Now showing 1 - 10 of 48
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    Characteristics of tail pipe (Nitric oxide) and resuspended dust emissions from urban roads – A case study in Delhi city
    (01-06-2020)
    Dheeraj Alshetty, V.
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    Kuppili, Sudheer Kumar
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    Nagendra, S. M.Shiva
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    Sethi, Virendra
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    Kumar, Rakesh
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    Sharma, Niraj
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    Namdeo, Anil
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    Bell, Margaret
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    Goodman, Paul
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    Chatterton, Tim
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    Barnes, Jo
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    De Vito, Laura
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    Longhurst, James
    Introduction: Personal exposure to elevated vehicle exhaust and non-exhaust emissions at urban roadside leads to carcinogenic health effects, respiratory illness and nervous system disorders. In this paper, an attempt has been made to investigate the exhaust and non-exhaust emissions emitted from selected roads in Delhi city. Methods: Based on the vehicular density per hour and speed, three categories of roads have been considered in the present study: (a) low density road (≤1000 vehicles/hour, V ≥ 10 m/s); (b) medium density road (>1000 vehicles/hour but ≤ 2000 vehicles/hour, V ≥ 7.5 m/s < 10 m/s); and (c) high density road (>2000 vehicles/hour, V < 7.5 m/s). At the selected roads, real-world exhaust emissions were measured using AVL DiTEST 1000 analyser. The silt load measurements were also carried out as per EPA AP-42 methodology at the selected roads. Results: Results indicated real-world NO exhaust emissions of 0.5 g/m3 (2.03 g/km) on high-density roads and 0.23 g/m3 (0.67 g/km) on low and medium density roads. These values were significantly higher than the Bharat Standard (BS) IV (0.25 g/km). The silt load on the different types of roads indicated 3, 25 and 44 g/m2 -day dust deposition on, low, medium and high-density road, respectively. PM2.5 and PM10 emission rates were measured using US-EPA AP-42 methodology and were found to be least at low-density roads with values of 0.54 and 2.22 g/VKT (VKT -Vehicle Kilometer Travelled) respectively, and highest for high density roads with values of 12.40 and 51.25 g/VKT respectively. Conclusion: The present study reveals that both tailpipe (exhaust) and resuspend able road dust (non-exhaust) emissions contributes significantly and deteriorates local air quality. Although there exists emission standards, but there are no enforced regulations for non-exhaust emissions (resuspension of road dust). Hence, there is need to regulate non-exhaust emissions on urban roads.
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    Publication
    Preface
    (01-01-2023)
    Devi, Lelitha
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    Errampalli, Madhu
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    Maji, Avijit
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    Joint Model of Application-Based Ride Hailing Adoption, Intensity of Use, and Intermediate Public Transport Consideration among Workers in Chennai City
    (01-04-2020)
    Devaraj, Aravinda
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    Ambi Ramakrishnan, Ganesh
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    Nair, Gopindra Sivakumar
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    Bhat, Chandra R.
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    Pinjari, Abdul R.
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    Pendyala, Ram M.
    The introduction of mobile application-based ride hailing services represents a convergence between technologies, supply of vehicles, and demand in near real time. There is growing interest in quantifying the demand for such services from regulatory, operational, and system evaluation perspectives. Several studies model the decision to adopt ride hailing and the extent of the use of ride hailing, either separately or by bundling them into a single choice dimension, disregarding potential endogeneity between these decisions. Unlike developed countries, the literature is sparser for ride hailing in developing countries, where the demand may differ considerably because of differences in vehicle ownership, and availability and patronage of many transit and intermediate public transport (IPT) modes (the shared modes carrying 40% shares in some cases). This study aims to bridge these gaps in the literature by investigating three interrelated choice dimensions among workers in Chennai city: consideration of IPT modes, the adoption of ride hailing services and the subsequent usage intensity of ride hailing services. The main factors influencing these decisions are identified by estimating a trivariate probit model. The results indicate that sociodemographic and locational characteristics and the availability of IPT modes influence ride hailing adoption, whereas work-related constraints and perception of other modes affect its frequency. Work and non-work characteristics affect both the dimensions of ride hailing. Further, endogeneity is observed between ride hailing and IPT adoption after controlling for these variables, whereas evidence of endogeneity is absent among other dimensions. Mainly, the model separates the effect of the exogenous influences on the usage frequency level from their effect on the adoption of ride hailing services.
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    Field data application of a non-lane-based multi-class traffic flow model
    (01-07-2020)
    Mohan, Ranju
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    Multi-class traffic flow modelling has various approaches several of which have focused on analytical proofs. A key limitation in this field of research is the limited field data applications. This study proposes a speed-gradient-based multi-class second-order model and shows its application to three different road sections, a mid-block section, a section with a bottleneck, and a section with a signal at the end, in Chennai, India. The model captures the congestion formation and dissipation phenomena well and could predict outflow and speed fluctuations generally observed in the field scenarios accurately. The prediction of traffic flow dynamics by the proposed model is also observed to be better when compared with two existing higher-order multi-class models.
