Browse Topic: Congestion

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Revolutionizing Mass Mobility: Sustainable, Safe, and Smart Transport Ecosystems2026-26-0360To be published on 01/16/2026
Mass Mobility Systems are critical for a sustainable and progressive society. As the world confronts the serious challenges of global warming and urban traffic congestion, efficient mass mobility solutions become critical in reducing carbon footprints and enabling equitable access. Advancement in mass mobility is not limited to electric buses alone but also includes innovations across conventional ICE vehicles, autonomous vehicles, Trains and other integrated transport networks. Safety, and accessibility for users remain critical to the sustainability of future mass mobility concepts. The COVID-19 pandemic exposed vulnerabilities in public transportation, highlighting the urgent need for safer and more resilient systems. Road safety, passenger well-being, and hygienic standards must be deeply embedded into future mobility solutions. Furthermore, strong last-mile connectivity will be essential to ensure that mass mobility truly meets the needs of all citizens. An effective Mass Mobility
Vasudevan, M, Kumar S, Ashok, Sridevi, M, Kumar, Rajiv, Kumar, Om
Revolutionizing Urban Mobility in India: The Emergence of the 2-3 Wheel Combi Vehicle and the L2-5 Regulatory Framework.2026-26-0187To be published on 01/16/2026
Urban mobility in India is evolving rapidly under the pressures of population growth, increasing congestion, and the demand for innovative transportation solutions. With infrastructure development and urbanization accelerating, there is a growing need for versatile vehicles that can adapt to both personal and commercial purposes while addressing urban vehicle density. To meet this demand, the 2-3 Wheel Combi Vehicle has emerged as a groundbreaking modular mobility solution, enabling seamless transitions between two-wheeled (2W) and three-wheeled (3W) configurations. This is world's 1st class changing vehicle, exemplified by Hero's SURGE. It offers a single, multi-functional platform that supports agile urban mobility, e-commerce deliveries, and income generation. This innovation is underpinned by India's pioneering and newly created L2-5 category, a unique regulatory framework established by the Ministry of Road Transport & Highways (MoRTH) under the Central Motor Vehicle Rules (CMVR
Ali Khan, Feroz, Gupta, Eshan
Dynamic Integration of Bilateral and Adaptive Cruise Control for Intuitive Vehicle Behavior and Congestion Mitigation2026-26-0037To be published on 01/16/2026
Bilateral Cruise Control (BCC) is a new concept that has been shown to reduce traffic congestion and enhance fuel/energy efficiency compared to Adaptive Cruise Control (ACC). BCC considers both lead and trailing vehicles to determine the ego vehicle’s acceleration, effectively dampening any disturbance down the vehicle string and reducing possibilities for congestion. Despite the advantages demonstrated with BCC, one major limitation is its non-intuitive behavior, which stems from the fact that the BCC reacts not just to the lead vehicle but also to the trailing vehicle’s movement. This paper identifies key issues with BCC control and proposes solutions that retain the benefits of BCC while maintaining intuitive behavior. Specifically, a novel switching strategy is proposed to switch between ACC and BCC control modes by critically analyzing the driving conditions. The proposed system ensures acceptable driving behavior with predictable braking and acceleration, resulting in an
A, Arya, A, Aishwarya, D, Vishal Mitaran, M, Senthil Vel, Kumar, Vimal
Establishing a Scalable Virtual Framework for ADAS Validation: Traffic Jam Pilot with Real-World Scene Integration2026-26-0506To be published on 01/16/2026
Advanced Driver Assistance Systems (ADAS) are instrumental in improving road safety and minimizing traffic-related incidents. However, their development and validation processes are resource-intensive, requiring substantial time, cost, and domain-specific expertise. Moreover, real-world testing introduces significant safety challenges. To address these issues, virtual simulation platforms offer high-fidelity environments for the secure and efficient testing of ADAS functions. This research presents a virtual validation framework for a Traffic Jam Pilot (TJP) algorithm utilizing such simulators. The framework features detailed models of camera and radar sensors, capturing essential parameters like detection range and field of view, alongside a vehicle plant model and road infrastructure modeling that includes elements such as curvature, slope, banking angles, and varying lane widths. A perception stack is developed using synthetic sensor data and is integrated with the TJP control
Agrawal, Mridul, Ithape, Avinash, Sharma, Prashant, Trivedi, Abhishek
Analysis and Optimization of Subsidy Scheme for China Europe Express2025-99-012311/11/2025
The analysis of the current subsidy scheme for China Europe Express shows that its effectiveness is limited to lines starting from inland cities and lines with unsaturated demand. A bi-level subsidy optimization model was constructed and Tabu Search algorithm was applied to solve the optimization subsidy plan. The evaluation results of the optimization subsidy scheme indicate that it can more effectively increase the market share of CRE, regulate the balance of freight supply and demand to a certain extent, reduce capacity vacancies, and alleviate line congestion.
