Dr. Tom V. Mathew
This research addresses the problem of traffic network design problem (NDP) under demand uncertainty. The origin-destination trip matrices are taken as random variables with known probability distributions. Instead of finding optimal network design solutions for a given future scenario, we are concerned with solutions which are in some sense .good. for a variety of demand realizations. We propose a general definition of robustness and develop a methodology using genetic algorithm (GA) to find robust network design (RNDP) solutions. The methodology generates globally feasible near optimal network design solutions. The study makes two important contributions to the network design literature. First, robust network design solutions are significantly different from the deterministic NDPs and not accounting for them could underestimate the network wide impacts. Second, we systematically evaluate the computational performance by using different test networks and GA control parameter settings to obtain the appropriate parameters for this problem.
State Departments of Transportation (DOT) that provide the bulk of matching funds to local transit agencies for the purchase of new buses, are duly concerned about the escalating costs of new buses and the lack of sufficient funds to keep up with their replacement costs. This research tries to develop an asset management strategy for state DOT.s to meet their long-term fleet needs. Earlier models developed a two-stage process to allocate capital dollars for the dual purpose of purchasing new buses and rebuilding existing buses, when the needs of all the constituent agencies in a peer group are considered, and to distribute funds among the agencies in an equitable manner. The proposed management strategy includes two optimization models. Model 1 attempts to maximize the weighted fleet life of all the buses that are being purchased and rebuilt for a given peer group, within the constraints of a fixed budget. Model 2 is designed to maximize the Remaining Life (RL) of the entire peer group comprising the existing buses as well as those being replaced or rebuilt. The need for every single bus that is eligible for replacement is addressed in the model either through replacement or rebuilding. This two stage model is tried to combine into a single optimization model. A comprehensive case study depicting a seven-year planning cycle for the entire fleet of medium sized buses in the state of Michigan was used to demonstrate the strategy.
This research first addresses the computational issue of Robust Network Design (RND) by adopting improved sampling techniques. Futher, the network reliability concepts need to be incorporated.
In the thesis a Genetic Algorithm based model was developed for designing an urban bus transit route network. The model was studied in different networks and applied to a large case study network. The size of the network is largest reported network in terms of number of nodes and links. The model behaved consistantly in all the networks. (Publications: Pattnaik et al. (1998), Tom & Mohan (2003))
Arterials form the backbone of any rural and urban road system. In developing countries, the road network system serve heterogeneous traffic with a wide range of variations in driver behaviour and static and dynamic characteristics of vehicles. In the present scenario, vehicular traffic is increasing at an exponential rate which has created problems like congestion, parking, environmental pollution, etc. Moreover, limited road space in urban areas restricts mobility and comfort. In turn, there has been an increased interest in traffic flow modelling which represents the vehicular traffic behaviour and gives relations between speed-flow-density. Research on traffic flow modeling started about fifty years ago and has resulted in serveral models describing different aspects of traffic flow operations, either by considering the influence of vehicles individually (microscopic models) or from the viewpoint of collective vehicular flow (macroscopic models).
Most of the traffic flow models are developed for homogeneous traffic where majority of the vehicles are passenger cars. These models cannot be implemented directly for the areterials of developing countries having vehicle with diverse physical characteristics. Due to the complexities involved in developing mathematical models for heterogeneous traffic, simulation based approaches are usually adopted by most researchers. Car following theory based on Newtonian laws are used to describe movement of vehicles in these models. In this approach the postion, speed, and acceleration of every vehicle at each time interval need to be computed from basic equtations of motion. Althogh this approch provides accurate individual vehicle details, they require high computational ressources making it unsuitable for many real time application. This has motivated the developement of computationally efficient models with reasonable accuracy. In this context, cellular automata (CA) has emerged as an efficient tool in modelling traffic flow. CA discretizes continuous variables and uses simple vehicle movement rules (acceleration, deceleration, randomisation, and updation) to describe traffic flow. Several studies demonstrated the use of CA in traffic flow modelling and proved its computational efficiency.
