Browse Topic: Congestion

Items (290)
Urban areas around the world are facing an increasing number of issues, such as air pollution, parking shortages, traffic congestion and inadequate transit options, all of which necessitate innovative solutions. Lot of people are becoming interested in micromobility in urban areas as a replacement for quick excursions and round trips to get to or from transportation services (e.g., Offices, Institutions, Hospitals, Tourist spots, etc.). This research examines the critical role that micromobility plays, concentrating on the effectiveness of micromobility smart electric scooters in resolving urgent urban problems. Micromobility, which includes both human and electric-powered vehicles, presents a viable substitute for normal and short-distance urban commuting. This study presents a micromobility smart electric scooter that is portable and easy to operate, with the goal of transforming urban transportation. 3D model was designed using SOLIDWORKS and analyzed using ANSYS. For strength and
Tappa, RajuSingh Chowhan, Sri AanshuShaik, AmjadMaroju, AbhinavTalluri, Srinivasa Rao
Eco-driving algorithms use the available information about traffic and route conditions to optimize the vehicle speed and achieve enhanced energy consumption while fulfilling a travel time constraint. Depending on what information is available, when it becomes accessible, and the level of automation of the vehicle, different energy savings can be achieved. In their basic formulation, eco-driving algorithms only leverage static information to evaluate the optimal speed, such as posted speed limits and location of stop signs. More advanced algorithms may also consider dynamic information, such as the speed of the preceding vehicle and Signal Phase and Timing of traffic lights, thus achieving higher energy efficiency. The objective of the proposed work is to develop an eco-driving algorithm that can optimize energy consumption by leveraging not only static route information, but also dynamic macroscopic traffic conditions, which are assumed to be available in real-time through
Villani, ManfrediShiledar, AnkurBlock, BrianSpano, MatteoRizzoni, Giorgio
Autonomous Navigation (AN) in complex-heterogeneous environments is an unsolved issue for both commercial and defense Autonomous Vehicle (AV) applications: A) Based on accumulated data through 2021 there are on average 9.1 driverless car crashes per million miles driven compared to 4.1 human-driven car crashes. B)The US Army recently reduced the requirement for its current Bradley replacement program of record from an “optionally manned fighting vehicle” to a system that “will not be something you operate entirely unmanned in its initial configuration”. C) Between 2021 and 2023 Ford, UBER, Lyft and Tesla have limited their fully AV operations due to safety related business concerns. It is clear a research breakthrough is needed to ensure AV software is mature to a point where it can handle complex driving scenarios. In complex dynamic domains (e.g. intersections or congested terrain) the expected mode of operation for ensured safety of these unmanned systems is still direct human
Frederick, Philip A.
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, ChenhuiLuo, QiujuWang, Xingyu
There have been numerous studies on stable platooning, but almost all of them have been on the longitudinal stability problem, wherein, without sufficient longitudinal stability, traffic congestion might occur more frequently than in traffic consisting of manually driven vehicles. Failure to solve this problem would reduce the value of autonomous driving. Recently, some researchers have begun to tackle the lateral stability problem, anticipating shortened intervehicle distances in the future. Here, the intervehicle distance in a platoon should be shortened to improve transportation efficiency. However, if an obstacle to be avoided exists, the following vehicles might have difficulty finding it quickly enough if the preceding vehicle occludes it from their sensors. Also, longer platoons improve transportation efficiency because the number of gaps between platoons is reduced. Hence, in this study, the lateral stability of platoons consisting of autonomous vehicles was analyzed for not
Kurishige, Masahiko
The conventional process of last-mile delivery logistics often leads to safety problems for road users and a high level of environmental pollution. Delivery drivers must deal with frequent stops, search for a convenient parking spot and sometimes navigate through the narrow streets causing traffic congestion and possibly safety issues for the ego vehicle as well as for other traffic participants. This process is not only time consuming but also environmentally impactful, especially in low-emission zones where prolonged vehicle idling can lead to air pollution and to high operational costs. To overcome these challenges, a reliable system is required that not only ensures the flexible, safe and smooth delivery of goods but also cuts the costs and meets the delivery target. In the dynamic landscape of last-mile delivery, LogiSmile, an EU project, introduced a solution to urban delivery challenges through an innovative cooperation between an Autonomous Hub Vehicle (AHV) and an Autonomous