Mai, Yuanyuan, Tian, Chunlin
Research on Urban Traffic Congestion Optimisation Strategies Based on V2X Technology2025-99-011711/11/2025
This study investigates urban traffic congestion optimisation strategies based on V2X technology. V2X technology (Vehicles and Internet of Everything) aims to alleviate urban traffic congestion, improve access efficiency, and reduce tailpipe emissions through real-time collection and fusion of traffic data to optimise traffic signal control and path planning. The efficacy of the optimisation strategies under different V2X penetration rates is evaluated by conducting multi-factor orthogonal experiments in different typical congestion scenarios. The experimental results show that the V2X-based signal optimisation, path induction, and event response combination strategies exhibit significant optimisation effects in all three scenarios: node bottleneck, corridor congestion, and event induction. Under the condition of 100% penetration, the combined strategy reduces delay by 41.9% in the node bottleneck scenario, improves accessibility by 28.1% in the corridor congestion scenario, and
Xi, Chaohu, Li, Jiasheng, Qu, Fengzhen, Liu, Hongjun, Liu, Xiaorui, Wang, Chunpeng
Advancing Vehicle-Level AC Thermal Management System Performance2025-28-043410/30/2025
Modern mobility solutions increasingly rely on HVAC systems due to growing transport demands, traffic congestion, and harsh environmental conditions. These systems, comprising a compressor, evaporator, condenser, and thermal expansion valve, require adequate airflow for optimal performance. Insufficient airflow, caused by factors like undersized ducts, improper fan settings, clogged filters, or high static pressures from duct restrictions, significantly hinders cooling capacity. The objective of this study is to develop a predictive model for passenger vehicle AC system performance under controlled environmental conditions. Discrepancies between predicted and desired performance will trigger a structured problem-solving process involving iterative testing, root cause analysis, and the development of corrective measures. The improvements will be focused on the vehicle-level HVAC design, adhering to customer specifications. This research will also establish an experimental validation
Meena, Avadhesh Kumar, Agarwal, Roopak, Sharma, Kamal, Kishore, Kamal
Analysis of the Correlation of Traffic Congestion Based on Multiple Factors: Taking the Roads in Beijing as an Example2025-99-007410/17/2025
In recent years, traffic issues in China have been emerging continuously, and the traffic congestion problem in Beijing is particularly prominent. We have explored the relationships between factors such as driving duration, road length, weather conditions in Beijing and traffic congestion. By using the Logistic Regression Model to analyze the relationships among driving duration, road length and traffic congestion, we found that both driving duration and road length are negatively correlated with traffic congestion. The model shows high accuracy and recall rate, demonstrating excellent performance. We also employed the Weighted Average Correlation Model to study the relationship between weather conditions and traffic congestion. The results indicate that traffic congestion is more severe in rain, snow, and foggy weather, while it is less serious in sunny and cloudy weather. Subsequently, through the noise level verification, the stability of the model was confirmed. At the same time
Feng, Jiarui, Han, Xiran
The Analysis of Community Entrance Openness on Transportation and Emission: A Comparison of Different Automobiles2025-99-008110/17/2025
With the escalating rate of urbanization in China, the urban construction sector is encountering numerous challenges, including issues such as traffic congestion and environmental pollution. To enhance traffic efficiency and offer planning guidance for urban development, this study focuses on the fully or partial opening of community entrances. VISSIM is utilized to examine the community opening and simulate the internal road network, while also employing the SPSS data analysis tool for supplementary analysis. The objective of this method is to compare and analyze the traffic conditions and environmental impact of the community before and after its opening with different automobiles. Through the establishment of a comprehensive evaluation system, the study calculates and analyzes the average vehicle speed, noise levels, energy consumption, and carbon dioxide emissions before and after the opening of the community. Finally, several recommendations are proposed to enhance community
Li, Mengyuan, Zhuo, Chenxu, Xiong, Simin, Xu, Lihao
A Study of the Applicability of Variable Guide Lanes at Signalized Intersections2025-99-001310/17/2025
