, fuel cell electric vehicle, automation test, hydrogen storage system

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Authors: Nitish Suvarna, Anjali Awasthi

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In an era marked by rapid technological advancements, the integration of Autonomous Vehicles into supply chain networks represents a transformative shift, promising to redefine the paradigms of logistics and transportation. This thesis delves into a comprehensive assessment of the impact of autonomous vehicles on supply chain performance, with a particular focus on network design, operational efficiency, and environmental sustainability. Employing the advanced simulation capabilities of anyLogistix (ALX), the study constructs a digital twin of a conventional supply chain network, encompassing suppliers, production facilities, distribution centers, and customer endpoints. The research methodically integrates Autonomous Vehicles into this intricate network, aiming to unravel the multifaceted effects on transportation logistics including transit times, cost-efficiency, and sustainability. Through simulations and scenarios analysis, the study scrutinizes the operational resilience and adaptability of supply chains in the face of dynamic market conditions and disruptive technologies like Autonomous Vehicles. Furthermore, the thesis undertakes carbon footprint analysis, quantifying the environmental benefits and challenges associated with the adoption of Autonomous Vehicles in supply chain operations. The insights from this research are anticipated to offer a strategic framework for industry stakeholders, guiding the adoption of Autonomous Vehicles to foster a more efficient, responsive, and sustainable supply chain ecosystem. The findings aim to serve as a cornerstone for future research and practical implementations in the realm of intelligent transportation and supply chain management.

Keywords: autonomous vehicle, agri-food supply chain, ALX simulation, anyLogistix

Procedia PDF Downloads 44

Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

Procedia PDF Downloads 56

Authors: Leo Byrne, Neil Watts

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In the complex and evolving landscape of global trade, maritime sanctions emerge as a critical tool wielded by the international community to curb illegal activities and alter the behavior of non-compliant states and entities. These sanctions, designed to restrict or prohibit trade by sea with sanctioned jurisdictions, entities, or individuals, face continuous challenges due to the sophisticated evasion tactics employed by countries like North Korea. As the Democratic People's Republic of Korea (DPRK) diverts significant resources to circumvent these measures, understanding the nuances of their methodologies becomes imperative for maintaining the integrity of global trade systems. The DPRK, one of the most sanctioned nations globally, has developed an intricate network to facilitate its trade in illicit goods, ensuring the flow of revenue from designated activities continues unabated. Given its geographic and economic conditions, North Korea predominantly relies on maritime routes, utilizing foreign ports to route its illicit trade. This reliance on the sea is exploited through various sophisticated methods, including the use of front companies, falsification of documentation, commingling of bulk cargos, and physical alterations to vessels. These tactics enable the DPRK to navigate through the gaps in regulatory frameworks and lax oversight, effectively undermining international sanctions regimes Maritime sanctions carry significant implications for global trade, imposing heightened risks in the maritime domain. The deceptive practices employed not only by the DPRK but also by other high-risk jurisdictions, necessitate a comprehensive understanding of UN targeted sanctions. For stakeholders in the maritime sector—including maritime authorities, vessel owners, shipping companies, flag registries, and financial institutions serving the shipping industry—awareness and compliance are paramount. Violations can lead to severe consequences, including reputational damage, sanctions, hefty fines, and even imprisonment. To mitigate risks associated with these deceptive practices, it is crucial for maritime sector stakeholders to employ rigorous due diligence and regulatory compliance screening measures. Effective sanctions compliance serves as a protective shield against legal, financial, and reputational risks, preventing exploitation by international bad actors. This requires not only a deep understanding of the sanctions landscape but also the capability to identify and manage risks through informed decision-making and proactive risk management practices. As the DPRK and other sanctioned entities continue to evolve their sanctions evasion tactics, the international community must enhance its collective efforts to demystify and counter these practices. By leveraging more stringent compliance measures, stakeholders can safeguard against the illicit use of the maritime domain, reinforcing the effectiveness of maritime sanctions as a tool for global security. This paper seeks to dissect North Korea's adaptive strategies in the face of maritime sanctions. By examining up-to-date, geographically, and temporally relevant case studies, it aims to shed light on the primary nodes through which Pyongyang evades sanctions and smuggles goods via third-party ports. The goal is to propose multi-level interaction strategies, ranging from governmental interventions to localized enforcement mechanisms, to counteract these evasion tactics.