Aslam, IqraAniculaesei, AdinaBuragohain, AbhishekZhang, MengBamal, DanielRausch, Andreas
This research investigates platoon dispersion characteristics in mixed-traffic flow of autonomous and human-driven vehicles. It presents a cellular automata-based platoon dispersion model. The study’s key findings are as follows: platoon dispersion initially increases and then decreases with the rise in autonomous vehicle proportions. When the autonomous vehicle proportion is approaching 100%, platoon dispersion descends rapidly and is completely eliminated while the proportion is 100%. Compared to platoon consisting entirely of human-driven vehicles, the peak value of standard deviation of vehicle speed is 1.71 times and the travel time drops by 38.19% when the proportion is 1. Moreover, the lane-changing behavior enhances platoon speed, acceleration, and space utilization at micro- and macrolevels by optimizing space resource allocation within the platoon. The study employs a two-lane mixed-flow platoon dispersion model that assumes uniform vehicle characteristics and prioritizes
Lu, TingLiu, ChenghaoLin, SitongSong, Wenjing
With the rapid growth of automobile ownership, traffic congestion has become a major concern at intersections. In order to alleviate the blockage of intersection traffic flow caused by signals, reduce the length of vehicle congestion and waiting time, and for improving the intersection access efficiency, therefore, this article proposes a vehicle speed guidance strategy based on the intersection signal change by combining the vehicle–road cooperative technology. The randomness of vehicle traveling speed in the road is being considered. According to the vehicle traveling speed, a speed guidance model is established under different conditions. Finally, the effectiveness of the speed guidance strategy in this article is verified through experimental simulation, and the benefits of the intersection with intelligent control and traditional control are compared, and the experimental results show that the intelligent control method in this article can effectively reduce vehicle congestion and
Li, WenliLi, AnRen, YongpengWang, Kan
Lots of invalid volume of traffic occurs as the vehicle repeatedly seeking the valid berth location, due to the existence of information islands, which reduces traffic efficiency, increases traffic congestion and the emission of pollutants. Aiming at eliminating the existence of information islands, this paper proposed a guidance strategy for parking space of autonomous valet parking, as taking merits of cooperative vehicle infrastructure system. The guidance strategy consists of an optimal guidance model and an adaptive ant-colony algorithm. Firstly, the optimal guidance model takes the minimum total parking cost as the objective function and the capacity of parking space as the constraints. Both the objective costs of parking and the subjective cost of customer are taken into accounts in the objective function. Secondly, comparing with traditional method, the adaptive ant-colony algorithm taking two improvements, in order to accelerate the convergence of the algorithm and avoid
Zhang, ZhoupingLiu, WeidongSun, ZhipengZhu, ZuweiHu, YimingZeng, Dequan
General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants. Each component in the design is rigorously analyzed and tested from component to system levels to ensure high
Nassiri Bavili, ArashBasher, KorobiChung, SungAlam, KhorshedLee, Jung-GiChoi, Hong GooKo, Jin-youngAnwar, Mohammad
Getting warehouse robots to and from their destinations efficiently while keeping them from crashing into each other is no easy task. It is such a complex problem that even the best path-finding algorithms struggle to keep up with the breakneck pace of e-commerce or manufacturing. In a sense, these robots are like cars trying to navigate a crowded city center. So, a group of MIT researchers who use AI to mitigate traffic congestion applied ideas from that domain to tackle this problem
In 2018, the state explicitly proposed to “promote the cancellation of expressway toll stations at provincial boundaries.” Electronic toll collection (ETC) has become the main toll collection method on expressways. With the construction of ETC toll lanes, the proportion of ETC vehicles in the expressway traffic flow is increasing, and the rapid processing of vehicle special situations is facing challenges. At present, various provinces have adopted various methods to improve the traffic efficiency and transaction success rate of ETC from the issuance link, customer service link, and lane transaction link. According to statistical data, the average transaction success rate of ETC lane is not higher than 99% at present. As of October 2021, the number of ETC users nationwide has reached 256 million, and there are an average of 40 million ETC transactions per day across the network, that is, about 400,000 special cases need to be processed. How to efficiently deal with special vehicles in
