Automated vehicles for highway operations (automated highway systems)

2005 ◽  
Vol 219 (1) ◽  
pp. 53-75 ◽  
Author(s):  
S E Shladover
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Research Effort ◽  
Automated Vehicles ◽  
Vehicle Automation ◽  
Safety Considerations ◽  
Automated Highway ◽  
Everyday Reality ◽  
And Control ◽  
Highway Automation

Considerable research effort has been devoted within the past 15 years to automating the driving of highway vehicles in order to improve their safety and efficiency of operation and to help to reduce traffic congestion. Although the highway environment is in some ways more structured than other environments in which automated vehicles have been proposed to operate, the density and complexity of road traffic still make the sensing and control problems challenging. Because highway vehicles are not ‘unmanned’ but are expected to carry passengers and to coexist with other passenger-carrying vehicles, the reliability and safety considerations in the design of their control systems are much more important than they are for vehicles that are truly unmanned. This paper reviews the progress that has been made in recent research on highway vehicle automation and indicates the important research challenges that still need to be addressed before highway automation can become an everyday reality.

Road Traffic Parameters Estimation by Dynamic Scene Analysis

2012 ◽  
pp. 223-238 ◽  
Author(s):  
H. S. Mohana ◽  
M. Ashwathakumar
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Road Transport ◽  
Traffic Analysis ◽  
Parameters Estimation ◽  
Monitoring And Control ◽  
The Road ◽  
Dynamic Scene Analysis ◽  
And Control

Traffic congestion and violation of traffic rules are very common in most of the road transport system. Continuous monitoring is becoming difficult. To improve the quality of road transport monitoring and control, the best possible alternative is machine vision. In this review, several works by researchers on traffic analysis are detailed, studied and reviewed critically for the purpose. Further, an attempt is made to classify the different road traffic analysis approaches available in the literature. Classification is based on principle used, algorithm adopted, techniques used, technology behind and other special considerations of the researchers.

Road Traffic Parameters Estimation by Dynamic Scene Analysis

2010 ◽  
Vol 2 (2) ◽  
pp. 64-78
Author(s):  
H. S. Mohana ◽  
M. Ashwathakumar
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Road Transport ◽  
Traffic Analysis ◽  
Parameters Estimation ◽  
Monitoring And Control ◽  
The Road ◽  
Dynamic Scene Analysis ◽  
And Control

Traffic congestion and violation of traffic rules are very common in most of the road transport system. Continuous monitoring is becoming difficult. To improve the quality of road transport monitoring and control, the best possible alternative is machine vision. In this review, several works by researchers on traffic analysis are detailed, studied and reviewed critically for the purpose. Further, an attempt is made to classify the different road traffic analysis approaches available in the literature. Classification is based on principle used, algorithm adopted, techniques used, technology behind and other special considerations of the researchers.

scholarly journals Developing Policy for Urban Autonomous Vehicles: Impact on Congestion

Urban Science ◽  
2018 ◽  
Vol 2 (2) ◽  
pp. 33 ◽  
Author(s):  
David Metz
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Road Traffic ◽  
Surface Transport ◽  
Urban Streets ◽  
Private Car ◽  
Vehicle Automation ◽  
The Cost ◽  
Road Traffic Congestion

An important problem for surface transport is road traffic congestion, which is ubiquitous and difficult to mitigate. Accordingly, a question for policymakers is the possible impact on congestion of autonomous vehicles. It seems likely that the main impact of vehicle automation will not be seen until driverless vehicles are sufficiently safe for use amid general traffic on urban streets. Shared use driverless vehicles could reduce the cost of taxis and a wider range of public transport vehicles could be economic. Individually owned autonomous vehicles would have the ability to travel unoccupied and may need to be regulated where this might add to congestion. It is possible that autonomous vehicles could provide mobility services at lower cost and wider scope, such that private car use in urban areas could decline and congestion reduce. City authorities should be alert to these possibilities in developing transport policy.