In the context of China’s rapidly expanding urbanization, there is an increasing trend of car ownership among residents, which has led to a concomitant rise in traffic demand and a worsening of traffic congestion. To address this challenge, Variable Guided Lanes have been proposed as a novel traffic management strategy. This strategy entails the real-time adjustment of lane function, in response to fluctuations in traffic flow, with the objective of enhancing intersection access efficiency. The present study employs the average delay of vehicles in the inlet lane of the intersection as the discriminating index, and the left-turn and straight flow in the inlet lane as the discriminating condition. The study establishes an equal average delay model and delineates a threshold curve to assess the suitability of the lane for the implementation of Variable Guided Lanes. Furthermore, the study investigates whether the characteristics of the variable lanes are altered for the applicability
Zhang, Qinan, Zhang, Yongzhong
The Traffic Light Control Strategy at Intersections in Intelligent Transportation Systems2025-99-000910/17/2025
This thesis explores strategies for controlling traffic signals at intersections within the context of ITS., emphasizing the role of DRL in optimizing traffic flow. In recent years, urbanization and the rapid increase in vehicle numbers in China have exacerbated traffic congestion, significantly hindering urban development. This study explores innovative approaches to alleviating traffic congestion, focusing on smart traffic signal systems that adjust according to real-time traffic conditions. The research reviews fundamental concepts in traffic signal control, including traffic flow, signal phases, and signal cycles, and investigates how DRL can dynamically adjust traffic light cycles to optimize intersection performance. The findings suggest that DRL provides an effective method for managing complex and unpredictable traffic environments, as it enables systems to self-learn and continuously refine their strategies based on environmental changes. The adoption of this technology holds
Liu, Junao, Zuo, Tingyou
Reducing Traffic Congestion with Reinforcement Learning-Driven Signal Control Systems2025-01-028307/02/2025
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
Variable Speed Limit Control Based on Deep Deterministic Policy Gradient under Mixed Traffic Environment12-09-01-000405/06/2025
The existing variable speed limit (VSL) control strategies rely on variable message signs, leading to slow response times and sensitivity to driver compliance. These methods struggle to adapt to environments where both connected automated vehicles (CAVs) and manual vehicles coexist. This article proposes a VSL control strategy using the deep deterministic policy gradient (DDPG) algorithm to optimize travel time, reduce collision risks, and minimize energy consumption. The algorithm leverages real-time traffic data and prior speed limits to generate new control actions. A reward function is designed within a DDPG-based actor-critic framework to determine optimal speed limits. The proposed strategy was tested in two scenarios and compared against no-control, rule-based control, and DDQN-based control methods. The simulation results indicate that the proposed control strategy outperforms existing approaches in terms of improving TTS (total time spent), enhancing the throughput efficiency
Ding, Xibin, Zhang, Zhaolei, Liu, Zhizhen, Tang, Feng
A Novel Model for Short-Term Traffic Flow Prediction on Highways Utilizing Multi-Head Attention–BiLSTM–BiGRU12-09-01-000204/24/2025
With the development of intelligent transportation systems and the increasing demand for transportation, traffic congestion on highways has become more prominent. So accurate short-term traffic flow prediction on these highways is exceedingly crucial. However, because of the complexity, nonlinearity, and randomness of highway traffic flows, short-term prediction of its flows can be difficult to achieve the desired accuracy and robustness. This article presents a novel architectural model that harmoniously fuses bidirectional long–short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), and multi-head attention (MHA) components. Bayesian optimization (BO) is also used to determine the optimal set of hyperparameters. Based on the PeMS04 dataset from California, USA, we evaluated the performance of the proposed model across various prediction intervals and found that it performs best within a 5-min prediction interval. In addition, we have conducted comparison and ablation
Chen, Peng, Wang, Tao, Ma, Changxi, Chen, Jun
Effect of Aftermarket Modifications on ADAS Functionality – 2021 Ford F-150 Light Vehicle2025-01-805704/01/2025
