The Los Angeles/Long Beach area is important for freight as it involves the twin ports and warehouses and freight hubs. The way freight is consolidated and distributed affects what is going on within the terminals and roadway and rail networks. The complexity and dynamics of the multimodal transportation networks in Los Angeles/Long Beach region that are also shared by passengers, together with the unpredictability of the effect of incidents, disruptions and demand, in temporal and special coordinates makes the local impact analysis of freight transportation a very challenging task despite recent advances in information technologies.

Under this project, the researchers developed a set of traffic simulation models for the Los Angeles/Long Beach region that allowed them to evaluate the impact of new traffic flow control systems, vehicle routing, policy interventions such as land use changes and other ITS technologies on the efficiency of the transportation system and on the environment. The developed simulation models include: macroscopic simulation model for studying and evaluating large traffic networks, and microscopic simulation model for smaller networks. The macroscopic model focusses on flows and covers a much larger area as it is computationally much more efficient than the microscopic one. The microscopic model models the motion of each truck and vehicle, traffic lights, stop signs, speed limits, traffic rules etc. and resembles the real situation as close as possible.

The developed simulation models have been used to evaluate different systems and application scenarios, including freight priority traffic signal control, multimodal freight routing and the impact analysis of the spatial pattern changes of warehousing and distribution.

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This is the final report for the project entitled "Evaluation of the Effects of Intelligent Cruise Control Vehicles in Mixed Traffic". The project was initially under MOU392 and switched to Task Order 4217 at the beginning of the 2nd year of the project. Due to this administrative change a final report was submitted to PATH for MOU392 covering all the tasks completed during the 1st year of the project. The two research tasks that were not completed under MOU392 became the main focus of Task Order 4217.

Automatic vehicle following is an important feature of a fully or partially automated highway system (AHS). The on-board vehicle control system should be able to accept and process inputs from the driver, the infrastructure and other vehicles, perform diag- nostics and provide the appropriate commands to actuators so that the resulting motion of the vehicle is safe and compatible with the AHS objectives. The purpose of this paper is to design and test a vehicle control system in order to achieve full vehicle automation in the longitudinal direction for several modes of operation, where the infrastructure manages the vehicle following. These modes include autonomous vehicles, cooperative vehicle following and platooning. The vehicle control system consists of a supervisory controller that processes the inputs from the driver, the infrastructure, other vehicles and the on-board sensors and sends the appropriate commands to the brake and throttle controllers. In addition, the controller makes decisions about normal, emergency and transition operations. Simulation results of some of the basic vehicle following maneu- vers are used to verify the claimed performance of the designed controllers. Experiments on I-15 that demonstrate the performance of the throttle controller with and without vehicle-to-vehicle communications in an actual highway environment are also included. Keywords: Vehicle Control, Automated Highway Systems, Automatic Vehicle Following, Supervisory Control.

The advance in research and development will make the deployment of automated vehicles a reality in the near future. The principal question is whether these technologies will lead to any benefits in terms of safety, capacity and traffic flow characteristics as they penetrate the current transportation system. Another aspect is how to exploit these technologies in order to achieve benefits without adversely affecting the efficiency of the current transportation system and the drivers who cannot afford them. The penetration of automated vehicles into the existing transportation system will lead to mixed traffic where they will coexist with manually driven vehicles. The controversial class is where automated vehicles are allowed to mix with manually driven vehicles. The motivation behind this concept is that the current roadway will not have to undergo any major changes. Vehicles will become more and more automated independent of AHS and should have the ability to operate in lanes with manually driven vehicles. As the number of automated vehicles increases, the benefits of automation will increase until saturation, where all vehicles will be automated in the same way with cruise control, air-bags, etc. At the initial stage, vehicles will be semi-automated with the capability to follow each other automatically in the same lane. These semi-automated vehicles will coexist with manually driven vehicles on the same roadway system. The purpose of this report is to analyze the requirements, issues and effects on safety and efficiency that will result from allowing semi-automated and fully-automated vehicles to operate on the existing highway system together with manually driven vehicles. Two scenarios are considered : in the first scenario no changes are assumed for the current roadway system. In the second scenario it is assumed that the roadway controls the flow of traffic by issuing speed commands to both automated and manual vehicles. The roadway communicates via a roadway/vehicle communication with the automated vehicles system and through variable message signs with the manually driven vehicles. It is found that a number of safety and human factors issues present in both scenarios need to be resolved and studied further before mixing of semi-automated/fully-automated vehicles with manual ones becomes possible. Full automation will eliminate the driver out of the driving loop which will have serious safety implications some of which are raised and analyzed. In addition the interaction of fully automated vehicles with manual ones pose several safety problems due to the unpredictable behavior of the drivers of the manual vehicles. The effects on capacity with respect to the percentage of semi-automated vehicles penetrating the system and the derating factor due to possible lane changes are analyzed. Theoretically as the percentage of semi-automated vehicles increases, capacity also increases in most cases due to the shorter headways of the semi-automated vehicles. In practice this may not be always the case due to the unpredictability of the manually driven vehicles and the randomness of the headway used by different drivers which may further change due to presence of the semi-automated vehicles. Simulations reveal that significant improvement in the traffic flow can be achieved with a high degree of penetration of fully-automated vehicles in mixed traffic. Effects of lane- changing of fully-automated vehicles on mixed traffic capacity are analyzed. The lane- change derating factor is quantified as a function of market penetration of fully-automated vehicles for different percentages of automated vehicles changing lanes. One of the significant findings of this research is that a single semi-automated/fully- automated vehicle may attenuate large disturbances caused by rapid accelerations/decelerations and prevent the slinky effect from propagating. This attenuation is shown to take place without any effect on the travel time. The stopping of the propagation of large acceleration/deceleration transients by the automated vehicle will have positive effects on fuel consumption and pollution. KEYWORDS Automated Highway Systems (AHS), Semi-automated Vehicle, Fully- automated/Automated Vehicle, Manual/Manually driven Vehicle, Intelligent Cruise Control (ICC), Frontal Collision Warning System (FCW), Frontal Collision Avoidance System (FCA), Variable Message Signs (VMS), Roadway/Vehicle Communication System (RVCS), Degree of Penetration, Throughput, Headway, Merge Derating Factor, Slinky-effect, Sensors, Actuators, Vehicle-to-Vehicle Communication, Zone of Relevance, Global Positioning System (GPS), Minimum Safety Spacing (MSS)