Guo, XiaohuiGuo, FengbinZhang, MengweiZheng, FengfeiLiu, Chunya
In a world increasingly concerned with environmental sustainability and traffic congestion, the need for innovative solutions to address daily commuting challenges has become paramount. This paper presents an innovative concept for an application/system that seeks to revolutionize the way corporate employees commute to work. By harnessing the power of data and technology, this application aims to reduce pollution, traffic, and fuel consumption while promoting shared transportation solutions among employees. The paper discusses the key features and benefits of this proposed application and its potential to create a greener and more efficient corporate commuting ecosystem
Thakare, Ashish
The advent of autonomous vehicles promises to revolutionize the transportation sector globally, and India, as one of the world's fastest-growing economies, stands at the forefront of this transformative technology. This paper presents a brief overview of the current state and potential implications of autonomous vehicles in the Indian context. With its densely populated cities, diverse traffic conditions, and complex road infrastructure, India presents unique challenges and opportunities for the deployment of autonomous vehicles. This technology has the potential to address critical issues such as road safety, congestion, and pollution while transforming the mobility experience for millions of people. However, several hurdles must be overcome to fully harness its benefits. The paper explores key considerations for the implementation of autonomous vehicles in India. These include adapting the technology to navigate chaotic traffic scenarios, addressing infrastructure limitations, and
Shetty, Sharan Harish
India is a highly populous country. The traffic problems faced by the people here are not uncommon. The increase in traffic leads to increase in accidents, pollution, inconvenience and frustration. It also comes with costs of additional fuel and time. Though public transport is extensively available in India, still it isn't sufficient for the population of India. Especially in Metro cities, public transport services are often crowded. So, to travel peacefully people are opting for commuting in their own vehicles. And as a result, more vehicles are coming on roads. Other major reasons for increasing traffic are lack of proper implementation of traffic rules and traffic signals out of sync. In addition to city traffic, congestion is also seen on highways, mainly at toll plazas. Although implementation of FASTag has reduced it to some extent, some toll plazas still face traffic congestion issues. This paper provides an idea to ease the traffic problems in the city and on the highways too
Jain, Pritesh
To mitigate the repercussions arising from traffic accidents on highways and prevent the cascading effect of queued vehicles, a comprehensive model is devised. This model is built upon the foundation of a traffic accident impact determination framework, which considers the merging capacity at entry lanes, as well as a dynamic and adaptable variable speed limit model to dissipate queuing congestion. The objective is to promptly restore vehicle flow after accidents, thereby eradicating queueing effects in the affected zone. The efficacy of this approach has been validated using data from the Sutong Bridge accident, and its effectiveness in eliminating vehicle queues has been verified through simulation data in the SUMO platform. Analysis of average speeds before and after implementing varying speed limits reveals that the proposed method can significantly enhance overall traffic efficiency by 37%. Moreover, the model’s versatile parameters demonstrate good applicability, providing
Shi, XiaoMinWang, BoKe, Guo
Smart cars or autonomous vehicles have garnered significant attention in recent years due to their potential to alleviate traffic congestion, enhance road safety, and improve fuel efficiency. However, effectively navigating through complex terrains requires the implementation of an efficient path planning algorithm. Traditional path planning algorithms often face limitations when confronted with intricate terrains. This study focuses on analyzing the path planning problem for intelligent vehicles in complex terrains by utilizing the optimization evaluation function of the artificial bee colony (ABC) algorithm. Additionally, the impact of turning radius at different speeds is considered during the planning process. The findings indicate that the optimal number of control points varies depending on mission requirements and terrain conditions, necessitating a comparison to obtain the optimal value. Generally, reducing the number of control points facilitates smoother paths, while