In this study, heterogeneous traffic flow modeling using cellular automata is attempted for a urban arterial. In this approach, CA model for homogeneous traffic is modified for heterogeneous traffic conditions. Accordingly, three models are proposed: single lane traffic flow model (SLTF), two lane traffic flow model (TLTF), and grid based traffic flow model (GBTF).
The first model (SLTF) is developed based on model developed by Nagel and Schreckenberg (1992) for freeway known as NaSch model. To incorporate heterogeneity, the NaSch model is modified by changing cell size based on the vehicle types and by considering different types of vehicle depending on their dynamic characteristics like maximum speed, acceleration and deceleration. It is also proposed to use modified randomisation rule for better performance of the model in heterogeneous traffic flow. In addition to this an incident occurrence rule is developed to study the behaviour of vehicular movement at the incident place. The model requires information like cell size, which represent the standard vehicle with the required clearance; types of vehicles and maximum velocity of each type of vehicle; the initial density (cells occupied with vehicles); mean arrival rate; classified volume for each type of vehicles; incident details like place and duration of incident; and driver behavior probabilities. The model is first tested for homogeneous traffic. The model is then calibrated to represent macrosopic parameters from the field data. A microscopic validation is done using the data generated by VISSIM software. The model provides relations of fundamental parameters, trajectory of individual vehicles, and animation of traffic flow. The output of macroscopic parameters shows that the models are giving satisfactory result.
The second model (TLTF) is an extention of the first to permit lane changing and overtaking. Various lane canging rules were developed by giving due consideration to the drivers behaviour. These model needs additional input of lane changing probability and maximum speed allowed in each lane. The model parameters like driver behaviour probability and lanechanging probability are calibrated. The model is then validated with the field data collected at macroscopic level as well as number of lane changing occurred. The developed model is applied to a long two lane road with the incident occurrence.
The above two models were found to be less effective when there is a wide variation in the vehicular size as each vehicle represented by a single cell. To overcome some of the limitations of these models, the third model (GBTF) is developed which allows the movement of small size vehicles (two-wheelers) side by side. In this model road stretch is divided by grid of cells. Eeach vehicle is represented by one or more cell and the number of cells is governed by size of the vehicle. The vehicle movement rules and data requirement are similar to the previous model. In this model, optimal cell size is decided based on the type of vehicle, clearance, distance headway at various speed, and minimum number of cells by which all kind of vehicle can be represented. The model is calibrated and then validated at microscopic and macroscopic level and found to be more accurate then previous models. However, this model need more computational time as compared to previous model.
The model is used to study the behaviour of heterogeneous traffic like lane changing, incident occurrence, and the effect of different compositon of traffic. This study gives a new computationally efficient model for heterogeneous traffic. However, these models can handle only uni-directional traffic at mid-block. Therefore, further study is required to explore the vehicular behaviour in bi-directional traffic at mid-block as well as intersection.
KEY WORDS: Traffic flow modelling, Simulation, Microscopic,Cellular Automata, Heterogeneous, Homogeneous, Congestion.
The activity based travel demand analysis has seen substantial development in the past few years. Over these years, various models of activity scheduling behaviour have been formulated and these models are typically part of more comprehensive activity-based models of travel demand. However, studies considering the characteristics of the people in the developing countries are minimal. In this context, the objective of this study is to develope a day activity-scheduling model for activity pattern analysis. To achieve this objective certain set of strategies are formulated. These include the design and administration of activity diaries, the developments of a microsimulation model for activity pattern analysis and scheduling, and the development of a tour mode choice model and a time of day model. The study area selected for the development of the activity-scheduling model is the Thane municipal corporation area of Mumbai metropolitan region, India.
A new type of survey instrument, called time-space diary, is designed combining good features of travel and time-use diary. First, a pilot survey is conducted to assess the suitability of the instrument and various method of survey administration based on the issues like non-response, missing data and cost of survey. Four methods, namely telephonic interview, delivered and mail back method, drop off and pick up method and face-to-face interview method are tried for the administration of the time-space diary. Finally, a main survey is conducted to collect two-day diary information of every individual, above five years, through a household personal interview. The survey was conducted in about 2500 households.
