Effects of Lanes Occupied on Urban Road Traffic Capacity

2014 ◽  
Vol 926-930 ◽  
pp. 3798-3801
Author(s):  
Zhi Wei Yang
Keyword(s):  
Traffic Flow ◽  
Road Traffic ◽  
Flow Speed ◽  
Urban Traffic ◽  
Correction Coefficient ◽  
Dynamic Changes ◽  
Traffic Jam ◽  
The Road ◽  
Discharge Capacitance ◽  
Traffic Capacity

The article is research on the influence of urban lane occupied for the road traffic capacity. Under the condition that the density of urban traffic flow is big, and it‘s successional, we consider the quantity of vehicle is continuous. Through analyzing the dynamic changes of the road traffic capacity and its influencing factors after accidents, we can get reasonable suggestions of reducing the length of traffic jam. First we establish a flow-speed-density model to describe the dynamic changes of the road traffic capacity. Then we can compare the traffic flow to the electric current according to its continuity. So the upstream traffic flow and the traffic capacity of the accident cross section are equal to the charging current and the discharging current. And the vehicle queue is translated to the voltage of the charge-discharge capacitance. We can get the length of the vehicle queue by the formula of the capacitance voltage approximately. Finally the correction coefficient is introduced. In conclusion, the road traffic capacity is depended on the distance from the upstream intersection and the lane that the accident happened on and so on. Meanwhile, if we don’t solve the accident timely, the length will rise sharply. It will cause serious traffic jam. So we suggest relevant departments timely deal with the accident, evacuate the traffic, and prompt drivers to change lanes in advance.

scholarly journals MTCS: A Method of Analyzing the Traffic Capacity of Urban Bus Lane Based on Vissim Simulation

2021 ◽  
Author(s):  
Hongtao Yuan ◽  
Huizhen Zhang ◽  
Minglei Liu ◽  
Cheng Wang ◽  
Yubiao Pan ◽  
...  
Keyword(s):  
Simulation Model ◽  
Traffic Flow ◽  
Public Transport ◽  
Empirical Formula ◽  
Road Traffic ◽  
The Road ◽  
Traffic Capacity ◽  
Urban Public Transport ◽  
Bus Lane ◽  
Urban Bus

Abstract As an effective method of improving the attractiveness of urban public transport and alleviating urban traffic congestion, bus lanes play an important role in the urban public transport system. The research on the capacity of bus lanes is conducive to improve the operation efficiency of urban bus roads and improve the service level of urban public transport. To obtain the maximum capacity of the bus lane, on one hand, the empirical formula can be used for theoretical calculation, and on the other hand, the simulation model can be established for analysis and verification. Based on the idea of simulation, a method using Vissim is proposed, called MTCS (Minimum Traffic Capacity Substitution Method). The method divides the bus lane into different sections by intersections and stops, establishes simulation model of the bus lane to calculate the traffic capacity of each section such as vehicle speed and flow and select the minimum traffic capacity of the sections as the traffic capacity of the bus lane, which is verified by using the road saturation. The simulation process uses the actual travel speed and traffic flow of the bus lane as evaluation indicators, with the aim of maximizing the road traffic flow while the actual speed of vehicles on the road is close to the desired speed, thus achieving the desired road traffic state. To verify and improve the effectiveness of the method, its analysis results are compared with the empirical formula, and various methods of enhancing traffic capacity are quantitatively simulated. The parameters of the simulation model are set by the actual bus lane example, and the experimental results show that by the methods of modifying the stop-station mode and the signal-lamp cycle, 10% and 14% improvements can be achieved, respectively. This has a good reference value for the construction of bus lanes and the adjustment of road facilities.

scholarly journals Data-driven profiling of traffic flow with varying road conditions

2019 ◽  
pp. 149-157 ◽  
Author(s):  
O K Golovnin
Keyword(s):  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Weather Conditions ◽  
Flow Speed ◽  
Data Driven ◽  
The Road ◽  
Data Driven Approach ◽  
Traffic Flow Characteristics ◽  
The City

The article describes the road, institutional and weather conditions that affect the traffic flow. I proposed a method for traffic flow profiling using a data-driven approach. The method operates with macroscopic traffic flow characteristics and detailed data of road conditions. The article presents the results of traffic flow speed and intensity profiling taking into account weather conditions. The study used road traffic and conditions data for the city of Aarhus, Denmark. The results showed that the method is effective for traffic flow forecasting due to varying road conditions.

scholarly journals A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Yiliang Zeng ◽  
Jinhui Lan ◽  
Bin Ran ◽  
Yaoliang Jiang
Keyword(s):  
Traffic Flow ◽  
Incomplete Data ◽  
Road Traffic ◽  
Flow Speed ◽  
State Assessment ◽  
Assessment System ◽  
Flow Data ◽  
The Road ◽  
Traffic State ◽  
Probe Vehicle

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

scholarly journals Evaluating Model of Road Traffic in Open Housing Estate Based on Cellular Automaton

2017 ◽  
Vol 6 (3) ◽  
pp. 99
Author(s):  
Jialin Wen ◽  
Min Zou
Keyword(s):  
Traffic Flow ◽  
Motor Vehicle ◽  
Road Traffic ◽  
Comprehensive Evaluation ◽  
Residential Area ◽  
Urban Traffic ◽  
The Road ◽  
Security Issues ◽  
Trunk Road ◽  
Driving Model

