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Title
Journal Publications and Book Chapters
Category
undergraduate
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0bf2a1e0639f43bbb40fe668924aada3
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https://cistup.iisc.ac.in/CiSTUP_Website/pages/research/recent-pub.php
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2026-03-23T22:41:45+00:00
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# Journal Publications and Book Chapters

**Source**: https://cistup.iisc.ac.in/CiSTUP_Website/pages/research/recent-pub.php
**Parent**: https://cistup.iisc.ac.in/

1. Sharma, A., Zheng, Z., Kim, J., Bhaskar, A., & Haque, M. M. (2021). Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors.
    *Transportation Research Part C: Emerging Technologies,*  124, 102934.
    [https://doi.org/10.1016/j.trc.2020.102934](https://doi.org/10.1016/j.trc.2020.102934 )
2. Jia, D., Sun, J., Sharma, A., Zheng, Z., & Liu, B. (2021). Integrated simulation platform for conventional, connected and automated driving: A design from cyber–physical systems perspective.
    *Transportation Research Part C: Emerging Technologies,*  124, 102984.
    [https://doi.org/10.1016/j.trc.2021.102984](https://doi.org/10.1016/j.trc.2021.102984 )
3. Haque, M. M., Oviedo-Trespalacios, O., Sharma, A., & Zheng, Z. (2021). Examining the driver-pedestrian interaction at pedestrian crossings in the connected environment: A Hazard-based duration modelling approach.
    *Transportation Research Part A: Policy and Practice,*  150, 33-48.
    [https://doi.org/10.1016/j.tra.2021.05.014](https://doi.org/10.1016/j.tra.2021.05.014 )
4. Banerjee, I., Deepa, L., and Pinjari A.R. (2021). Public Transit Ridership Forecasting Models.
    *In: Vickerman, Roger (eds.) International Encyclopedia of Transportation.*  Vol. 4, pp. 459-467. UK: Elsevier Ltd.
    [http://dx.doi.org/10.1016/B978-0-08-102671-7.10367-7]( http://dx.doi.org/10.1016/B978-0-08-102671-7.10367-7 )
5. Nirmale, S.K., Pinjari, A.R., and Sharma. A.  (2021). A discrete-continuous multi­-vehicle anticipation model of driving behaviour in heterogeneous disordered traffic conditions.
    *Transportation Research Part C.* Vol. 128,  103144.
    [https://doi.org/10.1016/j.trc.2021.103144](https://doi.org/10.1016/j.trc.2021.103144 )
6. Saxena, S., and Pinjari, A.R., Roy, A., and Paleti, R.  (2021). Multiple discrete-continuous choice models with bounds on consumptions.
    *Transportation Research Part A.* Vol. 149, pp. 237-265.
    [https://doi.org/10.1016/j.tra.2021.03.016](https://doi.org/10.1016/j.tra.2021.03.016 )
7. Pellegrini, A., Pinjari, A.R., and Maggi, R.  (2021). A multiple discrete continuous model of time use that accommodates non-additively separable utility functions along with time and monetary budget constraints.
    *Transportation Research Part A.* Vol. 144, pp. 37-53.
    [https://doi.org/10.1016/j.tra.2020.11.009](https://doi.org/10.1016/j.tra.2020.11.009 )
8. Pinjari, A.R., and Bhat, C.R.  (2021). Computationally Efficient Forecasting Procedures for Kuhn-Tucker Consumer Demand Model Systems: Application to Residential Energy Consumption Analysis.
    *Journal of Choice Modelling.*  Vol. 39, 100283.
    [https://doi.org/10.1016/j.jocm.2021.100283](https://doi.org/10.1016/j.jocm.2021.100283 )
9. Balusu, S., Mannering, F.L., and Pinjari, A.R.  (2021). Hazard-based duration analysis of the time between motorcyclists’ initial training and their first crash.