The prototype microsimulated activity-scheduling model developed in this study is for generating activity schedules and travel patterns for a 24-hour typical weekday and a holiday for all the persons in a household. A sequential object oriented approach is adopted for developing synthetic daily individual activity-travel patterns. This approach decomposes the entire daily activity-travel pattern into various components, namely, activity type, activity duration, activity location, time of the day and mode choice. The model makes use of the concept of the tour, a .container. of activities with a common purpose (subsistence, maintenance or leisure), to organize activity episodes into the schedules of persons in a household. The model also takes care of the interaction between the household members. In addition, tour mode choices are predicted based on certain rules of the trip chains within which they occur. The micro-simulated model is validated at the macro level. Validation is also done on the basis of its ability to reproduce the travel parameters.
The output from the microsimulated model is used for the formulation of two models, tour mode choice model and time of day model. The current model is developed only for the subsistence tours. A multinomial logit model is used for the model development. A sensitivity analysis is also carried out for both the models.
One of the innovative and novel approaches of this study is the design of time space diary in the context of a city in a developing country, which combines the advantage of both travel and time use diary format. In addition, microsimulation, an emerging and a promising approach to model travel behaviour is used for the development of activity scheduling model, suitable for a developing country which is minimally explored till now.
Key words: Microsimulation, Activity based model, Scheduling, Tour mode choice model, Tour time-of-day model.
Large scale urbanization and rapid growth of human population as well as vehicle population have laid severe stress on the existing urban transport system in India. It is estimated that by the turn of the century 35% of the total population in India will be living in urban areas. As per 2001 census, the number of Million Plus population cities in India is 27. With the sharing of the limited road capacity by a variety of modes in most cities, the problem has become unmanageable resulting in traffic congestion, inadequate parking area and environmental deterioration. Magnitude of the problem can be reduced by proper planning and control of the available infrastructure facilities.
There is a scope to reduce magnitude of the ill effects of the traffic congestion by simulating and analyzing the congested urban road networks by integrating the techniques used in transportation planning and traffic control. The models developed to integrate the transportation planning and traffic control in traffic assignment phase is popularly called as .Combined Traffic Assignment and Control (CTAC)..
If the traffic congestion can not be mitigated even by demand management using CTAC solutions, there would be a need for capacity enhancements and addition of links to increase the network supply. Capacity enhancements usually carried out under short term improvement programme and addition of links is carried out under long term improvement programme. This is called Network Design Problem (NDP).
Most of the network analysis software like SATURN, EMME/2, TRIPS etc. needs lot of input data preparation and interpretation of the results exogenously for analyzing the transport network with respect demand and supply management measures. Hence, there is a need for development of a single model which can integrate the CTAC (for demand management measures) and NDP (supply management measures) for effective analysis of transport networks.
In this research, refined integrated model of CTAC and NDP problem, application of NDP sub model to Pune city network, field studies carried out for two component link cost functions and two component link cost functions developed for different carriageway configurations, research progress during previous year and further research activities are presented.
The first proposed model is a capacity expansion problem of finding optimum capacity vector within the budget constraint and deterministic user equilibrium assignment at lower level. The upper level has been solved using genetic algorithm and lower level by Frank Wolfe algorithm. A comparison has been drawn with various available and attempted heuristics solutions. The results after solving a small and medium sized network shows the efficiency and ability of genetic algorithm to reach a near optimal solution. Sensitivity analysis of solution obtained has been shown with variation in the demand. Finally, the model has been applied in a real network of Pune city of size (370 nodes and 1131 links) to show the efficacy of the model to handle large networks. The major contribution in this part of research work is application of model to a large city network.
The second set of proposed models are extension to first model by including vehicular emissions at lower level and upper level respectively. Recent research findings have shown that travel time variables are affected differently from vehicular emissions, due to traffic flow improvement strategies. So these proposed models are an attempt to reduce emissions while performing network design. The second model is an attempt to solve network design problem when the user is environment cautious. This model modifies the link cost function to incorporate both link travel time as well as emission concerns. Similarly, the third model considers planner as environment cautious and plans the optimal capacity of road network while minimizing health damage cost due to pollutants as well as total system travel time. While developing the following models it was found to realistically quantify emissions there is a need of speed dependent emission factors. Therefore, an experimental study was done to develop speed dependent emission factors. Emission factors in the form of second degree polynomial with speed as the dependent variable were developed for three categories of vehicles and four pollutants namely CO, CO2, NOx, and HC.
