4.7 Article

An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2019.11.005

Keywords

Traffic signal optimization; Equitable traffic signal control; Connected Vehicles

Funding

  1. Pennsylvania State University (PSU) University Graduate Fellowship (UGF) program

Ask authors/readers for more resources

This paper extends a real-time, Connected Vehicle-based traffic signal control algorithm at isolated intersections to balance between two competing intersection objectives: efficiency and equity. In this approach, a central controller is used to collect real-time locations of connected vehicles at regular intervals, which can then be used to also identify the existence of some of the non-connected vehicles. The control algorithm then aims to optimize the discharge sequence of naturally occurring platoons of vehicles based on their proximity. Specifically, the strategy selects the platoon discharge sequence-and associated signal phase and timing plan-that minimizes average vehicle delay (measure of efficiency) while limiting the maximum delay any individual vehicle may experience (measure of equity). The latter objective is only possible with detailed vehicle-level information available from connected vehicles. The results show that without the threshold on maximum individual vehicle delay, average delay is often minimized at the expense of very large delays imposed onto some vehicles. By implementing a threshold, both the maximum vehicle delay and the distribution of individual vehicle delays-as measured by the standard deviation and a common measure of population inequity, the Gini coefficient-can be improved, often with only negligible impacts to intersection efficiency. However, the tradeoff between equity and efficiency becomes more significant as the maximum vehicle delay threshold decreases. Sensitivity tests show that this control algorithm works well for different total traffic demands and different demand patterns. The proposed algorithm is also effective under imperfect connected vehicle penetration rates when the connected vehicles make up more than 40% of the traffic stream. The results suggest that the proposed strategy can help significantly reduce long delays and inequitable treatment of vehicles at an intersection when vehicle-level information is available to a signal controller.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Engineering, Civil

Coordinated Perimeter Flow and Variable Speed Limit Control for Mixed Freeway and Urban Networks

Rebeka Yocum, Vikash V. Gayah

Summary: Recent studies have developed a coordinated traffic management scheme that implements perimeter flow control on an urban network and variable speed limits (VSL) on a freeway to reduce total travel time in a mixed network. VSL effectively meters traffic exiting the freeway into the urban network, improving overall system operations.

TRANSPORTATION RESEARCH RECORD (2022)

Article Transportation

Green time usage metrics on signalized intersections and arterials using high-resolution traffic data

Renato Guadamuz, Houjun Tang, Zhengyao Yu, S. Ilgin Guler, Vikash V. Gayah

Summary: The performance of traffic signal phasing and timing plans is influenced by fluctuations in traffic volumes. This study introduces new metrics and methods to evaluate the efficiency of green time allocation using high-resolution traffic data. An empirical application is conducted on a major arterial in Salt Lake City and provides insights for improving signal timing plans.

INTERNATIONAL JOURNAL OF TRANSPORTATION SCIENCE AND TECHNOLOGY (2022)

Article Transportation

Decentralized arterial traffic signal optimization with connected vehicle information

Xiao (Joyce) Liang, S. Ilgin Guler, Vikash V. Gayah

Summary: This paper proposes a decentralized signal control algorithm that leverages connected vehicle information to improve traffic operations. The algorithm optimizes signal timing based on real-time vehicle locations, speeds, and pedestrian waiting information, and facilitates coordination between adjacent intersections through sharing vehicle platoons information. Compared to the centralized algorithm and traditional strategy, the proposed algorithm is more computationally efficient and provides better operational performance, while being robust to different demand patterns.

JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS (2023)

Article Transportation

Simulation analysis of urban network performance under link disruptions: Impacts of information provisions in different street configurations

Zhengyao Yu, Vikash V. Gayah

Summary: This study examines the performance of three street network configurations under disruptive events using aggregated network-level operation metrics. The results show that a two-way network without left turns is the most efficient configuration, able to handle the most challenging disruptions. Additionally, providing advance information to drivers about disruptions may have negative effects on overall network performance.

JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS (2023)

Article Transportation

Development and evaluation of frameworks for real-time bus passenger occupancy prediction

Jonathan Wood, Zhengyao Yu, Vikash V. Gayah

Summary: Seating availability and boarding space on buses have a significant impact on riders' attitudes. However, little research has been done on short-term passenger occupancy predictions on individual buses. This study investigates the use of linear regression models and machine learning models to predict passenger occupancies on buses in real-time, based on data from bus operations and weather information. The results show that both models provide accurate estimates.

INTERNATIONAL JOURNAL OF TRANSPORTATION SCIENCE AND TECHNOLOGY (2023)

Article Transportation

A population-based incremental learning algorithm to identify optimal location of left-turn restrictions in urban grid networks

Murat Bayrak, Zhengyao Yu, Vikash V. Gayah

Summary: This paper proposes a population-based incremental learning (PBIL) algorithm to determine left-turn restrictions at intersections in order to maximize the network's operational performance. The algorithm is effective at identifying near-optimal configurations, suggesting that left turns should generally be restricted at intersections with the highest flow. This approach provides additional intersection capacity and reduces additional travel distance.

TRANSPORTMETRICA B-TRANSPORT DYNAMICS (2023)

Article Engineering, Civil

Total-delay-based Max Pressure: A Max Pressure Algorithm Considering Delay Equity

Hao Liu, Vikash V. Gayah

Summary: This paper proposes a novel decentralized signal control algorithm that improves traffic delay equity without significantly increasing average delay. The algorithm uses the sum of cumulative delay as the weight calculation metric, ensuring that less congested movements have a higher chance of being served. Microscopic simulations comparing the proposed algorithm with three baseline models demonstrate its effectiveness, especially for highly unbalanced traffic flows. Additionally, the algorithm outperforms other models in reducing traffic delay and increasing delay equity in a connected vehicle environment with a penetration rate less than or equal to 60%.

