scholarly journals Travel Time and Congestion Assessment Along Ujala Circle (S.G. Highway Ahmedabad)

2020 ◽  
Vol 9 (5) ◽  
pp. 995-1004
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Calculated Data ◽  
Noise Pollution ◽  
Flow Density ◽  
Time Loss ◽  
Environment Effects ◽  
Speed Flow ◽  
Density Relationship ◽  
Data Graph

The approximately 25201084 (2018) vehicular citizenry in Ahmedabad city so it is very necessary to negotiate its movements and infirmity effects like as air and noise pollution & other environment effects, traffic congestion, time loss, and so on. S.G Highway has 44.5 km long stretch of Ahmedabad, an oldest and most substantial stretch which started from Ujala circle. For declamation the traffic congestion, classified volume count survey (by Video Graphic method), travel time and delay survey (by Moving Observer Method), and for speed-flow-density relationship Spot speed study at Ujala circle during Friday has been accomplished and analyzed. From the calculated data, graph of flow v/s density, speed v/s density and speed v/s flow relationship has been prosecute with the R2 value of each relationship. This analysis proved that current traffic situation at Ujala circle is highly congested, which leads to the higher travel time taken by vehicle compare to free flow condition. From all analyzed data, alternate invigorating measures are prospected. Based on those alternative invigorating measures best alternative is choose as well as bring off simulation and validation of Model in the VISSIM software, also design in AutoCAD for better illustration of issue.

scholarly journals Urban Wasteful Transport and Its Estimation Methods

2018 ◽  
Vol 10 (12) ◽  
pp. 4562 ◽  
Author(s):  
Xiangyang Cao ◽  
Bingzhong Zhou ◽  
Qiang Tang ◽  
Jiaqi Li ◽  
Donghui Shi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Transport Theory ◽  
Road Traffic ◽  
Urban Traffic ◽  
Flow Density ◽  
Urban Road ◽  
Road Capacity ◽  
Density Relationship

The paper studies urban road traffic problems from the perspective of resource science. The resource composition of urban road traffic system is analysed, and the road network is proved as a scarce resource in the system resource combination. According to the role of scarce resources, the decisive role of road capacity in urban traffic is inferred. Then the new academic viewpoint of “wasteful transport” was proposed. Through in-depth research, the paper defines the definition of wasteful transport and expounds its connotation. Through the flow-density relationship analysis of urban road traffic survey data, it is found that there is a clear boundary between normal and wasteful transport in urban traffic flow. On the basis of constructing the flow-density relationship model of road traffic, combined with investigation and analysis, the quantitative estimation method of wasteful transport is established. An empirical study on the traffic conditions of the Guoding section of Shanghai shows that there is wasteful transport and confirms the correctness of the wasteful transport theory and method. The research of urban wasteful transport also reveals that: (1) urban road traffic is not always effective; (2) traffic flow exceeding road capacity is wasteful transport, and traffic demand beyond the capacity of road capacity is an unreasonable demand for customers; (3) the explanation that the traffic congestion should apply the comprehensive theory of traffic engineering and resource economics; and (4) the wasteful transport theory and method may be one of the methods that can be applied to alleviate traffic congestion.

Using GPS Technology to Relate Macroscopic and Microscopic Traffic Parameters

1996 ◽  
Vol 1520 (1) ◽  
pp. 89-96 ◽  
Author(s):  
Matthew J. Barth ◽  
Eric Johnston ◽  
Ramakrishna R. Tadi
Keyword(s):  
Traffic Congestion ◽  
Vehicle Emissions ◽  
Velocity Variation ◽  
Flow Density ◽  
Emission Model ◽  
Freeway Traffic ◽  
Traffic Sensors ◽  
Statistical Measures ◽  
Speed Flow ◽  
Emission Models

Traffic congestion on today's freeways is a serious problem, causing significant delays for both passengers and goods. Freeway traffic congestion also results in increased vehicle emissions; however, this increase has not been quantified using current vehicle emission models. Current models use emission factors based on driving cycles that do not properly represent freeway driving characteristics. This paper presents a new methodology for relating the macroscopic speed, flow, and density parameters measured by traffic sensors with statistics of microscopic driving traces under different levels of congestion. This approach can be used to better estimate freeway emissions when combined with an appropriate modal emissions model. Preliminary experimentation has been carried out with a vehicle equipped with global positioning system (GPS) instrumentation, allowing for precise localization in both space and time. With the GPS, second-by-second velocity traces are acquired and matched with simultaneously measured freeway traffic data obtained by embedded traffic sensors. Statistical measures of velocity variation are derived from the velocity traces and are functionally related to the macroscopic traffic parameters of speed, flow, and density. Given a known distribution of vehicle types, models, and model years, vehicle emissions can be related to these statistical measures of velocity variation using a modal emission model, and, thus given speed-flow-density measures of freeway traffic, localized emissions estimates can be made.

