Browse Topic: Urban mobility

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A Real-Time Repositioning Strategy for SAEV Fleets Using a Simulation-Informed Deep Learning Model2026-01-0035To be published on 04/07/2026
Shared Autonomous Electric Vehicles (SAEVs) can enhance urban mobility and efficiency. However, their operational performance is often hindered by the spatio-temporal imbalance between vehicle supply and passenger demand, leading to long wait times. This paper develops a novel repositioning framework where a lightweight CNN, informed by computationally intensive multi-agent simulations, enables real-time strategy deployment. The results show that: (1) An optimized repositioning policy, calibrated via multi-agent simulation, effectively cuts the mean passenger waiting time from 12.0 to 3.0 minutes (a 75% reduction). (2) A lightweight CNN surrogate model enables real-time deployment, reducing the policy computation time from ~4 hours to ~5 minutes (>98% faster). (3) The deep learning surrogate achieves this speed with a negligible performance trade-off, increasing the waiting time by only 0.156 minutes (4.9%) compared to the full optimization.
Shang, Kai, Wang, Ning
A Real-Time Vehicle Detection and Counting System Using a GUI Interface.2026-01-0156To be published on 04/07/2026
The growing need for intelligent traffic monitoring and environmental control has fuelled the importance of automated vehicle detection and counting systems. Fuel consumption estimation, vehicular emissions calculations, and traffic pattern comprehension- all play a vital role in shaping sustainable environmental policies. Therefore, accurate identification and counting of vehicles is essential. In this paper, we have shown the development of a real-time vehicle detection and counting application that uses computer vision and deep learning techniques to effectively detect, categorise, and count several types of vehicles on Indian roads. The computer vision vehicle counting application uses the YOLO (You Only Look Once) deep learning model for real-time identification and categorisation of diverse vehicle types, including cars, buses, trucks, and motorbikes [1]. A tracking module based on the SORT (Simple Online and Real-time Tracking) algorithm ensures unique identification of vehicles
Gusain, Ashna, Maurya, Akshay, PATHAK, SUNIL, Khan, Tuhin
Development of Plug-in Hybrid Motorbike and Analysis towards Sustainable Urban Mobility2026-28-0111To be published on 02/12/2026
The transportation system is one major catalyst to urban ecological imbalance. In developing countries, two-wheelers are considered a major mode of urban personal transportation because of their compactness, easy maneuver in heavy traffic and good fuel efficiency. In India, middle and lower middle-class people prefer to choose two wheelers and these vehicles are dominantly fueled by gasoline. Although, the energy consumption by a two-wheeler is comparatively less than that of a four-wheeler, they use about 60% of the nation's petroleum for on-road vehicles and the impact on urban air quality and climatic change is significantly high. This high proportion of gasoline utilization and emission contribution by two wheelers in cities demand greater attention as a way to improve urban air quality and near-term energy sustainability. Electrification of two-wheelers through the application of a plug-in hybrid idea is a promising solution. A plug-in hybrid motorbike was developed by putting
Kannan, Prashanth, Shaik, Amjad, Talluri, Srinivasa Rao
A Comprehensive Study: The Potential of Wireless Charging in Future E Mobility2026-26-01951/16/2026
Electric mobility is no longer a distant vision, it is a global imperative in the journey of fight against the climate change and the urban pollution. Yet, despite of explosive growth in the electric vehicle adoptions, a major bottleneck remains which is efficient and convenient charging. The current reliance on physical plug in charging station creates inconvenient, time consuming experience and also faces significant technical and economic challenges those threaten to stall the smooth clean transportation revolution. Without innovation in how we recharge our vehicle the promise of electric mobility appears under threat which is undermined by less efficient, less compatible, and infrastructure hurdles. Wireless charging technology stand out as the game changing breakthrough poised to tackle these all critical problems head on. By enabling the effortless, cable-free charging system across the wide spectrum of electric vehicles, from the personal cars to the public transport fleets and
Jain, Gaurav, Premlal, P, Pathak, Rahul, Gore, Pandurang
Revolutionizing Urban Mobility in India: The Emergence of the 2-3 Wheel Combi Vehicle and the L2-5 Regulatory Framework2026-26-01871/16/2026
Growing population in Indian cities has led to packed roads. People need a quick option to commute for both personal trips and business needs. The 2-3 Wheel Combination Vehicle is a new, modular solution that switches between a two-wheeler (2W) and a three-wheeler (3W). Hero has designed SURGE S32 to be a sustainable and flexible transportation option. It is world’s first class changing vehicle. The idea is to use a single vehicle for zipping through city traffic, making deliveries, or earning an income. Manufactured to deal with the challenges of modern life, this dual-battery convertible vehicle can easily transform from a two-wheeler to a three-wheeler and vice versa within three minutes. The Surge S32 is a versatile vehicle that replaces the need for multiple specialised vehicles. By lowering the number of vehicles on the road, it decreases road congestion, reduces emissions, and improves livelihoods. It powers by electricity, ensuring sustainability in all aspects. The current
Ali Khan, Feroz, Gupta, Eshan
Path Planning and Control Strategies for a Semi-Autonomous Light Commercial Vehicle Navigating and Avoiding Static Obstacles in Urban Environments2026-26-01341/16/2026