Li, DaPengGu, RuiZheng, YujunZuo, Songchen
Connected fuel cell vehicles (C-FCVs) have gained increasing attention for solving traffic congestion and environmental pollution issues. To reduce operational costs, increase driving range, and improve driver comfort, simultaneously optimizing C-FCV speed trajectories and powertrain operation is a promising approach. Nevertheless, this remains difficult due to heavy computational demands and the complexity of real-time traffic scenarios. To resolve these issues, this article proposes a two-level eco-driving strategy consisting of speed planning and energy management layers. In the top layer, the speed planning predictor first predicts dynamic traffic constraints using the long short-term memory (LSTM) model. Second, a model predictive control (MPC) framework optimizes speed trajectories under dynamic traffic constraints, considering hydrogen consumption, ride comfort, and traffic flow efficiency. A multivariable polynomial hydrogen consumption model is also introduced to reduce
Khalatbarisoltani, ArashHan, JieLiu, WenxueHu, Xiaosong
Because of the growing interest in LTE-V2X, there is a need to describe its performance under various conditions and scenarios. This article explores the deployment of long-term evolution vehicle-to-everything (LTE-V2X) technology for vehicle-to-infrastructure (V2I) communication and delves into the deployment of LTE-V2X communication in three major global regions: the United States, Europe, and China. We begin with an overview of the functionality of LTE-V2X and highlight the objectives of V2I communication in terms of safety and mobility applications—and describe why it will be the predominant type of V2X in the first few years of deployment. We also examine the specific Day-1 V2I message sets standardized in each region, along with their potential applications and benefits. The technical details and use cases using these messages are discussed, along with the benefits they offer in improving the accuracy, reliability, and safety for surface transportation. Additionally, our field
Hajisami, AbolfazlWeber, RalfMisener, JimChetlur, Vishnu VardhanRuder, MichaelChen, Shuping
The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability—both of which are important metrics often overlooked during the engineering design process. Therefore, to evaluate systems and inform critical near- and long-term decisions more effectively, a holistic evaluation framework is proposed focused on four key areas: (1) mobility, with emphasis on travel time and accessibility within an airport, (2) environment, focused on energy consumption and greenhouse gas (GHG) emissions associated with intra-airport mobility, (3) equity, specifically to the
Young, StanleyGrahn, RickDuvall, Andrew
Steady advances in autonomous vehicle development are expected to lead to improved traffic flow in terms of string stability compared with that for human-driven vehicles. Fluctuation in intervehicle distances among a group of vehicles without string stability is amplified as it propagates upstream (rearward), which may cause traffic congestion. Since it will take a few decades for autonomous vehicles to replace all human-driven vehicles, it is important to tackle the problem of traffic congestion in a mixed flow of human-driven and autonomous vehicles. Communication technologies such as fifth-generation mobile communication systems, which are improving rapidly, enable vehicle-to-vehicle communication with a sufficiently small delay. We previously reported a strategy based on vehicle-to-vehicle communication for avoiding traffic congestion by using leader–follower control, which is a distributed autonomous control strategy. However, it was designed and evaluated for single-lane traffic
Kurishige, Masahiko
Micromobility is often discussed in the context of minimizing traffic congestion and transportation pollution by encouraging people to travel shorter (i.e., typically urban) distances using bicycle or scooters instead of single-occupancy vehicles. It is also frequently championed as a solution to the “first-mile/last-mile” problem. If the demographics and intended users of micromobility vary largely by community, surely that means we must identify different reasons for using micromobility. Micromobility, User Input, and Standardization considers potential options for standardization in engineering and public policy, how real people are using micromobility, and the relevant barriers that come with that usage. It examines the history of existing technologies, compares various traffic laws, and highlights barriers to micromobility standardization—particularly in low-income communities of color. Lastly, it considers how engineers and legislators can use this information to effectively
Eastman, Brittany