    *Analytic Methods in Accident Research.* Vol.28, 100143.
    [https://doi.org/10.1016/j.amar.2020.100143](https://doi.org/10.1016/j.amar.2020.100143 )
10. Dias, F.F., T. Kim, C.R. Bhat, R.M. Pendyala, W.H.K. Lam, A.R. Pinjari, K.K.Srinivasan, Ramadurai, ​G. (2021). Modeling the evolution of ride-hailing adoption and usage: A case study of the Puget Sound region.
     *Transportation Research Record: Journal of the Transportation Research Board.* Vol. 2675(3), pp. 81-97.
     [https://doi.org/10.1177%2F0361198120964788](https://doi.org/10.1177%2F0361198120964788 )
11. Calastri, C., Hess, S., Pinjari, A.R., Daly, A. (2020). Accommodating correlation across days in multiple-discrete continuous models for time use.
     *Transportmetrica B: Transport Dynamics,* Vol. 8(1), pp. 108-128.
     [https://doi.org/10.1080/21680566.2020.1721379](https://doi.org/10.1080/21680566.2020.1721379 )
12. Devaraj, A., G.A. Ramakrishnan, G.S. Nair, K.K. Srinivasan, C.R. Bhat, A.R. Pinjari, G. Ramadurai, Pendyala, R.M. (2020). Joint Model of App-Based Ridehailing Adoption, Intensity of Use and Intermediate Public Transport (IPT) Consideration among Workers in Chennai City.
     *Transportation Research Record: Journal of the Transportation Research Board.* Vol. 2674(4), pp. 152-164.
     [https://doi.org/10.1177%2F0361198120912237](https://doi.org/10.1177%2F0361198120912237 )
13. Dias, F.F., P.S. Lavieri, S. Sharda, S. Khoeini, C.R. Bhat, R.M. Pendyala, A.R. Pinjari, G. Ramadurai, Srinivasan, K.K. (2020). A comparison of online and in-person activity engagement: The case of shopping and eating meals.
     *Transportation Research Part C,*  Vol. 114, pp. 643-656.
     [https://doi.org/10.1016/j.trc.2020.02.023](https://doi.org/10.1016/j.trc.2020.02.023 )
14. Momtaz, S.U., N. Eluru, S. Anowar, N. Keenya, B. Dey, A.R. Pinjari, F. Tabatabaee (2020). Fusing Freight Analysis Framework and Transearch Data: An Econometric Data Fusion Approach with Application to Florida.
     *ASCE Journal of Transportation Engineering, Part A: Systems.* 146(2).
     [https://doi.org/10.1061/JTEPBS.0000294](https://doi.org/10.1061/JTEPBS.0000294 )
15. Chen, T.T., Sze, N.N., Saxena, S., Pinjari, A.R., Bhat, C.R., and Bai,L. (2020). Evaluation of penalty and enforcement strategies to combat speeding offences among professional drivers: A Hong Kong stated preference experiment
     *Accident Analysis & Prevention,*  Vol. 135, 105366
     [https://doi.org/10.1016/j.aap.2019.105366](https://doi.org/10.1016/j.aap.2019.105366 )
16. Rambha, T., Nozick, L.K., and Davidson, R. (2021). Modeling Hurricane Evacuation Behavior using a Dynamic Discrete Choice Framework.
     *Transportation Research Part B: Methodological,*  150, pp.75-100.
     [https://doi.org/10.1016/j.aap.2019.105366](https://doi.org/10.1016/j.aap.2019.105366 )
17. Rambha, T., Nozick, L.K., Davidson, R., Yi, W. and Yang, K. (2021).A stochastic optimization model for staged hospital evacuation during hurricanes.
     *Transportation Research Part E: Logistics and Transportation Review,*  151, p.102321.
