scholarly journals Acceleration and Deceleration Rates of Various Vehicle Categories at Signalized Intersections in Mixed Traffic Conditions

2021 ◽  
Vol 49 (4) ◽  
pp. 324-332
Author(s):  
Sushmitha Ramireddy ◽  
Vineethreddy Ala ◽  
Ravishankar KVR ◽  
Arpan Mehar
Keyword(s):  
Close Relation ◽  
Accurate Estimation ◽  
Signal Design ◽  
Driver Behaviour ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Light Commercial Vehicle ◽  
Acceleration And Deceleration ◽  
Vast Variation ◽  
Two Wheeler

The acceleration and deceleration rates vary from one vehicle type to another. The same vehicle type also exhibits variations in acceleration and deceleration rates due to vast variation in their dynamic and physical characteristics, ratio between weight and power, driver behaviour during acceleration and deceleration manoeuvres. Accurate estimation of acceleration and deceleration rates is very important for proper signal design to ensure minimum control delay for vehicles, which are passing through the intersection. The present study measures acceleration and deceleration rates for four vehicle categories: Two-wheeler, Three-wheeler, Car, and Light Commercial Vehicle (LCV), by using Open Street Map (OSM) tracker mobile application. The acceleration and deceleration rates were measured at 24 signalized intersection approaches in Hyderabad and Warangal cities. The study also developed acceleration and deceleration models for each vehicle type and the developed models were validated based on field data. The results showed that the predicted acceleration and deceleration models showed close relation with those measured in the field. The developed models are useful in predicting average acceleration and deceleration rate for different vehicle types under mixed and poor lane disciplined traffic conditions.

Measurement and Evaluation of Real-World Speed and Acceleration Activity Envelopes for Light-Duty Vehicles

2015 ◽  
Vol 2503 (1) ◽  
pp. 128-136 ◽  
Author(s):  
Bin Liu ◽  
H. Christopher Frey
Keyword(s):  
Real World ◽  
Test Procedure ◽  
Accurate Estimation ◽  
Vehicle Type ◽  
Light Duty ◽  
Road Grade ◽  
Light Duty Vehicle ◽  
Curb Weight ◽  
Vehicle Activity ◽  
Light Duty Vehicles

Accurate estimation of vehicle activity is critically important for the accurate estimation of emissions. To provide a benchmark for estimation of vehicle speed trajectories such as those from traffic simulation models, this paper demonstrates a method for quantifying light-duty vehicle activity envelopes based on real-world activity data for 100 light-duty vehicles, including conventional passenger cars, passenger trucks, and hybrid electric vehicles. The vehicle activity envelope was quanti-fied in the 95% frequency range of acceleration for each of 15 speed bins with intervals of 5 mph and a speed bin for greater than 75 mph. Potential factors affecting the activity envelope were evaluated; these factors included vehicle type, transmission type, road grade, engine displacement, engine horsepower, curb weight, and ratio of horsepower to curb weight. The activity envelope was wider for speeds ranging from 5 to 20 mph and narrowed as speed increased. The latter was consistent with a constraint on maximum achievable engine power demand. The envelope was weakly sensitive to factors such as type of vehicle, type of transmission, road grade, and engine horsepower. The effect of road grade on cycle average emissions rates was evaluated for selected real-word cycles. The measured activity envelope was compared with those of dynamometer driving cycles, such as the federal test procedure, highway fuel economy test, SC03, and US06 cycles. The effect of intervehicle variability on the activity envelope was minor; this factor implied that the envelope could be quantified based on a smaller vehicle sample than used for this study.

scholarly journals Passenger Car Unit Estimation at Signalized Intersection for Non-lane Based Mixed Traffic Using Microscopic Simulation Model

2017 ◽  
Vol 45 (1) ◽  
pp. 12 ◽  
Author(s):  
Gowri Asaithambi ◽  
Hayjy Sekar Mourie ◽  
Ramaswamy Sivanandan
Keyword(s):  
Simulation Model ◽  
Signalized Intersection ◽  
Accurate Estimation ◽  
Mixed Traffic ◽  
Passenger Car ◽  
Traffic Conditions ◽  
Passenger Car Unit ◽  
Road Width ◽  
On The Road ◽  
Chennai City