With the sustainable development of the social economy and the continuous maturity of science and technology, urban rail transit has developed rapidly. It solved the problems of urban road load and people’s travel and brought about the problem of rail transit passenger congestion. The image detection algorithm for rail transit congestion is established based on the convolutional neural networks (CNN) structure to realize intelligent video image monitoring. The CNN structure is optimized through the backpropagation (BP) algorithm so that the model can detect and analyze the riding environment through the monitoring camera and extract the relevant motion characteristics of passengers from the image. Furthermore, the crowding situation of the riding environment is analyzed to warn the rail transit operators. In practical application, the detection accuracy of the algorithm reached 91.73%, and the image processing speed met the second-level processing. In the performance test, the proposed
Lin, XinWu, Shuang
Ridesharing is a shared vehicle service with the potential to meet the growing travel demand and shortage in transportation infrastructure capacity. Ridesharing services reduce the number of vehicles and reduce traffic congestion and emissions while providing mobility services to the same number of people with no additional transportation infrastructure investment. One of the significant challenges in implementing ridesharing services is matching drivers and riders. Conflicts between matching objectives in satisfying the interests of diverse stakeholders influence ridesharing efficiency in a transportation system. This study investigates the conflicts between two ridesharing matching objectives (i.e., minimization of system-wide trip time [TT] and minimization of system-wide vehicle miles traveled [VMT]) by applying a multi-objective optimization technique. The results indicate that an acceptable performance of a ridesharing system in terms of TT and VMT can be achieved by optimizing a
Nasr Azadani, MohammadAbolhassani, Amir
The purpose of this study was to construct driver models using long short-term memory (LSTM) in car-following situations, where other vehicles change lanes and cut in front of the ego vehicle (EGV). The development of autonomous vehicle systems (AVSs) using personalized driver models based on the individual driving characteristics of drivers is expected to reduce their discomfort with vehicle control systems. The driving characteristics of human drivers must be considered in such AVSs. In this study, we experimentally measured data from the EGV and other vehicles using a driving simulator consisting of a six-axis motion device and turntable. The experimental scenario simulated a traffic congestion scenario on a straight section of a highway, where a cut-in vehicle (CIV) changed lanes from an adjacent lane and entered in between the EGV and preceding vehicle (PRV). To construct a highly accurate model, we analyzed critical variables as input information affecting the output of the LSTM
Honda, KaiseiOikawa, ShokoHirose, Toshiya
Electric vehicle sharing (EVS) can alleviate traffic congestion and reduce emissions. However, the poor user experience and lack of word-of-mouth effect lead to the low utilization rate of EVS in China. Based on the demand and pain points of EVS, this paper concentrates on travel mode choice behavior of consumers under social networks and establishes an agent-based model for EVS diffusion. The results show that: (1) Social networks can promote the diffusion of EVS and the number of opinion leaders and the number of fans of opinion leaders play an important role. (2) Consumers are more sensitive to travel costs than non-travel time now, but with the improvement of demand for travel experience, consumers are more concerned with non-travel time. (3) The non-travel time of EVS needs to be reduced to 9, 8 and 7 minutes respectively to retain users when the travel cost increases to 0.7, 0.8 and 0.9 Yuan/minute
Shang, KaiWang, NingTian, Hangqi
Recognition of the necessity of connected and automated vehicles (CAVs) in transportation systems is gaining momentum. CAVs can improve the transportation network efficiency and safety by sharing information and cooperative control. This article addresses the problem of coordinating CAVs at highway on-ramps to achieve smooth traffic flow. We develop a multi-agent reinforcement learning (MARL) method based on value decomposition and centralized control to coordinate CAVs. The simulation results show that the proposed collaborative decision-making framework can effectively coordinate dynamic traffic flows and improve the metrics by more than 10% compared to the baseline methods under high traffic demand scenarios
Wang, JinzhuMa, ZhixiongZhu, Xichan
