Journal Publications and Book Chapters
- 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.
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.
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.
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.
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.
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.
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.
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.
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.
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
Mohan, R., & Ramadurai, G. (2019). Numerical Study with Field Data for Macroscopic
Continuum Modelling of Indian Traffic. Transportation in Developing Economies, 5(2), 16.
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.
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.
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,
Munigety, C. R. (2018). Modelling behavioural interactions of drivers’ in mixed traffic conditions.
Journal of Traffic and Transportation Engineering, 5(4), 284-295.
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.
Rahul, T. M., & Verma, A. (2018). Sustainability analysis of pedestrian and cycling
infrastructure – A case study for Bangalore. Case Studies on Transport Policy.
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.
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.
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.
Verma, A., Tahlyan, D., & Bhusari, S. (2018). Agent based simulation model for improving passenger
service time at Bangalore airport. Case Studies on Transport Policy.
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.