Intersection Collision Avoidance: From Driver Alerts to Vehicle Control

Maile, Michael; Chen, Q.; Brown, Gerald R.; Delgrossi, Luca

doi:10.1109/vtcspring.2015.7145888

Cited by 15 publications

(7 citation statements)

References 3 publications

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“…It is expected that vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications introduce safety benefits to two of the most frequent accident typesintersection and rear-end accidents. For example, intersection movement assist (IMA) warns the driver when approaching a dangerous intersection (Maile et al, 2015). The proliferation of vehicles with intermediate levels of autonomy (i.e., SAE level 2-4) is another factor expected to contribute to road safety, supplementing this research.…”

Section: Discussionmentioning

confidence: 93%

On the road safety benefits of advanced driver assistance systems in different driving contexts

Masello

Castignani

Sheehan

et al. 2022

Transportation Research Interdisciplinary Perspectives

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Section: Discussionmentioning

confidence: 93%

On the road safety benefits of advanced driver assistance systems in different driving contexts

Masello

Castignani

Sheehan

et al. 2022

Transportation Research Interdisciplinary Perspectives

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“…braking functions after calculating dangerous trajectories and possible collision points [36]. Another likely scenario in which CCS may be useful is the overtaking maneuver of AVs when they are utilized for long-distance highway trips [37].…”

Section: The Need For Safety and Collision Control Systems Within The...mentioning

confidence: 99%

5G as an Enabler of Connected-and-Automated Mobility in European Cross-Border Corridors—A Market Assessment

Rizopoulos¹,

Laskari²,

Kouloumbis³

et al. 2022

Sustainability

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5G systems are capable of facilitating remarkable technological advances and promoting sustainability in Internet-of-Things-centric fields, such as the Transport and Logistics (T&L) sector and applications in Connected-and-Automated Mobility (CAM). The current article provides an overview of the latest developments in the applications of the 5G mobile network standard in CAM and is specifically focused on analyzing existing and potential applications within European T&L corridors and subsequent markets. A focused marketplace analysis is conducteFd, highlighting the demands of commercialization clusters within European cross-border markets, as well as an analysis of how some of these demands can supplement the deployment of 5G products and services in the coming years. With the aim of providing a macro-level description of the landscape of 5G applications in CAM, the authors further discuss and classify the markets’ influencing factors according to the PESTEL framework, which is further enhanced to include the recent impacts of the COVID-19 pandemic and the war in Ukraine. The findings display that while 5G is a crucial underlying technology for the establishment of CAM, several factors, such as international security, political coordination at the EU level, and common technological standards across EU member states, will have a central role in the successful deployment of its applications.

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“…A major concern for autonomous driving is to drive safely with the goal of reducing the probability of accidents. In the autonomous driving literature, two types of techniques that can predict vehicle motions for accident avoidance have been widely used [19]: the time-to-collision (TTC) and time-to-lane-crossing (TLC) models. For off-road autonomous driving, this paper introduces the TTR (i.e., time-to-rollover) model to further enhance the safety of autonomous driving with the incorporation of 3D mapping information around the vehicle [20].…”

Section: Time-to-rollover Modelmentioning

confidence: 99%

Rollover-Free Path Planning for Off-Road Autonomous Driving

Tang

Ball

et al. 2019

Electronics

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Perception, planning, and control are three enabling technologies to achieve autonomy in autonomous driving. In particular, planning provides vehicles with a safe and collision-free path towards their destinations, accounting for vehicle dynamics, maneuvering capabilities in the presence of obstacles, traffic rules, and road boundaries. Existing path planning algorithms can be divided into two stages: global planning and local planning. In the global planning stage, global routes and the vehicle states are determined from a digital map and the localization system. In the local planning stage, a local path can be achieved based on a global route and surrounding information obtained from sensors such as cameras and LiDARs. In this paper, we present a new local path planning method, which incorporates a vehicle’s time-to-rollover model for off-road autonomous driving on different road profiles for a given predefined global route. The proposed local path planning algorithm uses a 3D occupancy grid and generates a series of 3D path candidates in the s-p coordinate system. The optimal path is then selected considering the total cost of safety, including obstacle avoidance, vehicle rollover prevention, and comfortability in terms of path smoothness and continuity with road unevenness. The simulation results demonstrate the effectiveness of the proposed path planning method for various types of roads, indicating its wide practical applications to off-road autonomous driving.

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Intersection Collision Avoidance: From Driver Alerts to Vehicle Control

Cited by 15 publications

References 3 publications

On the road safety benefits of advanced driver assistance systems in different driving contexts

On the road safety benefits of advanced driver assistance systems in different driving contexts

5G as an Enabler of Connected-and-Automated Mobility in European Cross-Border Corridors—A Market Assessment

Rollover-Free Path Planning for Off-Road Autonomous Driving

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