This paper presents the design and implementation of a Semi-Autonomous Light Commercial Vehicle (LCV) capable of following a person while performing obstacle avoidance in urban and controlled environments. The LCV leverages its onboard 360-degree view camera, RTK-GNSS, Ultrasonic sensors, and algorithms to independently navigate the environment, avoiding obstacles and maintaining a safe distance from the person it is following. The path planning algorithm described here generates a secondary lateral path originating from the primary driving path to navigate around static obstacles. A Behavior Planner is utilized to decide when to generate the path and avoid obstacles. The primary objective is to ensure safe navigation in environments where static obstacles are prevalent. The LCV's path tracking is achieved using a combination of Pure Pursuit and Proportional-Integral (PI) controllers. The Pure Pursuit controller is utilized as lateral control to follow the generated path, ensuring
Ayyappan, Vimal Raj, Dhanopia, Rashmi, Ali, Ashpak, N, Ragesh, Sato, Hiromitsu
Research on Passengers’ Willingness to Travel by Rail Transit Based on Objective Factors and Subjective Perceptions2025-99-025112/23/2025
In the context of the accelerating urbanization process, the problem of urban traffic congestion has become more severe. Rail transit, with its advantages of high efficiency, convenience, and environmental friendliness, has become a key force in alleviating urban traffic pressure. An in - depth exploration of passengers’ willingness to travel by rail transit is of great significance for optimizing urban traffic planning, improving the service quality of rail transit, and promoting the sustainable development of cities. This article starts from two dimensions: objective factors and passengers’ subjective perceptions, and comprehensively uses a variety of research methods to conduct an in - depth study on passengers’ willingness to travel by rail transit. In terms of objective factors, this article analyzes the differences in subjective perceptions among different passenger groups from the perspectives of gender, age, education level, and occupation. In terms of subjective perceptions
Wang, Gang, Huang, Lei, Yang, Yihao
Urban Mobility: A Technological Contribution to the Modeling of a Conceptual Framework in a Cyber-Physical Environment for Reducing Traffic Congestion in the Expanded Downtown Area of São Paulo2025-36-009512/18/2025
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Mello Filho, Luiz Vicente Figueira de, Canteras, Felippe Benavente, Meyer, Yuri Alexandre, Emiliano, William Machado, Júnior, Vitor Eduardo Molina, Gabriel, João Carlos, Iano, Yuzo
Vehicle Gear Shifting Optimization for Fuel Consumption and Emissions Minimization2025-36-011112/18/2025
Vehicles powered by internal combustion engines play a crucial role in urban mobility and still represent the vast majority of vehicles produced. However, these vehicles significantly contribute to pollutant emissions and fossil fuel consumption. In response to this challenge, various technologies and strategies have been developed to reduce emissions and enhance vehicle efficiency. This paper presents the development of a solution based on optimized gear-shifting strategies aimed at minimizing fuel consumption and emissions in vehicles powered exclusively by internal combustion engines. To achieve this, a longitudinal vehicle dynamics model was developed using the MATLAB/Simulink platform. This model incorporates an engine combustion simulation based on the Advisor (Advanced Vehicle Simulator) tool, which estimates fuel consumption and emissions while considering catalyst efficiency under transient engine conditions. Based on these models, an optimization method was employed to
Da Silva, Vitor Henrique Gomes, Carvalho, Áquila Chagas, Lopez, Gustavo Adolfo Gonzales, Casarin, Felipe Eduardo Mayer, Dedini, Franco Giuseppe, Eckert, Jony Javorski
2025 International Conference on Transportation Infrastructure and Engineering (ICTIE 2025)2025-99-030012/17/2025
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SAE TOMORROW TODAY - Solving the EV Charging Gap for City Drivers1353910/16/2025
The future of urban mobility depends on one thing: accessible EV charging infrastructure. For the 40 million U.S. drivers who park on city streets, the lack of home charging options makes transitioning to an EV nearly impossible. And that's where it's electric comes in. Unlike traditional public EV chargers, it's electric connects directly to nearby buildings and "juicy corners", offering a cost-effective, scalable solution that doesn't rely on expensive utility upgrades. Property owners benefit too -- earning passive income while enabling their communities to embrace clean, sustainable transportation. Listen in as we sit down with Nathan King, Co-Founder & CEO, and Tiya Gordon, Co-Founder & COO, discuss how it's electric is solving one of the biggest barriers to urban EV adoption by redefining how cities deploy curbside EV charging. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to
Patterson, Lori
The VERT GPF-Retrofit Program for Cleaner Urban Mobility within the HORIZON Europe AeroSolfd Project2025-24-00959/7/2025
Launched in 2022, AeroSolfd, a HORIZON Europe project, aims to advance clean urban mobility by developing affordable and sustainable retrofit solutions for gasoline vehicles. This three-year initiative addresses not only tailpipe emissions but also brake emissions and pollution in semi-enclosed environments. Within AeroSolfd, the Swiss-based VERT association focuses on reducing tailpipe emissions using state-of-the-art Gasoline Particulate Filter (GPF) technology featuring an uncoated ceramic multicell wall-flow filter. VERT, in partnership with HJS, CPK, BFH, developed and tested a GPF-retrofit system at Technology Readiness Level 8 (TRL 8). Results demonstrate over 99% filtration efficiency for particles smaller than 500 nm on standard cycles (WLTC) and real-world driving cycles (RDE). Forty-two gasoline vehicles (GDI and PFI) were retrofitted with the GPF retrofit across Germany, Switzerland, Israel, and Denmark over a 6 to 8-month operational period. No issues were observed with
Rubino, Lauretta, Mayer, Andreas C., Lutz, Thomas W., Czerwinski, Jan, Larsen, Lars C.
