Article
Engineering, Civil
Zongyuan Wu, Ben Waterson
Summary: This paper reviews the application of connected vehicles and autonomous vehicles in intersection infrastructure, as well as signal control and intersection management in different scenarios. The study summarizes optimization-based signal control methods and suggests future research directions that need attention.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Wei Wu, Yang Liu, Wei Liu, Fangni Zhang, Vinayak Dixit, S. Travis Waller
Summary: Most existing studies on AIM focus on algorithms for resolving conflicts among vehicles, while this paper proposes optimizing entrance and exit lanes to improve traffic efficiency. Two methods are developed for optimizing entering time and route choices, and a heuristic approach is adopted for real-time applicability.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Mohammed Lawal Ahmed, Rahat Iqbal, Charalampos Karyotis, Vasile Palade, Saad Ali Amin
Summary: Connected and Autonomous Vehicles (CAV) are becoming increasingly important in modern society for better mobility and societal impact. Although driven by AI and 5G/6G technologies, concerns about handing total control of driving to vehicles may hinder public adoption. Through quantitative data collection and machine learning techniques, the study successfully predicted user adoption for CAVs with high accuracies using various models such as Neural Networks and Random Forest.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Qinglu Ma, Shu Zhang, Qi Zhou
Summary: This paper proposes a traffic organization method based on Connected and Autonomous Vehicles (CAVs), which significantly improves traffic operational efficiency and reduces average travel time.
Article
Engineering, Civil
Xiao Pan, Boli Chen, Stelios Timotheou, Simos A. Evangelou
Summary: This paper addresses the speed planning problem for connected and autonomous vehicles (CAVs) at an unsignalized intersection with consideration of turning maneuvers. It is shown that the underlying optimization problem, subject to safety constraints, can be formulated as two second-order cone programs with convexification and relaxation. The investigation of Pareto optimal solutions highlights the importance of optimizing the trade-off between travel time and energy consumption.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Yan Yan, Haiping Du, Yafei Wang, Weihua Li
Summary: The platoon of connected autonomous vehicles plays a crucial role in future intelligent transportation by improving traffic efficiency and alleviating congestion. This paper proposes a multi-objective asymmetric sliding mode control strategy to address the challenging problems of control in connected autonomous vehicles. The results demonstrate that the proposed control strategy enhances stability and performance of the platoon.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Christian Vitale, Panayiotis Kolios, Georgios Ellinas
Summary: This study presents a novel framework for optimized intersection management considering vehicle location uncertainties. By using 0-1 integer linear programming optimizations, the acceleration profiles of vehicles in the intersection can be set to achieve high traffic throughput.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Transportation Science & Technology
Yunyi Liang, Shen Zhang, Yinhai Wang
Summary: This study addresses the optimization of road side unit (RSU) location at a single intersection to achieve low vehicle-to-road-side-unit (V2R) communication delay for connected-autonomous-vehicle-based (CAV-based) intersection control strategies. A two-stage stochastic mixed-integer nonlinear program is developed to minimize cost associated with RSU investment and V2R communication delay penalty, providing a cost-effective solution for low V2R communication delay in CAV environment. The proposed model outperforms a deterministic model, demonstrating its effectiveness and cost efficiency.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Computer Science, Information Systems
Jie Cui, Xuelian Chen, Jing Zhang, Qingyang Zhang, Hong Zhong
Summary: This study proposes a fine-grained access control scheme to restrict applications' access to data in connected and autonomous vehicles (CAVs). The system model includes a trusted third party, perception components, and multiple applications. The use of fast attribute-based encryption and a key update scheme based on the Chinese remainder theorem, along with theoretical analysis and simulation experiments, demonstrates the feasibility and efficiency of this approach.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Haoxuan Dong, Weichao Zhuang, Boli Chen, Guodong Yin, Yan Wang
Summary: This study introduces an enhanced eco-approach control strategy to improve energy efficiency at signalized intersections by predicting the movement of vehicle queues. Through a hierarchical framework and numerical simulations, it is shown that the EEAC strategy can effectively enhance energy utilization efficiency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Economics
Xiangdong Chen, Xi Lin, Meng Li, Fang He, Qiang Meng
