Showing papers by "Gitakrishnan Ramadurai published in 2015"

Discharge Headway Model for Heterogeneous Traffic Conditions

Abstract: Discharge headway is the headway between successive vehicles negotiating an intersection during the green time of signal oper- ation. It is an important parameter in signal operations and analysis since estimation of parameters such as saturation flow and capacity of an intersection depend on it. Although there have been several studies on discharge headway in homogeneous traffic conditions, there are only a few studies on discharge headways in heterogeneous traffic. This study examines the factors affecting discharge headway under heterogeneous traffic conditions which is characterized by mixed vehicle composition and lack of lane discipline. A novel method to measure headways in such cases is proposed here. To get individual vehicle headways, each lane is divided into multiple strips. The width of a strip is approximately equal to the width occupied by a motorcycle. The headways of vehicles in each strip are measured separately and used for analysis. Data collection for the study was carried out at signalized intersections in Chennai, India. Data was collected for one approach at all intersections. From the data collected, headways of individual vehicles were measured. Linear mixed effect regression was used to model discharge headway. The effect of vehicle type, lateral position on roadway, and green time on discharge headway were modeled. From the regression analysis, it was found that all these factors had significant impact on discharge headway. The discharge headway model proposed in this study could be used for obtaining saturation flow rates and capacity at signalized intersections under heterogeneous traffic conditions.

Grid-based real-time image processing (GRIP) algorithm for heterogeneous traffic

Abstract: The paper presents a fast algorithm for real-time image processing for counting and classification of vehicles in heterogeneous traffic recorded using a single stationary camera. The proposed method uses a single feature as the base parameter which is given by the user to classify the vehicles into four different classes. The algorithm has an error of 6.1% on an average for the total count when studied under varying illumination and weather conditions.

Scaling Laws in Chennai Bus Network

Abstract: In this paper, we study the structural properties of the complex bus network of Chennai. We formulate this extensive network structure by identifying each bus stop as a node, and a bus which stops at any two adjacent bus stops as an edge connecting the nodes. Rigorous statistical analysis of this data shows that the Chennai bus network displays small-world properties and a scale-free degree distribution with the power-law exponent, = 3:8. I. INTRODUCTION A. Chennai Bus Network Chennai is one of the metropolitan cities in India with a structured and a close-knit bus transport network. The Chennai bus network (CBN) is operated by the Metropolitan Transport Corporation (MTC), a state government undertaking. Spanning an area of 3,929 sq. km and with over 800 routes sprawling across entire Chennai, this extensive network also boasts of the largest bus terminus in Asia. With the population of the city being the sixth largest in the country, this medium of transport is most widely used for day-to-day commutation. The reason that the bus network, in general, achieves this favourable status lies primarily in two factors: (i) cost, and (ii) penetration. With high volume of commuters flowing through this network each day, the cost of travel per day, per person becomes significantly low. Although, this is a parameter which is usually met by every other public transport system, the penetration factor is the one which significantly makes bus networks the prime mode of transportation in cities. A high penetration effect exhibited by a bus network enables a person to travel between any two points in the city very easily which is in contrast to other public modes of transportation, where geographical constraints associated with the network layout are much higher in number. Thus, bus transportation allows flexibility in travel. A natural question arises here; what is the least number of buses one should change to go from one place to another? Or more precisely, why do we require changing buses at all? To answer these questions, we need to look at a more abstract and networked structure of the bus routes, and argue based on its various statistical properties. B. Complex Networks: overview

Contagion processes on urban bus networks in Indian cities

Abstract: Bus transportation is considered as one of the most convenient and cheapest modes of public transportation in Indian cities. Due to their cost-effectiveness and wide reachability, they help a significant portion of the human population in cities to reach their destinations every day. Although from a transportation point of view they have numerous advantages over other modes of public transportation, they also pose a serious threat of contagious diseases spreading throughout the city. The presence of numerous local spatial constraints makes the process and extent of epidemic spreading extremely difficult to predict. Also, majority of the studies have focused on the contagion processes on scale-free network topologies whereas, spatially-constrained real-world networks such as, bus networks exhibit a wide-spectrum of network topology. Therefore, we aim in this study to understand this complex dynamical process of epidemic outbreak and information diffusion on the bus networks for six different Indian cities using SI and SIR models. This will allow us to identify epidemic thresholds for these networks which will help us in controlling outbreaks by developing node-based immunization techniques.