Later on, the fourth model named Multi-objective network design for emission and travel time trade off has been proposed. The model uses revised version of fast and elitist non-dominated sorting genetic algorithm as the optimization tool to solve the problem. The model is tested on a small, medium, and large sized test networks. The pareto-optimal solutions generated can act as a trade off between total emissions and total system travel time to account for the planner's desired objectives. The reduction in amount of emission produced while performing capacity expansion proves the necessity of considering emissions along with travel time in network design problem.
The last part of the study i.e. fifth model deals with efficient solution techniques for network design under demand uncertainty. Presently most of such studies needs solving for large number of demand samples thus making them computationally intensive. Therefore, to overcome this limitation various efficient approaches to reduce the sample size of demand for obtaining a demand resilient network design solution have been presented. Specifically, sampling techniques for robust as well as stochastic network design problem and single point approximation and solution construction approach have been used to solve stochastic network design. The results shows the best technique for robust and stochastic network design under demand uncertainty for various demand distributions. The sixth model is a multi-objective formulation for robust network design which is solved using efficient multi-objective genetic algorithm. These studies showed the possibility of reducing the computation time and reaching a quality design solution for network design problem under uncertain demand.
Traffic network design problem attempts to and the optimal network expansion policies under budget constraints. This can be formulated as a bi-level optimization problem: the upper level determines the optimal link capacity expansion vector and the lower level determines the link flows subject to user equilibrium conditions. The lower level problem represents the driver's behavior in the sense that how he chooses the route. This behavior is represented using the classical Wardropian user equilibrium principles.
The first proposed model is a capacity expansion problem of finding optimum capacity vector within the budget constraint and Deterministic User Equilibrium assignment (DUE) at lower level. The upper level has been solved using Gentic Algorithm (GA) and lower level by Frank Wolfe algorithm. A comparision has been drawn with various available and attempted heuristics solutions. The results after solving a small and medium sized network shows the efficiency and ability of GA to reach a near optimal solution. Finally, the model has been applied in a real network of Pune city of size (370 nodes and 1131 links) to show the efficacy of the model to handle large networks. The major contribution in this part of research work is application of model to a large city network.
The second proposed model is extension to first model by including emission pricing at lower level. Traditionally, path travel time is identified as the sole criterion in choosing a particular route. However, in the context of emission pricing, driver's route choice includes travel time as well as environmental concerns. This model is an attempt to solve network design problem when the user is environment cautious. The problem is formulated as a bi-level continuous network design problem with the upper level problem determines the optimal link capacity expansions subject to user travel behavior. The link cost function is modified to incorporate both link travel time as well as emission concerns. Although the link cost function is modified, it is still convex and is therefore solved using convex combination method or Frank-Wolfe algorithm. The upper level problem is an example of system optimum assignment and can be solved using any efficient optimization algorithms. To illustrate the working of the model a small example network has been solved by the proposed algorithms. The reduction in amount of emission produced while performing capacity expansion proves the necessity of emission pricing. Then a medium sized network of Fort Area, Mumbai was further tested to study various computational and sensitivity analysis. The results further give direction to future work to evolve up with speed dependent emission factors. The speed dependent emission factor will give a better view of reduction in emission with improvement in travel time while performing optimal capacity expansion.
In addition to the above models, a new model for reliabilty analysis of transportation network has been proposed by modifying the basic model. This model at upper level has a objective of maximising the network reliabilty of a transportation network rather than optimally expanding the network.
Researches on traffic flow modelling were concentrated on various areas like mid-block, intersections and ramps, and many of the works were on homogeneous traffic conditions. In developing nations like India, the traffic scenario is even more chaotic, as the element of heterogeneity is brought in by varying vehicular, human, road and environmental factors. Simulation have established as a very vital tool for the traffic analyst, in getting to know more about the traffic flow and to verify the performance of control systems. Cellular automata(CA), a new entrant to this area, introduced a concept of minimal modelling, against the complex modeling procedures being in use till then. It has proven to be computationally efficient in analysing mid-block traffic for homogeneous and heterogeneous conditions.
