This paper aims to optimize on-ramp merging processes for connected automated vehicles by utilizing an existing hierarchical control architecture including a decision-maker and an operational controller. The decision-maker employs surrogate linear models to predict future vehicular acceleration analytically and computes a merging sequence to minimize merging times of on-ramp vehicles. The operational controller is formulated as a model predictive control problem, which utilizes a second-order vehicle dynamics model, and regulates vehicles accelerations and time instants to execute lateral movements of on-ramp vehicles for the merging processes respectively. Constraints on vehicular acceleration, speed, and inter-vehicle distance are considered by the decision-maker and the operational controller for practical usage. The proposed method to minimize the merging times of on-ramp vehicles and a first-in-first-out method are tested under different initial settings, including initial vehicular speeds, distributions of vehicular positions, and desired time gaps. The simulation results show that the proposed method is superior to the first-in-first-out method widely used in literature in improving merging traffic efficiency. We find that cooperation among vehicles makes the on-ramp vehicles join mainline traffic faster, and the acceptable time gap for merging affect choices of optimal merging sequences.

Autonomous vehicles (AVs) occupy a crucial part of the emerging mobility. Currently, the potential impacts of self-driving fleets are of great interest to public bodies and authorities. The impact is studied in pilots, but these still have a limited scope, therefore also simulation studies are necessary. This study aims to offer a comprehensive review of recent macro/mesoscopic agent-based models for AVs. Through keyword search, we extracted twenty-nine papers from the Web of Science database. These studies analysed AVs impact on the land-use, travel behaviour, environment and cost. Therefore, we summarise the similarities and particularities of modelling specifications and outcomes, meanwhile analysing the reasons for conflicting results. In general, the results from analysed papers are distinct from each other, and some even hold opposite results. There are several effective methods for increasing AVs customer acceptance. When implemented, it will bring significant amounts of benefit, including much lower energy consumptions, emission, operational costs and parking space demands. However, a more congested network and urban sprawl are the most unignorable problems. Finally, this research offers several suggestions and research directions regarding AV future development, which will be referential for both researchers and urban planners.

AbstractThis paper proposes a multilane traffic flow model based on the notions of conservation laws in Lagrangian coordinates. Both the mathematical formulation and the graphical representation are provided. A logit choice model is applied to describe drivers lane choice probability. The lane changing rate is estimated by employing the Incremental Transfer (IT) principle and the lane choice probability model. The numerical implementation of the model in the case of two lanes is discussed. The simulation results reveal that the proposed Lagrangian model is able to describe lane changing dynamics of vehicle platoons; while the lane changing equilibrium curve at the macroscopic level is consistent with that from the multilane Eulerian model as well as the observed data on the highway.