scholarly journals CTM Based Real-Time Queue Length Estimation at Signalized Intersection

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Shuzhi Zhao ◽  
Shidong Liang ◽  
Huasheng Liu ◽  
Minghui Ma
Keyword(s):  
Real Time ◽  
Queue Length ◽  
Urban Traffic ◽  
Urban Transport ◽  
Signalized Intersection ◽  
Transmission Model ◽  
Time Interval ◽  
Short Time Interval ◽  
Cell Transmission Model ◽  
The Road

Queue length is an important index of the efficiency of urban transport system. The traditional approaches seem insufficient for the estimation of the queue length when the traffic state fluctuates greatly. In this paper, the problem is solved by introducing the Cell Transmission Model, a macroscopic traffic flow, to describe the vehicles aggregation and discharging process at a signalized intersection. To apply the model to urban traffic appropriately, some of its rules were improved accordingly. Besides, we can estimate the density of each cell of the road in a short time interval. We, first, identify the cell, where the tail of the queue is located. Then, we calculate the exact location of the rear of the queue. The models are evaluated by comparing the estimated maximum queue length and average queue length with the results of simulation calibrated by field data and testing of queue tail trajectories. The results show that the proposed model can estimate the maximum and average queue length, as well as the real-time queue length with satisfactory accuracy.

scholarly journals Improving the Stochastic Model of Ionospheric Delays for BDS Long-Range Real-Time Kinematic Positioning

2021 ◽  
Vol 13 (14) ◽  
pp. 2739
Author(s):  
Huizhong Zhu ◽  
Jun Li ◽  
Longjiang Tang ◽  
Maorong Ge ◽  
Aigong Xu
Keyword(s):  
Real Time ◽  
Long Range ◽  
Ionospheric Delay ◽  
Time Interval ◽  
Short Time Interval ◽  
Dual Frequency ◽  
Triple Frequency ◽  
Ambiguity Fixing ◽  
Power Spectral ◽  
Observation Noise

Although ionosphere-free (IF) combination is usually employed in long-range precise positioning, in order to employ the knowledge of the spatiotemporal ionospheric delays variations and avoid the difficulty in choosing the IF combinations in case of triple-frequency data processing, using uncombined observations with proper ionospheric constraints is more beneficial. Yet, determining the appropriate power spectral density (PSD) of ionospheric delays is one of the most important issues in the uncombined processing, as the empirical methods cannot consider the actual ionosphere activities. The ionospheric delays derived from actual dual-frequency phase observations contain not only the real-time ionospheric delays variations, but also the observation noise which could be much larger than ionospheric delays changes over a very short time interval, so that the statistics of the ionospheric delays cannot be retrieved properly. Fortunately, the ionospheric delays variations and the observation noise behave in different ways, i.e., can be represented by random-walk and white noise process, respectively, so that they can be separated statistically. In this paper, we proposed an approach to determine the PSD of ionospheric delays for each satellite in real-time by denoising the ionospheric delay observations. Based on the relationship between the PSD, observation noise and the ionospheric observations, several aspects impacting the PSD calculation are investigated numerically and the optimal values are suggested. The proposed approach with the suggested optimal parameters is applied to the processing of three long-range baselines of 103 km, 175 km and 200 km with triple-frequency BDS data in both static and kinematic mode. The improvement in the first ambiguity fixing time (FAFT), the positioning accuracy and the estimated ionospheric delays are analysed and compared with that using empirical PSD. The results show that the FAFT can be shortened by at least 8% compared with using a unique empirical PSD for all satellites although it is even fine-tuned according to the actual observations and improved by 34% compared with that using PSD derived from ionospheric delay observations without denoising. Finally, the positioning performance of BDS three-frequency observations shows that the averaged FAFT is 226 s and 270 s, and the positioning accuracies after ambiguity fixing are 1 cm, 1 cm and 3 cm in the East, North and Up directions for static and 3 cm, 3 cm and 6 cm for kinematic mode, respectively.