     [https://doi.org/10.1016/j.aap.2019.105366](https://doi.org/10.1016/j.aap.2019.105366 )
18. Simmhan, Y., Rambha, T., Khochare, A., Ramesh, S., Baranawal, A., George, J.V., Bhope, R.A., Namtirtha, A., Sundararajan, A., Bhargav, S.S. and Thakkar, N., (2020). GoCoronaGo: Privacy Respecting Contact Tracing for COVID-19 Management.
     *Journal of the Indian Institute of Science,*  pp.1-24.
     [https://doi.org/10.1016/j.aap.2019.105366](https://doi.org/10.1016/j.aap.2019.105366 )
19. Menon, N., Zhang, Y., Pinjari, A.R., & Mannering, F. (2020). A statistical analysis of consumer perceptions towards
    automated vehicles and their intended adoption. *Transportation Planning and Technology,*  43, 253-278.
    <https://doi.org/10.1080/03081060.2020.1735740>
20. Tahlyan, D., & Pinjari, A. R. (2020). Performance evaluation of choice set generation algorithms for
    analysing truck route choice: insights from spatial aggregation for the breadth first search link elimination (BFS-LE) algorithm.
    *Transportmetrica A: Transport Science,*  16(3), 1030-1061.
    [https://doi.org/10.1080/23249935.2020.1725790](https://doi.org/10.1080/23249935.2020.1725790 )
21. Zhao, D., Balusu, S. K., Sheela, P. V., Li, X., Pinjari, A. R., & Eluru, N. (2020).
    Weight-categorized truck flow estimation: A data-fusion approach and a Florida case study.
    *Transportation Research Part E: Logistics and Transportation Review,*  136, 101890.
    [https://doi.org/10.1016/j.tre.2020.101890](https://doi.org/10.1016/j.tre.2020.101890 )
22. Tahlyan, D., Balusu, S. K., Sheela, P. V., Maness, M., & Pinjari, A. R. (2020).
    An empirical assessment of the impact of incorporating attitudinal variables on model transferability.
    In K.G. Goulias & A.W. Davis (Eds.).  *Mapping the Travel Behavior Genome*  (pp. 145-165). Elsevier.
    [https://doi.org/10.1016/B978-0-12-817340-4.00009-7](https://doi.org/10.1016/B978-0-12-817340-4.00009-7 )
23. Mohan, R., & Ramadurai, G. (2020). Field data application of a non-lane-based multi-class traffic flow model.
    *IET Intelligent Transport Systems*  14(7), 657-667.
    [http://dx.doi.org/10.1049/iet-its.2019.0583]( http://dx.doi.org/10.1049/iet-its.2019.0583 )
24. Nath, R. B., & Rambha, T. (2019). Modelling Methods for Planning and Operation of Bike-Sharing Systems.
    *Journal of the Indian Institute of Science,* 99(4), 621-645.
    <https://doi.org/10.1007/s41745-019-00134-8>
25. Rambha, T., E., Jafari., & Boyles, S.D. (2019). Transportation Network Issues in Evacuation. In K. K. Stephens (Eds.),
     *New Media in Times of Crisis*  (pp. 144-161). New York, NY: Routledge.
26. Menon, N., Barbour, N., Zhang, Y., Pinjari, A. R., & Mannering, F. (2019).
    Shared autonomous vehicles and their potential impacts on household vehicle ownership:
    An exploratory empirical assessment.  *International Journal of Sustainable Transportation,*  13(2), 111-122.
    <https://doi.org/10.1080/15568318.2018.1443178>
27. Gurram, S., Stuart, A. L., & Pinjari, A. R. (2019). Agent-based modeling to estimate exposures
    to urban air pollution from transportation: Exposure disparities and impacts of high-resolution data.
    *Computers, Environment and Urban Systems,*  75, 22-34.
    [https://doi.org/10.1016/j.compenvurbsys.2019.01.002](https://doi.org/10.1016/j.compenvurbsys.2019.01.002 )
28. Ma, J., Ye, X., & Pinjari, A. R. (2019). Practical Method to Simulate Multiple Discrete-Continuous Generalized Extreme
    Value Model: Application to Examine Substitution Patterns of Household Transportation Expenditures.
