Traffic during peak hours is getting worse over time and the duration of the peak is increasing in most metropolitan areas as more drivers try to use limited roadway capacity. Bottlenecks caused by traffic incidents or road construction limit roadway capacity even further and can cause traffic “shock waves.” When an incident causes a highway lane to close unexpectedly, vehicles are forced to change lanes close to the incident and at low speeds. These forced lane changes interfere with traffic flow in open lanes and decrease the overall flow of the roadway. Heavy-duty trucks can exacerbate congestion because they are larger and slower than passenger vehicles. Advanced technologies may help to improve traffic flow in these situations. Variable speed limits can change based on road, traffic, and weather conditions. Speed limits can be reduced in real time when congestion is imminent to smooth traffic flow and handle more traffic volume at a slower, but not stop-and-go, speed. Lane change control systems provide lane change recommendations well upstream of blocked lanes, spreading lane changes over a greater distance and minimizing bottlenecks that disrupt traffic flow.

This policy brief summarizes findings from researchers at the University of Southern California who simulated traffic patterns along a section of Interstate 710 near the Ports of Long Beach/Los Angeles, a congested area that gets substantial truck traffic. They simulated the use of variable speed limit and lane change control systems to evaluate the potential traffic impacts of these systems.

This brief is based on research from two NCST projects: Eco-Friendly Intelligent Transportation System Technology for Freight Vehicles, and Reducing Truck Emissions and Improving Truck Fuel Economy via ITS Technologies.

The aim of this project is to use intelligent transportation system (ITS) technologies that take into account the presence of trucks in the traffic flow, in order to improve impact on the environment by reducing fuel consumption and pollution levels in areas where the truck volume is relatively high. The work is divided into two parts.

In the first part, we propose an integrated variable speed limit (VSL), ramp metering (RM) and lane change (LC) controller using feedback linearization. The proposed integrated controller keeps the bottleneck flow at the maximum level and homogenizes the density and speed of the traffic flow along the highway sections. This improvement of the traffic flow characteristics lead to improved fuel economy and reduction in tailpipe emissions of both trucks and passenger vehicles. In order to evaluate the performance of the integrated traffic controller, a microscopic traffic simulation network of the I-710 highway, which is connected to the Ports of Long Beach/Los Angeles and has high truck volume, is developed. We use Monte-Carlo traffic flow simulations to demonstrate that the integrated traffic controller can generate consistent improvements with respect to travel time, safety, fuel economy and emissions under different traffic conditions.

In the second part, we compared the proposed feedback linearization controller with the widely-used model predictive traffic controller in terms of performance and robustness with respect to perturbations on traffic demand, model parameters and measurement noise. Results show that both controllers are able to improve the total time spent, which leads to improvements in fuel economy and emissions, under different levels of perturbation and noise. The feedback linearization controller however, guarantees good performance and robustness properties than the model predictive controller with much less computational effort.

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This report presents the work performed in collaboration with University of California, Riverside (UCR) as part of a project to University of California, Davis funded by the California Energy Commission (CEC).

The aim of the project is to research intelligent traffic control strategies, which will have positive impact on the environment by reducing fuel consumption and pollution levels in areas where the truck volume is relatively high, using as an example for demonstration a network adjacent to the twin ports of Los Angeles and Long Beach.

The work is divided into two parts. The first part involves the development of a microscopic traffic simulation network in a selected area around the Ports of Long Beach/Los Angeles in collaboration with UCR to be used for simulation studies of different Intelligent Transportation Technologies for traffic flow control.

The second part deals with the evaluation of the impact of combined variable speed limit (VSL) and lane change control on the environment during highway incidents where the volume of trucks is relatively high. We use the simulation model developed in the first part to carry out microscopic Monte-Carlo traffic flow simulations of traffic in order to evaluate the benefits of combined VSL and lane change control during incidents on I-710 that involve closure of lanes and capacity drops. We demonstrated that this combined control strategy is able to generate consistent improvements with respect to travel time, safety, and environmental impact under different traffic conditions and incident scenarios.

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In the last few decades, efforts to reduce emissions from heavy-duty diesel trucks (HDDTs) and their health impacts have been focused on imposing increasingly stringent emissions standards. This has led to significant advancements in emission control technologies and alternative fuel vehicle technologies. While these technologies are effective at reducing emissions from HDDTs, the turnover of the existing HDDT population to these advanced technologies would require a large amount of investment and along time. In the near term, other efforts to reduce emissions of the existing HDDTs and mitigate their impacts on communities are needed. Many studies have shown the promise of intelligent transportation systems (ITS) technologies in reducing the energy consumption and environmental footprint of people and goods movement through various means. This research is aimed at developing and evaluating eco-friendly ITS strategies for freight vehicles and traffic, with a focus on strategies that are applicable to the transportation systems in the South Coast Air Basin. Four specific strategies are examined in this research, including: 1) connected eco-driving, 2) truck eco-routing, 3) integrated traffic control, and 4) intelligent parking assist. This report describes the evaluation of each strategy, discusses results, and provide recommendations for future implementation.

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