U-Shift IV: Innovations and Challenges in Autonomous Urban Mobility2025-01-02847/2/2025
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
Pohl, Eric, Scheibe, Sebastian, Münster, Marco, Osebek, Manuel, Kopp, Gerhard, Siefkes, Tjark
Reducing Traffic Congestion with Reinforcement Learning-Driven Signal Control Systems2025-01-02837/2/2025
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
Kalra, Vikhyat, Tulpule, Punit, Giuliani, Pio Michele
A Power Split eCVT Hybrid for Sustainable Urban Mobility2024-32-00294/18/2025
The main drivers for powertrain electrification of two-wheelers, motorcycles and ATVs are increasingly stringent emission and noise limitations as well as the upcoming demand for carbon neutrality. Two-wheeler applications face significantly different constraints, such as packaging and mass targets, limited charging infrastructure in urban areas and demanding cost targets. Battery electric two wheelers are the optimal choice for transient city driving with limited range requirements. Hybridization provides considerable advantages and extended operation limits. Beside efficiency improvement, silent and zero emission modes with solutions allowing fully electric driving, combined boosting enhances performance and transient response. In general, there are two different two-wheeler base categories for hybrid powertrains: motorcycles featuring frame-integrated internal combustion engine (ICE) and transmission units, coupled with secondary drives via chain or belt; and scooters equipped with
Schoeffmann, W., Fuckar, G., Hubmann, C., Gruber, M.
Next-Gen Italian Urban Mobility: Emissions LCA and TCO Prospective for Innovative Transportation Solutions2025-01-85934/1/2025
Reducing vehicle numbers and enhancing public transport can significantly cut emissions in the transport sector. Hydrogen-fueled and battery electric buses show the potential for decarbonization, but a Life Cycle Assessment (LCA) is essential to evaluate carbon emissions from energy production and manufacturing. In addition, even associated pollutant emissions, together with components’ wear, must be taken into account to evaluate the overall environmental impact. Total Cost of Ownership (TCO) analysis complements this by assessing long-term expenses, enabling stakeholders to balance environmental and economic considerations. This study examines carbon and pollutant emissions alongside TCO for innovative urban mobility powertrains (compared with diesel), focusing on Italian current and future hydrogen and electricity mix scenarios, even considering 100 % green hydrogen (100GH), the goal being to support sustainable decision-making and to promote eco-friendly transport solutions. The
Brancaleoni, Pier Paolo, Damiani Ferretti, Andrea Nicolò, Corti, Enrico, Ravaglioli, Vittorio, Moro, Davide
Efficient Sidewalk Route Planning on Aerial Images with Cost-Based A* and Mini-Max Objective Function2025-01-80324/1/2025
With the growing diversification of modern urban transportation options, such as delivery robots, patrol robots, service robots, E-bikes, and E-scooters, sidewalks have gained newfound importance as critical features of High-Definition (HD) Maps. Since these emerging modes of transportation are designed to operate on sidewalks to ensure public safety, there is an urgent need for efficient and optimal sidewalk routing plans for autonomous driving systems. This paper proposed a sidewalk route planning method using a cost-based A* algorithm and a mini-max-based objective function for optimal routes. The proposed cost-based A* route planning algorithm can generate different routes based on the costs of different terrains (sidewalks and crosswalks), and the objective function can produce an efficient route for different routing scenarios or preferences while considering both travelling distance and safety levels. This paper’s work is meant to fill the gap in efficient route planning for
Bao, Zhibin, Lang, Haoxiang, Lin, Xianke
Letter from the Guest Editors13-06-01-00013/27/2025
Letter from the Guest Editors
Kolhe, Mohan Lal, Zhang, Ronghui
A Real-Time Multiplayer SUMO-Unity Co-Simulation Platform for Vehicle-Aircraft Coordinated Operation2025-01-71972/21/2025
As the demands for air travel and air cargo continue to grow, airport surface operations are becoming increasingly congested, elevating the operational risks for all entities. Conventional measurement methods in airport traffic scenarios are limited by high temporal and spatial costs, uncontrollable variables, and their inabilities to account for low-probability events. Moreover, current simulation software for airport operations exhibits weak simulation capabilities and poor interactivity. To address these issues, this study developed a virtual reality traffic simulation platform for airport surface operations. The platform integrated 3D modeling technologies, including Blender and Unity, with the Photon Fusion multiplayer platform and Simulation of Urban Mobility (SUMO) traffic simulation software. By incorporating Logitech external devices, the platform enabled real-time human-driven simulations, multiplayer online interactions, and validation of airport traffic flow models. To
Zhang, Yuheng, Han, Zhongyi, Zhang, Yuhan, Ye, Zhirui
Privacy Risk Assessment of Travel Trajectories in Metro AFC Data2025-01-72142/21/2025
The rapid expansion of metro systems in major cities worldwide has resulted in the accumulation of vast amounts of travel data through Automatic Fare Collection (AFC) systems. While this data is crucial for enhancing and optimizing transportation networks, it also raises significant concerns regarding passenger privacy due to the potential exposure of individual travel patterns. In this paper, we propose a novel privacy risk assessment model aimed at quantifying the uniqueness of travel trajectories and evaluating the associated privacy threats. Utilizing AFC data from Chengdu collected in March 2021, we first employ an information entropy approach to assess the uniqueness of travel trajectories across different time granularities. We then apply the K-Means clustering algorithm to classify these trajectories into categories based on their uniqueness levels, enabling us to investigate how factors like travel time and routes influence trajectory uniqueness. To further understand the
Fan, Xiaoting, Qu, Xu, Yang, Hongtai
AI-Based Smart Vehicle Parking System2024-01-524212/10/2024
This project presents the development of an advanced Autonomous Mobile Robot (AMR) designed to autonomously lift and maneuver four-wheel drive vehicles into parking spaces without human intervention. By leveraging cutting-edge camera and sensor technologies, the AMR integrates LIDAR for precise distance measurements and obstacle detection, high-resolution cameras for capturing detailed images of the parking environment, and object recognition algorithms for accurately identifying and selecting available parking spaces. These integrated technologies enable the AMR to navigate complex parking lots, optimize space utilization, and provide seamless automated parking. The AMR autonomously detects free parking spaces, lifts the vehicle, and parks it with high precision, making the entire parking process autonomous and highly efficient. This project pushes the boundaries of autonomous vehicle technology, aiming to contribute significantly to smarter and more efficient urban mobility systems.
