congestion | National Center for Sustainable Transportation

Advanced Eco-Driving for Connected and Automated Vehicles in Complex Traffic Scenarios

Research Product Type

Dissertation / Thesis

In this dissertation, advanced eco-trajectory planning algorithms have been developed to address four challenges.

Advancing Seaport Environmental Sustainability: Case Studies from the San Pedro Bay Ports Clean Air Action Plan

Research Product Type

Training Resource

This brief discusses studies highlighting the institutional challenges the Port of Los Angeles and Port of Long Beach face while working with a multitude of stakeholders and regulatory bodies to address both environmental sustainability and economic competitiveness.

Automated Vehicles and Central Business District Parking: The Effects of Drop-Off Travel on Traffic Flow and Vehicle Emissions

Principal Investigator Caroline Rodier, Ph.D.
University of California, Davis

Automated vehicles have the potential to reduce the need for parking, but they also have the potential to increase congestion through picking up and dropping off passengers. This project studies such possible environmental effects.

Project Status

Complete

Centrally Coordinated Schedules and Routes of Airport Shuttles with LAX Terminals as Application Area

Research Product Type

Research Report

In this project, the authors developed a centrally coordinated shuttle scheduling and routing management system for mixed fleets of diesel and electric shuttles using a digital twin of LAX to LA downtown traffic road network by optimizing the total combined cost of energy consumption and travel time.

Centrally Coordinated Schedules and Routes of Airport Shuttles with LAX Terminals as Application Area

Principal Investigator Petros Ioannou, Ph.D.
University of Southern California

The purpose of this project is to develop a CENtrally COordinated Shuttle system (CENCOS) which can effectively coordinate airport shuttle schedules and routes in order to minimize curb congestion at the pick-up and drop-off points, reduce operational cost, improve quality of service with considerable benefits to mobility and environment.

Project Status

Complete

Congestion Reduction through Efficient Container Movement under Stochastic Demand

Principal Investigator Maged Dessouky, Ph.D.
University of Southern California

This project develops a framework for efficiently transporting empty freight containers.

Project Status

Complete

Congestion Reduction through Efficient Empty Container Movement

Principal Investigator Maged Dessouky, Ph.D.
University of Southern California

The researchers created a model to solve the "Empty Container Problem" of freight operations. They tested the model using data from the Port of Los Angeles and the Port of Long Beach.

Project Status

Complete

Congestion Reduction Through Efficient Empty Container Movement

Research Product Type

Research Report

This study proposes a mathematical model that solves the empty container problem using double and single container trucks.

Congestion Reduction Through Efficient Empty Container Movement Under Stochastic Demand

Research Product Type

Research Report

n this work, the authors developed a scheduling assignment for loaded and empty containers that builds on earlier models but incorporates stochastic (random) future demand. This report shows that the truck miles needed to satisfy the demand at all locations is reduced by about 4-7% when considering future stochastic demand as opposed to only considering today’s demand.

Congestion Reduction via Personalized Incentives

Principal Investigator Meisam Razaviyayn, Ph.D.
University of Southern California

The purpose of this research is to develop real-time algorithms to reduce traffic congestion and improve routing efficiency via offering personalized incentives to drivers.

Project Status

Complete