Lily Elefteriadou’s research while affiliated with University of Florida and other places

Autonomous Shuttles (AS) hold promise for enhancing transportation services. However, due to safety and other concerns, most AS deployments have occurred in controlled testing environments, which do not capture the complexity of real-world conditions. While studies worldwide have evaluated user acceptance, ridership impact, and cost efficiency, there is a notable absence of research on the traffic impacts of existing and planned AS deployments. This gap is partly due to limited data available to accurately evaluate and simulate the dynamics of AS and their anticipated impact on measures such as speeds and capacities. To address these issues, our study uses simulation to evaluate the anticipated traffic impacts of deploying AS using real-world data from AS deployment. The research team simulated a real-world signalized arterial considering existing vehicle demand and composition, and used a calibrated Intelligent Driving Model (using AS field data) to evaluate the network performance under various potential deployment scenarios. The study assesses intersection delay, number of stops, average speed, and average number of lane changes. The results indicate that deploying AS in mixed traffic signalized arterials is likely to have a relatively small negative impact on traffic performance. The simulation showed that, for every five conventional buses replaced with five AS, there is an average increase in delay of 0.62 seconds per vehicle, an average increase in number of stops of 0.015 stops per vehicle, a reduction in average speed by 0.72km/hr (0.45mph), and an increase of 0.04 in the number of lane changes per mile. Surprisingly, the analysis showed that the only statistically significant change is that in the number of lane changes; the changes in the remaining performance metrics were not statistically significant.

Chapter 1 discussed the movement of an individual vehicle and provided the equations of motion assuming there are no other vehicles around. This chapter examines the interactions between vehicles, which is at the heart of traffic flow theory. It is these interactions that produce the observed traffic operational conditions, including crashes and congestion. Traffic operational characteristics of interest include capacity (i.e., the maximum amount of traffic that can pass through a point or section in vehicles or other units of traffic per unit time), prevailing speed (i.e., the speed at which the facility operates under a given set of prevailing conditions, including the demand, the highway design, etc.), delay, and travel time. These characteristics are discussed in more detail in Part II.

This paper formulates a cooperative traffic control methodology that integrates traffic signal timing and ramp metering decisions into an optimization model to improve traffic operations in a corridor network. A mixed integer linear model is formulated and is solved in real time within a model predictive controller framework, where the cell transmission model is used as the system state predictor. The methodology is benchmarked in a case study corridor in San Mateo, CA, in VISSIM with two optimization scenarios, namely, optimal metering and optimal signal control, and two simulation scenarios with a preset metering plan and no metering. The numerical results show that integrated traffic signal and ramp metering control reduces delays, stops, and travel times of the corridor by up to 33.1%, 36%, and 16.4%, respectively, compared to existing benchmark conditions. With appropriate weights prioritizing freeway or arterial street operations, the integrated control balances traffic congestion between the arterial street and the freeway.

Interchange ramp terminals provide connections between various types of highways (arterial-freeway, freeway-freeway, arterial-arterial). Alternative intersection designs are innovative configurations that have the potential to improve operations by rerouting certain movements. The first part of this chapter presents examples of interchange configurations, discusses traffic operational effects of interchange characteristics and signalization for two-intersection interchanges, and summarizes the HCM7 methodological framework for these types of facilities. The second part discusses traffic operations and the HCM7 methodology for alternative intersections.

Flow, speed, and density are the three primary characteristics of traffic and are used to describe various aspects of operations of a highway facility. When describing and assessing traffic operations, we are often concerned with the movement of a group of vehicles, or the traffic stream, rather than the movement of each vehicle. In those cases, it is more convenient to describe traffic operations in terms of macroscopic measures of traffic.

Signalized intersections operate with the assistance of a traffic signal, and they cyclically assign the right-of-way to a movement or a combination of movements. Ideally, the amount of time assigned to each combination of movements minimizes the travel time and delay and/or the number of stops in the network and allocates capacity optimally. An arterial is a highway facility with a series of signalized intersections along its length, while an urban network or a surface street network consists of a group of interconnected arterials and side streets.

Two-lane highways, which have one lane per direction, are unique operationally since they may allow passing using the opposing traffic stream. According to the US Federal Highway Administration [1], two-lane highway facilities represent about 97% of the total highway system and more than 65% of the total nonurban vehicular travel in the United States. Hence, two-lane highways provide most of the primary interurban highway networks and are the basis of the secondary highway and collector networks. Figure 13.1 provides a sketch of a two-lane highway.

This chapter discusses the operational evaluation of a highway system considering both freeways and arterials. Previous chapters have considered each of those facilities as an isolated system. However, when congestion occurs and queues spill back into a facility, the analysis should consider the entire freeway-arterial system (the concept is similar to the analysis of freeway systems discussed in Chap. 9, when queues spread to upstream segments). The first section of this chapter discusses spillback from an arterial to a freeway, and the second section examines the impact of spillback from a freeway to an arterial. The last section discusses the performance measurement framework used in the HCM7 to assess highway networks.

Freeways are defined as those facilities that afford uninterrupted flow of traffic, i.e., there is full access control. Control of access refers to public access rights from properties along the freeway; access to freeway facilities is allowed only through selected public roads, typically on- and off-ramps [1]. Thus, freeways generally operate at higher speeds and higher capacities than urban arterial streets or local roadways.