Both automotive aftermarket vehicle modifications and Advanced Driver Assistance Systems (ADAS) are growing. However, there is very little information available in the public domain about the effect of aftermarket modifications on ADAS functionality. To address this deficiency, a research study was previously performed in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations. These included stock as well as three typical aftermarket configurations comprised of increased tire diameters, a suspension level kit, and two different suspension lift kits. Physical tests were carried out to investigate ADAS performance of lane keeping, crash imminent braking, traffic jam assist, blind spot detection, and rear cross traffic alert systems. The results of the Silverado study showed that the ADAS functionality of that vehicle was not significantly altered by aftermarket modifications. To determine if the results of the Silverado study were
Bastiaan, Jennifer, Muller, Mike, Morales, Luis
Optimizing Electric Vehicle Charging Station Locations Based on Urban Road Network Congestion Tracing2025-01-721603/19/2025
Exhaust emissions from congested road segments constitute a significant source of urban air pollution. Resolving traffic congestion throughout the road network presents considerable challenges. However, alleviating tailpipe emissions on congested roads can be achieved by increasing the proportion of electric vehicles (EVs) in the traffic flow. Therefore, we propose a method for optimizing the layout of EV charging stations based on urban road networks congestion tracing. This method traces congestion sources through similarity between road networks, and evaluates the installation potential value of adjacent candidate installation points using the congestion contribution degree of the road segment as an indicator. The analysis is conducted on 100 routes within the Qinhuai district of Nanjing city, using spatiotemporal similarity metrics. The utilization of point-of-interest and traffic data from online mapping sources overcomes the complexity of road network structure and the sparsity
Zeng, Wenyi, Jian, Lu, Hu, Xiaojian
Analysis of Crash Precursors under Different Traffic Flow Conditions with Enhanced Interpretability2025-01-713402/21/2025
This study investigates the precursors of crashes under varying traffic states through an in-depth analysis of freeway traffic data. This method effectively addresses the limitations associated with using surrogate measures in traffic safety research. We used the k-means clustering method to categorize traffic states into three types: free flow, transitional state, and congested flow. By employing the case-control study experimental approach, we conducted an in-depth analysis of the traffic data. During the feature selection process, we set matching rules to choose control group data that meet the criteria of time, location, and traffic state. Initially, traffic flow feature variables were constructed based on multiple dimensions, including time window width, spatial location, traffic flow parameters, and statistical characteristics. To reduce feature multicollinearity, we used correlation matrices and variance inflation factors (VIF). We then applied Recursive Feature Elimination (RFE
Zhou, Feixiang, Liu, Shaoweihua, Feng, Shi, Zhang, Yujie, Luo, Xi
An Integrated Lane Change Control Method for Freeway Segments with Lane Drop in a Connected Mixed Traffic Environment2025-01-719002/21/2025
Segment with lane drops are very important in freeway systems since they are major constrains to traffic flow and safety. The frequency of capacity reductions and higher safety risks is proportional to an increase in lane-changing actions, which worsen traffic congestion, decrease road capacity, and increase the risk of an accident. Traditional traffic management strategies that rely on physical structures and driver’s decision making often fail under such conditions. This paper provides a detailed lane change control strategy specific to freeway segments with lane reduction in the connected and autonomous vehicle (CAV) environment. The strategy combines both centralized and decentralized techniques to improve the vehicle’s lane-changing behavior and density. A cellular transmission model of lane-level is proposed for the centralized control of the linked vehicles based on the ratio of the driver compliance. The model derives the density equation and transforms the lane-changing
Ma, Yuheng, Guo, Xiucheng, Zhang, Yiming, Cao, Jieyu
Study on Variable Speed Limit Control Strategy of Highway under Intelligent Connected Environment2025-01-718902/21/2025
This paper presents a novel variable speed limit control strategy based on an Improved METANET model aimed at addressing traffic congestion in the bottleneck areas of expressways while considering the impact of an intelligent connected environment. Traffic flow simulation software was employed to compare the outcomes of the traditional variable speed limit model with those derived from the proposed strategy. The results indicated that under three scenarios—main road, ramp, and lane closure—with a 100% penetration rate of intelligent connected vehicles, the average delay for vehicles utilizing the new model decreased by 9.37%, 11.11%, and 7.22%, respectively. This study offers an innovative approach to highway variable speed limits under an intelligent connected environment.