It is widely believed that Advanced Air Mobility (AAM) is poised to have a significant societal impact in the coming years to move people and cargo more rapidly and efficiently. AAM refers to a new mode of transportation utilizing highly automated airborne vehicles for transporting goods and/or people. The main goals of AAM vehicles are to reduce emissions, to increase connectivity and speed, while helping to reduce traffic congestion. These vehicles can take off and land vertically in designated urban locations called vertiports
There has been a radical shift in the way individuals commute. The growing interest in the comfort and luxury of private vehicles has resulted in severe traffic congestion, a major concern worldwide. India, a highly populous country, requires public transportation that can attract and provide seamless, affordable, fast, and secure commutes to its citizens while remaining sustainable and environmentally friendly. An analysis of the Indian Railway shows the need and demand for a high-speed transport system. High-speed rails have always garnered attention for their speed, technology, and communication capabilities. Hyperloop technology is one such endeavor that has piqued the world's interest. Hyperloop is a futuristic mode of transportation currently under development. It has a floating pod that races along inside giant low-pressure tubes, either above or below ground. The testing pod is capable of covering 400 m in 15 s under a preliminary experiment. This study examines the overview of
Chhetri, Ahilya
Global warming, pollution, dependence on foreign oil resources and rising petroleum prices are major issues the nations facing today. Increasing density of IC engine powered vehicles, urban air pollution, traffic congestion and wastage of valuable land for parking have negative impact economically, ecologically and politically. Moreover, an increasing preference for personal mobility, owing to the pandemic and social distancing norms has witnessed notable growth in automobile sales. Hence, a strategy to replace conventional vehicles is urgently required by electric vehicles, which is one of the most promising alternative technologies. Governments also recognized the value of electric mobility in building a cleaner, smarter and more sustainable future cities. Adoption of low-cost, light weight and low power electric vehicles designed for the city environment can considerably reduce the impact of personal mobility not only by reducing energy consumption but also by minimizing the use of
Shaik PhD, AmjadTalluri, Srinivasa RaoSathineni, NivedYenepelli, SharathchandraMaddi, Yashwanth ReddyMallypally, Akshith Reddy
Nowadays, the technology war always shows the need for rushing hours in the transportation sector. Turbines and IC engines, which generate power, can only be operated with the help of high-pressure air. In this research, an analytical study introduces an innovative boat vehicle driven by air-water interactions. The principles of an OWC (Oscillating Water Column) wave energy converter device is reviewed to find the effects of air-water interactions that are the key concepts for introducing the partially levitated transportation method. The physical conditions around the boat vehicle, such as squat conditions and speed variations, are reviewed under different stream conditions to explore the possibilities of converting the potential energy of water into kinetic energy under dynamic conditions. An experimental Froude - model analysis is presented to find the velocity and kinetic energy at upstream and downstream conditions of the channel. A 1D analytical method using Matlab is performed
Santhiyagu, Arulanantha SamyMayakrishnan, Jaikumar
Dangerous driving behavior will cause serious traffic accidents, which will not only threaten life and property but also cause traffic congestion and reduce road capacity. Speed detection is an important detection method to identify whether a driver is driving dangerously. Traditional speed detection methods need additional sensors, which will increase the cost of speed measurement. This paper proposes a vehicle speed estimation algorithm based on the imaginary projection plane (IPP). The IPP will be established according to the height, field angle, and vertical tilt angle of the camera and will be used to establish the mapping relationship between the world coordinates and image coordinates of the vehicle. By combining YOLOv4 and DeepSORT, the vehicle license plate is detected and tracked, and the center point of the vehicle license plate is taken as the feature point of vehicle speed estimation. The vehicle speed is estimated according to the IPP. A real vehicle experiment is carried
Wang, YongyuanYan, ShuHuang, Qi
If every commuter drove the same few roads at the same time every day, the traffic would be unbearable. That’s exactly what’s happening in the skies above the nation, called the national airspace (NAS). Multiple flights from different airlines try to use the most direct flight paths, converging on the same airports. With limited runway space, that causes jumbo-sized traffic congestion. So, NASA worked with the Federal Aviation Administration (FAA), commercial airlines, and airports to develop and test a new program to manage airport traffic on the ground — the Integrated Arrival, Departure, and Surface (IADS) system. In 2022, the FAA began incorporating IADS capabilities at 27 of the busiest airports in the country
