Abstract
The phenomenon of stop-and-go traffic and its environmental impact has become a crucial issue that needs to be tackled, in terms of the junctions between freeway and urban road networks, which consist of freeway off-ramps, downstream intersections, and the junction section. The development of Connected and Automated Vehicles (CAVs) has provided promising solutions to tackle the difficulties that arise along intersections and freeway off-ramps separately. However, several problems still exist that need to be handled in terms of junction structure, including vehicle merging trajectory optimization, vehicle crossing trajectory optimization, and heterogeneous decision-making. In this paper, a two-stage CAV trajectory optimization strategy is presented to improve fuel economy and to reduce delays through a joint framework. The first stage considers an approach to determine travel time considering the different topological structures of each subarea to ensure maximum capacity. In the second stage, Pontryagin’s Minimum Principle (PMP) is employed to construct Hamiltonian equations to smooth vehicle trajectory under the requirements of vehicle dynamics and safety. Targeted methods are devised to avoid driving backwards and to ensure an optimal vehicle gap, which make up for the shortcomings of the PMP theory. Finally, simulation experiments are designed to verify the effectiveness of the proposed strategy. The evaluation results show that our strategy could effectively militate travel delays and fuel consumption.
Highlights
According to the Greenhouse Gas (GHG) Emissions Report presented by the UnitedStates Environmental Protection Agency (EPA), transportation has become the largest source of greenhouse gas emissions in America in 2018, contributing to approximately 28%of national GHG emissions
A typical integrated freeway off-ramp and urban road network structure contains three zones: the Off-Ramp Zone (ORZ), the Junction Section (JS), and the Downstream Intersection (DI). Vehicles coming from both the freeway and the urban road network merge in the Merging Zone (MZ), which is located at the ORZ
In order to evaluate the feasibility of the proposed vehicle trajectory optimization strategy, we employed MATLAB and VISSIM to construct a joint simulation framework
Summary
States Environmental Protection Agency (EPA), transportation has become the largest source of greenhouse gas emissions in America in 2018, contributing to approximately 28%. Trajectory optimization strategy plays an important role in the eco-driving approach [3], which attempts to smooth vehicle trajectory and avoid idling by optimizing the acceleration/deceleration profile using connected and automated vehicle (CAVs) technology [7] Interweaving areas, such as urban intersections or freeway merging areas, are the main bottleneck points and grievously obstruct traffic capacity. The above studies aimed at the control of vehicles in urban intersections or freeway ramps These proposed methods can effectively satisfy the traffic management needs of the corresponding areas, especially in the context of CAV technology. The contribution of this study is to propose a two-stage CAV trajectory optimization strategy for such junctions to improve fuel economy and driving comfort on the basis of ensuring maximum capacity (or reducing vehicle delays).
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