Safety Evaluation of Flower Roundabout Considering Autonomous Vehicles Operation

Abstract

With the significant technological growth that affected autonomous vehicles in the last decade, several consequences occurred as: human factor exclusion, entry and exit manoeuvres precision from roundabouts, and headway reduction. In this paper, it was carried out a microsimulation approach study that aims to evaluate benefits in terms of safety obtained with flower roundabouts in a scenario where traffic is characterized by conventional vehicles “CVs” and Connected Autonomous Vehicles “CAVs”. This study focused on the evaluation of CAVs and CVs operation with the presence of the so called “weak users” or rather, pedestrians and bikes. Then, simulated scenarios were characterized by the presence of zebra-crossings in main roads, positioned at 20 m from circulatory carriageway edges. Micro simulation choice is due to the absence of survey data collection because the presence of CAVs in ordinary traffic is still minimal. The micro simulation was carried out through VISSIM, so it was operated with a specific methodological path, consisting, in the application, of O–D matrix based on real cases, in order to achieve an assessment of potential conflicts in relation with the increase in CAVs. Simulation results showed that higher safety levels were achieved for special cases of O–D distribution and with CAVs present. Finally, considering crash absence in results related to CAVs presence, safety interventions of such roundabout types have to be thorough. There were 10 O/D matrices analysed through VISSIM considering parameters as: average tail length, maximum tail length, average speed, vehicles, and number of stops quantity. As reported in the conclusion section, O/D matrices that showed minimum conflicts and maximum dynamic performances were identified.

Impact of Autonomous Vehicles on Roundabout Capacity

“…A recent paper by Severino et al focused on the evaluation of connected automated vehicles and the connected vehicles operation with the presence of pedestrians and bicycles. They simulated scenarios with zebra crossings in the main roads, positioned 20 m from circulatory carriageway edges [15].…”

Applying Data Mining Approaches for Analyzing Hazardous Materials Transportation Accidents on Different Types of Roads

“…Led by the government, the joint management of several departments should crack down on the unlicensed transport of Hazmat, strengthen the source of management, and establish a long-term management mechanism. It is crucial to increase the number of streetlights and optimize traffic signal devices at intersections to improve the technical conditions of rural roads [53]. Observation windows should be fitted into the copilot doors of heavy vehicles, and these vehicles should be equipped with other side assistance systems, such as blind spot cameras and radar, to reduce the impact of visual blind spots on transport safety.…”

Deep-Neural-Network-Based Modelling of Longitudinal-Lateral Dynamics to Predict the Vehicle States for Autonomous Driving

“…Recent advances on neural networks have led to dramatic progress in solving many complex engineering problems, and demand for such solutions is increasing with time. A wide range of topics starting from dynamics modelling, intelligent control to transportation research is being handled by neural networks [1][2][3]. This technique has naturally found substantial applications in autonomous vehicles, with vehicle lateral and longitudinal dynamics modelling and control being typical applications [4][5][6].…”