To reduce carbon emissions and mitigate traffic congestion in urban environments, new innovative transportation concepts are required. While public transportation covers certain segments, it cannot supply all possible routes, use cases, and preferences and hence, other solutions are needed as well. Urban drive missions are not typically calling for huge powers or even large energy capacities. In the vehicle design, this should be shown as rightsizing. It is not only the powertrain that should be rightsized but also the vehicle physical dimensions, to enable, e.g., convenient maneuvering. Furthermore, due to the variety of options (walking, biking, scooters, public transportation etc.), one might need a personal vehicle only occasionally, and therefore, a vehicle with shared and multipurpose capabilities would be an asset. Lastly, since small urban vehicles are considered unsafe, improving the safety and general confidence on small vehicles is vital for the market penetration
Pippuri-Mäkeläinen, JenniTribioli, LauraChiappini, DanielePasqualino, PaolaMiljavec, DamijanKeränen, JanneFarzam Far, MehrnazCamposano, Jose
Due to traffic congestion and environmental pollution, connected automated vehicle (CAV) technologies based on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communication (V2I) have gained increasing attention from both academia and industry. Connected hybrid electric vehicles (CHEVs) offer great opportunities to reduce vehicular operating costs and emissions. However, in complex traffic scenarios, high-quality real-time energy management of CHEVs remains a technical challenge. To address the challenge, this paper proposes a hierarchical eco-driving strategy that consists of speed planning and energy management layers. At the upper layer, by leveraging the real-time traffic data provided by vehicle-to-everything (V2X) communication, dynamic traffic constraints are predicted by the traffic flow predictor developed based on the Hankel dynamic mode decomposition algorithm (H-DMD). Then, the vehicle speed curve is planned under dynamic traffic constraints through a model
Han, JieHu, XiaosongLin, Xianke
OTA (over the air) updates help automotive manufacturers to reduce vehicle warranty and recall costs. Vehicle recall is expensive, and many automotive manufacturers have implemented OTA updates. Updating parameters for connected vehicles can be challenging when dealing with thousands of vehicles across different regions. For example, how does the manufacturer prioritise which vehicles need updating? Environmental and geographical factors affect degradation rates and vehicles in hotter regions or congested cities may degrade faster. For EVs, updating the BMS (battery management system) parameters requires careful analysis prior to the update being deployed, to maximise impact and reduce the likelihood of adverse behaviour being introduced. The analysis overhead increases with the number of vehicles. This is because it requires simulation and optimisation of the fleet BMS calibration in a digital twin environment. A targeted approach is the best option to prioritise vehicles for software
Mohd Azmin, FarraenMustafa, Kenan
As new technology is added to vehicles and traffic congestion increases, there is a concern that drivers will be overloaded. As a result, there has been considerable interest in measuring driver workload. This can be achieved using many methods, with subjective assessments such as the NASA Task Loading Index (TLX) being most popular. Unfortunately, the TLX is unanchored, so there is no way to compare TLX values between studies, thus limiting the value of those evaluations. In response, a method was created to anchor overall workload ratings. To develop this method, 24 subjects rated the workload of clips of forward scenes collected while driving on rural, urban, and limited-access roads in relation to 2 looped anchor clips. Those clips corresponded to Level of Service (LOS) A and E (light and heavy traffic) and were assigned values of 2 and 6 respectively. Subjects said if they would perform any of 3 tasks—dialing a phone, manually tuning a radio, or entering a destination—while they
Green, Paul
Hydrostatic torque modulation is a new, at moment theoretical approach, to developing advanced AWD4WD transmissions. The basic component is a rotational hydrostatic modulator. It is derived from a low-speed high-torque hydrostatic machine. As such, it can be integrated into a standard mechanical AWD4WD transmission as a replacement for the clutch, where torque is controlled through energy dissipation. Controlled by a simple solenoid valve, it provides torque vectoring with a reaction time shorter than 0.5 s, and it provides additional safety features that result in a more robust AWD4WD transmission. As it can modulate torque with energy flow control/transfer, it offers much more than existing systems based on controlled clutches. Specifically, hydrostatic torque modulation, when it is integrated into the AWD4WD transmission, brings CVT or ICT performance. As torque modulation is performed through the control of the energy flow, it provides torque control from 0 km/h without using a