scholarly journals Values of Travel Time for Recreational Trips under Different Behavioural Rules

2021 ◽  
Vol 13 (12) ◽  
pp. 6831
Author(s):  
Rosa Marina González ◽  
Concepción Román ◽  
Ángel Simón Marrero
Keyword(s):  
Travel Time ◽  
National Parks ◽  
Traffic Congestion ◽  
National Park ◽  
Revealed Preference ◽  
Discrete Choice Models ◽  
Model Specification ◽  
Regret Minimization ◽  
Random Regret Minimization

In this study, discrete choice models that combine different behavioural rules are estimated to study the visitors’ preferences in relation to their travel mode choices to access a national park. Using a revealed preference survey conducted on visitors of Teide National Park (Tenerife, Spain), we present a hybrid model specification—with random parameters—in which we assume that some attributes are evaluated by the individuals under conventional random utility maximization (RUM) rules, whereas others are evaluated under random regret minimization (RRM) rules. We then compare the results obtained using exclusively a conventional RUM approach to those obtained using both RUM and RRM approaches, derive monetary valuations of the different components of travel time and calculate direct elasticity measures. Our results provide useful instruments to evaluate policies that promote the use of more sustainable modes of transport in natural sites. Such policies should be considered as priorities in many national parks, where negative transport externalities such as traffic congestion, pollution, noise and accidents are causing problems that jeopardize not only the sustainability of the sites, but also the quality of the visit.

scholarly journals Measuring Recurrent and Nonrecurrent Traffic Congestion

2003 ◽  
Vol 1856 (1) ◽  
pp. 118-124 ◽  
Author(s):  
Alexander Skabardonis ◽  
Pravin Varaiya ◽  
Karl F. Petty
Keyword(s):  
Los Angeles ◽  
Travel Time ◽  
San Francisco ◽  
Traffic Congestion ◽  
Real Life ◽  
Time Variability ◽  
Loop Detectors ◽  
Bay Area ◽  
Freeway Corridors ◽  
Travel Time Variability

A methodology and its application to measure total, recurrent, and nonrecurrent (incident related) delay on urban freeways are described. The methodology used data from loop detectors and calculated the average and the probability distribution of delays. Application of the methodology to two real-life freeway corridors in Los Angeles, California, and one in the San Francisco, California, Bay Area, indicated that reliable measurement of congestion also should provide measures of uncertainty in congestion. In the three applications, incident-related delay was found to be 13% to 30% of the total congestion delay during peak periods. The methodology also quantified the congestion impacts on travel time and travel time variability.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

Closure to “High Density Vehicular Flow-Density Relationship”

1968 ◽  
Vol 94 (2) ◽  
pp. 269-270
Author(s):  
Danilo M. Garcia ◽  
John Hugh Jones
Keyword(s):  
High Density ◽  
Flow Density ◽  
Density Relationship

scholarly journals Minimizing Traffic Congestion Through Continuous-Time Route Reservations With Travel Time Predictions

2019 ◽  
Vol 4 (1) ◽  
pp. 141-153 ◽  
Author(s):  
Charalambos Menelaou ◽  
Stelios Timotheou ◽  
Panayiotis Kolios ◽  
Christos G. Panayiotou ◽  
Marios M. Polycarpou
Keyword(s):  
Travel Time ◽  
Continuous Time ◽  
Traffic Congestion

scholarly journals Estimates of Economic Cost of Congestion Travel Time Delay Between Onne-Seaport and Eleme-Junction Traffic Corridor

2020 ◽  
Vol 11 (2) ◽  
pp. 33-43
Author(s):  
Theophilus C. Nwokedi ◽  
Lazarus I. Okoroji ◽  
Ifiok Okonko ◽  
Obed C. Ndikom
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Oil And Gas ◽  
Economic Cost ◽  
Oil And Gas Industry ◽  
Research Approach ◽  
Traffic Corridor ◽  
Output Losses

AbstractTravelers along the Onne-seaport to Eleme-junction road corridor in the hub of the oil and gas industry in Port-Harcourt, Nigeria, have continued to experience very serious traffic congestion travel time delays, culminating into loss of man-hours and declining productivity. This study estimated the economic cost of traffic congestion travel time delay along the corridor, with a view to providing economic justification for developing traffic management policies and road infrastructure, to remedy it. A mixed research approach was adopted in which data was sourced through field survey and from secondary sources. The gross output model was used to estimate the output losses occasioned by productive time losses related to traffic congestion. The study established that the average daily traffic congestion travel time delay along the traffic corridor by travelers in trucks, car, bus and taxi modes are 104.17 minutes, 46.60 minutes, 58.5 minutes and 56.4 minutes respectively. The estimated daily aggregate economic cost of output losses associated with traffic congestion time delay on the corridor is 46049809.8 naira (210923.5USD) for all modes. This justifies any investment in traffic congestion remedial strategies along the route.

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