Article
Computer Science, Information Systems
Areeya Rubenecia, Myungwhan Choi, Hyo-Hyun Choi
Summary: In this paper, a three-dimensional intersection traffic management platform for small autonomous UAVs in urban airspace is presented. The platform aims to provide safe and systematic management of UAVs, with a scheduling scheme to efficiently utilize the intersection and avoid collisions among UAVs. Simulations show that the scheduling scheme reduces the UAVs' average time in the system by 27%.
Article
Economics
Mohamad Shatanawi, Anas Alatawneh, Ferenc Meszaros
Summary: The introduction of autonomous vehicles and shared autonomous vehicles is expected to improve network performance and accessibility, but it may also lead to increased vehicle miles traveled. This study investigated the impact of road pricing schemes on network performance and social welfare in different future traffic scenarios. The results showed that the effects of road pricing schemes vary depending on the penetration rates of autonomous vehicles, and implementing dynamic pricing strategies can lead to better outcomes in certain scenarios.
RESEARCH IN TRANSPORTATION ECONOMICS
(2022)
Article
Transportation
Behzad Bamdad Mehrabani, Jakob Erdmann, Luca Sgambi, Seyedehsan Seyedabrishami, Maaike Snelder
Summary: This study proposes an open-source solution framework for the multiclass simulation-based Traffic Assignment Problem (TAP) in mixed traffic of Connected and Autonomous Vehicles (CAVs) and Human-Driven Vehicles (HDVs), aiming to better understand the impact of CAVs on mixed traffic flow.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Green & Sustainable Science & Technology
Mohamad Shatanawi, Ferenc Meszaros
Summary: This research investigates the impact of varying the share distribution of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) on network performance and consumer surplus in Budapest using simulation-based dynamic traffic assignment. The results suggest that the emergence of AVs and SAVs improves overall network performance, particularly with an increasing share distribution of SAVs. Similarly, consumer surplus increases in all future scenarios, especially with an increasing share distribution of AVs.
Article
Computer Science, Interdisciplinary Applications
Mariano Gallo
Summary: This paper proposes models and algorithms for estimating traffic flows generated by the centralised management of autonomous vehicles in both exclusive and mixed traffic conditions. The research demonstrates the impact of autonomous vehicles on traffic flows and provides a method for evaluating the inclusion of autonomous vehicles in traffic planning, design or policy interventions.
SIMULATION MODELLING PRACTICE AND THEORY
(2023)
Article
Transportation
Farzaneh Azadi, Nikola Mitrovic, Aleksandar Z. Stevanovic
Summary: A concept called CADLARIC was proposed for managing traffic flows in CAV environment, which requires high infrastructure demand. To overcome this, CFLARIC, a more robust concept that offers a full spectrum of lane assignment possibilities, was proposed. Three CFLARIC strategies were tested and proved to outperform traditional control methods in terms of efficiency and safety.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Transportation
Shun Su, Emmanouil Chaniotakis, Santhanakrishnan Narayanan, Hai Jiang, Constantinos Antoniou
Summary: This paper investigates the optimization of Reservation-based Autonomous Car Sharing (RACS) systems, aiming at minimizing the total vehicle travel time and customer waiting time. The proposed solution algorithms are tested in two different networks of varying complexity, and the performance of the algorithms is evaluated.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2022)
Article
Engineering, Civil
Shian Wang, Raphael Stern, Michael W. Levin
Summary: This article focuses on smoothing unstable traffic flow by controlling autonomous vehicles (AVs), aiming to minimize vehicle speed perturbation. A dynamic model for mixed traffic flow with both human-driven vehicles (HVs) and AVs is developed, and an optimal control problem is formulated based on Pontryagin's minimum principle to determine the optimal AV control policy. Numerical results demonstrate the effectiveness of the proposed approach in traffic smoothing and improvement on vehicle fuel economy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Sajjad Shafiei, Ziyuan Gu, Hanna Grzybowska, Chen Cai
Summary: The advent of autonomous vehicles is expected to bring new mobility experiences for travelers, such as the ability to self-park. This study investigates the dynamics of travelers shifting to private-owned autonomous vehicles and its negative impact on road traffic congestion. A distance-based pricing scheme is also integrated into the modeling framework to examine its effects on mode choice and traffic network performance. The results show that the distance-based pricing scheme can effectively limit the usage of autonomous vehicles and reduce traffic congestion, particularly in urban centers and peripheral suburbs.