It has been referred in document issued by the State Council recently that China will promote the block system gradually in the future, no more enclosed residential compounds will be built in principle, and existing residential and corporate will open up step by step as well. The proposal of open area quickly aroused a heated discussion in the whole society. In addition to the most basic security issues, it is one of the main topics that whether the open district can really optimize the road network structure and improve the traffic in the end.Based on the cellular automata model and the actual situation, this paper simulates the traffic flow around the residential area, establishes motor vehicle driving model and makes a comprehensive evaluation of the surrounding road traffic after the opening of different types of residential area. According to the result of the index, it shows that three structures of residential area can relieve the burden of urban traffic flow while one structure of residential area that will aggravate the burden of urban traffic flow. Finally, the paper comes to the conclusion that excessive traffic flow of the trunk road which has adverse effect on road traffic.

scholarly journals GIS-based analysis of urban traffic model: Case study in Beijing

2021 ◽  
Vol 268 ◽  
pp. 01056
Author(s):  
Yongkai Liang ◽  
Jingyuan Li ◽  
Hai Liu
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Low Frequency ◽  
Flow Speed ◽  
Urban Traffic ◽  
Model Case ◽  
Sudden Rise ◽  
Cubic Polynomial

Taking the traffic flow characteristics of Beijing's entire road network as the object, and using the low-frequency traffic big data of GIS (Geographic Information System), the roads of the whole road network are divided into four road grades, and the traffic flow-speed models are constructed respectively. In view of the deviation of the model calculation caused by the sudden rise and fall of the traveling vehicle at night, the flow of the traffic flow model is corrected by cubic polynomial fitting, and the mathematical model is compared, calibrated and verified. Focus on analyzing the influence of roads of different grades and seasons on the characteristics of road traffic flow, and provide data support for further research on intelligent transportation.

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

A Traffic Capacity Model of Lane Occupation

2014 ◽  
Vol 599-601 ◽  
pp. 2083-2087
Author(s):  
Yi Xuan He
Keyword(s):  
Traffic Flow ◽  
Queue Length ◽  
Production Condition ◽  
Modern Society ◽  
Traffic Jam ◽  
Traffic Flow Theory ◽  
Related Data ◽  
Traffic Capacity ◽  
Capacity Model ◽  
Big City

In modern society, traffic jam has already become a major problem which curbs the development of big city. And lane occupation is an important reason why traffic jam happens. After studying on the production condition, time and queue length of traffic jam after lane occupation happens, we propose a model based on famous traffic flow theory and we use related data to verify the rightness of our model. Result shows that our model can predict the development of traffic jam caused by lane occupation

scholarly journals ANALISIS KAPASITAS DAN KINERJA LALU LINTAS PADA RUAS JALAN JENDERAL SUDIRMAN JAKARTA

2021 ◽  
Vol 4 (1) ◽  
pp. 95
Author(s):  
Sarah Haryati ◽  
Najid Najid
Keyword(s):  
Flow Speed ◽  
Traffic Volume ◽  
Capital City ◽  
Free Flow ◽  
Degree Of Saturation ◽  
Level Of Service ◽  
Traffic Jam ◽  
Traffic Capacity ◽  
Traffic Behavior

Jakarta as the capital city of Indonesia is the center of economy, culture, and politics. Jenderal Sudirman street always crowded with passing vehicles, traffic snarls up everyday. The causes of these traffic jam is an increase the number of vehicles and cause a change in traffic behavior. Theoretically there is a fudamental relationship between flow, speed, & density, so the purpose of these research are to analyze and evaluate performance of traffic capacity in various conditions based on Manual Kapasitas Jalan Indonesia 1997 and Greenshields model. Conclusion of the analysis are, after compared with traffic volume, capacity and speed based on MKJI are 3.127,6 pcu/hour and 55,7 km/hour, but the capacity of the model are selected because it’s largest, for sudirman – thamrin it’s 8.272,5 pcu/hour, and for thamrin – sudirman it’s 8.067,9 pcu/hour, While the calculation of free flow for sudirman – thamrin it’s 41.2 km/hour the lowest occurs in  evening, and for thamrin – sudirman it’s 43,9 km/hour the lowest occurs in  afternoon. The largest capacity it’s used for the next analysis, the next analysis are calculating degree of saturation and level of service, the result  shows that the roads are at C and D.ABSTRAKJakarta ibu kota negara Indonesia merupakan pusat ekonomi, budaya, dan politik. Sebuah jalan di Jakarta yaitu Jenderal Sudirman selalu dipadati kendaraan. Lalu lintas di Jalan Jenderal Sudirman setiap hari mengalami kemacetan penyebabnya adalah peningkatan jumlah kendaraan di dalam kota dan menyebabkan perubahan perilaku lalu lintas, secara teoritis terdapat hubungan yang mendasar antara arus, kecepatan, dan kepadatan. Tujuan penelitian ini adalah untuk menganalisis, mengevaluasi kinerja dan kapasitas lalu lintas di berbagai macam kondisi, tentu berdasarkan pedoman Manual Kapasitas Jalan Indonesia dan kapasitas model Greenshields. Dari hasil analisis hasil perhitungan kapasitas dan kecepatan arus bebas berdasarkan MKJI sebesar 3.127,6 smp/jam dan 55,7 km/jam setelah dibandingkan dengan volume lalu lintas dipilih kapasitas model yang terbesar yaitu sebesar 8.272,5 smp/jam pada sudirman - thamrin & 8.067,9 smp/jam pada thamrin - sudirman, dan hasil perhitungan kecepatan arus bebas terendah sebesar 41,2 km/jam di sore hari untuk sudirman - thamrin, sebaliknya thamrin - sudirman terendah sebesar 43,9 km/jam di siang hari. Gunakan kapasitas yang terpilih tersebut untuk analisis berikutnya yaitu perhitungan ratio perbandingan arus dan kapasitas (DS) dan tingkat pelayanan yan berada pada tingkat pelayanan huruf C dan D di kedua arahnya.

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