Keywords: maritime, maritime sanctions, international sanctions, compliance, risk

Procedia PDF Downloads 52

Authors: Marco F. Benaglia, Mei H. Chen, Kune M. Tsai, Chia H. Hung

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As societal and family structures, consumer dietary habits, and awareness about food safety and quality continue to evolve in most developed countries, the demand for refrigerated and frozen foods has been growing, and the issues related to their preservation have gained increasing attention. A well-established cold chain logistics system is essential to avoid any temperature abuse; therefore, assessing potential disruptions in the operational processes of cold chain logistics centers becomes pivotal. This study preliminarily employs HACCP to find disruption factors in cold chain logistics centers that may cause temperature abuse. Then, concept mapping is applied: selected experts engage in brainstorming sessions to identify any further factors. The panel consists of ten experts, including four from logistics and home delivery, two from retail distribution, one from the food industry, two from low-temperature logistics centers, and one from the freight industry. Disruptions include equipment-related aspects, human factors, management aspects, and process-related considerations. The areas of observation encompass freezer rooms, refrigerated storage areas, loading docks, sorting areas, and vehicle parking zones. The experts also categorize the disruption factors based on perceived similarities and build a similarity matrix. Each factor is evaluated for its impact, frequency, and investment importance. Next, multiple scale analysis, cluster analysis, and other methods are used to analyze these factors. Simultaneously, key disruption factors are identified based on their impact and frequency, and, subsequently, the factors that companies prioritize and are willing to invest in are determined by assessing investors’ risk aversion behavior. Finally, Cumulative Prospect Theory (CPT) is applied to verify the risk patterns. 66 disruption factors are found and categorized into six clusters: (1) "Inappropriate Use and Maintenance of Hardware and Software Facilities", (2) "Inadequate Management and Operational Negligence", (3) "Product Characteristics Affecting Quality and Inappropriate Packaging", (4) "Poor Control of Operation Timing and Missing Distribution Processing", (5) "Inadequate Planning for Peak Periods and Poor Process Planning", and (6) "Insufficient Cold Chain Awareness and Inadequate Training of Personnel". This study also identifies five critical factors in the operational processes of cold chain logistics centers: "Lack of Personnel’s Awareness Regarding Cold Chain Quality", "Personnel Not Following Standard Operating Procedures", "Personnel’s Operational Negligence", "Management’s Inadequacy", and "Lack of Personnel’s Knowledge About Cold Chain". The findings show that cold chain operators prioritize prevention and improvement efforts in the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster, particularly focusing on the factors of "Temperature Setting Errors" and "Management’s Inadequacy". However, through the application of CPT theory, this study reveals that companies are not usually willing to invest in the improvement of factors related to the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster due to its low occurrence likelihood, but they acknowledge the severity of the consequences if it does occur. Hence, the main implication is that the key disruption factors in cold chain logistics centers’ processes are associated with personnel issues; therefore, comprehensive training, periodic audits, and the establishment of reasonable incentives and penalties for both new employees and managers may significantly reduce disruption issues.

Keywords: concept mapping, cold chain, HACCP, cumulative prospect theory

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Authors: Petr Šimek

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This work deals with the problem of synchronization of bus frames during transmission using USB (Universal Serial Bus). The principles for synchronization between USB and the non-deterministic CAN (Controller Area Network) bus will be described here. Furthermore, the work deals with ensuring the time sequence of communication frames when receiving from multiple communication bus channels. The structure of a general object for storing frames from different types of communication buses, such as CAN and LIN (Local Interconnect Network), will be described here. Finally, an evaluation of the communication throughput of bus frames for USB High speed will be performed. The creation of this architecture was based on the analysis of the communication of control units with a large number of communication buses. For the design of the architecture, a test HW with a USB-HS interface was used, which received previously known messages, which were compared with the received result. The result of this investigation is the block architecture of the control program for test HW ensuring correct data transmission via the USB bus.

