scholarly journals A Proposal of Foot Over Bridge at Congested Intersection

2021 ◽  
pp. 406-413
Author(s):  
Shivani Bhoyar ◽  
Dr. B.V. Khode ◽  
Jitesh Bhoyar ◽  
Renu Upadhyay
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Heavy Traffic ◽  
Sudden Change ◽  
Short Term ◽  
Accident Rate ◽  
Continuous Increase ◽  
Moving Vehicle ◽  
Mixed Traffic Flow ◽  
Improvement Plan

The motto of this study is to suggest the best possible NMT infrastructure at the intersection having mixed traffic flow along with the heavy traffic leading towards the congestion, delay and accidents. Variety Square, Nagpur has been selected for study purpose, this square is having major landmarks contributing towards continuous increase in the traffic flow and the current infrastructure is up-to-date to meet the today's demand. It has been seen or observed that the non availability of proper NMT infrastructure leading towards the decrease in the contribution of NMT users, Which is indirectly forcing the user to use motorized transportation over NMT? This behaviour is adversely affecting the environment resulting into the increasing carbon footprint, sudden change in environment, pollution, increase in green house gases etc. It is high time now to consider the junction improvement plan as the short term improvement. So, traffic volume study is carried out at the variety square by manual count method. So, the main objective of this study is to propose the foot over bridge at variety square, Nagpur to eliminate the traffic congestion delay conflict between pedestrian and the moving vehicle and to decrease the accident rate, which will eventually increase the contribution of the NMT users by providing promising safety.

SHORT TERM TRAFFIC FLOW PREDICTION IN HETEROGENEOUS CONDITION USING ARTIFICIAL NEURAL NETWORK

Transport ◽  
2013 ◽  
Vol 30 (4) ◽  
pp. 397-405 ◽  
Author(s):  
Kranti Kumar ◽  
Manoranjan Parida ◽  
Vinod Kumar Katiyar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Volume ◽  
Flow Data ◽  
Highway Traffic ◽  
Short Term ◽  
Artificial Neural ◽  
Input Variables

Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea to avoid traffic instabilities and to homogenize traffic flow in such a way that risk of accidents is minimized and traffic flow is maximized. There is a need to predict traffic flow data for advanced traffic management and traffic information systems, which aim to influence traveller behaviour, reducing traffic congestion and improving mobility. This study applies Artificial Neural Network for short term prediction of traffic volume using past traffic data. Besides traffic volume, speed and density, the model incorporates both time and the day of the week as input variables. Model has been validated using actual rural highway traffic flow data collected through field studies. Artificial Neural Network has produced good results in this study even though speeds of each category of vehicles were considered separately as input variables.

Study on the Traffic Capacity of Expressway Based on Cellular Automata Model

2014 ◽  
Vol 701-702 ◽  
pp. 172-179
Author(s):  
Xiao Dong Xia ◽  
Lin Ling Xu
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Heavy Traffic ◽  
Accident Rate ◽  
Cellular Automata Model ◽  
Traffic Capacity ◽  
Low Load ◽  
The Right ◽  
The Relationship ◽  
Shape Changes

Based on the Nagel-Schrekenberg cellular automaton model of traffic flow, this article analyzed the influence that driving on the right side takes to the traffic flow in the condition of light and heavy traffic. With the combination of fluid dynamics and vehicle dynamics, we established the Cellular Automata model for mixed speed two-lane traffic flow on the rule driving on the right side. Then we used the AHP method to find out the large bus share rate, the number of vehicles changing lanes and the influence law of safety factors on traffic flow. We came to a conclusion that the relationship between traffic flow and load are inverted U shape changes in the low load and high load conditions, the accident rate is the maximum when the V/C (the ratio of traffic flow and the ability of corresponding section) is the minimum; with the increase of V/C, the accident rate decreased gradually.

scholarly journals Forecasting Short-Term Traffic Flow by Fuzzy Wavelet Neural Network with Parameters Optimized by Biogeography-Based Optimization Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jeng-Fung Chen ◽  
Shih-Kuei Lo ◽  
Quang Hung Do
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Mean Squared Error ◽  
Transportation Systems ◽  
Wavelet Neural Network ◽  
Percentage Error ◽  
Short Term ◽  
Fuzzy Wavelet Neural Network

