This project will develop a practical tool for policymakers to infer the effects of alternative strategies for reducing traffic congestion in Los Angeles.
The purpose of this study is to develop an analytical framework for assignment of individual vehicular trips into viable carpooling pairs under a constrained set of reasonable restrictions, such as temporal and spatial bounds/limits and user preferences.
Community-based carpooling has the potential to alleviate traffic congestion and reduce the transportation carbon footprint. One of the major barriers to implementation is the difficulty of optimizing carpool formation in large systems. This study utilizes two different methods to solve the carpooling optimization problem: 1) bipartite algorithm and 2) integer linear programming.
This White Paper presents recommendations for using information technology solutions to increase the efficiency of California’s multi modal freight system.
This study investigates the impact of traffic-related air pollutants, specifically NO2 and PM2.5, in Riverside's Innovation Corridor, a six-mile roadway serving key urban centers and logistics activities.
This project will evaluate the impact of sustainable traffic interventions on local air quality at signalized intersections along the Innovation Corridor using a dense network of low-cost air quality monitors.
This research aims to improve freight vehicle utilization and energy efficiency (productive ton-miles per unit of energy) by modeling and evaluating the innovative shared mobility services for freight
This paper studies the problem of offering incentives to organizations to change the behavior of their individual drivers (or individuals relying on the organization’s services).