Qi, Tiancheng, Qu, Xinhui, Gu, Haiyan, Sang, Zheming, Ning, Fangyue
Regulatory and Policy Framework for Urban Drone Logistics Systems2025-01-714402/21/2025
The swift and relentless progression of drone technology has ushered in novel opportunities within the realm of urban logistics, especially for the potential of drones to modify last-mile delivery and improve customer fulfillment through mobile application integration, offering the potential for delivery systems that are both efficient and environmentally sustainable. This development is not just a technological leap but a transformative shift in how goods are moved within urban spaces, potentially reducing traffic congestion and emissions from traditional vehicles. Nevertheless, the safety issues of drone flights in cities are becoming increasingly serious, and the accountability related to drone accidents is not clear, raising concerns in society regarding the use and safety of drones. Therefore, to fully utilize the potential of drones in urban logistics, the incorporation of drones into the urban airspace environment necessitates the establishment of a strong regulatory and policy
Ma, Jie, Yang, Junjie, Diao, Weile, Du, Yiling, Chen, Weiqi
Validating Human Factors-Based Classification Models for Safe and Efficient Mixed-Autonomy Interactions at Intersections Using a Virtual Simulator12-08-02-001902/12/2025
The introduction of autonomous vehicles (AVs) promises significant improvements to road safety and traffic congestion. However, mixed-autonomy traffic remains a major challenge as AVs are ill-suited to cooperate with human drivers in complex scenarios like intersection navigation. Specifically, human drivers use social cooperation and cues to navigate intersections while AVs rely on conservative driving behaviors that can lead to rear-end collisions, frustration from other road users, and inefficient travel. Using a virtual driving simulator, this study investigates the use of a human factors-informed cooperation model to reduce AV reliance on conservative driving behaviors. Four intersection scenarios, each involving a left-turning AV and a human driver proceeding straight, were designed to obfuscate the right-of-way. The classification models were trained to predict the future priority-taking behavior of the human driver. Results indicate that AVs employing the human factors-informed
Ziraldo, Erika, Oliver, Michele
Technical Paper for 11 TH SAE India International Mobility Conference Relevance of Autonomous Vehicles in the Indian Context2024-28-012212/05/2024
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
Design and Development of a Micromobility Smart Electric Scooter to Revolutionize Urban Commuting2024-28-002110/17/2024
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, Raju, Singh Chowhan, Sri Aanshu, Shaik, Amjad, Maroju, Abhinav, Talluri, Srinivasa Rao
Optimal Eco-Driving with Infrastructure-to-Vehicle Communication for Speed Adaptation Based on Real-Time Dynamic Macroscopic Traffic Conditions2024-24-002509/18/2024
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, Manfredi, Shiledar, Ankur, Block, Brian, Spano, Matteo, Rizzoni, Giorgio
Exploration of a Precise Traffic Restriction Policy on Urban River-Crossing Corridors: A Case Study in Changsha, China13-06-02-001008/08/2024
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
Lateral Platooning Control with Precise Path Tracking and Strong Disturbance Suppression Performance2024-01-507407/24/2024
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
Runtime Safety Assurance of Autonomous Last-Mile Delivery Vehicles in Urban-like Environment2024-01-299107/02/2024
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, Iqra, Aniculaesei, Adina, Buragohain, Abhishek, Zhang, Meng, Bamal, Daniel, Rausch, Andreas
Lane-Changing Behavior’s Impact on Platoon Dispersion in Mixed Autonomous Vehicle Traffic: Insights from Simulation12-08-02-001307/01/2024
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, Ting, Liu, Chenghao, Lin, Sitong, Song, Wenjing
Research on Speed Guidance Strategy at Continuous Signal Intersection Based on Vehicle–Road Coordination Technology12-07-04-002304/13/2024
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, Wenli, Li, An, Ren, Yongpeng, Wang, Kan
A Guidance Strategy for Parking Space of Autonomous Valet Parking with Cooperative Vehicle Infrastructure System2024-01-257104/09/2024
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, Zhouping, Liu, Weidong, Sun, Zhipeng, Zhu, Zuwei, Hu, Yiming, Zeng, Dequan
Development of Robust Traction Power Inverter Residing in Integrated Power Electronics for Ultium Electric Vehicles2024-01-221104/09/2024
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, Arash, Basher, Korobi, Chung, Sung, Alam, Khorshed, Lee, Jung-Gi, Choi, Hong Goo, Ko, Jin-young, Anwar, Mohammad
AI Model to Streamline Operations in a Robotic WarehouseTBMG-5036804/01/2024
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.