    *Transportation Research Record,*  2673(8), 145-156.
    <https://doi.org/10.1177/0361198119842819>
29. Pinjari, A. R. (2019). Recent Advances in Transportation Research.
    *Journal of the Indian Institute of Science,* 
    99(4), 549-551. [https://doi.org/10.1007/s41745-019-00136-6](https://doi.org/10.1007/s41745-019-00136-6 )
30. Mohan, R. (2019). Multi-class AR model: comparison with microsimulation model for traffic flow
    variables at network level of interest and the two-dimensional formulation. *International Journal of Modeling and
    Simulation.* <https://doi.org/10.1080/02286203.2019.1675015>
31. Mohan, R., & Ramadurai, G. (2019). Numerical Study with Field Data for Macroscopic
    Continuum Modelling of Indian Traffic. *Transportation in Developing Economies,*  5(2), 16.
    [https://doi.org/10.1007/s40890-019-0081-9](https://doi.org/10.1007/s40890-019-0081-9 )
32. Balusu, S. K., Pinjari, A. R., Mannering, F. L., & Eluru, N. (2018).
    Non-decreasing threshold variances in mixed generalized ordered response models:
    A negative correlations approach to variance reduction. *Analytic Methods in Accident Research,* 20, 46-67. <https://doi.org/10.1016/j.amar.2018.09.003>
33. Mayakuntla, S. K., & Verma, A. (2018). A novel methodology for construction of driving
    cycles for Indian cities. *Transportation Research Part D: Transport and Environment,*  65, 725–735.
    <https://doi.org/10.1016/j.trd.2018.10.013>
34. Munigety, C. R. (2018). A spring-mass-damper system dynamics-based driver-vehicle
    integrated model for representing heterogeneous traffic. *International Journal of Modern Physics B,* 
    32(11). <https://doi.org/10.1142/S0217979218501357>
35. Munigety, C. R. (2018). Modelling behavioural interactions of drivers’ in mixed traffic conditions.
    *Journal of Traffic and Transportation Engineering,*  5(4), 284-295.
    <https://doi.org/10.1016/j.jtte.2017.12.002>
36. Rahul, T. M., & Verma, A. (2017). The influence of stratification by motor-vehicle ownership on
    the impact of built environment factors in Indian cities.  *Journal of Transport Geography,*  58, 40–51.
    <https://doi.org/10.1016/j.jtrangeo.2016.11.008>
37. Rahul, T. M., & Verma, A. (2018). Sustainability analysis of pedestrian and cycling
    infrastructure – A case study for Bangalore. *Case Studies on Transport Policy.*
    <https://doi.org/10.1016/j.cstp.2018.06.001>
38. Rambha, T., Boyles, S. D., Unnikrishnan, A., & Stone, P. (2018). Marginal cost pricing
    for system optimal traffic assignment with recourse under supply-side uncertainty.
    *Transportation Research Part B: Methodological,*  110, 104–121.
    <https://doi.org/10.1016/j.trb.2018.02.008>
39. Sharon, G., Albert, M., Rambha, T., Boyles, S., & Stone, P. (2018). Traffic Optimization for a
    Mixture of Self-Interested and Compliant Agents. In *AAAI Conference on Artificial Intelligence.*
    <https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16414>
40. Verma, A., Raturi, V., & Kanimozhee, S. (2018). Urban Transit Technology Selection for Many-to-Many Travel
    Demand Using Social Welfare Optimization Approach. *Journal of Urban Planning and Development,*  144(1), 4017021.