Summary: This study proposes a novel intersection design called knotted intersection (KI) to resolve the complexity of conflicting relations at intersections in a full CAV environment. The design is associated with a set of control rules for smooth traffic operation. The KI design is extended to a road network composed of multiple intersections to improve overall efficiency.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Engineering, Electrical & Electronic
Md Abdus Samad Kamal, Kotaro Hashikura, Tomohisa Hayakawa, Kou Yamada, Jun-ichi Imura
Summary: This paper presents a more practical technique for predictive driving of automated vehicles by extending the existing adaptive cruise control scheme. The proposed scheme predicts the state of the preceding vehicle and computes the vehicle control input more circumspectly, enabling efficient driving in urban traffic.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Transportation Science & Technology
Shian Wang, Michael W. Levin, Ryan James Caverly
Summary: This paper introduces a continuous-time stochastic dynamic model for the optimal parking management of connected autonomous vehicles in a given area with multiple parking lots. By regulating parking rates, the total demand for parking can be distributed among a set of parking lots to maintain the availability of each parking garage.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Review
Computer Science, Information Systems
Hamed Faghihian, Arman Sargolzaei
Summary: Connected autonomous vehicles (CAVs) have emerged as a promising solution for enhancing transportation efficiency. Electric CAVs (E-CAVs) present a significant opportunity to shape the future of efficient transportation systems and offer similar prospects but through distinct approaches, particularly in the control of acceleration and regenerative brakes.
Article
Transportation Science & Technology
Maksat Atagoziev, Ece Guran Schmidt, Klaus Werner Schmidt
Summary: This paper investigates an approach for automating and coordinating lane changes in a group of connected and autonomous vehicles (CAVs) with the goal of minimizing the time taken for all lane changes and maintaining small inter-vehicle distances. The paper presents an algorithm for minimizing the lane change time of a single CAV, which is subsequently applied to all lane-changing CAVs. The algorithm computes CAV reference trajectories based on a second-order vehicle model in real-time, and supports the implementation of these trajectories using cooperative adaptive cruise control to ensure safe driving.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Computer Science, Interdisciplinary Applications
Rasool Mohebifard, Ali Hajbabaie
Summary: This paper presents a methodology to control the trajectory of cooperative connected automated vehicles (CAVs) at roundabouts with a mixed fleet of CAVs and human-driven vehicles (HVs). By optimizing the trajectories of CAVs, total travel times can be reduced, and increasing CAV market penetration rates can lead to considerable improvements.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2022)
Article
Engineering, Civil
Amir Mirheli, Leila Hajibabai
Summary: This study presents a bi-level optimization program for designing and managing electric vehicle charging infrastructure, which effectively determines the optimal location, capacity, and pricing scheme.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Mehrdad Tajalli, S. M. A. Bin Al Islam, George F. List, Ali Hajbabaie
Summary: This paper presents a new approach using simulation to analyze the effectiveness of vehicle communications and control strategies in preventing crashes caused by red-light violations. The algorithms created in this study predict and avoid collisions through sensing and communication interfaces connecting vehicles, pedestrians, and signal controllers. The simulation analysis suggests that implementing vehicle-to-vehicle and vehicle-to-pedestrian communications can significantly reduce the number of near-crash events, and adding vehicle-to-infrastructure communication may further decrease such events.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Engineering, Civil
Ramin Niroumand, Leila Hajibabai, Ali Hajbabaie, Mehrdad Tajalli
Summary: This paper studies the effects of different autonomous driving behaviors on the safety and mobility performance of an isolated intersection in a mixed-autonomy environment. The results show that more aggressive autonomous driving behavior leads to lower average delay, increased number of stops, and more frequent activation of the white signal phase, which reduces speed variance and the number of rear-end near-collisions.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Operations Research & Management Science
Leila Hajibabai, Ali Hajbabaie, Julie Swann, Dan Vergano
Summary: This article provides an overview of vaccine distribution logistics in the United States and describes the data collected during the vaccination campaign. The data is made freely available for researchers and other stakeholders to gain insights and inform future pandemic response. The article also aims to inspire other researchers to share their data in a timely manner.
