Journal Article10.3141/2257-10
Cycle-by-cycle queue length estimation for signalized intersections using sampled trajectory data
112
TL;DR: This method is able to provide cycle-by-cycle queue length estimation for signalized intersections with sampled vehicle trajectories as the only input, and the results indicate that this trajectory-based approach is promising.
read more
Abstract: Queue length estimation is an important component of intersection performance measurement. Different approaches based on different data sources have been presented. With the latest developments in vehicle detection technologies, especially probe vehicle technologies, use of vehicle trajectory data has become possible. In this paper, an improved method for queue length estimation for signalized intersections is proposed. This method is able to provide cycle-by-cycle queue length estimation for signalized intersections with sampled vehicle trajectories as the only input. The keystone of the entire approach is the concept of the critical point (CP), which represents the changing vehicle dynamics. A CP extraction algorithm is introduced to identify CPs from raw trajectories. Using the CPs related to queue formation and dissipation, the authors propose an improved queue length estimation method based on shock waves. The performance of this approach is evaluated with several data sets under different flow and s...
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Cooperative Deep Reinforcement Learning for Large-Scale Traffic Grid Signal Control
TL;DR: The proposed Coder framework, which combines multiple regional agents and a centralized global agent, could reduce on average 30% congestions in terms of the number of waiting vehicles during high density traffic flows in simulations.
235
Queue Length Estimation Using Connected Vehicle Technology for Adaptive Signal Control
TL;DR: A mathematical model for real-time queue estimation using connected vehicle (CV) technology from wireless sensor networks and a discrete wavelet transform (DWT) is applied to the queue estimation algorithm in this paper for the first time.
145
A data fusion approach for real-time traffic state estimation in urban signalized links
TL;DR: A novel data fusion approach is proposed for the high-resolution (second-by-second) estimation of queue length, vehicle accumulation, and outflow in urban signalized links that renders the proposed methodology more robust to varying penetration rates of connected vehicles.
97
Real-time estimation of lane-based queue lengths at isolated signalized junctions
TL;DR: In this paper, a real-time estimation approach for lane-based queue lengths is developed based on time occupancy rates and impulse memories, as calculated by the detector and signal information from a set of upstream and downstream detectors.
References
Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
On kinematic waves II. A theory of traffic flow on long crowded roads
TL;DR: The theory of kinematic waves is applied to the problem of estimating how a ‘hump’, or region of increased concentration, will move along a crowded main road, and is applicable principally to traffic behaviour over a long stretch of road.
5.1K
•Journal Article
On kinetic waves, II . A theory of traffic flow on long crowded roads
M J Lighthill,G B Whitham +1 more
TL;DR: In this paper, a functional relationship between flow and concentration for traffic on crowded arterial roads has been postulated for some time, and has experimental backing, from which a theory of the propagation of changes in traffic distribution along these roads may be deduced.
3.9K
Shock Waves on the Highway
TL;DR: In this article, a simple theory of traffic flow is developed by replacing individual vehicles with a continuous fluid density and applying an empirical relation between speed and density, which is a simple graph-shearing process for following the development of traffic waves.
3.8K
•Book
Traffic flow fundamentals
Adolf D. May
- 07 Dec 1989
TL;DR: The remaining portion of the book, Chapters 8 through 13, is devoted to analytical techniques involving the total traffic flow situation; chapter subjects are, respectively, demand-supply analysis, capacity analysis, traffic stream models, shock wave analysis, queueing analysis, and computer simulation models.
1.8K