A few works have been done using CA based simulation on intersections and networks too, but most of them are single-lane, with homogeneous traffic conditions, leaving a wide area open for exploration in the heterogeneous traffic flow in developing countries. The ultimate objective of this study is to develop a computationally efficient network level traffic flow model using CA for urban conditions prevailing in developing nations like India. The model is developed in phases, starting with a four legged signalized intersection as the base module. A network model is then to be built. The model is to be validated with real field data, and compared with established simulation models.
Emission inventory models estimate emissions using vehicular activity data and emission factors The accuracy of the inventory models, therefore, greatly depends on the accuracy of the emission factors and information on vehicle activity The emission factors derived from the real-world driving cycle can provide better estimates of emissions for an urban area Hence, the critical component of all emission models is a driving cycle representing the traffic behaviour Although, standard/ certification Indian driving cycles for motorized two-wheelers and modified Indian driving cycle for cars were developed to test the compliance of Indian vehicles to the relevant emission standards, they neglect higher speed and acceleration and assume all vehicle activities to be similar Therefore, in this study, an attempt has been made to develop a real-world driving cycle using micro-trips extracted from real-world data for estimating emission factors for selected pollutants for an urban region Micro-trip is an excursion between two successive time points at which the vehicle is stopped (idle) This part of motion consists of acceleration, cruise and deceleration modes By convention, a period of rest is at the beginning and end of a micro-trip Each vehicle trip representing speed-time profile of different operating modes of vehicle operation is divided at each idle value.
The uniqueness of this methodology is that the driving cycle is constructed considering five important parameters of the time-space profile, namely, the percentage acceleration, deceleration, idle, cruise, and the average speed and is based on new concept of micro-trips Therefore, this approach is expected to be a better representation of heterogeneous traffic behaviour The real-world driving cycle for the city of Pune in India is constructed for cars and motorized two-wheelers and is compared with existing synthesized cycles Since Pune city has the highest motorised two-wheelers followed by cars and due to limited resources, real-world driving cycles were developed for cars and motorised two-wheelers only However, severe acceleration and deceleration modes of the real-world driving cycle make them difficult to drive on chassis dynamometer thereby limiting its acceptability.
In order to demonstrate the feasibility of testing real-world driving cycle on chassis dynamometer and to develop the emission factors, a chassis dynamometer test has been performed Further, the same vehicles were tested using the conventional driving cycle and the measured values of exhaust emissions was compared Four vehicles, namely, two passenger cars and two motorized two-wheelers each of different age brackets representing old and new technology, was randomly selected from the field and tested on the chassis dynamometer It was observed that the emission factors obtained with the real-world driving cycle are most of the time higher than the synthesized cycles for a given vehicle Therefore, real-world driving cycle gives better insight to the relationship between micro-level driving behaviour and emissions which will be useful in various emission control measures.
The emission factors so obtained from the chassis dynamometer tests and vehicular activity data collected are further used as input parameters in inventory models for estimating total emissions A survey format (questionnaire) was designed to collect vehicle factors and its utilization characteristics that have major influence on emission at selected fuel stations in the vicinity of major intersections The data such as vehicle type, make, model year, fuel used, annual distance traveled, vehicle mileage, average speed, fuel consumption and fuel efficiency was collected from the primary survey Approximately 10,000 data samples were collected from the 21 fuel stations covering different categories of the vehicles such as motorized two-wheelers, cars, taxies, three-wheeled auto-rickshaws, buses, light commercial vehicles and Heavy commercial vehicles The vehicular activity data and emission factors obtained above was used to build two emission inventory models, namely, Average Speed based Emission Model and Fuel Consumption based Emission Model The former involves use of emission factor, cold start, vehicle related parameters like number of vehicles, age of the vehicle, fuel type, average speed and average period of vehicle operation per day The corrections are made in the abstract of the revised report as: The latter uses the fuel consumption and vehicle mileage other than emission factor and number of vehicles These models improve on existing models that are not completely suitable for Indian roads (narrow roads, variation in width of the roads, structural and function condition of roads), traffic conditions (congested, absence of lane discipline) and heterogeneity of vehicles in India This study presents an air quality assessment for a typical urban area like Pune city, India.