Atheef, M. Syed, Sundar, K. Sham, Kumar, P. P. Prem, Karthika, J.
Technical Paper for 11 TH SAE India International Mobility Conference Relevance of Autonomous Vehicles in the Indian Context2024-28-012212/5/2024
Autonomous vehicles (AVs) are positioned to revolutionize transportation, by eliminating human intervention through the use of advanced sensors and algorithms, offering improved safety, efficiency, and convenience. In India, where rapid urbanization and traffic congestion present unique challenges, AVs still hold a significant promise. This technical paper discusses the relevance of autonomous vehicles in the Indian context and the challenges that need to be addressed before the widespread adoption of autonomous vehicles in India. These challenges include the lack of infrastructure, concerns regarding road safety, software vulnerabilities, adaptability of change towards autonomous vehicles, and the management of traffic. The paper also highlights the government's initiatives to encourage the development and adoption of autonomous vehicles, ideology behind the legal framework and the required changes in terms of technological advancements, and urban planning. In a brief manner, this
Mishra, Adarsh, Mathur, Gaurav
Self-Organisation Theory Based Trajectory Optimisation Method for CAVs in Diverging Area2024-01-700711/15/2024
The highway diverging area is a crucial zone for highway traffic management. This study proposes an evaluation method for traffic flow operations in the diverging area within an Intelligent and Connected Environment (ICE), where the application of Connected and Automated Vehicles (CAVs) provides essential technical support. The diverging area is first divided into three road sections, and a discrete state transition model is constructed based on the discrete dynamic traffic flow model of these sections to represent traffic flow operations in the diverging area under ICE conditions. Next, an evaluation method for the self-organization degree of traffic flow is developed using the Extended Entropy Chaos Degree (EECD) and the discrete state transition model. Utilizing this evaluation method and the Deep Q-Network (DQN) algorithm, a short-term vehicle behavior optimization method is proposed, which, when applied continuously, leads to a vehicle trajectory optimization method for the
Fang, Zhaodong, Qian, Pinzheng, Su, Kaichun, Qian, Yu, Leng, Xiqiao, Zhang, Jian
CDO-TCN-BiGRU: An Optimized Hybrid Deep Learning Model for Shared Bicycles Demand Forecasting12-08-03-002410/22/2024
Accurate prediction of the demand for shared bicycles is not only conducive to the operation of relevant enterprises, but also conducive to improving the image of the city, facilitating people’s travel, and solving the balance between supply and demand of bicycles in the region. To precisely predict the demand of shared bicycles, a model combining temporal convolution network (TCN) and bidirectional gating recurrent unit (BiGRU) model is proposed, and the Chernobyl disaster optimizer (CDO) is used to optimize its hyperparameters. It has the ability of TCN to extract sequence features and gated recurrent unit (GRU) to mine time series data and combine the characteristics of CDO with fast convergence and high global search ability, so as to reduce the influence of model hyperparameters. This article selects the shared bicycles travel data in Washington, analyzes its multi-characteristics, and trains it as the input characteristics of the model. In the experiments, we performed comparison
Ma, Changxi, Huang, Xiaoyu, Zhao, Yongpeng, Wang, Tao, Du, Bo
Integration of AI-Powered Vehicles with Smart City Infrastructure to Transform the Future of Automotive World2024-28-002810/17/2024
Artificial Intelligence (AI) has emerged as a transformative force across various industries, revolutionizing processes and enhancing efficiency. In the automotive domain, AI's adaption has ushered in a new era of innovation and driving advancements across manufacturing, safety, and user experience. By leveraging AI technologies, the automotive industry is undergoing a significant transformation that is reshaping the way vehicles are manufactured, operated, and experienced. The benefits of AI-powered vehicles are not limited to their manufacturing, operation, and enhancing the user experience but also by integrating AI-powered vehicles with smart city infrastructure can unlock much more potential of the technology and can offer numerous advantages such as enhanced safety, efficiency, growth, and sustainability. Smart cities aim to create more livable, resilient, and inclusive communities by harnessing innovation through technologies like Internet of Things (IoT), devices, data
Shrimal, Harsh
EMS Optimization of a Series-Hybrid Urban Bus with Hydrogen-Fueled Engine Accounting for NOx Emissions and Eco-Driving2024-24-00099/18/2024
The need to reduce vehicle-related emissions in the great cities has led to a progressive electrification of urban mobility. For this reason, during the last decades, the powertrain adopted for urban buses has been gradually converted from conventional Internal Combustion Engine (ICE), diesel, or Compressed Natural Gas (CNG), to hybrid or pure electric. However, the complete electrification of Heavy-Duty Vehicles (HDVs) in the next years looks to be still challenging therefore, a more viable solution to decarbonize urban transport is the hybrid powertrain. In this context, the paper aims to assess, through numerical simulations, the benefits of a series hybrid-electric powertrain designed for an urban bus, in terms of energy consumption, and pollutants emissions. Particularly a Diesel engine, fueled with pure hydrogen, is considered as a range extender. The work is specifically focused on the design of the Energy Management Strategy (EMS) of the series-hybrid powertrain, by comparing
Nacci, Gianluca, Cervone, Davide, Frasci, Emmanuele, LAKSHMANAN, Vinith Kumar, Sciarretta, Antonio, Arsie, Ivan
Next-gen Urban Buses: Autonomy and ConnectivityEPR20240198/26/2024
The deployment of autonomous urban buses brings with it the hope of addressing concerns associated with safety and aging drivers. However, issues related autonomous vehicle (AV) positioning and interactions with road users pose challenges to realizing these benefits. This report covers unsettled issues and potential solutions related to the operation of autonomous urban buses, including the crucial need for all-weather localization capabilities to ensure reliable navigation in diverse environmental conditions. Additionally, minimizing the gap between AVs and platforms during designated parking requires precise localization. Next-gen Urban Buses: Autonomy and Connectivity addresses the challenge of predicting the intentions of pedestrians, vehicles, and obstacles for appropriate responses, the detection of traffic police gestures to ensure compliance with traffic signals, and the optimization of traffic performance through urban platooning—including the need for advanced communication