    <https://doi.org/10.1061/(asce)up.1943-5444.0000409>
41. Verma, A., Tahlyan, D., & Bhusari, S. (2018). Agent based simulation model for improving passenger
    service time at Bangalore airport. *Case Studies on Transport Policy.*
    <https://doi.org/10.1016/j.cstp.2018.03.001>

# Conference Publications

1. Agarwal, P. and T. Rambha. (2021). An Empirical Analysis of the Effect of Travel Time Variability on Transit Routing.
    *International Conference on COMmunication Systems & NETworkS,*  Bangalore, India.
2. Rambha, T., M. Albert, G. Sharon, S. D. Boyles, and P. Stone. (2019). Identifying Compliant Users Needed for Social Optimum Routing in Traffic Networks.
    *TRISTAN X,*  Hamilton Island, Australia.
3. Singh, N. and T. Rambha. (2019). Offline Optimization of Cab Supply for Ride-Sharing Applications using Hypergraph Matching.
    *15th World Conference on Transport Research,*  Mumbai, India.
4. Kushwaha, V., Pinjari, A.R., and Sundaresan R. (2021). Evaluating the Benefit of Collaboration between Rideshare and Transit Service Providers
    *COMSNETS 2021: International Conference on COMmunication Systems & NETworkS*
5. Biswas, M., Pinjari, A.R., and Ghosh, S. (2020). A Choice Modeling Framework with Stochastic Variables and Random Coefficients
    *COMSNETS 2020: International Conference on COMmunication Systems & NETworkS*
6. Nirmale, S.K., and Pinjari, A.R. (2020). Discrete-Continuous Choice Framework to Model Driver Behaviour in Heterogeneous Traffic Conditions
    *COMSNETS 2020: International Conference on COMmunication Systems & NETworkS*
7. Nirmale, S.K., Pinjari, A.R., and Munigety, C. R. (2019). A copula-based joint multinomial discrete-continuous choice framework to model driver behaviour in mixed traffic conditions
    *WCTR 2019: World Conference on Transport Research*
8. Nirmale, S.K., and Pinjari, A.R. (2020). Driver Behaviour Models with Perception Errors: A Choice Modelling Framework with Stochastic Variables
    *TRB 2020: Annual Meeting of the Transportation Research Board*
9. Saxena, S., Pinjari, A.R., Roy, A., and Paleti, R (2021). Multiple Discrete-Continuous Choice Models with Bounds on Consumption: Application to Episode-level Activity Participation and Time use Analysis.
    *TRB 2021: Annual Meeting of the Transportation Research Board*
10. Saxena, S., Pinjari, A.R., and Paleti, R (2020). A Multiple Discrete-Continuous Modelling Framework for Disaggregate Activity Participation and Time-Use Analysis
     *TRB 2020: Annual Meeting of the Transportation Research Board*
11. Saxena, S., Pinjari, A.R., and Paleti, R (2019). Multiple Discrete Continuous Choice Models with Conditional Constraints on Budget Allocations: An Application to Disaggregate Time-Use Analysis.
     *ICMC 2019: International Choice Modelling Conference*
12. Pellegrini, A., Saxena, S., Pinjari, A.R., and, Dekker, T. (2019). Alternative non-additively separable utility functions for random utility maximization-based multiple discrete continuous models.
     *ICMC 2019: International Choice Modelling Conference*
13. Saxena, S., Pinjari, A.R., Paleti, R., and Tahlyan, D. (2019). A Rank Ordered Logit Multivariate Count Data Framework for Analysing Route Choice Portfolios
     *WCTR 2019: World Conference on Transport Research*
14. Banerjee, I., Kala, J. V., Bhat, T.M., Pinjari, A.R. (2019). Transit ridership forecasting models: design considerations and a case study for Bangalore
    [Accepted for presentation]  *5th Conference of Transportation Research Group of India, CTRG,*  Bhopal, India.
15. Shankari, K., Yedavalli P., Rashidi, T.H., Banerjee, I. (2019). e-mission: a platform for reproducible and extensible human travel data collection.
     *World Conference on Transport Research, WCTR 2019,*  Mumbai.