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.

scholarly journals Lane-Based Traffic Signal Simulation and Optimization for Preventing Overflow

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1368
Author(s):  
Chi-kwong Wong ◽  
Yiu-yin Lee
Keyword(s):  
Traffic Signal ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Design Constraint ◽  
Traffic Demand ◽  
Cycle Times ◽  
Simulation And Optimization ◽  
The Road ◽  
Proposed Model ◽  
Lane Based

In the lane-based signal optimization model, permitted turn directions in the form of lane markings that guide road users to turn at an intersection are optimized with traffic signal settings. The spatial queue requirements of approach lanes should be considered to avoid the overdesigning of the cycle, effective red, and effective green durations. The point-queue system employed in the conventional modeling approach is unrealistic in many practical situations. Overflow conditions cannot be modeled accurately, while vehicle queues are accumulated that block back upstream intersections. In a previous study, a method was developed to manually refine the traffic signal settings by using the results of lane-based optimization. However, the method was inefficient. In the present study, new design constraint sets are proposed to control the effective red and effective green durations, such that traffic enters the road lanes without overflow. The reduced cycle times discharge the accumulated vehicles more frequently. Moreover, queue spillback and residual queues can be avoided. One of the most complicated four-arm intersections in Hong Kong is considered as a case study for demonstration. The existing traffic signal settings are ineffective for controlling the observed traffic demand, and overflow occurs in short lanes. The optimized traffic signal settings applied to the proposed optimization algorithm effectively avoided traffic overflow. The resultant queuing dynamics are simulated using TRANSYT 15 Cell Transmission Model (CTM) to verify the proposed model. The model application is extended to handle the difficult residual queue scenario. It is found that the proposed model can optimize the traffic signal settings in cases where there are short initial residual queues.

scholarly journals LONG-TERM TRACKING OF A SPECIFIC VEHICLE USING AIRBORNE OPTICAL CAMERA SYSTEMS

2016 ◽  
Vol XLI-B2 ◽  
pp. 521-525
Author(s):  
F. Kurz ◽  
D. Rosenbaum ◽  
H. Runge ◽  
D. Cerra ◽  
G. Mattyus ◽  
...  
Keyword(s):  
Low Cost ◽  
Basic Density ◽  
Urban Traffic ◽  
Frame Rate ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Good Correspondence ◽  
Congested Traffic ◽  
Camera Systems

In this paper we present two low cost, airborne sensor systems capable of long-term vehicle tracking. Based on the properties of the sensors, a method for automatic real-time, long-term tracking of individual vehicles is presented. This combines the detection and tracking of the vehicle in low frame rate image sequences and applies the lagged Cell Transmission Model (CTM) to handle longer tracking outages occurring in complex traffic situations, e.g. tunnels. The CTM model uses the traffic conditions in the proximities of the target vehicle and estimates its motion to predict the position where it reappears. <br><br> The method is validated on an airborne image sequence acquired from a helicopter. Several reference vehicles are tracked within a range of <i>500m</i> in a complex urban traffic situation. An artificial tracking outage of <i>240m</i> is simulated, which is handled by the CTM. For this, all the vehicles in the close proximity are automatically detected and tracked to estimate the basic density-flow relations of the CTM model. Finally, the real and simulated trajectories of the reference vehicles in the outage are compared showing good correspondence also in congested traffic situations.

A wave-oriented variable cell transmission model in an urban road

2021 ◽  
Author(s):  
Zeyu Shi ◽  
Yangzhou Chen ◽  
Jingyuan Zhan ◽  
Xiangyu Guo ◽  
Shuke An
Keyword(s):  
Traffic Flow ◽  
Urban Traffic ◽  
Transmission Model ◽  
Hybrid Automata ◽  
State Variables ◽  
Cell Transmission Model ◽  
Fundamental Diagram ◽  
Influence Area ◽  
Cell Transmission ◽  
The Waves

To describe the dynamics of traffic flow in the urban link accurately, the waves which generate at intersections are adopted as the influencing factors of traffic flow. Based on the urban traffic waves, a wave-oriented variable cell transmission model (WVCTM) is proposed to illustrate the urban traffic flow. In this model, the average density and length are the state variables. The cells are divided by traffic waves. The upstream cell is the influence area of the waves at the upstream intersection, the downstream cell is the influence area of the waves at the downstream intersection, and the rest is the mediate cell. Consistent with the fundamental diagram and the cell division, the traffic states of urban links are divided into six modes. The variation of modes is explained by hybrid automata. Finally, an experiment is designed to verify the feasibility of WVCTM. The data in the experiment come from the actual scene. Compared with the cell transmission model (CTM) and variable-length CTM (VCTM), WVCTM possesses the valuable performance to predict the traffic states. Likewise, it is rational that WVCTM can correctly illustrate the urban traffic flow.

Urban Traffic Jam Simulation Based on the Cell Transmission Model

2008 ◽  
Vol 11 (1) ◽  
pp. 43-64 ◽  
Author(s):  
Jiancheng Long ◽  
Ziyou Gao ◽  
Xiaomei Zhao ◽  
Aiping Lian ◽  
Penina Orenstein
Keyword(s):  
Urban Traffic ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Jam ◽  
Simulation Based ◽  
Cell Transmission
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