Hsu, Tsung-Ming
Toward Explainability in Urban Motion Prediction—Survey and Outlook12-08-01-00098/24/2024
With the influx of artificial intelligence (AI) models aiding the development of autonomous driving (AD), it has become increasingly important to analyze and categorize aspects of their operation. In conjunction with the high predictive power innate to AI solutions, due to the safety requirements inherent to automotive systems and the demands for transparency imposed by legislature, there is a natural demand for explainable and predictable models. In this work, we explore the various strategies that reveal the inner workings of these models at various component levels, focusing on those adapted at the modeling stage. Specifically, we highlight and review the use of explainability in state-of-the-art AI-based scenario understanding and motion prediction methods, which represent an integral part of any AD system. We break the discussion down across three key axes that are inherent to any AI solution: the data, the model architecture, and the loss optimization. For each of the axes, we
Okanovic, Ilma, Stolz, Michael, Hillbrand, Bernhard
A Multi-Target Urban Transportation Structure Model under the Optimal Capacity Limitation of Road Networks13-06-01-00038/10/2024
The construction of urban transportation infrastructures on the supply side is severely limited due to the extensive development of central urban land. Therefore, optimizing the traffic structure with limited resources is particularly important. The work used the optimum capacity of the road network as one of the constraints. Multi-objective linear programming was used to establish the traffic structure model. The total travel volume, energy consumption, travel quality, and social cost were selected as the optimization objectives of the urban transportation structure. The influencing factors of infrastructure capacity (e.g., total travel demand, optimal capacity of road network, slow traffic capacity, and parking lot capacity) were selected as the constraint conditions in optimizing urban transportation structure. The objective was to develop an optimization model considering the constraints of urban infrastructure. Finally, the optimal traffic structure was compared with the actual
Zhang, Jinwei, Gao, Jianping
Exploration of a Precise Traffic Restriction Policy on Urban River-Crossing Corridors: A Case Study in Changsha, China13-06-02-00108/8/2024
Many cities are built around rivers in the world, and the river-crossing corridors are often their traffic bottlenecks, leading to severe congestions. Changsha is a city divided into two parts by a river with eight river-crossing corridors in China. Aiming at this issue, take Changsha as an example, this study explores developing a precise traffic restriction policy on those river-crossing corridors. First, an investigation is conducted to collect traffic flow data of those corridors. It is found that those corridors generally have serious congestion at peak hours, but their congestion levels vary greatly by corridor and direction. Then, two Greenberg models are developed for the 4-lane and 6 & 8-lane corridors, respectively, to figure out their traffic flow features. Third, a precise traffic restriction policy that balances traffic flows in different corridors is proposed. It would restrict 10% of motor vehicles on those most congested corridors, and the restricted vehicles are
Liu, Chenhui, Luo, Qiuju, Wang, Xingyu
Exploration of the Impact of Built Environment Factors on Morning and Evening Peak Ridership at Urban Rail Transit Stations: A Case Study of Changsha, China13-06-02-00097/22/2024
To identify the influences of various built environment factors on ridership at urban rail transit stations, a case study was conducted on the Changsha Metro. First, spatial and temporal distributions of the station-level AM peak and PM peak boarding ridership are analyzed. The Moran’s I test indicates that both of them show significant spatial correlations. Then, the pedestrian catchment area of each metro station is delineated using the Thiessen polygon method with an 800-m radius. The built environment factors within each pedestrian catchment area, involving population and employment, land use, accessibility, and station attributes, are collected. Finally, the mixed geographically weighted regression models are constructed to quantitatively identify the effects of these built environment factors on the AM and PM peak ridership, respectively. The estimation results indicate that population density and employment density have significant but opposite influences on the AM and PM peak
Su, Meiling, Liu, Ling, Chen, Xiyang, Long, Rongxian, Liu, Chenhui
Toward Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations12-08-01-00037/12/2024
Understanding driving scenes and communicating automated vehicle decisions are key requirements for trustworthy automated driving. In this article, we introduce the qualitative explainable graph (QXG), which is a unified symbolic and qualitative representation for scene understanding in urban mobility. The QXG enables interpreting an automated vehicle’s environment using sensor data and machine learning models. It utilizes spatiotemporal graphs and qualitative constraints to extract scene semantics from raw sensor inputs, such as LiDAR and camera data, offering an interpretable scene model. A QXG can be incrementally constructed in real-time, making it a versatile tool for in-vehicle explanations across various sensor types. Our research showcases the potential of QXG, particularly in the context of automated driving, where it can rationalize decisions by linking the graph with observed actions. These explanations can serve diverse purposes, from informing passengers and alerting
Belmecheri, Nassim, Gotlieb, Arnaud, Lazaar, Nadjib, Spieker, Helge
Effects of Renewable Fuels on the Performance and Emissions of a Small Displacement Diesel Engine for Urban Mobility2024-37-00196/12/2024
In the frame of growing concerns over climate change and health, renewable fuels can make an important contribution to decarbonizing the transport sector. The current work presents the results of an investigation into the impact of renewable fuels on the combustion and emissions of a turbocharged compression-ignition internal combustion engine. An experimental study was undertaken and the engine settings were not modified to account for the fuel's chemical and physical properties, to analyze the performance of the fuel as a potential drop-in alternative fuel. Three fuels were tested: mineral diesel, a blend of it with waste cooking oil biodiesel and a hydrogenated diesel. The analysis of the emissions at engine exhaust highlights that hydrogenated fuel is cleaner, reducing CO, total hydrocarbon emissions, particulate matter and NOx.
