Application of automatic vehicle identification technology for real-time journey time estimation

Tam, Mei Lam; Lam, William H. K.

doi:10.1016/j.inffus.2010.01.002

Cited by 34 publications

(11 citation statements)

References 9 publications

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“…AVI systems have been widely used for real-time travel time estimation (23,24). Although one study by the authors used traffic data from an AVI system in a real-time traffic safety application (11), in this study data from an AVI system, real-time weather data, and roadway geometry were used to assess the safety risk on a freeway section that features mountainous terrain.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Interaction of Crash Occurrence, Mountainous Freeway Geometry, Real-Time Weather, and Traffic Data

Ahmed

Abdel-Aty

2012

Transportation Research Record

139

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This study investigated the effect of the interaction between roadway geometric features and real-time weather and traffic data on the occurrence of crashes on a mountainous freeway. The Bayesian logistic regression technique was used to link a total of 301 crash occurrences on I-70 in Colorado with the space mean speed collected in real time from an automatic vehicle identification (AVI) system and real-time weather and roadway geometry data. The results suggested that the inclusion of roadway geometrics and real-time weather with data from an AV I system in the context of active traffic management systems was essential, in particular with roadway sections characterized by mountainous terrain and adverse weather. The modeling results showed that the geometric factors were significant in the dry and the snowy seasons and that the likelihood of a crash could double during the snowy season because of the interaction between the pavement condition and steep grades. The 6-min average speed at the crash segment during the 6 to 12 min before the crash and the visibility 1 h before the crash were found to be significant during the dry season, whereas the logarithms of the coefficient of variation in speed at the crash segment during the 6 to 12 min before the crash, the visibility 1 h before the crash, as well as the precipitation 10 min before the crash were found to be significant during the snowy season. The results from the two models suggest that different active traffic management strategies should be in place during these two distinct seasons.

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Section: Introductionmentioning

confidence: 99%

Assessment of Interaction of Crash Occurrence, Mountainous Freeway Geometry, Real-Time Weather, and Traffic Data

Ahmed

Abdel-Aty

2012

Transportation Research Record

139

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“…The delay in traffic information delivery, accidents, vehicles break down and are the major reasons of traffic congestion [19]. The electronic payment system contains specific software technologies including an automatic detection system for vehicles, which detects vehicles passing through with the help of hardware equipment [20][21]; an automated vehicle categorization system that identifies and categorizes the vehicle type; a transaction processing system that records the cross-axis transaction for the user, after identifying the vehicle [7]; and a system for identifying violations and deducting unpaid tolls [22]. Alongside this software technology, electronic toll payment systems make use of various hardware technologies for the paying of tolls on the highway including RFID Units, which respond to radio signals via a RFID chip installed in a unit or label on the windshield near the rear-view mirror of the vehicle [23]; video toll systems that use aerial cameras to identify vehicles at the toll [24]; a dedicated short-circuit communication system, including a transmitter and receiver, which deducts the desired amount from the inventory, based on credit cards [25]; and the visual protection surfaces (VPS) technique that stores vehicles' coordinates and sends transaction information to toll agents through the Global Mobile Communications System [7].…”

Section: Literature Reviewmentioning

confidence: 99%

Developing a Solution for Intelligent Urban Transportation Management Using the Internet of Things

2020

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The increasing use of technologies based on Internet of Things in cars and other transportation vehicles, as well as innovations in tracking systems and spatial information systems, have created the opportunity to collect tolls on urban roads in a more intelligent, more efficient, and a wider way. Considering the cultural and infrastructure variables in different cities, different approaches have been designed for this purpose, but so far, no work has been done in this area in Tehran. Therefore, in this research, a system of hardware and software based on the Internet of things was developed based on global positioning system (GPS)/ global system for mobile communication (GSM) for automated urban tolls in Tehran, which manages the location of a user's car and manages toll payments at any given moment. In addition, in this system, considering the cultural issues in the country, the infrastructure in the metropolis of Tehran, and important issues of the city, the trespass submission system is designed in accordance with the existing surveillance cameras and an infrared-based structure was used to reduce the burden of image processing in order to improve efficiency. The data obtained from this system will have more potential than only the urban toll management.

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“…How to extend such method to the dynamic reliable path finding problems (e.g., Li et al [30]) is worthy of further investigation. (v) The proposed algorithm can be combined with some stochastic travel time estimation methods (Tam and Lam [31,32]; Chang et al [33]; Shao et al [34,35]) so as to provide a reliable route guidance system in reality. …”

Section: Conclusion and Future Studiesmentioning

confidence: 99%

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

Shen

Shao

Zhang

et al. 2017

Mathematical Problems in Engineering

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There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user's risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the -shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.

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Application of automatic vehicle identification technology for real-time journey time estimation

Cited by 34 publications

References 9 publications

Assessment of Interaction of Crash Occurrence, Mountainous Freeway Geometry, Real-Time Weather, and Traffic Data

Assessment of Interaction of Crash Occurrence, Mountainous Freeway Geometry, Real-Time Weather, and Traffic Data

Developing a Solution for Intelligent Urban Transportation Management Using the Internet of Things

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

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