City Statistics

Fontana city in San Bernardino County, California has a population of 196,069.

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Network and Traffic Characteristics

The street composition based on functional class is provided below. The table on the right provides traffic characteristics such as vehicle miles traveled (VMT), vehicle hours of delay (VHD), fuel consumption, and emissions. The total VMT includes both automobile and truck trips.

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Traffic Metrics

Distribution of Average daily traffic (fig 1), Vehicle hours of delay (fig 2), and Fuel consumption (fig 3) across links are shown below.

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Streets with the highest flow

The map shows the streets with highest Average daily traffic (ADT) by road functional class.

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Trip Legs Profile

The number of trips originating from the city is 422,658 and the number of trips ending in the city is 422,736. The bar graph illustrates the distribution of trips by purpose that end in the city. The figure on the right presents a heat map showcasing the destinations of work trips.

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About Mobiliti

Mobiliti is an agent-based scalable parallel discrete event simulation platform. It ingests a road network and a travel demand model to produce a temporal representation of the traffic dynamics. The routing algorithm for generating the dynamics is a shortest travel time route, and a portion of the trips are given the ability to dynamically re-route when the vehicle starts to experience delays from congestion.

Authored by: Anu Kuncheria and Jane Macfarlane

Contributors: Cy Chan, Colin Laurence, Dimitris Vlachogiannis, Prasanna Balaprakash, Tanwi Mallick

References

Chan, C., Kuncheria, A., & Macfarlane, J. (2023). Simulating the Impact of Dynamic Rerouting on Metropolitan-scale Traffic Systems. ACM Transactions on Modeling and Computer Simulation, 33(1–2), 7:1-7:29. https://doi.org/10.1145/3579842
Chan,C., Wang,B., Bachan,J., & Macfarlane,J. (2018). Mobiliti: Scalable Transportation Simulation Using High-Performance Parallel Computing, 21st International Conference on Intelligent Transportation Systems (ITSC), Nov. 2018, pp. 634–641, iSSN: 2153-0017
Chan,C., Kuncheria,A., Zhao,B., Cabannes,T., Keimer,A., Wang,B., Bayen,A., & Macfarlane,J. Quasi-Dynamic Traffic Assignment using High Performance Computing, arXiv:2104.12911 [cs], Apr. 2021
Kuncheria, A., Walker, J.L. and Macfarlane, J. (2023). Socially-aware evaluation framework for transportation, Transportation Letters, pp. 1–18. Available at: https://doi.org/10.1080/19427867.2022.2157366.

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