Chiavola, Ornella, Matijošius, Jonas, Palmieri, Fulvio, Recco, Erasmo
Transportation Ecosystem and Autonomy: Vol. 1EPRCOMPV1920235/3/2024
One-way car-sharing services (CSSs) are believed to be a promising transportation mode for urban mobility. Because of the disparity of city functional areas and population, travel demand and vehicle supply in a CSS system may inevitably tend to be imbalanced as well. Therefore, an essential requirement of one-way CSSs is the capability of providing fleet management solutions to improve the quality of service and system performance. In other words, a CSS depends heavily on technologies that offer strategic decisions for topics like fleet sizing, location and capacity of depots and charging stations, matching of travelers with vehicles, relocation of vehicles and dispatchers for fleet rebalancing, and the balancing and charging schedules of electric vehicles. This chapter addresses trending CSS technologies and outlines some insights into the existing unsettled issues and potential solutions. The discussions and outlook are presented as a collection of key points encountered in system
Guo, Ge, Hou, Yuqin, Kang, Ming, Lv, Chen, Hemphill, Jeff
A Traffic Microsimulation Based Study of an Electric Road System with Dynamic Wireless Power Transfer2024-26-01021/16/2024
Electrification of road transport is a critical step towards establishment of a sustainable transport ecosystem. However, a major hindrance to electric mobility is the high cost and weight of the battery pack. Downsizing the battery pack will not only address these issues, but will also reduce embedded emissions due to battery manufacturing. One approach towards reducing battery pack size and still offering the user of electric vehicles similar mobility experiences as in case of conventional vehicles is to set up extensive network of charging or battery swapping stations. Another approach is to provide the vehicle with required energy while it is on the move. However, conventional systems such as overhead line or conducting rails have several disadvantages in the urban environment. One solution that has come up in this regard in recent times is the concept of Electric Roads System (ERS), which involves dynamic wireless power transfer (DWPT) to the vehicles from power transmitters
Sardar, Arghya, Prasad, Mukti
Vehicle Trajectory Prediction in Highway Merging Area Using Interactive Graph Attention Mechanism2023-01-711012/31/2023
Accurately predicting the future trajectories of surrounding traffic agents is important for ensuring the safety of autonomous vehicles. To address the scenario of frequent interactions among traffic agents in the highway merging area, this paper proposes a trajectory prediction method based on interactive graph attention mechanism. Our approach integrates an interactive graph model to capture the complex interactions among traffic agents as well as the interactions between these agents and the contextual map of the highway merging area. By leveraging this interactive graph model, we establish an agent-agent interactive graph and an agent-map interactive graph. Moreover, we employ Graph Attention Network (GAT) to extract spatial interactions among trajectories, enhancing our predictions. To capture temporal dependencies within trajectories, we employ a Transformer-based multi-head self-attention mechanism. Additionally, GAT are utilized to model the interactions between traffic agents
Wu, Xigang, Chu, Duanfeng, Deng, Zejian, Xin, Guipeng, Liu, Hongxiang, Lu, Liping
A Comparison of Methanol, Methane and Hydrogen Fuels for SI Engines: Performance and Pollutant Emissions2023-24-00378/28/2023
The urban mobility electrification has been proposed as the main solution to the vehicle emission issues in the next years. However, internal combustion engines have still great potential to decarbonize the transport sector through the use of low/zero-carbon fuels. Alcohols such us methanol, have long been considered attractive alternative fuels for spark ignition engines. They have properties similar to those of gasoline, are easy to transport and store. Recently, great attention has been devoted to gaseous fuels that can be used in existing engine after minor modification allowing to drastically reduce the pollutant emissions. In this regard, this study tries to provide an overview on the use of alternative fuels, both liquid and gaseous in spark ignition engines, highlighting the benefits as well as the criticalities. The investigation was carried out on a small displacement spark ignition engine capable to operate both in port fuel and direct injection mode. Engine was fueled with
Catapano, Francesco, Di Iorio, Silvana, Magno, Agnese, Sementa, Paolo, Vaglieco, Bianca Maria
Theoretical Analysis of Multi-Zone and Transported Probability Density Function Approaches Applied to Low Temperature Combustion Process2023-24-00608/28/2023
Electrification of transport, together with the decarbonization of energy production are suggested by the European Union for the future quality of air. However, in the medium period, propulsion systems will continue to dominate urban mobility, making mandatory the retrofitting of thermal engines by applying combustion modes able to reduce NOx and PM emissions while maintaining engine performances. Low Temperature Combustion (LTC) is an attractive process to meet this target. This mode relies on premixed mixture and fuel lean in-cylinder charge whatever the fuel type: from conventional through alternative fuels with a minimum carbon footprint. This combustion mode has been subject of numerous modelling approaches in the engine research community. This study provides a theoretical comparative analysis between multi-zone (MZ) and Transported probability density function (TPDF) models applied to LTC combustion process. The generic thermo-kinetic balances for both approaches have been
Maroteaux, Fadila, Mancaruso, Ezio, Pommier, Pierre-Lin, Vaglieco, Bianca Maria
HORIZON Europe Project AeroSolfd: GPF-Retrofit for Cleaner Urban Mobility2023-24-01148/28/2023
