Prediction of traveller information and route choice based on real-time estimated traffic state

Ahmed, Afzal; Ngoduy, Dong; Watling, David

doi:10.1080/21680566.2015.1052110

Cited by 9 publications

(15 citation statements)

References 50 publications

(71 reference statements)

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“…Reference [8] applied the CTM to simulate the formation and dissipation of congestion in a two-way rectangular grid network. Reference [18] developed a traffic state estimation method by combining the CTM and extended Kalman filter (EKF) recursive algorithm. The CTM is used to predict traffic density, and the EKF recursive algorithm is used to deal with empirical traffic data from sensors.…”

Section: A Modeling Congestion Propagations Based On Simulationsmentioning

confidence: 99%

A Spatiotemporal Apriori Approach to Capture Dynamic Associations of Regional Traffic Congestion

2020

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Due to the interactions among adjacent roads in urban road networks, traffic congestion gradually propagates to neigboring roads, resulting in regional congestion. To develop advanced regional traffic control strategies, it is necessary to clearly understand the characteristics of regional congestion evolution. To this end, this paper proposes a data-driven approach to mine the spatiotemporal associations of regional traffic congestion. By introducing both time and space attributes, the intra-transaction spatiotemporal Apriori (IntraT-ST-Apriori) algorithm is developed to address the static features of regional traffic congestion; while the inter-transaction spatiotemporal Apriori (InterT-ST-Apriori) algorithm is developed to capture the dynamic characteristics of regional traffic congestion. Case studies are carried out for the urban road network in Tianjin, China, based on empirical data. The results indicate that the Intra-ST-Apriori algorithm can excavate the underlying associations of regional traffic congestion. Furthermore, the congestion propagation trajectories can be clearly revealed based on the InterT-ST-Apriori algorithm. It is expected that the proposed approach can support the regional traffic management and control, significantly relieving traffic congestion.

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Section: A Modeling Congestion Propagations Based On Simulationsmentioning

confidence: 99%

A Spatiotemporal Apriori Approach to Capture Dynamic Associations of Regional Traffic Congestion

2020

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“…EKF can linearize the nonlinear dynamics and assume that the process and noise obey Gaussian distribution. In order to achieve the optimal path selection of the network, the bandwidth and round-trip delay of each path were estimated by using EKF in [36][37][38]. In [39], Cavusoglu B et al proposed the use of EKF and unknown input streams in a non-linear system to adaptively achieve prediction of available bandwidth [40], and proposed an EKF-based bandwidth estimation (EBE) scheme.…”

Section: Research Background and Related Workmentioning

confidence: 99%

Research of Wireless Congestion Control Algorithm Based on EKF

Wang¹,

Tang²,

Hong³

2020

Symmetry

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The random variation of bandwidth in wireless networks causes some significant challenges to the congestion control protocols based on bandwidth estimation. In this paper, a wireless congestion control scheme based on extended Kalman filtering and bandwidth (CSEKB) is proposed. The CSEKB can effectively perceive the bandwidth oscillation of wireless networks and distinguish the type of packet loss by establishing a noise perception factor. According to the congestion factor, the congestion control parameters are adjusted to correspondingly improve the performance of the wireless network. Moreover, the variation trend of the size of the congestion window presents a law of similar normal distribution curve, which has a certain degree of local symmetry. The CSEKB was implemented in Network simulator 3 (NS3) and compared with TCP Westwood (TCPW), CUBIC, and extended Kalman filtering-based bandwidth estimation (EBE). Through extensive simulation studies, the proposed CSEKB demonstrated the significant performance in wireless networks. First, the CSEKB can achieve congestion control based on the accurate prediction of available bandwidth, and improve average throughput and link utilization. In addition, the CSEKB has good fairness and friendliness compared with several other well-known congestion control methods.

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“…Ngoduy [18] developed a technique for estimating the real-time traffic state for a section of freeway using a particle filtering algorithm. CTM-EKF (Cell Transmission Model-Extended Kalman Filter-) based technique has been applied for real-time traffic state estimation for traffic network disrupted with an incident [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Incident Detection and Capacity Estimation Using Loop Detector Data

Rizvi

Ahmed

Shen

2020

Journal of Advanced Transportation

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Given the fact that the existing literature lacks the real-time estimation of road capacity and incident location using data from inductance loop detectors, a data-driven framework is proposed in this study for real-time incident detection, as well as road capacity and incident location estimation. The proposed algorithm for incident detection is developed based on the variation in traffic flow parameters acquired from inductance loop detectors. Threshold values of speed and occupancy are determined for incident detection based on the PeMS database. The detection of the incident is followed by the real-time road capacity and incident location estimation using a Cell Transmission Model (CTM) based approach. The data of several incidents were downloaded from PeMS and used for the development of the proposed framework presented in this study. Results show that the developed framework detects the incident and estimates the reduced capacity accurately. The location of the incident is estimated with an overall accuracy of 92.5%. The performance of the proposed framework can be further improved by incorporating the effect of the on-ramps, off-ramps, and high-occupancy lanes, as well as by modeling each lane separately.

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Prediction of traveller information and route choice based on real-time estimated traffic state

Cited by 9 publications

References 50 publications

A Spatiotemporal Apriori Approach to Capture Dynamic Associations of Regional Traffic Congestion

A Spatiotemporal Apriori Approach to Capture Dynamic Associations of Regional Traffic Congestion

Research of Wireless Congestion Control Algorithm Based on EKF

Real-Time Incident Detection and Capacity Estimation Using Loop Detector Data

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