16. Mohan, R., & Gupta, R. K. (2020). Multi-class DTA framework for non-lane-based traffic scenario.
    [Accepted for presentation]  *8th International Symposium on Dynamic Traffic assignment,*  University of Washington, Seattle.
17. Mohan, R. (2019). Development of dynamic traffic assignment framework for heterogeneous traffic lacking lane discipline.
     *5th Conference of Transportation Research Group of India,*  Bhopal, India.
18. Mohan, R., & Ramadurai, G. (2019). Field data application of a non-lane based multi-class traffic flow model.
     *15th World Conference on Transport Research,*  Mumbai, India.
19. Mohan, R., Eldhose, S., & Manoharan, G. (2019). Choice of applicability of VISSIM at network level in heterogeneous traffic scenario.
     *15th World Conference on Transport Research,*  Mumbai, India.
20. Mohan, R., & Ramadurai, G. (2019). Multi-class Traffic Flow Model Based on Three-Dimensional Flow-Concentration Surface (No. 19-04534).
     *98th Annual meeting of the Transportation Research Board,*  Washington DC.
21. Rambha, T., Nozick, L., & Davidson, R. (2019). Modeling Departure Time Decisions During Hurricanes Using a Dynamic Discrete Choice Framework.
    *Transportation Research Board Annual Meeting.*  (No. 19-06045)
22. Nirmale, S. K., Pinjari, A. R., & Biswas, M. (2019). Multi-stimuli driver behaviour models with perception errors: An integrated latent variable and discrete-continuous framework with empirical applications to heterogeneous and homogeneous traffic conditions.
    *International Choice Modelling Conference 2019.*
23. Biswas, M., Pinjari, A. R., & Dubey, S. K. (2019). Travel time variability and route choice: An integrated modelling framework.
     *11th International Conference on Communication Systems & Networks (COMSNETS)*  (pp. 737-742). IEEE.
24. Gurram, S., A.L. Stuart, & Pinjari, A.R. (2018). Impacts of Transit-Oriented Compact-Growth on Air Pollutant Concentrations and Exposures in the Tampa Region.
     *7th International Conference on Innovations in Travel Modeling,*  Atlanta.
25. Munigety, C.R., & Naidu, Y. K. (2018). A driver-vehicle integrated model using car-following and engine dynamics.
     *97th Annual Meeting of Transportation Research Board,* Washington D.C., USA.
26. Munigety, C.R., & Vishnoi, S.C. (2018). A hybrid socio-physical system-based driver behavioral model for representing traffic dynamics.
     *97th Annual Meeting of Transportation Research Board,* Washington D.C., USA.
27. Munigety, C.R., Ramesh, A. K., & Vishnoi, S.C. (2018). A multi-regime car-following model for representing vehicle-type dependent driving behavior in mixed traffic.
     *97th Annual Meeting of Transportation Research Board,* Washington D.C., USA.
28. Nirmale, S., & Pinjari, A.R. (2018). Influence Zone, Multi-Stimuli, and Two-Dimensional (IZMS-2D) Driving Behavior in Heterogenous Traffic Conditions: An Econometric Framework and Exploratory Analysis of Driving Behaviours in India.
     *15th International Conference of Travel Behaviour Research,*  Santa Barbara.
29. Tahlyan, D., Sheela, P.V., Maness, M., & Pinjari, A.R. (2018). Improving the Spatial Transferability of Travel Demand Forecasting Models: An Empirical Assessment of the Impact of Incorporating Attitudes on Model Transferability.
     *7th International Conference on Innovations in Travel Modeling,* Atlanta.

# Reports

1. Centre for infrastructure, Sustainable Transport, and Urban Planning. (2019) *"Development of a Traffic Modelling Framework for Analysis of Strategies Aimed
   at Decongesting Phase I, Electronics City, Bangalore."*  Electronics City Industrial Township Authority