Ultrafine particles, in particular solid sub-100 nm particles pose high risks to human health due to their high lung deposition efficiency, translocation to all organs including the brain and their harmful chemical composition; due to dense traffic, the population in urban environments is exposed to high concentrations of those toxic air contaminants, despite these facts, they are still widely neglected. Therefore, the EU-Commission set up a program for clean and competitive solutions for different problem areas which are regarded to be hotspots of such particles. HORIZON AeroSolfd is an EU project, co-funded by Switzerland that will deliver affordable, adaptable, and sustainable retrofit solutions to reduce exhaust tailpipe emissions from petrol engines, brake emissions and pollution in semi-closed environments. VERT, a Swiss based international industry organization, has a long research history in the field of nanoparticle filtration and it is in charge of reducing tailpipe emissions
Rubino, Lauretta, Mayer, Andreas, Czerwinski, Jan, Lutz, Thomas, Larsen, Lars, Engelmann, Danilo, Lehmann, Martin
An Approach to Model a Traffic Environment by Addressing Sparsity in Vehicle Count Data2023-01-08544/11/2023
For realistic traffic modeling, real-world traffic calibration data is needed. These data include a representative road network, road users count by type, traffic lights information, infrastructure, etc. In most cases, this data is not readily available due to cost, time, and confidentiality constraints. Some open-source data are accessible and provide this information for specific geographical locations, however, it is often insufficient for realistic calibration. Moreover, the publicly available data may have errors, for example, the Open Street Maps (OSM) does not always correlate with physical roads. The scarcity, incompleteness, and inaccuracies of the data pose challenges to the realistic calibration of traffic models. Hence, in this study, we propose an approach based on spatial interpolation for addressing sparsity in vehicle count data that can augment existing data to make traffic model calibrations more accurate. This study will primarily assist in traffic modeling for Fuel
Patil, Mayur, Tulpule, Punit, Midlam-Mohler, Shawn
Intersection Signal Control Based on Speed Guidance and Reinforcement Learning2023-01-07214/11/2023
As a crucial part of the intelligent transportation system, traffic signal control will realize the boundary control of the traffic area, it will also lead to delays and excessive fuel consumption when the vehicle is driving at the intersection. To tackle this challenge, this research provides an optimized control framework based on reinforcement learning method and speed guidance strategy for the connected vehicle network. Prior to entering an intersection, vehicles are focused on in a specific speed guidance area, and important factors like uniform speed, acceleration, deceleration, and parking are optimized. Conclusion, derived from deep reinforcement learning algorithm, the summation of the length of the vehicle’s queue in front of the signal light and the sum of the number of brakes are used as the reward function, and the vehicle information at the intersection is collected in real time through the road detector on the road network. Finally, the proposed method is implemented
Lu, Gaohui, Zhan, Zhenfei, Rehman, Hamza, Chen, Xiatong, He, Xin
The LCA Analysis Applied to Urban Mobility2022-24-00229/16/2022
Electric propulsion is the object of intense research efforts all over the world, as a viable solution to fossil resource exploitation and pollutant emissions, towards a sustainable development. In this paper, we perform a thorough Life Cycle Assessment (LCA) of multiple electrical solutions for urban mobility, from bicycles to buses, comparing the results to those of traditional, fossil-fuel-based vehicles. This activity is of particular interest as the decision of European Parliament to interrupt the fossil fuel vehicles starting from 2035. To assess the life-cycle impact of each solution, several routes within middle size Italian cities, representative of the most Italian cities have been considered. This analysis has been performed by means of an ad-hoc integrated procedure with on-line, free tools that account also for traffic distribution. To carry out a complete study, an LCA analysis has been done which includes all life’s phase of the vehicles, starting from production to
Andreassi, Luca, De Angelis, Lorenzo
Car-sharing Mobility-on-Demand SystemsEPR20220188/24/2022
One-way car-sharing services (CSSs) are believed to be a promising transportation mode for urban mobility. Due to the disparity of city functional areas and population, travel demand and vehicle supply in a CSS may inevitably tend to be imbalanced as well. Therefore, an essential requirement of one-way CSSs is the capability of providing fleet management solutions to improve quality of service and system performance. In other words, a CSS depends heavily on technologies that offer strategic decisions on topics like Fleet sizing Location and capacity of depots and charging stations Matching of travelers with vehicles Relocation of vehicles and dispatchers for fleet rebalancing Balancing and charging schedules of electric vehicles Car-sharing Mobility-on-Demand Systems addresses trending CSS technologies and outlines some insights into the existing unsettled issues and potential solutions. The discussions and outlook are presented as a collection of key points encountered in system
Guo, Ge, Hou, Yuqin, Kang, Ming
A Hybrid Sensor-Fusion System to Locate the Electric Gridlines by UAV for Range Extension in Urban Areas2022-26-00075/26/2022
This paper explores the efficacy and efficiency of a system for the effective location of electric gridlines during daytime and night-time by the onboard and offboard transceivers of UAV through vehicle to infrastructure communication. The usage of electric gridlines in urban areas helps to extend the range of the UAVs by charging the onboard battery using an extended arm. The same arm can also be used for direct propulsion of the motors onboard UAV, thereby minimizing the reliance on battery. UAVs with advanced Image processing algorithms are utilized in the inspection of the electric grid lines themselves in the Power industry. The camera based algorithms are not effective during night-time when the gridlines are near invisible. This can be mitigated by evaluating light in other spectral ranges, but this would add to the load of the UAV. We propose a system which combines multiple information sources and helps locate the gridlines for range extension, specifically for the delivery of
Pappala, Lokendra Pavan Kumar, Enagandula, Srujan, Manoharan, Sandeepkumar
Co-Simulation Platform for Modeling and Evaluating Connected and Automated Vehicles and Human Behavior in Mixed Traffic12-05-04-00254/21/2022