Simulation of truck congestion in Chennai port

Abstract: The primary focus of this study is to understand the current port operating condition and recommend short term measures to improve traffic condition in the port of Chennai. The cause of congestion is identified based on the data collected and observation made at port gates as well as at terminal gates in Chennai port. A simulation model for the existing road layout is developed in micro-simulation software VISSIM and is calibrated to reflect the prevailing condition inside the port. The data such as truck origin/destination, hourly inflow and outflow of trucks, speed, and stopping time at checking booths are used as input. Routing data is used to direct traffic to specific terminal or dock within the port. Several alternative scenarios are developed and simulated to get results of the key performance indicators. A comparative and detailed analysis of these indicators is used to evaluate recommendations to reduce congestion inside the port.

Freight Trip Generation Models for Chennai, India

Abstract: Urban freight trip generation is an important component of urban transportation planning. However, it does not receive the same degree of importance as passenger trip generation in studies done in India. In this context a focused study on freight trip generation will throw light on its importance. While there are studies in India available on trip generation rates for passenger travel there are no numbers to quote for freight trips. The main purpose of this paper is to study freight demand through the estimation of freight trip generation models developed with disaggregated survey data at the establishment level. The survey gave significant insight into the freight trip generation characteristics in Chennai city. From the data collected it is seen that on an average about 3 freight trips are made to an establishment and 6 trips leave an establishment every day. Predominantly bikes and small pick-up vans are used for carrying goods in the city. The authors compare their study to a similar study conducted recently in New York City. Overall, establishments in Chennai attract more trips than in New York City. This is in contrast to what is observed in the passenger trip rates where Indian cities have lesser value compared to western countries.

Strategies for traffic signal control in Indian cities

Abstract: Most Indian cities face oversaturated flow conditions during peak periods. In this paper we revisit the traffic signal control to improve urban network performance. Three novel strategies that address congested heterogeneous traffic flow are presented. The first two strategies - keeping intersection signal cycle times shorter and bottleneck metering - are derived from field observed data while the third - exclusive lanes and storage area near intersections for two wheelers - is supported based on a micro-simulation model. Potential improvements are presented based on the strategies. While most recent studies have focused on area wide / network signal control improvements our study shows potential for significant improvement even at the level of an isolated signal.

Submission to the DTA2012 Special Issue: A Case for Higher-Order Traffic Flow Models in DTA

Abstract: An accurate Dynamic Traffic Assignment (DTA) model should capture real world traffic flow dynamics and predict ‘dynamic’ travel times. Traditional DTA models used simple traffic flow functions such as exit flow functions, delay functions, point queues, and deterministic physical queue models. Recently, simulation based models apply well accepted traffic flow theoretic models to simulate traffic flow. However, a significant number of papers over the last decade have adopted an approximation of LWR traffic flow model, the cell transmission model, for simulating traffic flow in a DTA model. This paper compares three models, namely, LWR, Payne and Aw-Rascle, models, for their suitability to be embedded in a DTA model. Model calibration and flow simulation is performed separately using two different speed–density relationships. Results showed the importance of choice of speed-density relationship in traffic flow simulation. Models were used to simulate traffic state at different discretization levels and it was observed that as discretization becomes finer, the models' accuracy increases. Finally, the models were applied to a two node, two link network to analyze their performance in a DTA framework. The higher-order models captured congestion dissipation better than LWR model which consistently underestimates congestion and travel time.