scholarly journals Real-time multiple model joint estimation for an urban traffic junction subject to jump dynamics

2020 ◽  
Vol 53 (2) ◽  
pp. 14984-14989
Author(s):  
Luana Chetcuti Zammit ◽  
Simon G. Fabri ◽  
Kenneth Scerri
Keyword(s):  
Real Time ◽  
Urban Traffic ◽  
Joint Estimation ◽  
Multiple Model ◽  
Jump Dynamics

PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Rusmadi Suyuti
Keyword(s):  
Information System ◽  
Real Time ◽  
Travel Demand ◽  
Urban Traffic ◽  
Road User ◽  
Traffic Information ◽  
Estimation Methods ◽  
Traffic Counts ◽  
Real Time Traffic ◽  
Demand Models

Traffic information condition is a very useful  information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.  

JOINT ESTIMATION OF THE TRANSMISSIBILITY AND SEVERITY OF EBOLA VIRUS DISEASE IN REAL TIME

2017 ◽  
Vol 25 (04) ◽  
pp. 587-603 ◽  
Author(s):  
YUSUKE ASAI ◽  
HIROSHI NISHIURA
Keyword(s):  
Real Time ◽  
Ebola Virus ◽  
Virus Disease ◽  
Critical Role ◽  
Estimation Method ◽  
Case Fatality ◽  
Ascertainment Bias ◽  
Joint Estimation ◽  
Ebola Virus Disease ◽  
Strong Impact

The effective reproduction number [Formula: see text], the average number of secondary cases that are generated by a single primary case at calendar time [Formula: see text], plays a critical role in interpreting the temporal transmission dynamics of an infectious disease epidemic, while the case fatality risk (CFR) is an indispensable measure of the severity of disease. In many instances, [Formula: see text] is estimated using the reported number of cases (i.e., the incidence data), but such report often does not arrive on time, and moreover, the rate of diagnosis could change as a function of time, especially if we handle diseases that involve substantial number of asymptomatic and mild infections and large outbreaks that go beyond the local capacity of reporting. In addition, CFR is well known to be prone to ascertainment bias, often erroneously overestimated. In this paper, we propose a joint estimation method of [Formula: see text] and CFR of Ebola virus disease (EVD), analyzing the early epidemic data of EVD from March to October 2014 and addressing the ascertainment bias in real time. To assess the reliability of the proposed method, coverage probabilities were computed. When ascertainment effort plays a role in interpreting the epidemiological dynamics, it is useful to analyze not only reported (confirmed or suspected) cases, but also the temporal distribution of deceased individuals to avoid any strong impact of time dependent changes in diagnosis and reporting.

Methodology to Increase Flexibility in Inter-Region Flow Control for Urban Traffic

2021 ◽  
pp. 036119812199742
Author(s):  
Sunghoon Kim ◽  
Monica Menendez ◽  
Hwasoo Yeo
Keyword(s):  
Flow Control ◽  
Real Time ◽  
Urban Traffic ◽  
Test Results ◽  
Flow Restriction ◽  
Region Flow ◽  
The Subject ◽  
Negative Impacts ◽  
Transfer Flow ◽  
Supply Level

Perimeter control is used to regulate transfer flows between urban regions. The greedy control (GC) method takes either the minimum or the maximum for the control inputs. Although it has the advantage of simplicity for real-time feasibility, a few existing studies have shown that it can sometimes have negative impacts because of unnecessary transfer flow restrictions. To reduce unnecessary restrictions, this study provides a method that gives flexibility to ease the strict conditions of the conventional GC. First, we propose a modification as a way of granting exceptions to the flow restriction under specific conditions. Second, we develop an algorithm to determine the threshold dynamically for accepting the exception, by comparing the possible outflow loss of the subject region and the possible outflow gain of its neighboring regions. The test results show that this flexible greedy control can handle the balance between the transfer demands and the greed of regions for securing the supply level, while increasing the performance in both vehicle hours traveled and trip completion.

Real-Time Parametric Modeling and Estimation of Urban Traffic Junctions

2019 ◽  
Vol 20 (12) ◽  
pp. 4579-4589 ◽  
Author(s):  
Luana Chetcuti Zammit ◽  
Simon G. Fabri ◽  
Kenneth Scerri
Keyword(s):  
Real Time ◽  
Parametric Modeling ◽  
Urban Traffic

scholarly journals Real‐time automatic helmet detection of motorcyclists in urban traffic using improved YOLOv5 detector

2021 ◽  
Author(s):  
Wei Jia ◽  
Shiquan Xu ◽  
Zhen Liang ◽  
Yang Zhao ◽  
Hai Min ◽  
...  
Keyword(s):  
Real Time ◽  
Urban Traffic

scholarly journals Real-time urban regional route planning model for connected vehicles based on V2X communication

2020 ◽  
Vol 13 (1) ◽  
pp. 517-538 ◽  
Author(s):  
Pangwei Wang ◽  
Hui Deng ◽  
Juan Zhang ◽  
Mingfang Zhang
Keyword(s):  
Land Use ◽  
Travel Time ◽  
Real Time ◽  
Land Use Planning ◽  
Route Planning ◽  
Urban Traffic ◽  
Urban Transport ◽  
Connected Vehicles ◽  
Planning Model ◽  
Optimal Route

Advancement in the novel technology of connected vehicles has presented opportunities and challenges for smart urban transport and land use. To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper. First, considering the traffic signal timing and phase information collected by V2X, road section resistance values are calculated dynamically based on real-time vehicular driving data. Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. Finally, we design the test scenario with different traffic saturation levels and collect 150 sets of data to analyze the feasibility of the proposed method. The numerical results have shown that the average travel times calculated by the proposed optimal route are 8.97 seconds, 12.54 seconds, and 21.85 seconds, which are much shorter than the results of traditional navigation routes. This proposed model can be further applied to the whole urban traffic network and contribute to a greater transport and land-use efficiency in the future.

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