Keywords: Driving cycle, Driving characteristics, Micro-trips, Matrices, Chassis dynamometer, Emission factor, emission inventory modeling and Emissions
In the present study, several popular and widely used car following models are evaluated using substantial field data collected under hetergeneous traffic conditions. The data was collected using vehicles equipped with global positioning system (GPS) receivers under heterogeneous traffic conditions from two urban arterials in India. The models are evaluated by comparing several measures of error between the observed and computed model values. The error values are computed after calibrating the model specific parameters by minimizing the error using Genetic algorithm (GA) as the optimization tool. Subsequently, the models are validated with the calibrated parameters using different data set. All these analysis are done separately on data sets corresponding to different lead and following vehicular combinations. Six vehicle combinations are selected by considering car, auto rickshaw, and bus as lead and following vehicles. The desired spacing of vehicle are different for each vehicular combination, indicating the existence of distinct car following behaviour. Similar conclusions are derived from the calibrated sensitivity coefficients for each vehicular combination. From the study, Gipps and Krauss models emerged as the best models and Theil's coefficient as the most suitable measure of error. Based on the results of car following models studied, few modifications to the existing models are suggested. In real traffic conditions, driver may be observing not only the preceding vehicle but a line of vehicles in front. So the study of platoon behaviour consisting of multiple vehicles may be of interest. This is particularly important in heterogeneous traffic conditions where the fast moving vehicles form a queue behind slow moving vehicles leading to traffic jam. Finally the report ends with a lead to the study of this particular platoon stability also called asymptotic stability behaviour in heterogeneous traffic.
The conventional traffic assignment models do not consider the junction delay due to signal control. Whereas the signal design assumes constant link flows. Thus the signal setting affects the traffic assignment and visa versa. This interdependency is not considered when the signal setting and traffic assignment are done in isolation. The mutual interaction between user route choices and signal control decisions to arrive at network traffic equilibrium is investigated in this study.
Accordingly, a bi-level optimisation model is proposed. The lower level problem represents Wardrop's user equilibrium model, which incorporated driver's reaction to a given signal control pattern. The upper-level problem is to determine an optimal green split that minimizes the system objective function of total network travel time, taking account of driver's route choice behavior in response to signal split changes. The lower level problem is formulated as a user equilibrium problem and solved using the Frank Wolfe algorithm. The solution to the upper level problem is obtained using genetic algorithm. The link travel time function is modified by adding the signal delay term retaining the convexity property of the function. Two variations of the model are proposed; the first optimising the green split and the second optimising the green split and cycle time.
Both models are tested on a small example network. The study on the example network demonstrated the working of the new combined traffic assignment and signal control problems and the need for combining the present network equilibrium assignment techniques with the signal setting to get a better assignment solution.
The models are also applied for a real medium sized network of the city of Bombay for two peak hours. The results indicate the changes in the link flows and the reduction in the system travel time. The second model performs better in terms of a lower system travel time and smooth convergence of link flows.
Indian metropolitans have evidenced rapid rate of growth from decades due to surging economy. Traffic demand has increased tremendously due to increase in population as well as vehicle ownerships. Cities are expanding and becoming overcrowded limiting the breadth of road network.
In order to cater the peaking demand it has become essential to adopt effective Traffic Management Systems. One of such aspect is Area Traffic Control (ATC) system. Presently ATC systems like SCOOT and SCAT are popular in advance countries but such systems cannot cope up with Indian situations without adaptation to Indian traffic scenario.
An indigenous Area Traffic Control System is developed by Center for Development of Advance Computing known as Composite Signal Coordination Strategy (CoSiCoSt). Study presented herein aims at evaluating this system and its effectiveness in Indian scenario.
For evaluation data was collected and by using Highway Capacity Manual (HCM) procedure delay is computed. A spreadsheet is modeled which computes critical demand to capacity ratio, degree of saturation of intersection, delay per lane group, delay per approach and delay for intersection as a whole. However the results computed where much on higher side the reason being insufficient data and factors directly adopted from HCM.