Modeling, prediction, and evaluation of personalized driving behaviors are crucial to emerging advanced driver-assistance systems (ADAS) that require a large amount of customized driving data. However, collecting such type of data from the real world could be very costly and sometimes unrealistic. To address this need, several high-definition game engine-based simulators have been developed. Furthermore, the computational load for cooperative automated driving systems (CADS) with a decent size may be much beyond the capability of a standalone (edge) computer. To address all these concerns, in this study we develop a co-simulation platform integrating Unity, Simulation of Urban MObility (SUMO), and Amazon Web Services (AWS), where Unity provides realistic driving experience and simulates on-board sensors; SUMO models realistic traffic dynamics; and AWS provides serverless cloud computing power and personalized data storage. To evaluate this platform, we select cooperative on-ramp
Zhao, Xuanpeng, Liao, Xishun, Wang, Ziran, Wu, Guoyuan, Barth, Matthew, Han, Kyungtae, Tiwari, Prashant
Aerodynamic Optimization Using Add-On Devices: Comparison Between CFD and Wind Tunnel Experimental Test2022-01-08853/29/2022
JUNO is an urban concept vehicle (developed at the Politecnico of Torino), equipped by an ethanol combustion engine, designed to obtain low consumptions and reduced environmental impact. For these goals the main requirements that were considered during the designing process were mass reduction and aerodynamic optimization, at first on the shape of the car body and then, thanks to add-on devices. JUNO’s aerodynamic development follows a defined workflow: geometry definition and modelling, CFD simulations and analysis, and finally geometry changes and CFD new verification. In this paper the results of the CFD simulations (using STARCCM+ and RANS k-ε) with a corresponding 1/1 scale wind tunnel tests made using the real vehicle. Particularly, the results in term of: total drag coefficient (Cx), total lift coefficient (Cz), the total pressure in the side and rear analyzing twenty different aerodynamics configurations made up of different combination of some aerodynamics add-on devices. From
Carello, Massimiliana, Verratti, Marco
Unsettled Issues Concerning Urban Air Mobility InfrastructureEPR202102511/15/2021
Urban air mobility (UAM) refers to urban transportation systems that move people by air. UAM offers the potential for reducing traffic congestion in cities and providing an integrated approach to urban mobility. With the emergence of electric vertical takeoff and landing (eVTOL) aircraft, drone technology, and the possibility of automated aircraft, interest in this topic has grown considerably for private sector solution providers—including aerospace and technology companies—as well as urban planners and transportation professionals. Unsettled Issues Concerning Urban Air Mobility Infrastructure discusses the infrastructure requirements to effectively integrate UAM services into the overarching urban transportation system to enable multimodal trips and complete origin to destination travel. Click here to access the full SAE EDGETM Research Report portfolio.
McQueen, Bob
Co-Simulation Platform for Modeling and Evaluating Connected and Automated Vehicles and Human Behavior in Mixed TrafficSAE-PP-0020611/13/2021
Modeling, prediction, and evaluation of personalized driving behaviors are crucial to emerging advanced driver-assistance systems (ADAS) which require a large amount of customized driving data. However, collecting such type of data from the real world could be very costly and sometimes unrealistic. To address this need, several high-definition game engine-based simulators have been developed. Furthermore, the computational load for cooperative automated driving systems (CADS) with a decent size may be much beyond the capability of a standalone (edge) computer. To address all these concerns, in this study we develop a co-simulation platform integrating Unity, Simulation of Urban MObility (SUMO), and Amazon Web Services (AWS), where Unity provides realistic driving experience and simulates on-board sensors; SUMO models realistic traffic dynamics; and AWS provides serverless cloud computing power and personalized data storage. To evaluate this platform, we select cooperative on-ramp
Wang, Ziran, Zhao, Xuanpeng, Liao, Xishun, Wu, Guoyuan, Barth, Matthew, Han, Kyungtae, Tiwari, Prashant
Stability and Handling of a Three Wheeled Personal Vehicle2021-26-00849/22/2021
It has been predicted that the prevailing COVID-19 situation would result in increased demand for personal vehicles. There is a renewed interest in the 3 wheeled vehicles for short urban mobility in western countries due to their inherent cost advantages which will make it affordable for the common man. As the world is moving towards electric vehicle technology, a light 3 wheeled vehicle option will also help in reducing battery weight and thereby help in addressing the range concerns. In addition, slow speed 3-wheelers need not pass extensive safety regulation tests in many western countries including the USA. Three-wheeled vehicles are not new to developing countries like India as three-wheeled auto-rickshaws are quite popular for short distance shared travel. The existing single front wheel design known as delta design may have a stigma attached to it due to historic reasons in India. There is also a perception that the three-wheeled vehicles are highly unstable. Therefore, the
Nimje, Rahul, Manivasagam, Dr. Shanmugam, Patil, Amol
Unsettled Issues in Advanced Air Mobility CertificationEPR20210146/18/2021
Advanced air mobility (AAM) refers to urban transportation systems that move people and goods by air. This has significant implications for reducing traffic congestion in cities and for providing an integrated approach to urban mobility. With the emergence of drone technology and the possibility of more autonomous aircraft, interest has grown considerably in AAM. Unsettled Issues in Advanced Air Mobility Certification discusses the impact of AAM on private sector solution providers including aerospace and technology companies and goes into solutions for urban planners and transportation professionals for better integration across all AAM modes. Click here to access the full SAE EDGETM Research Report portfolio.
McQueen, Bob
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