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    Heterogeneous traffic flow modelling using second-order macroscopic continuum model
    (23-01-2017)
    Mohan, Ranju
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    Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the ‘gap filling’ behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.
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    A continuous-time linear complementarity system for dynamic user equilibria in single bottleneck traffic flows
    (01-06-2012)
    Pang, Jong Shi
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    Han, Lanshan
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    Ukkusuri, Satish
    This paper formally introduces a linear complementarity system (LCS) formulation for a continuous-time, multi-user class, dynamic user equilibrium (DUE) model for the determination of trip timing decisions in a simplified single bottleneck model. Existence of a Lipschitz solution trajectory to the model is established by a constructive time-stepping method whose convergence is rigorously analyzed. The solvability of the time-discretized subproblems by Lemke's algorithm is also proved. Combining linear complementarity with ordinary differential equations and being a new entry to the mathematical programming field, the LCS provides a computational tractable framework for the rigorous treatment of the DUE problem in continuous time; this paper makes a positive contribution in this promising research venue pertaining to the application of differential variational theory to dynamic traffic problems. © 2011 Springer and Mathematical Optimization Society.
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    Contagion processes on urban bus networks in Indian cities
    (01-11-2016)
    Chatterjee, Atanu
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    Bus transportation is the most convenient and cheapest way of public transportation in Indian cities. Due to cost-effectiveness and wide reachability, buses bring people to their destinations every day. Although the bus transportation has numerous advantages over other ways of public transportation, this mode of transportation also poses a serious threat of spreading contagious diseases throughout the city. It is extremely difficult to predict the extent and spread of such an epidemic. Earlier studies have focused on the contagion processes on scale-free network topologies; whereas, 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. We identify epidemic thresholds for these networks which help us in controlling outbreaks by developing node-based immunization techniques. © 2016 Wiley Periodicals, Inc. Complexity 21: 451–458, 2016.
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    Modeling the Evolution of Ride-Hailing Adoption and Usage: A Case Study of the Puget Sound Region
    (11-01-2020)
    Dias, Felipe F.
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    Kim, Taehooie
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    Bhat, Chandra R.
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    Pendyala, Ram M.
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    Lam, William H.K.
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    Pinjari, Abdul R.
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    Ride-hailing services have grown in cities around the world. There are, however, few studies and even fewer publicly available data sources that provide a basis to understand and quantify changes in ride-hailing usage over time. Ride-hailing use may change over time because of socio-demographic shifts, economic and technological changes, and service attribute enhancements, as well as changes in unobserved attributes such as attitudes and perceptions, lifestyle preferences, technology savviness, and social influences. It is important to quantify the effects of these different forces on ride-hailing frequency so that robust forecasts of ride-hailing use can be developed. This paper uses repeated cross-sectional data collected in 2015 and 2017 in the Puget Sound region to analyze the differential effects of socio-demographic variables on the evolution of ride-hailing adoption and usage. By doing so, the study is able to isolate and quantify the pure effect of the passage of time on adoption of ride-hailing services. A joint binary probit-ordered probit model is estimated on the pooled dataset to explicitly account for sample-selection differences between the 2015 and 2017 surveys that may affect estimates of ride-hailing adoption in the two years. Model estimation results are used to compute average treatment effects of different variables on ride-hailing usage over time. It is found that the effects of most demographic variables on individuals’ propensity to use ride-hailing are softening over time, leading to reduced differences in ride-hailing use among market segments. This suggests that there is a “democratization” of ride-hailing services over time.
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    Submission to the DTA2012 Special Issue: A Case for Higher-Order Traffic Flow Models in DTA
    (31-07-2014)
    Mohan, Ranju
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    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.
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    Incorporating spatial interactions in zero-inflated negative binomial models for freight trip generation
    (01-10-2021)
    Middela, Mounisai Siddartha
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    This paper formulates a spatial autoregressive zero-inflated negative binomial model for freight trip productions and attractions. The model captures the following freight trip characteristics: count data type, positive trip rates, overdispersion, zero-inflation, and spatial autocorrelation. The spatial autoregressive structure is applied in the negative binomial part of the models to obtain unbiased estimates of the effects of different regressors. Further, we estimate parameters using the full information maximum likelihood estimator. We perform empirical analysis with an establishment based freight survey conducted in Chennai. Separate models are estimated for trips generated by motorised two-wheelers and three-wheelers, and pickups besides an aggregate model. Spatial variables such as road density and indicator of geolocation are insignificant in all the models. In contrast, the spatial autocorrelation is significant in all of the models except for the freight trips attracted and produced by pickups. From a policy standpoint, the elasticity results show the importance of considering spatial autocorrelation. We also highlight the bias due to aggregation of vehicle classes, based on the elasticities.