Keywords: analysis, CAN, interface, LIN, synchronization, USB

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Authors: Frederick Kobe O. Obar, Preity B. Quinzon, Trisha B. Tumbokon, Mario Joshua D. Marron, Kenichi Katsuo Kichiro A. Rimorin

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The Public Utility Vehicle Modernization Program (PUVMP) is a program meant to reform the current state of the Philippines’ public transportation sector. This study determined the impact of the Public Utility Vehicle Modernization Program on San Fernando City, La Union's jeepney drivers, interviewing six individuals, three with traditional vehicles and three with modernized units. This study used a descriptive qualitative research design and employed purposive sampling to select the six participants suited for the study, who were then subjected to a semi-structured face-to-face interview. The gathered data was then analyzed through thematic analysis. The findings highlighted evidence that the jeepney drivers experienced abrupt and prevailing changes in their routine and in their everyday work. This study concludes that while the sentiment of the program was appreciated, it has changed the environment for jeepney drivers drastically, provoking many reactions. These changes have, of course, shifted the daily lives of the jeepney drivers significantly, but through adaptability, they found ways. Recommendations include flexible compliance policies, educational initiatives, and support for drivers, providing valuable insights for informed decision-making in the ongoing transportation modernization discussion. This study concluded that while the drivers are not opposed to reform, they are not entirely in approval of the current effects of the program as it is being implemented in their local area.

Keywords: transport reform, transport modernization, public transport, jeepney drivers, PUVMP, urban planning, public utility vehicles

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Authors: Ehsan Yari

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In this paper, a numerical study of sheet cavitation has been performed on DTMB4119 and E779A marine propellers with the boundary element method. In propeller design, various parameters of geometry and fluid are incorporated. So a program is needed to solve the flow taking the whole parameters changing into account. The capability of analyzing the wetted and cavitation flow around propellers in steady, unsteady, uniform, and non-uniform conditions while decreasing computational time compared to numerical finite volume methods with acceptable precision are the characteristic features of the present method. Moreover, modifying the position of the detachment point and its corresponding potential value has been considered. Numerical results have been validated with experimental data, showing a good conformation.

Keywords: cavitation, BEM, DTMB4119, E779A

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Authors: Mingwei Yi, Liujie Guo, Zongjun Pan, Xiang Lin, Xiaoming Yi

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With the rapid expansion of road construction mileage in China, the scale of road maintenance needs has concurrently escalated. As the service life of roads extends, the design of pavement repair and maintenance emerges as a crucial component in preserving the excellent performance of the pavement. The remaining service life of asphalt pavement structure is a vital parameter in the lifecycle maintenance design of asphalt pavements. Based on an analysis of pavement structural integrity, this study introduces a characterization and assessment of the remaining life of existing asphalt pavement structures. It proposes indicators such as the transverse crack spacing and the length of longitudinal cracks. The transverse crack spacing decreases with an increase in maintenance intervals and with the extended use of semi-rigid base layer structures, although this trend becomes less pronounced after maintenance intervals exceed 4 years. The length of longitudinal cracks increases with longer maintenance intervals, but this trend weakens after five years. This system can support the enhancement of standardization and scientific design in highway maintenance decision-making processes.

Keywords: structural integrity, highways, pavement evaluation, asphalt concrete pavement

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Authors: Saad Roustom, Hajo Ribberink

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In most cities in the world, traffic has increased strongly over the last decades, causing high levels of congestion and deteriorating inner-city air quality. This study analyzes the impact of connected and automated vehicles (CAVs) on traffic performance and greenhouse gas (GHG) emissions under different CAV penetration rates in mixed fleet environments of CAVs and driver-operated vehicles (DOVs) and under three different traffic demand levels. Utilizing meso-scale traffic simulations of the City of Ottawa, Canada, the research evaluates the traffic performance of three distinct CAV driving behaviors—Cautious, Normal, and Aggressive—at penetration rates of 25%, 50%, 75%, and 100%, across three different traffic demand levels. The study employs advanced correlation models to estimate GHG emissions. The results reveal that Aggressive and Normal CAVs generally reduce traffic congestion and GHG emissions, with their benefits being more pronounced at higher penetration rates (50% to 100%) and elevated traffic demand levels. On the other hand, Cautious CAVs exhibit an increase in both traffic congestion and GHG emissions. However, results also show deteriorated traffic flow conditions when introducing 25% penetration rates of any type of CAVs. Aggressive CAVs outperform all other driving at improving traffic flow conditions and reducing GHG emissions. The findings of this study highlight the crucial role CAVs can play in enhancing urban traffic performance and mitigating the adverse impact of transportation on the environment. This research advocates for the adoption of effective CAV-related policies by regulatory bodies to optimize traffic flow and reduce GHG emissions. By providing insights into the impact of CAVs, this study aims to inform strategic decision-making and stimulate the development of sustainable urban mobility solutions.

