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Proceedings ArticleDOI

Video based adaptive road traffic signaling

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TLDR
A video based adaptive traffic signaling scheme for reducing waiting period of vehicles at road junctions without detecting or tracking vehicles is proposed and found to be a much faster and effective control strategy.
Abstract
The ability to exert real time, adaptive control, of the transportation process is the core of an intelligent traffic system. We propose a video based adaptive traffic signaling scheme for reducing waiting period of vehicles at road junctions without detecting or tracking vehicles. The traffic signal timing parameters at a given intersection are adjusted automatically as functions of the local traffic conditions. The video sequences recorded at junctions are used for generating Spatial Interest Points (SIP) and Spatio-Temporal Interest Points (STIP). The traffic congestion at the junction is estimated using SIP and STIP. The decision rules are based on a definitive analogy between road traffic and computer data traffic wherein road vehicles are compared with data packets on the network. The system is similar in approach to the technique of Weighted Round Robin (WRR) queuing, a scheduling discipline used in data communication networks. Local traffic information is used to adjust the phase split keeping the cycle time constant. Two methods have been proposed. The first method, Optimal Weight Calculator (OWC), minimizes traffic at an intersection by determining the optimal phase splits or weights. The second method, Fair Weight Calculator (FWC), calculates weights relative to the road with minimum traffic to bring more fairness. After applying the respective algorithms mathematically on varying traffic conditions, OWC was found to be more equitable in the allocation of green time which is suitable for highly weight-sensitive junctions. For traffic with road priorities, FWC was found to be a much faster and effective control strategy.

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Journal ArticleDOI

Computer vision-guided intelligent traffic signaling for isolated intersections

TL;DR: A new approach of traffic flow-based intelligent signal timing by temporally clustering optical flow features of moving vehicles using Temporal Unknown Incremental Clustering (TUIC) model is proposed and can achieve better average waiting time and throughput as compared to the state-of-the-art signal timing algorithms.
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Camera Location for Real-Time Traffic State Estimation in Urban Road Network Using Big GPS Data

TL;DR: A traffic state network (TSN) is presented to model the relationship among all road sections based on big GPS data, which contains mass traffic information, and effectively describes the relationship of road sections in traffic state.
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State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends

TL;DR: The key role of real-time traffic signal control technology in managing congestion at road junctions within smart cities is explored and the benefits of synchronizing the traffic signals on various busy routes for the smooth flow of traffic at intersections are examined.
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Video analytics revisited

TL;DR: In this study, the authors discuss various issues and problems in video analytics, proposed solutions and present some of the important current applications of video analytics.
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On vehicle state tracking for long-term carpark video surveillance

TL;DR: This work proposes a parking state machine that tracks the vehicle state in a large outdoor car park area and proves to be fairly accurate, fast and robust against severe scene variations.
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