Article
Engineering, Civil
Xin Huang, Peiqun Lin, Mingyang Pei, Bin Ran, Manchun Tan
Summary: Oversaturation has become a serious issue for urban intersections worldwide due to the rapid increase in population and traffic demands. The emergence of connected and automated vehicle (CAV) technologies demonstrates the potential to improve oversaturated arterial traffic. This paper proposes an efficient reservation-based cooperative ecodriving model (RCEM) for an isolated intersection under partial and complete CAV market penetration, which can simultaneously optimize the CAV trajectories and intersection controller.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Economics
Qian Ge, Ke Han, Xiaobo Liu
Summary: The study focuses on the dispatch and routing problems of shared autonomous vehicles (DR-SAV) in a mixed traffic environment. By proposing a computationally tractable traffic assignment framework, the optimization of SAV trip matching and routing is improved, leading to a significant reduction in total travel cost.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Computer Science, Interdisciplinary Applications
Amin Rezaei, Brian Caulfield
Summary: The study showed that AVs could significantly improve traffic quality, particularly by reducing stops, queue length, and delay time. Both TVs and AVs can efficiently share the road, with traffic quality improvement increasing as the proportion of AVs to TVs increases.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Chemistry, Analytical
Rui Li, Qi Ouyang, Yue Cui, Yang Jin
Summary: This paper presents a steering control approach based on preview theory, with the prediction of constrained variables and adjustment of control law using an error states system. An optimization algorithm is conducted to improve adaptability, and theoretical stability is guaranteed using Lyapunov theory. Simulation results demonstrate favorable performance in tracking accuracy and system stability under extreme conditions.
Article
Computer Science, Interdisciplinary Applications
Xiang Zhang, Steven Travis Waller, Dung-Ying Lin
Summary: This study is the first in the literature to examine the Braess paradox considering parking behavior in the autonomous vehicle (AV) environment and model the network design problem for the autonomous transportation system (NDP-ATS). It shows the existence of two distinct Braess paradoxes in AV traffic networks and develops a bi-level programming model to avoid the deterioration caused by these paradoxes. The results highlight the efficacy of the modeling framework for infrastructure development and policy assessment for AV traffic.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Transportation Science & Technology
Mohammad Hadi Mansourianfar, Ziyuan Gu, S. Travis Waller, Meead Saberi
Summary: The paper proposes a joint routing and pricing control scheme to incentivize CAVs to seek system-optimal routing, reducing total system travel time and discouraging congestion by human-driven vehicles in city centers.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Management
David Rey, Michael W. Levin, Vinayak V. Dixit
Summary: The study introduces novel online mechanisms for traffic intersection auctions where users bid for priority service. Two Markov chain models are proposed to determine the expected waiting time of participants in the auction, along with a mechanism to calculate incentive-compatible payments in the dynamic sense, maximizing social welfare in the long run. Findings suggest that the proposed online mechanisms are incentive-compatible in the dynamic sense, in contrast to static incentive-compatible mechanisms that may lead to misreporting by users.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Multidisciplinary Sciences
Michael W. Levin, Mingfeng Shang, Raphael Stern
Summary: The novel coronavirus, first identified in China, quickly became a global pandemic. Short-term travel associated with driving is predicted to significantly contribute to the spread of COVID-19. Studies suggest that reducing intrastate travel could help contain the virus spread and prevent a substantial increase in cases.
Article
Transportation
Di Kang, Zhexian Li, Michael W. Levin
Summary: This paper investigates the safety buffers needed between intersecting vehicles under Autonomous Intersection Management (AIM) by optimizing vehicle trajectories and considering reaction times. The tradeoff between low reaction times (more false positives) and high reaction times (greater safety buffer) is analyzed through sensitivity analyses.
