CarTel

Hull, Bret; Bychkovsky, Vladimir; Zhang, Yang; Chen, Kevin; Goraczko, Michel; Miu, Allen; Shih, Eugene; Balakrishnan, Hari; Madden, Samuel

doi:10.1145/1182807.1182821

Cited by 795 publications

(39 citation statements)

References 43 publications

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“…Incremental planning for multiple drivers was studied in [24] using the assumption that the stochastic travel time for a road segment changes according to the number of previously planned drivers. Many traffic routing systems have been developed based on travel time estimation from GPS data collected by probe vehicles [10], [25], [7], [8], [14], [3], [9]. Prior research for estimating traffic flow includes [6], [22], [21].…”

Section: A Related Workmentioning

confidence: 99%

Congestion-aware Traffic Routing System using sensor data

Aslam

Lim²,

Rus³

2012

2012 15th International IEEE Conference on Intelligent Transportation Systems

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In this paper, we present a congestion-aware route planning system. First we learn the congestion model based on real data from a fleet of taxis and loop detectors. Using the learned street-level congestion model, we develop a congestionaware traffic planning system that operates in one of two modes:(1) to achieve the social optimum with respect to travel time over all the drivers in the system or (2) to optimize individual travel times. We evaluate the performance of this system using 10,000+ taxis trips and show that on average our approach improves the total travel time by 15%.

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Section: A Related Workmentioning

confidence: 99%

Congestion-aware Traffic Routing System using sensor data

Aslam

Lim²,

Rus³

2012

2012 15th International IEEE Conference on Intelligent Transportation Systems

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“…Data mules are mobile nodes that buffer and carry data from one place in the network to another. The CarTel project [97] uses vehicles both as probes to collect data about travel times and as data mules to deliver information to the system's central server.…”

Section: Traffic Monitoring In Vanetmentioning

confidence: 99%

Friend: A cyber-physical system for traffic flow related information aggregation and dissemination

El-Tawab

Olariu

Almalag

2012

2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)

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A cyber-physical system for traffic Flow-Related Information aggrEgatioN and Dissemination. By integrating resources and capabilities at the nexus between the cyber and physical worlds, FRIEND will contribute to aggregating traffic flow data collected by the huge fleet of vehicles on our roads into a comprehensive, near real-time synopsis of traffic flow conditions. We anticipate providing drivers with a meaningful, color-coded, at-a-glance view of flow conditions ahead, alerting them to congested traffic.FRIEND can be used to provide accurate information about traffic flow and can be used to propagate this information. The workhorse of FRIEND is the ubiquitous lane delimiters (a.k.a. cat's eyes) on our roadways that, at the moment, are used simply as dumb reflectors.Our main vision is that by endowing cat's eyes with a modest power source, detection and communication capabilities they will play an important role in collecting, aggregating and disseminating traffic flow conditions to the driving public. We envision the cat's eyes system to be supplemented by road-side units (RSU) deployed at regular intervals (e.g. every kilometer or so). The RSUs placed on opposite sides of the roadway constitute a logical unit and are connected by optical fiber under the median. Unlike inductive loop detectors, adjacent RSUs along the roadway are not connected with each other, thus avoiding the huge cost of optical fiber. Each RSU contains a GPS device (for time synchronization), an active Radio Frequency Identification (RFID) tag for communication with passing cars, a radio transceiver for RSU to RSU communication and a laptop-class computing device.The physical components of FRIEND collect traffic flow-related data from passing vehicles. The collected data is used by FRIEND's inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic flow-related information along the roadway. The second contribution of this thesis is the development of an incident classification and detection algorithm that can be used to classify different types of traffic incident. Then, it can notify the necessary target of the incident. We also compare our incident detection technique with other VANET techniques.Our third contribution is a novel strategy for information dissemination on highways. First, we aim to prevent secondary accidents. Second, we notify drivers far away from the accident of an expected delay that gives them the option to continue or exit before reaching the incident location. A new mechanism tracks the source of the incident while notifying drivers away from the accident. The more time the incident stays, the further the information needs to be propagated. Furthermore, the denser the traffic, the faster it will backup. In high density highways, an incident may form a backup of vehicles faster than low density highways. In order to satisfy this point, we need to propagate information as a function of density and time.iv

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“…VSN is a network of mobile sensors equipped on vehicles, such as taxis and buses [3,[7][8][9],which can be used for urban sensing, such as traffic monitoring [10,11]. VSNs facilitate collection of surveillance data over a wider area than the fixed infrastructure [6,12].…”

Section: Related Workmentioning

confidence: 99%

Towards Effective Bus Lane Monitoring Using Camera Sensors

Li¹,

Yu²,

He³

2011

WSN

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City administrators need to guarantee bus priority in urban public transportation. Building large-scale dedicated bus lanes is a cost-effective solution but it suffers from illegal utilization of dedicated bus lines by other non-permitted vehicles. In general, two systems can be utilized for bus lane monitoring: road-side system and bus mounted system. Although the former one has the advantage in terms of larger surveillance coverage, the investment cost makes it less feasible because of scalability issue. In this paper, we focus on bus mounted system to improve surveillance coverage without additional infrastructure cost. We introduce DoubleChecking, a cooperative violator identification scheme that can accurately pick out those non-permitted vehicles or violators. DoubleChecking is designed to improve the surveillance coverage of bus mounted system by using communications/cooperation between mounted camera sensors and existing camera sensors around intersections. Through theoretical analysis and simulation results, we show that DoubleChecking yields good performance for violator identification.

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CarTel

Cited by 795 publications

References 43 publications

Congestion-aware Traffic Routing System using sensor data

Congestion-aware Traffic Routing System using sensor data

Friend: A cyber-physical system for traffic flow related information aggregation and dissemination

Towards Effective Bus Lane Monitoring Using Camera Sensors

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