Bozic, Ante
The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem
Luo, ChagenXu, FengZeng, DequanHu, YimingDeng, ZhenwenFu, ZhiqiangLi, ZhuorenZhang, Peizhi
The advances in automotive technology continue to deliver safety and driving comfort benefits to society. The Automated Driving Assistance System (ADAS) technology is at the forefront of this evolution. Today, various vehicle models on the road have features like lane centering, automated emergency braking, adaptive cruise control, traffic jam assist etc. During early development, such feature algorithms often assume ideal environmental and vehicle conditions while doing performance evaluation. It is imperative that one uses realistic scenarios for production development. To demonstrate this, the lane centering ADAS feature performance is studied using a test vehicle. The feature considered here is an end-to-end feature, i.e., from camera sensor output to steering actuation. Lane centering control system often has multiple control loops within the vehicle system. The delay in steering system response has a significant effect on overall lane centering performance and driver feel. This
Awathe, ArpitVarunjikar, TejasGanguli, Subhabrata
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
The future of bus transit in new millennium is promising. This optimism is based on an anticipated long-term slowdown in growth of suburbs and revitalization of central cities. It reflects and escalates the public concern with traffic congestion, sprawl and pollution. This calls for double the use of public transport to address above issues. It calls for changing the mind-set of society towards public transports like buses, coaches etc. This could happen if bus design ensures right comfort, safety and TCO by ensuring refined bus transport. Hence, it is responsibility of OEMs to provide the new generation buses and coaches, which will ensure the public demands of comforts in terms of NVH refinement. This paper covers the unique approach used to convert the existing bus NVH refinement to next level as a short-term solution and with the intention of articulating NVH strategies for new generation bus development. This work explains combined experimental and simulation approach deployed
Doshi, SohinTaware, GirishKalsule, DhanajiBijwe, VilasNaidu, Sudhakara
The article proves the necessity for heating the air in the pneumatic engine of a hybrid power unit designed for moving a compact wheeled vehicle. The aim is to improve the pneumatic engine operation indicators by heating the compressed air before it is supplied to the cylinder using the obtained theoretical and experimental studies. For the easy-to-use of assessing the effectiveness of heating the air supplied to a pneumatic engine, the experiments were carried out by two pressure ps = 0.7 MPa and ps = 0.9 MPa, according to them the testing of a pneumatic unit was conducted without heating the compressed air at the temperature equal to the ambient temperature Ts = 293 K. Also, during the experiments a pneumatic engine was tested at other temperatures while supplying the compressed air at the inlet to the engine cylinder. So, at an inlet pressure ps = 0.7 MPa, the compressed air was heated up to the temperature Ts = 383 K, and at a pressure ps = 0.9 MPa it was heated up to the
Leontiev PhD, DmitryVoronkov, OleksandrNikitchenko, IgorKorohodskyi, VolodymyrRyzhykh, LeonidRudenko, NataliiaMakarova, Tamara
Traffic congestion and the resulting socio-economic losses, air pollution, etc. have been the pivotal factors that hinders the development of many cities. It is essential to develop route guidance to provide drivers with optimal routes to the destinations with a low congestion and a great road capacity to alleviate traffic congestion on the road network. This paper proposed a novel route guidance algorithm for individuals based on the connected vehicle (CV) in the vehicle infrastructure cooperative environment, providing drivers with real-time route selection, thereby alleviating the congestion of the road network, more importantly, realized the route guidance for individuals through microscopic traffic simulation software, VISSIM, and VISSIM COM interfaces, and evaluate the effects and influencing factors of individual route guidance. The methodology first developed an application program to analyze the road network, which could obtain any specified number of alternate route sets
Jiang, YinghongWang, ShihanWang, QiulanSun, JianNi, Ying
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