Improved Road Usage Through Congestion-Free Route Reservations

2017 ◽  
Vol 2621 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Charalambos Menelaou ◽  
Stelios Timotheou ◽  
Panayiotis Kolios ◽  
Christos G. Panayiotou
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Critical Density ◽  
Control Mechanisms ◽  
Time Dimension ◽  
First Case ◽  
Alternative Routes ◽  
And Control ◽  
Road Traffic Congestion ◽  
Road Segments

Road traffic congestion occurs as demand exceeds the capacity of particular road segments. The consequences (including traveling delay, fuel consumption, and emission of pollutants) have a major impact on cities, thus interest for new and innovative solutions to the problem remain high despite great efforts that have been made to alleviate the problem. The recent literature has shown that better management and control mechanisms could significantly curb the effects. One such mechanism, in which route reservations are made across congestion-free road segments, is elaborated in this work. The proposed route reservation scheme assumes that vehicles communicate their origin–destination pairs to a controller that identifies and reserves road segments to be traversed in the space and time dimension. The scheme is mathematically formulated, and two algorithms with complementary objective functions are discussed. In the first case, vehicles are routed through road segments that do not exceed their critical density while travel time is minimized. In the second case, road segments below critical density are used while reservations are made in such a way as to balance traffic across the available alternative routes. Analytical and simulation results demonstrate the considerable benefits that can be realized by applying the proposed solutions.

Safety Enhancement by Automated Driving: What are the Relevant Scenarios?

2020 ◽  
Vol 64 (1) ◽  
pp. 1686-1690
Author(s):  
Niklas Grabbe ◽  
Michael Höcher ◽  
Alexander Thanos ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Test Cases ◽  
Automated Driving ◽  
Road Traffic Safety ◽  
Human Driver ◽  
Driving Task ◽  
Promising Solution ◽  
Vehicle Automation ◽  
Safety Enhancement

Automated driving offers great possibilities in traffic safety advancement. However, evidence of safety cannot be provided by current validation methods. One promising solution to overcome the approval trap (Winner, 2015) could be the scenario-based approach. Unfortunately, this approach still results in a huge number of test cases. One possible way out is to show the current, incorrect path in the argumentation and strategy of vehicle automation, and focus on the systemic mechanisms of road traffic safety. This paper therefore argues the case for defining relevant scenarios and analysing them systemically in order to ultimately reduce the test cases. The relevant scenarios are based on the strengths and weaknesses, in terms of the driving task, for both the human driver and automation. Finally, scenarios as criteria for exclusion are being proposed in order to systemically assess the contribution of the human driver and automation to road safety.

scholarly journals The Way Forward for Indirect Structural Health Monitoring (iSHM) Using Connected and Automated Vehicles in Europe

2021 ◽  
Vol 6 (3) ◽  
pp. 43
Author(s):  
Konstantinos Gkoumas ◽  
Kyriaki Gkoktsi ◽  
Flavio Bono ◽  
Maria Cristina Galassi ◽  
Daniel Tirelli
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Transport Infrastructure ◽  
Policy Framework ◽  
Strategic Decisions ◽  
Automated Vehicles ◽  
Civil Infrastructures ◽  
Vehicle Automation ◽  
Labor Requirements

Europe’s aging transportation infrastructure requires optimized maintenance programs. However, data and monitoring systems may not be readily available to support strategic decisions or they may require costly installations in terms of time and labor requirements. In recent years, the possibility of monitoring bridges by indirectly sensing relevant parameters from traveling vehicles has emerged—an approach that would allow for the elimination of the costly installation of sensors and monitoring campaigns. The advantages of cooperative, connected, and automated mobility (CCAM), which is expected to become a reality in Europe towards the end of this decade, should therefore be considered for the future development of iSHM strategies. A critical review of methods and strategies for CCAM, including Intelligent Transportation Systems, is a prerequisite for moving towards the goal of identifying the synergies between CCAM and civil infrastructures, in line with future developments in vehicle automation. This study presents the policy framework of CCAM in Europe and discusses the policy enablers and bottlenecks of using CCAM in the drive-by monitoring of transport infrastructure. It also highlights the current direction of research within the iSHM paradigm towards the identification of technologies and methods that could benefit from the use of connected and automated vehicles (CAVs).

scholarly journals Impact of External Human–Machine Interface Communication Strategies of Automated Vehicles on Pedestrians’ Crossing Decisions and Behaviors in an Urban Environment

2021 ◽  
Vol 13 (15) ◽  
pp. 8396
Author(s):  
Marc Wilbrink ◽  
Merle Lau ◽  
Johannes Illgner ◽  
Anna Schieben ◽  
Michael Oehl
Keyword(s):  
Urban Traffic ◽  
Automated Vehicles ◽  
Negative Effects ◽  
Communication Tools ◽  
Automated Vehicle ◽  
Additional Information ◽  
Road Users ◽  
Vulnerable Road Users ◽  
And Behaviors ◽  
Vehicle Automation

The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

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