In India, traffic on roads is mixed in nature with widely varying static and dynamic characteristics of vehicles. At intersections, vehicles do not follow ordered queue and lane discipline. Different vehicle types occupy different spaces on the road, move at different speeds, and start at different accelerations. The problem of measuring volume of such mixed traffic has been addressed by converting different vehicles categories into equivalent passenger cars and expressing the volume in terms of Passenger Car Unit (PCU) per hour. The accurate estimation of PCU values for different roadway and traffic conditions is essential for better operation and management of roadway facilities. Hence, the objective of the present study is to estimate the PCU values at signalized intersection in mixed traffic and to study the influence of traffic volume, traffic composition and road width on PCU values.For this purpose, a mixed traffic simulation model developed specifically for a signalized intersection was used. The model was calibrated and validated with the traffic data collected from a signalized intersection in Chennai city. Simulation runs were carried out for various combinations of vehicular composition, volume levels and road width. It was observed that presence of heavy vehicles and increase in road width affects the PCU values. The obtained PCU values were statistically checked for accuracy and proven to be satisfied. The PCU values obtained in this study can be used as a guideline for the traffic engineers and practitioners in the design and analysis of signalized intersections where mixed traffic conditions exist.

Marginalized Particle Filtering Framework for Tuning of Ensemble Filters

2011 ◽  
Vol 139 (11) ◽  
pp. 3589-3599 ◽  
Author(s):  
Václav Šmídl ◽  
Radek Hofman
Keyword(s):  
Particle Filtering ◽  
Computational Cost ◽  
Close Relation ◽  
Error Variance ◽  
Environmental Modeling ◽  
Joint Estimation ◽  
Accurate Estimation ◽  
Measurement Error Variance ◽  
Inflation Factor ◽  
Hybrid Filters

Abstract Marginalized particle filtering (MPF), also known as Rao-Blackwellized particle filtering, has been recently developed as a hybrid method combining analytical filters with particle filters. This paper investigates the prospects of this approach in environmental modeling where the key concerns are nonlinearity, high-dimensionality, and computational cost. In the formulation herein, exact marginalization in the MPF is replaced by approximate marginalization, yielding a framework for creation of new hybrid filters. In particular, the authors propose to use the MPF framework for online tuning of nuisance parameters of ensemble filters. Conditional independence–based simplification of the MPF algorithm is proposed for computational reasons and its close relation to previously published methods is discussed. The strength of the framework is demonstrated on the joint estimation of the inflation factor, the measurement error variance, and the length scale parameter of covariance localization. It is shown that accurate estimation can be achieved with a moderate number of particles. Moreover, this result was achieved with naively chosen proposal densities, leaving space for further improvements.

scholarly journals Financial Statement Analysis of Ashok Leyland Limited, India

2016 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Harshadeep Chilukuri ◽  
Stephy Thankam Varghese
Keyword(s):  
Automobile Industry ◽  
Commercial Vehicle ◽  
Financial Statement ◽  
Commercial Vehicles ◽  
Lower Growth ◽  
Light Commercial Vehicle ◽  
The World ◽  
The Government ◽  
Two Wheeler ◽  
Near Future