Forecasting short-term traffic flow is a key task of intelligent transportation systems, which can influence the traveler behaviors and reduce traffic congestion, fuel consumption, and accident risks. This paper proposes a fuzzy wavelet neural network (FWNN) trained by improved biogeography-based optimization (BBO) algorithm for forecasting short-term traffic flow using past traffic data. The original BBO is enhanced by the ring topology and Powell’s method to advance the exploration capability and increase the convergence speed. Our presented approach combines the strengths of fuzzy logic, wavelet transform, neural network, and the heuristic algorithm to detect the trends and patterns of transportation data and thus has been successfully applied to transport forecasting. Other different forecasting methods, including ANN-based model, FWNN-based model, and WNN-based model, are also developed to validate the proposed approach. In order to make the comparisons across different methods, the performance evaluation is based on root-mean-squared error (RMSE), mean absolute percentage error (MAPE), and correlation coefficient (R). The performance indexes show that the FWNN model achieves lower RMSE and MAPE, as well as higherR, indicating that the FWNN model is a better predictor.

A new bus lane on urban expressway with no-bay bus stop

2016 ◽  
Vol 30 (03) ◽  
pp. 1550264 ◽  
Author(s):  
Zhao Tian ◽  
Limin Jia
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Rapid Development ◽  
Heavy Traffic ◽  
Transit System ◽  
Lane Changing ◽  
Public Transport System ◽  
Bus Stop ◽  
Bus Lane ◽  
Lower Ratio

The sharp increase in residents and vehicles causes heavy traffic pressure in many cities. To ease traffic congestion, it has been the common sense that we should develop public transit system. The priority of the bus appears particularly necessary with the rapid development of the public transport system. The bus lane is an important embodiment of the bus priority. Focusing on the problem of the unreasonable dedicated bus lane (DBL) under the lower ratio of buses, this paper proposed a new bus lane with limited physical length. And this bus lane can reduce the lane-changing conflict caused by the buses and cars running on roads without bus lanes. Based on the cellular automata (CA) traffic flow model and the lane-changing behavior of the vehicle including the optional lane-changing and the mandatory lane-changing, a three-lane traffic model with an isolated no-bay bus stop is proposed. The ordinary three-lane traffic without a bus lane and the cases of traffic with a DBL or the proposed bus lane are simulated, and the comparisons in the form of the fundamental diagrams are made among them. It is shown that the no-bay bus stop can act as a bottleneck on the traffic flow because of the mandatory lane-changing behavior. Under a certain ratio of the bus number to the total vehicles number, (1) the traffic with the proposed bus lane has less lane-changing conflict and can provide higher traffic capacity than the ordinary traffic without a bus lane, (2) compared with the DBL, the proposed bus lane is advantageous in easing congestion on the ordinary lanes when the traffic flow is high and can avoid unreasonable allocation of the road resources.

Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

2016 ◽  
Vol 27 (09) ◽  
pp. 1650099 ◽  
Author(s):  
Mianfang Liu ◽  
Shengwu Xiong ◽  
Bixiang Li
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Rapid Development ◽  
System Stability ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Feedback Strategy ◽  
Threshold Control ◽  
Mixed Traffic Flow ◽  
System Equilibrium

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

scholarly journals The Deep 3D Convolutional Multi-Branching Spatial-Temporal-Based Unit Predicting Citywide Traffic Flow

2020 ◽  
Vol 10 (21) ◽  
pp. 7778 ◽  
Author(s):  
Zain Ul Abideen ◽  
Heli Sun ◽  
Zhou Yang ◽  
Amir Ali
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Short Term Memory ◽  
Time Estimation ◽  
External Factors ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
Real World Datasets

Recently, for public safety and traffic management, traffic flow prediction is a crucial task. The citywide traffic flow problem is still a big challenge in big cities because of many complex factors. However, to handle some complex factors, e.g., spatial-temporal and some external factors in the intelligent traffic flow forecasting problem, spatial-temporal data for urban applications (i.e., travel time estimation, trajectory planning, taxi demand, traffic congestion, and the regional rainfall) is inherently stochastic and unpredictable. In this paper, we proposed a deep learning-based novel model called “multi-branching spatial-temporal attention-based long-short term memory residual unit (MBSTALRU)” for the citywide traffic flow from lower-level layers to high-level layers, simultaneously. In our work, initially, we have modeled the traffic flow with spatial correlations multiple 3D volume layers and propose the novel multi-branching scheme to control the spatial-temporal features. Our approach is useful for exploring temporal dependencies through the 3D convolutional neural network (CNN) multiple branches, which aim to merge the spatial-temporal characteristics of historical data with three-time intervals, namely closeness, daily, and weekly, and we have embedded features by attention-based long-short term memory (LSTM). Then, we capture the correlation between traffic inflow and outflow with residual layers units. In the end, we merge the external factors dynamically to predict citywide traffic flow simultaneously. The simulation results have been performed on two real-world datasets, BJTaxi and NYCBike, which show better performance and effectiveness of the proposed method than previous state-of-the-art models.

