Making intersections safer with I2V communication

Abstract

Intersections are hazardous places. Threats arise from interactions among pedestrians, bicycles and vehicles, more complicated vehicle trajectories in the absence of lane markings, phases that prevent determining who has the right of way, invisible vehicle approaches, vehicle obstructions, and illegal movements. These challenges are not fully addressed by the "road diet" and road redesign prescribed in Vision Zero plans, nor will they be completely overcome by autonomous vehicles with their many sensors and tireless attention to surroundings. Accidents can also occur because drivers, cyclists and pedestrians do not have the information they need to avoid wrong decisions. In these cases, the missing information can be computed and broadcast by an intelligent intersection. The information gives the current full signal phase, an estimate of the time when the phase will change, and the occupancy of the blind spots of the driver or autonomous vehicle. The paper develops a design of the intelligent intersection, motivated by the analysis of an accident at an intersection in Tempe, AZ, between an automated Uber Volvo and a manual Honda CRV and culminates in a proposal for an intelligent intersection infrastructure. The intelligent intersection also serves as a software-enabled version of the 'protected intersection' design to improve the passage of cyclists and pedestrians through an intersection.

VerifAI: A Toolkit for the Formal Design and Analysis of Artificial Intelligence-Based Systems

“…3 shows a (simplified) SCENIC program we wrote to reproduce the accident, allowing variation in the initial positions of the cars. We then ran simulations from random initial conditions sampled from the program, with the turning car using a controller trying to follow the ideal left-turn trajectory computed from OpenStreetMap data using the Intelligent Intersections Toolbox [13]. The car going straight used a controller which either maintained a constant velocity or began emergency breaking in response to a message from a simulated "smart intersection" warning about the turning car.…”

Behavioral decision‐making model of the intelligent vehicle based on driving risk assessment

“…It is difficult for intelligent vehicles to accurately identify the behavior of other road users in this situation. With the development of V2X technologies, researchers have started to use V2X technologies to replace traffic lights and to explore new management approaches to improve traffic safety and efficiency at intersections (Grembek, Kurzhanskiy, Medury, Varaiya, & Yu, 2019; Xu et al., 2018). In the Grand Cooperative Driving Challenge 2016, the urban test scenario focused on the cooperative crossing of a T‐intersection without traffic lights.…”

Intelligent transportation systems (ITS): A systematic review using a Natural Language Processing (NLP) approach

“…Ehlers et al [47] proposed bowtie analysis as a conceptual framework for evaluating the safety of C-ITS and the prevention of road traffic accidents or consequence mitigation (using three case studies under the assumption of a single-vehicle accident). Grembek et al [48] proposed a design for an intelligent intersection (an intersection that manages all surrounding information).…”