Further, heterogeneous traffic at one of the junction in the selected corridor is simulated in VISSIM. This software is based on car following theory. VISSIM provides wide range of results like average travel time, speed, delay, length of queue, delay caused due to transits etc. However, the results obtained cannot be directly relied upon without being compared with actual delay.
In order to get reliable results it becomes essential to crosscheck and calibrate HCM models as well as VISSIM accordingly. For this an exhaustive survey is planned for collection of actual field delay and data to for calibration of HCM and VISSIM. Once the models are calibrated, delay and other performance measure are estimated for coordinated movements along the corridor. Survey for measuring delay after implementation of the CoSiCoSt will be done and impact of Area Traffic Control System will be evaluated.
The objective of this study is to develop an architecture for an area traffic control system suitable for heterogeneous traffic conditions. Scope of the study includes:
The broad objective of this study is to develop methodologies for valuating the performance of ATC systems under heterogeneous traffic conditions. For this study, ATC system deployed by CDAC, India, namely Composite Signal Control Strategy (CoSiCoSt) is selected. To achieve above objective, the scope of study are as follows:
This study mainly attempts to develop a methodology to integrate the transportation planning model and a traffic engineering model. The individual consideration of the models and the optimization is no longer useful in the field of transportation and especially in congested networks. This motivated to consider the combination of these models to have a flow of traffic in a congested network and decrease the delay at intersections and travel time on links. This is obtained with effective consideration of the offsets concept with signal coordination in the signal control model. A problem is formulated with constraints. The problem is handled by using the optimizing technique .This technique is used to optimize a network performance index, the total network travel time. This total travel time includes link travel time and junction delays. This problem is solved in two stages, referring the both stages as upper stage and lower stage. The upper stage is dealt with the signal control and lower stage is dealt with User Equilibrium assignment. The study is mainly focused on small and medium sized networks.
The objective of this study is to develop a public transit fleet management considering the variability in the travel time and to develop a passenger information system suitable for trip planning. The scope of the study includes:
The objective of this project is to develop a loop detector based permanent traffic data collection and video surveillance system for an urban arterial. The scope of the study include:
Travel time reliability is increasingly being recognized as a major factor influencing travel decisions and, consequently, as an important performance measure in transportation management. In this project study a thorough and detailed review of transportation network reliability measures is presented. The study focused on the two most important kinds of network travel time reliability namely the OD travel time reliability and the total system travel time reliability. A new procedure is used to simulate variability associated with the OD travel demand as well as network link capacities and the effect of different route choice models on the value of the travel times (both OD and total system) and on the corresponding travel time reliabilities. Numerical results are presented to examine what the aggregate impact of changes in variability caused by demand and supply variations might have on network assignment. Although the numerical results are based on a small network they clearly show the significance of the route choice model on the estimation of travel time reliability measures. The different assumptions used in modeling route choice behavior could result in different estimates of travel time reliability. Keywords: Travel time reliability, travel time variability, route choice models, traffic assignment.
Transit route network design (TRND) problem for urban bus operation involves the determination of a set of transit routes and the associated frequencies that achieves the desired objective. This can be formulated as an optimization problem of minimizing the total system cost: the sum of operating cost and the generalized travel cost. A review of previous approaches to solve this problem reveals the deficiency of conventional optimization techniques and the suitability of genetic algorithm (GA) based models to handle such combinatorial optimization problems. Since GAs are computational intensive optimization techniques, its application to large and complex problems is limited. The computational performance of GA model can be improved by exploiting their inherent parallel nature. Accordingly, two parallel computing models are proposed in this study. The first is global parallel GA model where the fitness evaluation is done concurrently in parallel processing environment. The second is an island parallel GA model where multiple GA population evolve in parallel and exchange the fittest individuals periodically. These models are implemented using both parallel virtual machine (PVM) and message passing interface (MPI), two commonly used libraries. An existing GA model for transit route network design for a large city is used as a case study. These models are tested for speedup and efficiency. From the study it is observed that global model with PVM may prove faster than other models for a similar problem.