<p><em>The Indian auto industry is one of the largest in the world. The industry accounts for 7.1 per cent of the country's Gross Domestic Product (GDP). As of Financial Year 2014-2015, around 31 per cent of small cars sold globally were manufactured in India. The Two Wheelers segment with 81 per cent market share is the leader of the Indian Automobile market owing to a growing middle class and a young population.</em></p><p><em>               </em><em>     Moreover, the growing interest of the companies in exploring the rural markets further aided the growth of the sector. India is also a prominent auto exporter and has strong export growth expectations for the near future. In April-January 2016, exports of Commercial Vehicles registered a growth of 18.36 per cent over April-January 2015. In addition, several initiatives by the Government of India and the major automobile players in the Indian market were expected to make India a leader in the Two Wheeler (2W) and Four Wheeler (4W) market in the world by 2020.</em></p><p><em> </em><em>India’s second largest commercial vehicle maker Ashok Leyland has shown a declining trend in the total sales during August 2016 by 6 per cent due to lower growth in Medium and Heavy Vehicle segment. The company sold ten thousand eight hundred and ninety-seven (10,897) vehicles in the month gone by, compared with 11,544 units sold in the same month last year. Medium &amp; Heavy commercial vehicle sales during the month declined 8 percent to 8201 units while light commercial vehicle sales grew by 2 percent to 2696 units on yearly basis. The contribution of Ashok Leyland in the growth of the automobile industry is very high. Hence an attempt is made to analyse the financial statement of <strong>Ashok Leyland.</strong></em></p><em><strong></strong></em>

Accurate Estimation of Cutting Time Based on Control Principle of Machine Tool

2016 ◽  
Vol 10 (3) ◽  
pp. 429-437 ◽  
Author(s):  
Kosuke Saito ◽  
◽  
Hideki Aoyama ◽  
Noriaki Sano ◽  
◽  
...  
Keyword(s):  
Machine Tool ◽  
Machine Tools ◽  
Tool Path ◽  
Estimation Error ◽  
Numerical Control ◽  
Accurate Estimation ◽  
Flexible System ◽  
Acceleration And Deceleration ◽  
Nc Machine ◽  
Control Principle

The accurate estimation of cutting time before beginning a cutting process is necessary to improve the productivity of machining. Commercial computer-aided machining (CAM) systems estimate the cutting time by dividing the tool path length by the designated feed rate in a numerical control (NC) program. However, the actual cutting time generally exceeds the estimated cutting time for curved surfaces because of the acceleration and deceleration of the NC machine tool. There are systems that estimate cutting time while considering acceleration and deceleration along the controlled axes, but these are applicable only to particular machine tools. In this study, a flexible system for the accurate estimation of cutting time, based on the control principle of a machine tool, is developed. Experiments to estimate cutting time are conducted for the machining of complex shapes using two different NC machine tools. The actual cutting time is compared with the cutting time estimated by the developed system and that by a commercial CAM system. The estimation error of the proposed system is only 7%, while that of the commercial CAM system is 51%.

scholarly journals Introducing a Re-Sampling Methodology for the Estimation of Empirical Macroscopic Fundamental Diagrams

2018 ◽  
Vol 2672 (20) ◽  
pp. 239-248 ◽  
Author(s):  
Lukas Ambühl ◽  
Allister Loder ◽  
Michiel C. J. Bliemer ◽  
Monica Menendez ◽  
Kay W. Axhausen
Keyword(s):  
Traffic Control ◽  
Critical Density ◽  
Network Capacity ◽  
Accurate Estimation ◽  
Fundamental Diagram ◽  
Data Set ◽  
Urban Dynamics ◽  
Traffic Conditions ◽  
Macroscopic Fundamental Diagram ◽  
Inaccurate Estimation

The uncertainty in the estimation of the macroscopic fundamental diagram (MFD) under real-world traffic conditions and urban dynamics might result in an inaccurate estimation of the MFD parameters—especially if congestion is rarely observed network-wide. For example, as data normally come from punctual observations out of the whole network, it is unclear how representative these observations might be (i.e., how much is the observed capacity affected by the network’s inhomogeneity). Similarly, if the observed data do not exhibit a distinct congested branch, it is hard to determine the network capacity and critical density. This, in turn, also leads to uncertainties and errors in the parametrization of the MFD for applications, for example traffic control. This paper introduces a novel methodology to estimate (i) the level of inhomogeneity in the network, and (ii) the critical density of the MFD, even when no congested branch is observed. The methodology is based on the idea of re-sampling the empirical data set. Using an extensive data set from Lucerne, Switzerland, and London, UK, insights are provided on the performance and the application of the proposed methodology. The proposed methodology is used to illustrate how the level of inhomogeneity is lower in Lucerne than in the three areas of the network of London that are investigated. The proposed measure of the level of inhomogeneity gives city planners the possibility to analyze and investigate how efficiently their road network is utilized. In addition, the analysis shows that, for the network of Lucerne, the proposed methodology allows accurate estimation of the critical density up to 16 times more often than would be possible otherwise. This simple and robust estimation of the critical density is crucial for the application of many traffic control algorithms.