TRANSPORTATION RESEARCH RECORD (2023)

Article Transportation Science & Technology

Scalable multi-region perimeter metering control for urban networks: A multi-agent deep reinforcement learning approach

Dongqin Zhou, Vikash V. Gayah

Summary: Perimeter metering control based on macroscopic fundamental diagrams has gained attention in traffic management. Existing methods require accurate knowledge of traffic dynamics, but this paper proposes a scalable model-free scheme based on multi-agent deep reinforcement learning that overcomes this limitation. Experimental results show the scheme's effectiveness, resilience, and transferability in managing traffic in urban networks.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2023)

Article Engineering, Civil

Opposing Hysteresis Patterns in Flow and Outflow Macroscopic Fundamental Diagrams and Their Implications

Guanhao Xu, Pengxiang Zhang, Vikash V. Gayah, Xianbiao Hu

Summary: The relationship between average network flow and density (flow-MFD) and the relationship between trip completion and density (o-MFD) are two key aggregated traffic models. Recent studies have shown that these two relationships might have different patterns when traffic conditions vary. This paper presents an alternative explanation for these findings by showing that a vehicle's entire trip contributes to a network's average flow, while only its end contributes to the trip completion rate. This lag can lead to different patterns in the o-MFD. The paper provides examples and simulations to support these explanations.

TRANSPORTATION RESEARCH RECORD (2023)

Article Engineering, Civil

Improving Deep Reinforcement Learning-Based Perimeter Metering Control Methods With Domain Control Knowledge

Dongqin Zhou, Vikash V. V. Gayah

Summary: This paper proposes integrating domain control knowledge (DCK) into agent designs to improve learning and control performances. Two types of DCK are introduced to provide knowledge-guided exploration strategies for agents to explore the most rewarding part of the action spaces. Experimental results show that integrating DCK can effectively enhance learning and control performances, improve agents' resilience against environmental uncertainties, and mitigate scalability issues.

TRANSPORTATION RESEARCH RECORD (2023)

Article Ergonomics

Estimation of crash type frequency accounting for misclassification in crash data

Asif Mahmud, Vikash V. Gayah, Rajesh Paleti

Summary: This study introduces a novel approach to address the issue of crash misclassification and incorporates it into two commonly used crash frequency prediction models. The proposed models demonstrate their capability to estimate true parameters and provide more reliable results compared to models that ignore misclassification errors.

ACCIDENT ANALYSIS AND PREVENTION (2023)

Article Economics

Non-unimodal and non-concave relationships in the network Macroscopic Fundamental Diagram caused by hierarchical streets

Guanhao Xu, Vikash V. Gayah

Summary: Recent research has shown that there are unimodal, concave relationships between average network productivity and accumulation or density in urban networks. These relationships, known as network Macroscopic Fundamental Diagrams (MFDs), have implications for the modeling of traffic congestion and the development of regional traffic control strategies. However, real street networks are not homogeneous and have hierarchical structures, which may result in non-unimodal patterns in MFDs. This paper examines how the presence of hierarchical roadway structures can affect a network's MFD using analytical models, simulations, and empirical data. The findings suggest that the presence of roadway hierarchies can lead to non-unimodal or non-concave MFD patterns, contrary to traditional assumptions.

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2023)

Article Engineering, Civil

Network-Wide Implementation of Roundabouts Versus Signalized Intersections on Urban Streets: Analytical and Simulation Comparison

David Taglieri, Hao Liu, Vikash V. Gayah

Summary: This paper examines the impact of implementing roundabouts at intersections in a dense urban network on operational performance. Three intersection strategies are compared: signalized intersections allowing left turns, signalized intersections prohibiting left turns, and modern roundabouts. The results show that roundabouts perform better than signalized intersections in networks with a single travel lane in each direction, but signalized intersections with two travel lanes outperform roundabouts in terms of flow-moving and trip-serving capacities. The higher fuel consumption rate in roundabouts is attributed to more frequent acceleration and deceleration.

TRANSPORTATION RESEARCH RECORD (2023)

Article Ergonomics

Crash modification factors of rumble strips on horizontal curves of two-lane rural roads: A propensity scores potential outcomes approach

Tanveer Ahmed, Asif Mahmud, Vikash V. Gayah

Summary: This study uses the propensity score potential outcome framework to investigate the impact of rumble strips on crashes on horizontal curves. The findings suggest that centerline rumble strips reduce sideswipe and head-on crashes but increase run off the road and hit fixed object crashes. Shoulder rumble strips, either alone or in combination with centerline rumble strips, decrease crash frequencies for most types except sideswipe and head-on crashes.

ACCIDENT ANALYSIS AND PREVENTION (2024)

Article Engineering, Civil

Macroscopic Analysis of the Impacts of Shared Bikes on Traffic Safety

Muyang Lu, Vikash V. Gayah, S. Ilgin Guler

Summary: Crashes involving vulnerable roadway users have been on the rise recently. This study incorporates exposure metrics related to nonmotorized and public transportation use to develop a crash-prediction model. The results show a positive correlation between shared-bike trips and POI visits with increases in pedestrian and cyclist crash frequencies.

TRANSPORTATION RESEARCH RECORD (2023)

Article Transportation Science & Technology

3-Strategy evolutionary game model for operation extensions of subway networks

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

Integrated optimization of container allocation and yard cranes dispatched under delayed transshipment

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

Range-constrained traffic assignment for electric vehicles under heterogeneous range anxiety

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

Demand forecasting and predictability identification of ride-sourcing via bidirectional spatial-temporal transformer neural processes

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

Partial trajectory method to align and validate successive video cameras for vehicle tracking

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

Dynamic routing for the Electric Vehicle Shortest Path Problem with charging station occupancy information

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)