JOURNAL OF TRANSPORTATION SAFETY & SECURITY
(2022)
Article
Engineering, Civil
Shian Wang, Raphael Stern, Michael W. Levin
Summary: This article focuses on smoothing unstable traffic flow by controlling autonomous vehicles (AVs), aiming to minimize vehicle speed perturbation. A dynamic model for mixed traffic flow with both human-driven vehicles (HVs) and AVs is developed, and an optimal control problem is formulated based on Pontryagin's minimum principle to determine the optimal AV control policy. Numerical results demonstrate the effectiveness of the proposed approach in traffic smoothing and improvement on vehicle fuel economy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Transportation Science & Technology
Te Xu, Simanta Barman, Michael W. Levin, Rongsheng Chen, Tianyi Li
Summary: This paper proposes a novel max-pressure signal control method that considers transit signal priority to achieve maximum stability for private vehicles and reliable transit service. The method, validated through simulations, shows promising results in reducing travel time.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Environmental Studies
D. Kang, F. Hu, M. W. Levin
Summary: This study examines the impacts of induced AV trips on the transportation network and proposes a solution algorithm. Test results demonstrate that the use of AVs increases average travel time and allows for the repurposing of parking spaces.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Engineering, Civil
Simanta Barman, Michael W. Levin
Summary: This study examines the performance of different variations of MP signal timing policies in realistic scenarios and finds that MP control strategies generally outperform current signal control. The findings suggest that most of the claimed performance benefits of MP policies can still be achieved in real-life traffic conditions.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Engineering, Civil
Shian Wang, Aidan Mahlberg, Michael W. Levin
Summary: This article studies the optimal control of automated vehicles at an autonomous intersection. It develops a mathematical model and an optimization problem to maximize traffic throughput and minimize passenger discomfort. The proposed control mechanism is applied to coordinate the movement of AVs at an autonomous intersection without using traffic lights and is validated through numerical experiments. The research is important for the future development of autonomous vehicles.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Environmental
Hagen Fritz, Mengjia Tang, Kerry Kinney, Zoltan Nagy
Summary: Air quality is an important factor that affects people's perception of their indoor environment and health. Through the development and evaluation of machine learning models, we found that building ventilation rate, relative humidity, and formaldehyde are the most influential factors in predicting indoor air quality perception, while PM2.5 and TVOCs are the main predictors of sleep quality.
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION
(2022)
Article
Economics
Michael W. Levin
Summary: The maximum demand that can be served by shared autonomous vehicles (SAVs) depends on network characteristics, travel demand, and dispatch policy. This study provides equations for describing the maximum set of demands that can be served and presents a dispatch policy that achieves the predicted level of passenger throughput. The stability of the network is analyzed using a Markov chain queueing model and Lyapunov drift.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Transportation Science & Technology
Shian Wang, Zhexian Li, Michael W. Levin
Summary: This study develops a continuous-time dynamical model based on the Lotka-Volterra equations to capture the temporal evolution of market shares between autonomous vehicles (AVs) and legacy vehicles (LVs). The model incorporates a discrete choice model to represent the likelihood of choosing AVs or LVs. An optimal control problem is formulated to determine the optimal AV integration policy, considering subsidies and infrastructure investment. Numerical results demonstrate the effectiveness and robustness of the proposed approach, and a cost-benefit analysis evaluates the desirability of AV integration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Transportation Science & Technology
Shian Wang, Mingfeng Shang, Michael W. Levin, Raphael Stern
Summary: Stop-and-go waves caused by unstable traffic can be reduced by synthesizing feedback controllers for autonomous vehicles (AVs) to smooth nonlinear mixed traffic flow. By leveraging feedback control theory, AVs can closely track a virtual speed profile, reducing traffic waves. The proposed approach includes a class of effective additive AV controllers and sufficient conditions for car-following safety and mixed traffic string stability. The approach is illustrated with a theoretical intelligent driver model (IDM) and commercially available adaptive cruise control (ACC) vehicles, showing its effectiveness and robustness in simulation.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Transportation Science & Technology
Simanta Barman, Michael W. Levin
Summary: Max-pressure (MP) control is proven to maximize network throughput or stabilize the network. This paper proves that even with a limited deployment, MP control can stabilize a network within feasible demand. An optimization formulation is presented to find the optimal intersections to install MP control given a limited budget. A greedy efficient algorithm is also presented to solve the optimization problem. Simulation results show that limited deployment of MP control outperforms random deployment in terms of servable stable demand.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Xiang Zhang, Wei Liu, Michael Levin, S. Travis Waller
Summary: This study investigates the morning commuting and parking patterns of autonomous vehicles (AVs) under different spatial road capacity allocation schemes. The study analyzes equilibrium departure/arrival and parking patterns for AVs subject to spatial road capacity allocation. The study also examines optimal capacity allocation strategies under both user equilibrium and system optimum AV traffic patterns to minimize the total system travel cost.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Review
Engineering, Civil
Michael W. Levin
Summary: Max-pressure control is a mathematically proven method for signal timing that improves network throughput. It has evolved from a simple store-and-forward queueing model to include practical aspects and adapt to local queues and network demand. Numerical results from calibrated microsimulation models consistently show that max-pressure control outperforms existing methods, and researchers have started experimenting with it on real roads. This review paper provides a summary of the mathematical approach, methodological improvements, and numerical results for researchers and practitioners interested in this state-of-the-art signal timing method.
JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS
(2023)