This is the final report for the project entitled \Evaluation and Analysis of Automated Highway System Concepts and Architectures" in response to the contractual requirements of the Memorandum of Understanding MOU# 235, between the Partners of Advanced Transit and Highways (PATH) and the University of Southern California, administered at the University of Califor- nia at Berkeley. The purpose of this project was to select, evaluate and analyze a num- ber of promising Automated Highway System (AHS) operational concepts based on previous work. The evaluation and analysis includes headway dis- tributions for vehicle following and lane changing, capacity calculations and the modeling, analysis and control of the resulting traffic flow. The design, analysis and simulation parts of the project were performed at the Center of Advanced Transportation Technologies at the University of Southern Cali- fornia. The work performed under this project is presented in the form of five reports presented in part I, II, III, IV, and V of this final report. In addition to these reports oppy disks containing the \Inter Vehicle Spacing Software Tool" is included. Keywords: Automated Highway Systems, Vehicle Following, Vehicle Spac- ing, Highway Capacity, Highway Safety, Accident Avoidance, Collision Avoid- ance, Braking Scenarios, Brake Performance, Lane Changing, Merging, Macro- scopic Models, Tra c Flow, Hybrid Systems, Roadway Controller.

The transportation sector is responsible for 28% of US greenhouse emissions, with a considerable amount being generated by medium- and heavy-duty trucks. Multiple strategies will be needed to improve efficiency and reduce carbon dioxide (CO2) emissions in the trucking industry. Researchers at the University of Southern California developed a truck routing model that minimizes fuel consumption and reduces emissions while explicitly accounting for parking availability and hours-of-service constraints. The researchers used the model to test various scenarios that reflect the practical constraints faced by drivers.

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In this project we investigate the effect of heavy-duty trucks, equipped with different Adaptive Cruise Control (ACC) systems, on the environment and traffic flow characteristics. The sluggish dynamics of trucks whether manual or ACC that is due to their limited acceleration capabilities filter speed disturbances caused by leading vehicles and lead to beneficial effects on the environment and traffic flow characteristics. This response however may lead to higher travel times in certain situations as well as invite cut-ins from neighboring lanes causing additional disturbances. A new ACC design that is developed and experimentally tested reduces some of the negative effects of trucks in mixed traffic.

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.

Highway bottlenecks caused by traffic incidents, lane drop, ramp merging or slow vehicles negatively impact traffic mobility and safety. Traffic regulation techniques, such as adjusting speed limits, providing lane-change recommendations, and restricting on-ramp vehicle inputs with traffic signals in response to an incident, have been found to mitigate congestion from these types of bottlenecks. However, most existing research assumes that traffic models and measured traffic data are accurate and that vehicle drivers always comply with recommendations from the infrastructure. These assumptions are rarely true in the real world and can lead to inconsistencies between the theoretical benefits and the actual benefits obtained in field tests.

Researchers at the University of Southern California developed, analyzed, and evaluated an innovative approach to alleviate highway bottleneck congestion. The approach includes issuing variable-speed advisories and lane-change recommendations when needed to the upstream vehicles, as well as ramp control to manage incoming traffic, while accounting for inaccuracies in traffic data and road information and the complex behavior of human driving. This policy brief summarizes the key findings from that research.

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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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