Keywords: connected and automated vehicles, congestion, GHG emissions, mixed fleet environment, traffic performance, traffic simulations

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Loïc Warscotte, Jehan Boreux

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The scientific literature of changepoint detection is vast. Today, a lot of methods are available to detect abrupt changes or slight drift in a signal, based on CUSUM or EWMA charts, for example. However, these methods rely on strong assumptions, such as the stationarity of the stochastic underlying process, or even the independence and Gaussian distributed noise at each time. Recently, the breakthrough research on locally stationary processes widens the class of studied stochastic processes with almost no assumptions on the signals and the nature of the changepoint. Despite the accurate description of the mathematical aspects, this methodology quickly suffers from impractical time and space complexity concerning the signals with high-rate data collection, if the characteristics of the process are completely unknown. In this paper, we then addressed the problem of making this theory usable to our purpose, which is monitoring a high-speed weigh-in-motion system (HS-WIM) towards direct enforcement without supervision. To this end, we first compute bounded approximations of the initial detection theory. Secondly, these approximating bounds are empirically validated by generating many independent long-run stochastic processes. The abrupt changes and the drift are both tested. Finally, this relaxed methodology is tested on real signals coming from a HS-WIM device in Belgium, collected over several months.

Keywords: changepoint, weigh-in-motion, process, non-parametric

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Authors: Samira Hamiditehrani

Abstract:

Automated vehicles (AVs) are emerging technologies that could potentially offer a wide range of opportunities and challenges for the transportation sector. The advent of AV technology has also resulted in new business models in shared mobility services where many ride hailing and car sharing companies are developing on-demand AVs including shared automated vehicles (SAVs) and pooled automated vehicles (Pooled AVs). SAVs and Pooled AVs could provide alternative shared mobility services which encourage sustainable transport systems, mitigate traffic congestion, and reduce automobile dependency. However, the success of on-demand AVs in addressing major transportation policy issues depends on whether and how the public adopts them as regular travel modes. To identify conditions under which individuals may adopt on-demand AVs, previous studies have applied human behavior and technology acceptance theories, where Theory of Planned Behavior (TPB) has been validated and is among the most tested in on-demand AV research. In this respect, this study has three objectives: (a) to propose and validate a theoretical model for behavioral intention to use SAVs and Pooled AVs by extending the original TPB model; (b) to identify the characteristics of early adopters of SAVs, who prefer to have a shorter and private ride, versus prospective users of Pooled AVs, who choose more affordable but longer and shared trips; and (c) to investigate Canadians’ intentions to adopt on-demand AVs for regular trips. Toward this end, this study uses data from an online survey (n = 3,622) of workers or adult students (18 to 75 years old) conducted in October and November 2021 for six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa, Montreal, Calgary, and Hamilton. To accomplish the goals of this study, a base bivariate ordered probit model, in which both SAV and Pooled AV adoptions are estimated as ordered dependent variables, alongside a full structural equation modeling (SEM) system are estimated. The findings of this study indicate that affective motivations such as attitude towards AV technology, perceived privacy, and subjective norms, matter more than sociodemographic and travel behavior characteristic in adopting on-demand AVs. Also, the results of second objective provide evidence that although there are a few affective motivations, such as subjective norms and having ample knowledge, that are common between early adopters of SAVs and PooledAVs, many examined motivations differ among SAV and Pooled AV adoption factors. In other words, motivations influencing intention to use on-demand AVs differ among the service types. Likewise, depending on the types of on-demand AVs, the sociodemographic characteristics of early adopters differ significantly. In general, findings paint a complex picture with respect to the application of constructs from common technology adoption models to the study of on-demand AVs. Findings from the final objective suggest that policymakers, planners, the vehicle and technology industries, and the public at large should moderate their expectations that on-demand AVs may suddenly transform the entire transportation sector. Instead, this study suggests that SAVs and Pooled AVs (when they entire the Canadian market) are likely to be adopted as supplementary mobility tools rather than substitutions for current travel modes

Keywords: automated vehicles, Canadian perception, theory of planned behavior, on-demand AVs

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Authors: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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