TRANSPORTATION SCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Leila Hajibabai, Asya Atik, Amir Mirheli
Summary: This paper aims to design an EV charging network with an embedded power distribution network (PDN) layout to support electric mobility in the future. A mixed-integer bilevel model is proposed to minimize the cost of PDN operations, charging facility deployments, and transportation. The problem is solved using a column and constraint generation algorithm, and the proposed methodology is shown to be robust through numerical experiments and sensitivity analyses.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Engineering, Civil
Amir Mirheli, Leila Hajibabai
Summary: This paper investigates the design and utilization management of electric vehicle (EV) charging networks, with a focus on user-centric decisions. A hierarchical model is proposed, which incorporates charging network design, demand-driven pricing, and user charging decisions. The goal is to minimize travel costs and charging expenses for users, while optimizing facility deployment cost, charging income, and user-centric costs.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Leila Hajibabai, Amir Mirheli
Summary: This study presents a dynamic scheduling scheme for EV charging facilities considering uncertainties in charging demand, charger availability, and charging rate. The proposed methodology, utilizing a dynamic programming model and integrated generalized Nash equilibrium technique, minimizes costs and improves the efficiency of the charging network. This research is of great importance for promoting EV adoption and supporting environmental sustainability.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Ramin Niroumand, Sina Bahrami, Hedayat Z. Aashtiani, Ali Hajbabaie
Summary: This paper examines the impact of flow-dependent energy consumption changes on route choice and user equilibrium conditions in battery electric vehicles (BEVs) during traffic congestion. It proposes a model for flow-dependent energy consumption user equilibrium and presents an algorithm to solve the problem.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Operations Research & Management Science
Muhammad Mobaidul Islam, Abdullah Al Redwan Newaz, Li Song, Benjamin Lartey, Shih-Chun Lin, Wei Fan, Ali Hajbabaie, Mubbashar Altaf Khan, Alireza Partovi, Tienake Phuapaiboon, Abdollah Homaifar, Ali Karimoddini
Summary: Connected autonomous vehicles (CAVs) are increasingly popular as a solution to road traffic issues. However, current efforts in CAV development are not fully integrated yet. This paper surveys literature on CAV developments, summarizes their impacts, and explores the current state of CAVs in terms of technology and infrastructure. Challenges for the adoption of CAVs are also identified.
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2023)
Article
Computer Science, Interdisciplinary Applications
Asya Atik, Leila Hajibabai
Summary: This study presents a mixed-integer linear program to optimize incident response operations in terms of travel time and demand coverage. The proposed integrated methodology includes column generation, Lagrangian relaxation, and a density-based clustering technique. The empirical case study in Raleigh, NC demonstrates the efficiency and superiority of the proposed algorithm in solving the problem of clearing roadways and preventing secondary incidents.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Engineering, Civil
Ramin Niroumand, Leila Hajibabai, Ali Hajbabaie
Summary: This study proposes a distributed coordination strategy for controlling a mixed traffic stream of connected automated vehicles (CAVs) and connected human-driven vehicles (CHVs). The study introduces a white phase where CAVs act as traffic controllers and negotiate the right-of-way to lead a group of CHVs. The study formulates the problem as a distributed mixed-integer non-linear program and develops a methodology for trajectory agreement and signal timing parameter selection among vehicles. Numerical experiments show that the proposed methodology efficiently controls vehicle movements at signalized intersections under different CAV market shares.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Ali Hajbabaie, Mehrdad Tajalli, Eleni Bardaka
Summary: This paper examines the impact of connected and automated vehicles on saturation headway and capacity at signalized intersections. Different scenarios are tested using Vissim, with four vehicle types modeled: human-driven vehicles, connected vehicles, automated vehicles, and connected automated vehicles. The results show that increasing the market-penetration rate of connected and automated vehicles can reduce saturation headway and increase intersection capacity. However, increasing the market-penetration rate of automated vehicles has a negative impact on traffic operations. The study also reveals the highest increase and decrease in lane-group capacity in traffic streams with 100% connected automated vehicles and 100% automated vehicles respectively.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
