Journal Publications and Book Chapters
- Banerjee, I., Deepa, L., and Pinjari A.R. (2020) "Public Transit Ridership Forecasting Models." Encyclopedia of Transportation. edited by Roger Vickerman et al. Forthcoming
- 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
- 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
- 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, 8(1), 108-128. https://doi.org/10.1080/21680566.2020.1721379
- Chen, T., Sze, N. N., Saxena, S., Pinjari, A. R., Bhat, C. R., & 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, 135, 105366. https://doi.org/10.1016/j.aap.2019.105366
- 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
- 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
- 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
- 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
- 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.
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Menon, N., Barbour, N., Zhang, Y., Pinjari, A. R., & Mannering, F. (2018). Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment. Forthcoming, International Journal of Sustainable Transportation. https://doi.org/10.1080/15568318.2018.1443178
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Banerjee, I., Kala, J. V., Bhat, T.M., Pinjari, A.R. (2019, December 18-21). "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.
- Shankari, K., Yedavalli P., Rashidi, T.H., Banerjee, I. (2019, May 26-31). e-mission: a platform for reproducible and extensible human travel data collection. World Conference on Transport Research, WCTR 2019 Mumbai.
- Mohan, R., & Gupta, R. K. (2020). Multi-class DTA framework for non-lane-based traffic scenario. Accepted for presentation at the 8th International Symposium on Dynamic Traffic assignment, University of Washington, Seattle.
- Mohan, R. (2019). Development of dynamic traffic assignment framework for heterogeneous traffic lacking lane discipline. Presented at the 5th Conference of Transportation Research Group of India, Bhopal, India.
- Mohan, R., & Ramadurai, G. (2019). Field data application of a non-lane based multi-class traffic flow model. Presented at the 15th World Conference on Transport Research, Mumbai, India.
- Mohan, R., Eldhose, S., & Manoharan, G. (2019). Choice of applicability of VISSIM at network level in heterogeneous traffic scenario. Presented at the 15th World Conference on Transport Research, Mumbai, India.
- Mohan, R., & Ramadurai, G. (2019). Multi-class Traffic Flow Model Based on Three-Dimensional Flow-Concentration Surface (No. 19-04534). Presented at the 98th Annual meeting of the Transportation Research Board, Washington DC.
- 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)
- Saxena, S., Pinjari, A. R., & Paleti, R. (2019, March). Multiple Discrete Continuous Choice Models with Conditional Constraints on Budget Allocations: An Application to Disaggregate Time-Use Analysis. In International Choice Modelling Conference 2019.
- Nirmale, S. K., Pinjari, A. R., & Biswas, M. (2019, March). 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. In International Choice Modelling Conference 2019.
- Biswas, M., Pinjari, A. R., & Dubey, S. K. (2019, January). Travel time variability and route choice: An integrated modelling framework. In 2019 11th International Conference on Communication Systems & Networks (COMSNETS) (pp. 737-742). IEEE. https://doi.org/10.1109/COMSNETS.2019.8711185
- 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. Proceedings of the 7th International Conference on Innovations in Travel Modeling, Atlanta.
- Munigety, C.R., & Naidu, Y. K. (2018). A driver-vehicle integrated model using car-following and engine dynamics. Presented at the 97th Annual Meeting of Transportation Research Board, Washington D.C., USA.
- Munigety, C.R., & Vishnoi, S.C. (2018). A hybrid socio-physical system-based driver behavioral model for representing traffic dynamics. Presented at the 97th Annual Meeting of Transportation Research Board, Washington D.C., USA.
- 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. Presented at the 97th Annual Meeting of Transportation Research Board, Washington D.C., USA.
- 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. Proceedings of the15th International Conference of Travel Behaviour Research, Santa Barbara.
- Rambha, T., Nozick, L., & Davidson, R. (2019) Modeling departure time decisions during hurricanes during a dynamic discrete choice framework. Accepted for presentation at the 98th Annual Meeting of Transportation Research Board, Washington D.C., USA.
- 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. Proceedings of the 7th International Conference on Innovations in Travel Modeling, Atlanta.
Reports
- 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