Effect of type of lead vehicle on following headway behaviour in mixed traffic

2014 ◽  
Vol 11 (1) ◽  
pp. 28-43 ◽  
Author(s):  
Ravindra Kumar ◽  
Purnima Parida ◽  
Wafaa Saleh
Keyword(s):  
Transport Systems ◽  
Mixed Traffic ◽  
Driver Behaviour ◽  
Traffic Condition ◽  
Content Type ◽  
Traffic Conditions ◽  
Study Results ◽  
Strategic Study ◽  
The Impact ◽  
Lead Vehicle

Purpose – There is gap in literature on understanding of the issues of following headway behaviour of the driver and a lack of sufficient data in different traffic conditions. The purpose of this paper is to find the effects of type of lead vehicle on following headway in mixed traffic condition in India on different category of roads and flow. Design/methodology/approach – Real-world headway data were collected through video and extracted. Data were analysed using tools and statically approach was adopted to present the results in detail. Findings – Results shows the impact of type of lead vehicle on driver following time headway behaviour under different level of traffic and types of road characteristics. It was found that driver following behaviour is affected by the type of lead vehicle. It also shows that drivers are inconsistent in their choice of headway. Research limitations/implications – This research has special strategic study area of India in typical two cities Silchar and Shillong of northeast region of India. The traffic characteristic and composition is quite different as compared to other cities of India. Therefore the study results cannot be generalized for whole India. Practical implications – The result of the study has focused on impact of type of lead vehicle on following behaviour. This can be useful to safety reduction and changing the driver behaviour through education and display of information. However, the real application of this result is to be implemented by local transport and road managing authority to reduce accidents and increase safety of drivers. Originality/value – In mixed traffic conditions, the impact of type of lead vehicle on following behaviour affects the safety of drivers and the accounting for such behaviour is never been explored in mixed traffic condition. If the study is implemented, it can be useful to simulation modeller and intelligent transport systems (ITS) to design and operate many in-vehicle systems for smooth traffic processes.

ANALYSIS OF MICROSCOPIC DATA UNDER HETEROGENEOUS TRAFFIC CONDITIONS

Transport ◽  
2010 ◽  
Vol 25 (3) ◽  
pp. 262-268 ◽  
Author(s):  
Mallikarjuna Chunchu ◽  
Ramachandra Rao Kalaga ◽  
Naga Venkata Satish Kumar Seethepalli
Keyword(s):  
Processing Technique ◽  
Lateral Distribution ◽  
Heterogeneous Traffic ◽  
Image Processing Technique ◽  
Trajectory Data ◽  
Traffic Conditions ◽  
Traffic Stream ◽  
Wide Road ◽  
Two Wheeler ◽  
Lateral Gaps

Collecting microscopic data is difficult under heterogeneous traffic conditions. This data is essential when modelling heterogeneous traffic at a microscopic level. In this paper, microscopic data collected under heterogeneous traffic conditions using a video image processing technique is presented. Data related to heterogeneous traffic such as vehicle composition in the traffic stream, a lateral distribution of vehicles, lateral gaps and longitudinal gaps have been collected. The lateral distribution of vehicles on a ten‐meter wide road has been analyzed with a specific emphasis on motorized two‐wheeler movement. Using trajectory data, an attempt to examine the gap maintaining the behaviour of vehicles under different traffic conditions has been made. Empirical relationships between the lateral gap and area occupancy have been proposed for various vehicle combinations. The influence of difference in the lateral positions of leading and following vehicles on the longitudinal gap has been analyzed.

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