The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors

Jia, Zhanfeng; Chen, Chao; Coifman, Benjamin; Varaiya, Pravin

doi:10.1109/itsc.2001.948715

Cited by 41 publications

(10 citation statements)

References 3 publications

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“…A method to classify the vehicle based on Fourier transform (Lamas-Seco et al 2015) with a single -loop is proposed to improve traffic management system. Categorization (Ki, Baik 2006;Lu et al 2012;Meta, Cinsdikici 2010) and evaluation (De Lima et al 2010;Jia et al 2001) based on single-loop system are used widely. Wang et al (2018) proposed a prediction model based on nonparametric regression approach.…”

Section: Related Workmentioning

confidence: 99%

“…To get the vehicle trajectory information, vehicle reidentification techniques can be used. Few related techniques are travel time estimation (Coifman 2002;Liu et al 2007), monitoring highway (Chen et al 2001) and incident detection (Yao et al 2014;Oh et al 2006;Jia et al 2001). Few of the approaches have proposed to use Internet of Things (IoT) and Cloud computing technologies to provide better services for road transportation system (Aazam et al 2014;Botta et al 2016;Tao et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Intelligent Traffic Light Control and Deviation System for Traffic Congestion Avoidance Using Multi-Agent System

Sathiyaraj

Bharathi

2019

Transport

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An efficient and intelligent road traffic management system is the corner stone for every smart cities. Vehicular Ad-hoc NETworks (VANETs) applies the principles of mobile ad hoc networks in a wireless network for Vehicle-to-vehicle data exchange communication. VANETs supports in providing an efficient Intelligent Transportation System (ITS) for smart cities. Road traffic congestion is a most common problem faced by many of the metropolitan cities all over the world. Traffic on the road networks are widely increasing at a larger rate and the current traffic management systems is unable to tackle this impediment. In this paper, we propose an Efficient Intelligent Traffic Light Control and Deviation (EITLCD) system, which is based on multi-agent system. This proposed system overcomes the difficulties of the existing traffic management systems and avoids the traffic congestion problem compare to the prior scenario. The proposed system is composed of two systems: Traffic Light Controller (TLC) system and Traffic Light Deviation (TLD) system. The TLC system uses three agents to supervise and control the traffic parameters. TLD system deviate the vehicles before entering into congested road. Traffic and travel related information from several sensors are collected through a VANET environment to be processed by the proposed technique. The proposed structure comprises of TLC system and makes use of vehicle measurement, which is feed as input to the TLD system in a wireless network. For route pattern identification, any traditional city map can be converted to planar graph using Euler’s path approach. The proposed system is validated using Nagel–Schreckenberg model and the performance of the proposed system is proved to be better than the existing systems in terms of its time, cost, expense, maintenance and performance.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Efficient Intelligent Traffic Light Control and Deviation System for Traffic Congestion Avoidance Using Multi-Agent System

Sathiyaraj

Bharathi

2019

Transport

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“…The two architectures were combined into the vehicle-to-vehicle-to-infrastructure (V2V2I) architecture in [19], and vehicular ad-hoc networks (VANETs) are becoming increasingly more popular [17]. The means by which speed is determined from gathering data discretely at loop detectors is widely used by departments of transportation and was originally proposed in [18].…”

Section: Related Workmentioning

confidence: 99%

Analysis of the Traveling Salesman Problem with a subset of intermediate cities and dynamic edge weights used with intelligent transportation systems

Miller

2009

2009 7th International Conference on Information, Communications and Signal Processing (ICICS)

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In this paper a specialized routing problem for vehicles in a transportation network that need to visit multiple destinations before returning to the starting location in the minimum time is presented. Although this problem is similar to the Traveling Salesman Problem (TSP), it differs because the edge weights can change constantly and the vehicle only needs to visit a subset of the nodes in the graph. The Dynamic Fastest Paths with Multiple Unique Destinations (DynFast-MUD) algorithm [23] provides a solution to this problem which is tested in a live environment in this study. There are currently 50 vehicles in Anchorage, Alaska that contain devices that report the speed, location, and direction to a central server through a vehicle-to-infrastructure (V2I) architecture. Using this data, the shortest route to a predefined set of destinations was compared to the path identified by the DynFast-MUD algorithm once a day for a two week period. The results show that with this relatively limited number of vehicles contributing to the dynamic changing edge weights, the DynFast-MUD algorithm always provides a route that is at least as fast as the shortest route. It is hypothesized that with more vehicles reporting speed and location data, the DynFast-MUD algorithm will produce even better results.

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“…Vehicle-to-vehicle [7] and vehicle-to-infrastructure [6,8,9] communication have been studied for a number of years. With V2V communication, vehicle ad-hoc networks (VANETs) were proposed and analyzed in [10], as well as secure mobile computing.…”

Section: Related Workmentioning

confidence: 99%

“…With V2V communication, vehicle ad-hoc networks (VANETs) were proposed and analyzed in [10], as well as secure mobile computing. V2I communication research is generally conducted utilizing inductor loops as a means of data gathering and estimating the speeds based on the occupancy, number of vehicles, and average length of a vehicle [8]. Further, using this data to attempt routing of vehicles along fastest paths has been done in [9].…”

Section: Related Workmentioning

confidence: 99%

Analysis of Vehicle Lane Changes for Determining Fastest Paths in the V2V2I ITS Architecture

Miller

2008

2008 11th International IEEE Conference on Intelligent Transportation Systems

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In this paper I perform an analysis of vehicle lane changes and how they relate to fastest path determination. I converted live discrete loop detector data from the California Department of Transportation into continuous data to be utilized by vehicles in a vehicle-to-vehicle-to-infrastructure (V2V2I) intelligent transportation system (ITS) architecture.The continuous data was then used by FreeSim (http://www.freewaysimulator.com) to simulate live traffic conditions. As the time to traverse the edges in the transportation network were being constantly updated, additional vehicles were inserted into the network to determine travel times and fastest paths from a source node to a destination node. The output shows that faster and more accurate paths can be found if lane data is obtained rather than just summary data of loop detectors. Further, if vehicles can be routed along paths with optimal lane changes to decrease the total travel time, a savings of approximately 33% of the travel time can be experienced. It is also shown that the number of lane changes needed in the fastest path with regards to lanes is lower than the number of lane changes needed for other candidate fastest paths, and highways with less congestion require fewer lane changes.

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The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors

Cited by 41 publications

References 3 publications

An Efficient Intelligent Traffic Light Control and Deviation System for Traffic Congestion Avoidance Using Multi-Agent System

An Efficient Intelligent Traffic Light Control and Deviation System for Traffic Congestion Avoidance Using Multi-Agent System

Analysis of the Traveling Salesman Problem with a subset of intermediate cities and dynamic edge weights used with intelligent transportation systems

Analysis of Vehicle Lane Changes for Determining Fastest Paths in the V2V2I ITS Architecture

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