An optimization‐based traffic diversion model during construction closures

2019 ◽  
Vol 34 (12) ◽  
pp. 1087-1099
Author(s):  
Arezoo Memarian ◽  
Jay M. Rosenberger ◽  
Stephen P. Mattingly ◽  
James C. Williams ◽  
Hossein Hashemi
Keyword(s):  
Traffic Diversion

Traffic Diversion to Toll Roads

1957 ◽  
Vol 122 (1) ◽  
pp. 883-902
Author(s):  
John T. Lynch
Keyword(s):  
Toll Roads ◽  
Traffic Diversion

Real-time demand-based traffic diversion

2020 ◽  
pp. 115-145
Keyword(s):  
Real Time ◽  
Traffic Diversion

Traffic diversion due to motorway tolls

1999 ◽  
Author(s):  
M.G.H. Bell
Keyword(s):  
Traffic Diversion

Impacts on Traffic Diversion Rates of Changed Message on Changeable Message Sign

2008 ◽  
Vol 2047 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Simon Foo ◽  
Baher Abdulhai ◽  
Fred L. Hall
Keyword(s):  
Traffic Diversion

Evaluation of Arterial and Freeway Interaction for Determining the Feasibility of Traffic Diversion

2011 ◽  
Vol 137 (8) ◽  
pp. 509-519 ◽  
Author(s):  
Yao-Jan Wu ◽  
Mark E. Hallenbeck ◽  
Yinhai Wang ◽  
Kari Edison Watkins
Keyword(s):  
Traffic Diversion

scholarly journals Crowdsourcing-Driven Road Condition Marking and Traffic Diversion System

2019 ◽  
Author(s):  
MING-FEI QIN ◽  
JING-WEI ZHANG ◽  
QIU-YU CHEN ◽  
CAI-QING YAO ◽  
QIONG WANG ◽  
...  
Keyword(s):  
Road Condition ◽  
Traffic Diversion

scholarly journals Highway Travel Time Prediction of Segments Based on ANPR Data considering Traffic Diversion

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Wenjun Du ◽  
Bo Sun ◽  
Jiating Kuai ◽  
Jiemin Xie ◽  
Jie Yu ◽  
...  
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
State Of The Art ◽  
The State ◽  
Attention Mechanism ◽  
Critical Parameters ◽  
Depth Information ◽  
Highway Traffic ◽  
Residual Network ◽  
Traffic Diversion

Travel time is one of the most critical parameters in proactive traffic management and the deployment of advanced traveler information systems. This paper proposes a hybrid model named LSTM-CNN for predicting the travel time of highways by integrating the long short-term memory (LSTM) and the convolutional neural networks (CNNs) with the attention mechanism and the residual network. The highway is divided into multiple segments by considering the traffic diversion and the relative location of automatic number plate recognition (ANPR). There are four steps in this hybrid approach. First, the average travel time of each segment in each interval is calculated from ANPR and fed into LSTM in the form of a multidimensional array. Second, the attention mechanism is adopted to combine the hidden layer of LSTM with dynamic temporal weights. Third, the residual network is introduced to increase the network depth and overcome the vanishing gradient problem, which consists of three pairs of one-dimensional convolutional layers (Conv1D) and batch normalization (BatchNorm) with the rectified linear unit (ReLU) as the activation function. Finally, a series of Conv1D layers is connected to extract features further and reduce dimensionality. The proposed LSTM-CNN approach is tested on the three-month ANPR data of a real-world 39.25 km highway with four pairs of ANPR detectors of the uplink and downlink, Zhejiang, China. The experimental results indicate that LSTM-CNN learns spatial, temporal, and depth information better than the state-of-the-art traffic forecasting models, so LSTM-CNN can predict more accurate travel time. Moreover, LSTM-CNN outperforms the state-of-the-art methods in nonrecurrent prediction, multistep-ahead prediction, and long-term prediction. LSTM-CNN is a promising model with scalability and portability for highway traffic prediction and can be further extended to improve the performance of the advanced traffic management system (ATMS) and advanced traffic information system (ATIS).

Optimizing Work-Zone Schedule with Floating Car Data Considering Traffic Diversion and Managed Lanes

2019 ◽  
Vol 145 (1) ◽  
pp. 04018076 ◽  
Author(s):  
Liuhui Zhao ◽  
Steven I. Chien ◽  
Bo Du
Keyword(s):  
Work Zone ◽  
Managed Lanes ◽  
Floating Car Data ◽  
Traffic Diversion

scholarly journals AN ECONOMIC APPRAISAL OF THE IMPACT OF TRAFFIC DIVERSION - THE N1 TOLL ROAD AND ITS ALTERNATIVE

2008 ◽  
Vol 76 (4) ◽  
pp. 652-666
Author(s):  
n.g. meyer ◽  
m. breitenbach ◽  
r.d. kekana
Keyword(s):  
Economic Appraisal ◽  
Toll Road ◽  
The Impact ◽  
Traffic Diversion
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