The past decade has witnessed many developing countries opening up their economy resulting in greater private sector participation in road infrastructure projects. These countries traditionally followed economic evaluation for the project appraisal. The economic evaluation includes intangible costs and benefits of the project which do not appear in cash flow statement. Hence the economic evaluation cannot indicate the financial performance of a project. Therefore, financial evaluation is important in the context of privatization and commercialization of road projects under BOT scheme. Even though such approaches are very common in developed countries, the financing methods, tax rates and accounting techniques are quite different in developing countries. Therefore, to examine the financial performance of the project and to determine the risks involved, sound financial model are necessary. This paper presents a simulation based financial model for BOT projects. The model takes the length of road, cost of construction volume of traffic, mode wise toll rates and other project specific details as input, performs financial evaluation, and calculates IRR and NPV for project and equity separately. In addition, the model also performs sensitivity analysis and scenario analysis on critical project parameters. A case study of a 40 km road expansion project from Pune (India) has been taken to demonstrate the working of the simulation model. The model gave financially sound project and equity IRR. The sensitivity analysis showed volume of traffic and toll rates as the most sensitive parameters to financial performance for the given project.
Urban development and great mobility of people and goods have brought an enormous increase in transportation sector. While on one hand, there has been an undoubted economic growth as a result of these activities; on the other side they have raised severe environmental concerns. Transportation sector is the major source for air pollution in urban areas. Several traffic management schemes are proposed to reduce the impact of air pollution. They may range from micro level management plans like improving road surfaces, road geometry, or better intersection design. At the macro level, they may include schemes like capacity expansion, introduction of alternate mass transportation system etc. An important decision tool in such planning stage is to estimate reasonably accurately the reduction in vehicular emission. This paper presents a generalized methodology to estimate the reduction in emission due to any macro level traffic management schemes. A transport movement takes place by a transport mode on a route. The trip assignment procedure chooses the route to be followed. There are many assignment procedures available and the most popular one is the Wardrop.s User Equilibrium assignment. The basics assumption of this assignment is that a user will select a route that minimizes his/her travel time. The process of assignment selects the routes through the network and loads the trips to the links. The required inputs for assignment are the mode wise origin.destination matrix and network details. The output from the process includes the link flows and system travel costs. Once the link flows are estimated, then the emission can be computed. Based on the trips loaded on the links, the amount of pollutants emitted at the network level is quantified by emission models. Introduction of traffic management scheme will change the travel pattern and will be modeled using the revised origin-destination trip matrix. The above process is repeated and new quantities can be estimated. Emission from the vehicles depends broadly on technical and operational factors of the vehicles, which are quantified in the form of vehicular emission factors. An emission model depends on the travel-related, weather-related, vehicle-related, roadway related, traffic related and driver related factors. The above procedure is illustrated through a case study. The area taken as the case study was the fort area, Mumbai. The origin-destination trip matrix is estimated from the link counts. Link count includes cars, buses and two-wheelers. The OD matrix is assigned to the network and the link flow are computed. From the emission factors of each category of vehicles and the link length the total emission for that link is estimated. This is aggregated to the network level. Then a traffic management scheme is proposed: introduction of a rail corridor. The shift to the rail traffic is estimated by model-split model, thus providing a new OD matrix. This new OD matrix is assigned to the network to compute the new emission quantities for the network. Two pollutants namely CO and TSP (total suspended particulates) is considered in the case study.
Abstract: The density of subway travelers in Mumbai is one of the highest in the world. This level of congestion brings about significant challenges in modeling the dynamics of crowd behavior especially at while subway riders want to enter/exit the train. This study will develop fluid based particle models to understand the dynamics of crowd behavior in congested train compartments using data collected from multiple video cameras. The data will be collected during peak periods and non-peak periods both in the general and ladies compartments. The video feed will be analyzed using state of the art image processing techniques to obtain spatial and temporal characteristics of individual travelers. Similar data will be collected at the CST terminal to understand the dynamics of crowd movement in open areas. The insights obtained from this problem will be an important input into agent based simulation models and in the better design of egress for trains and design features in open terminals. (Along with Satish Ukkusuri, RPI, USA).