Design and Application of Electronic Toll Collection Special Situation Processing System12-07-03-001804/01/2024
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, Xiaohui, Guo, Fengbin, Zhang, Mengwei, Zheng, Fengfei, Liu, Chunya
A Smart Transportation System for Existing Vehicles and Roads Infrastructure to Ease Traffic and Toll Problems in India2024-26-018101/16/2024
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
Energy Conservation and Protecting Global Health by Automated Corporate Transport Services Application/System2024-26-023801/16/2024
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 Scope of Autonomous Vehicle Mobility with an Indian Context2024-26-008701/16/2024
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
A Dynamic Variable Speed Limit Control Method for Dispersal of Queue Effects in Traffic Accidents2023-01-708912/31/2023
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, XiaoMin, Wang, Bo, Ke, Guo
Artificial Bee Colony Algorithm for Smart Car Path Planning in Complex Terrain2023-01-706212/20/2023
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, DaPeng, Gu, Rui, Zheng, Yujun, Zuo, Songchen
Speedy Hierarchical Eco-Planning for Connected Multi-Stack Fuel Cell Vehicles via Health-Conscious Decentralized Convex Optimization14-13-01-000812/04/2023
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, Arash, Han, Jie, Liu, Wenxue, Hu, Xiaosong
A Tutorial on V2I Communication: Evaluating the LTE-V2X for Day-1 V2I and V2V Integration in Congested Scenarios12-06-04-002711/29/2023
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, Abolfazl, Weber, Ralf, Misener, Jim, Chetlur, Vishnu Vardhan, Ruder, Michael, Chen, Shuping
A Multi-Dimensional Benefit Assessment of Automated Mobility Platforms (AMP) for Large Facilities: Mobility, Energy, Equity, and Facility Management & Design2023-01-151209/05/2023
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, Stanley, Grahn, Rick, Duvall, Andrew
Using Distributed Autonomous Adaptive Cruise Control Vehicles to Mitigate Congestion in a Two-Lane Traffic Flow2023-01-505508/22/2023
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
A Safety Reasoning Copilot Design for Future Uncrewed Ground Vehicles (UGVs)2024-01-406908/10/2023
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.
Micromobility, User Input, and StandardizationEPR202301507/18/2023
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
Research on Image Detection Algorithm of Rail Traffic Congestion Degree Based on Convolutional Neural Networks13-05-01-000707/04/2023
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, Xin, Wu, Shuang
Multi-objective Optimization in a “Specified Driver’s Origin and Destination” Ridesharing System13-05-01-000304/27/2023
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, Mohammad, Abolhassani, Amir
Study on the Diffusion Law of Electric Vehicle Sharing in Complex Social Network Environment2023-01-088904/11/2023
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, Kai, Wang, Ning, Tian, Hangqi
Construction of Driver Models for Cut-in of Other Vehicles in Car-Following Situations2023-01-057504/11/2023
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, Kaisei, Oikawa, Shoko, Hirose, Toshiya
Multi-agent Decision-Making Framework Based on Value Decomposition for Connected Automated Vehicles at Highway On-Ramps12-06-03-001601/16/2023
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, Jinzhu, Ma, Zhixiong, Zhu, Xichan
Vertiport Assessment and Mobility Operations SystemTBMG-4712012/01/2022
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.
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