scholarly journals “Traffic Congestion and Speed Delays at Benz Circle, Vijayawada Due to Construction Activities”, A Case Study

2018 ◽  
Vol 7 (2.1) ◽  
pp. 75
Author(s):  
B Akhila ◽  
K Sai Krishna ◽  
M Sri Nikhil ◽  
Malathi Narra
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
High Speed ◽  
Heavy Traffic ◽  
Negative Effects ◽  
The Mean ◽  
Mean Time

In urban areas, traffic congestion is a major problem. Heavy traffic flow on National Highways with high speed, when mixed up with local traffic at crossings, traffic congestion is likely to occur. This causes many negative effects like pollution, delay, accidents and improper traffic management at crossings. At Benz circle one of the rotary intersections in Vijayawada, the above problem frequently occurs. To reduce the ill effects, some solution is needed to be provided. So, as a solution- Construction of flyover at this intersection is proposed and accepted as the best alternative or solution for the problem. For this classified volume count survey and analysis is carried out and the capacity of the existing lane is checked. But in the mean-time of construction there might be increase in the traffic congestion and speed delays due to the diversion of routes. 

A new feedback control scheme for the lattice hydrodynamic model with drivers’ sensory memory

2020 ◽  
pp. 2150022
Author(s):  
Zhang Yicai ◽  
Zhao Min ◽  
Sun Dihua ◽  
Zhou Zhaomin ◽  
Chen Dong
Keyword(s):  
Feedback Control ◽  
Traffic Flow ◽  
Hydrodynamic Model ◽  
Traffic Congestion ◽  
Sensory Memory ◽  
Economic Losses ◽  
Short Term ◽  
Control Scheme ◽  
The Stability

With development of economy, the problem of traffic congestion is becoming more and more serious, which has caused economic losses and environmental pollution. Therefore, it is necessary to put forward reasonable solutions through the study of traffic flow theory. This paper proposes a new hydrodynamic model of traffic flow considering the drivers’ sensory memory and a new corresponding feedback control scheme. Through the stability analysis of the model, the stability conditions are derived. The obtained phase-plot shows that the sensory memory of drivers can affect the instability region, and the new feedback control term will reduce the unstable region. The numerical simulations by analyzing the short-term, long-term behaviors and hysteresis loop of traffic flow verify the impacts of the drivers’ sensory memory and the control sign.

scholarly journals Traffic Flow Analysis and Solutions to Ease Traffic Flow at Unsignalized Taxila Intersection

2018 ◽  
Author(s):  
Danish Farooq ◽  
Tayyab Akram
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Heavy Traffic ◽  
Flow Analysis ◽  
Traffic Information ◽  
General Level ◽  
Transportation Problems ◽  
Traffic System ◽  
Traffic Systems ◽  
The City

Transportation system of a city affects all aspects of its citizen’s economic and personal activities. At a general level, the traffic problem considered as a situation of mismatch between supply (i.e., roads and their capacity) and demands (i.e., travel needs). The city administrators have tried to balance it by creating infrastructures (e.g., new roads, expanding capacity, under pass) or policy changes (e.g., banning heavy traffic movement during peak or day hours). Major problems that motorists are facing on highways intersection are congestion, accidents, and costs. Too many automobiles, trucks, buses, bicycles, and pedestrians are attempting to use the same space to reach their destiny. N-5 (major highway in Pakistan) passes through Taxila where at some intersection extreme traffic congestion sets in. Transportation problems are evident at some locations with complex roadway geometrics. So a traffic study is to be conducted to quantify the extent of transportation problems. This study aims to gain information and understanding about traffic system through the derivation of traffic information from traffic data, and then to apply this information in the assessment of the performance of traffic systems and their interaction with land use activities. This research is an effort to provide suggestion and recommendations to enforce an efficient traffic flow system.

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