Autonomicity: A Modeling Framework for Equitable Policy Analysis for Future Transportation

Research Team: Jay Jayakrishnan (lead) and Michael Hyland

UC Campus(es): UC Irvine

Problem Statement: Travelers in the Los Angeles region spend over 100 hours in congestion a year. Reducing congestion has been the focus of much research and policy discussions, but the advent of shared mobility schemes as well as the future possibility of autonomous vehicles has only made finding a solution more complicated. Currently, many researchers and policy makers believe that tolling roads may hold the key to changing drivers’ behavior and improving the efficiency of the transportation system. However, many newly constructed toll roads have failed to attract the expected number of drivers, resulting in underutilized road capacity. Furthermore, some drivers see tolling as an unfair burden on their ‘right’ to free travel on urban roads, making congestion pricing policies politically difficult to implement in the United States and around the world.

Project Description: This project will leverage an agent‐based simulation platform (“Autonomicity”) that was developed at UC Irvine to study options for efficient and equitable congestion pricing for multiple types of road users, including low‐income populations. For instance, this smart mobility platform could be used to study a scenario where travelers desiring a faster travel option pay for it, and those willing to forgo the fastest option could receive incentives. Two main modules to be introduced into Autonomicity will be: 1) a pricing module to find the optimal tolls/incentives, and 2) a dynamic traffic assignment module to find optimal systemwide traffic patterns. The research will produce a user‐friendly decision‐support tool for policymakers.

Status: In Progress

Budget: $142,225