Influence of Lane Width on Semi- Autonomous Vehicle Performance

2020 ◽  
Vol 2674 (9) ◽  
pp. 279-286 ◽  
Author(s):  
Alfredo García ◽  
Francisco Javier Camacho-Torregrosa
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Lateral Control ◽  
Maximum Width ◽  
Vehicle Performance ◽  
Minimum Width ◽  
Road Infrastructure ◽  
Lane Width ◽  
Rapid Deployment ◽  
The Impact

In the medium-term, the number of semi-autonomous vehicles is expected to rise significantly. These changes in vehicle capabilities make it necessary to analyze their interaction with road infrastructure, which has been developed for human-driven vehicles. Current systems use artificial vision, recording the oncoming road and using the center and edgeline road markings to automatically facilitate keeping the vehicle within the lane. In addition to alignment and road markings, lane width has emerged as one of the geometric parameters that might cause disengagement and therefore must be assessed. The objective of this research was to study the impact of lane width on semi-autonomous vehicle performance. The automatic lateral control of this type of vehicle was tested along 81 lanes of an urban arterial comprising diverse widths. Results showed that the semi-autonomous system tended to fail on narrow lanes. There was a maximum width below which human control was always required—referred to as the human lane width—measuring 2.5 m. A minimum width above which automatic control was always possible—the automatic lane width—was established to be 2.75 m. Finally, a lane width of 2.72 m was found to have the same probability of automatic and human lateral control, namely the critical lane width. Following a similar methodology, these parameters could be determined for other vehicles, enhancing the interaction between autonomous vehicles and road infrastructure and thus supporting rapid deployment of autonomous technology without compromising safety.

scholarly journals An Efficiency Enhancing Methodology for Multiple Autonomous Vehicles in an Urban Network Adopting Deep Reinforcement Learning

2021 ◽  
Vol 11 (4) ◽  
pp. 1514 ◽  
Author(s):  
Quang-Duy Tran ◽  
Sang-Hoon Bae
Keyword(s):  
Reinforcement Learning ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Effective Means ◽  
Urban Network ◽  
Learning Agents ◽  
Policy Optimization ◽  
The Impact

To reduce the impact of congestion, it is necessary to improve our overall understanding of the influence of the autonomous vehicle. Recently, deep reinforcement learning has become an effective means of solving complex control tasks. Accordingly, we show an advanced deep reinforcement learning that investigates how the leading autonomous vehicles affect the urban network under a mixed-traffic environment. We also suggest a set of hyperparameters for achieving better performance. Firstly, we feed a set of hyperparameters into our deep reinforcement learning agents. Secondly, we investigate the leading autonomous vehicle experiment in the urban network with different autonomous vehicle penetration rates. Thirdly, the advantage of leading autonomous vehicles is evaluated using entire manual vehicle and leading manual vehicle experiments. Finally, the proximal policy optimization with a clipped objective is compared to the proximal policy optimization with an adaptive Kullback–Leibler penalty to verify the superiority of the proposed hyperparameter. We demonstrate that full automation traffic increased the average speed 1.27 times greater compared with the entire manual vehicle experiment. Our proposed method becomes significantly more effective at a higher autonomous vehicle penetration rate. Furthermore, the leading autonomous vehicles could help to mitigate traffic congestion.

scholarly journals Assessment of Social Acceptance for Autonomous Vehicles in Southeastern Poland

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5778
Author(s):  
Agnieszka Dudziak ◽  
Monika Stoma ◽  
Andrzej Kuranc ◽  
Jacek Caban
Keyword(s):  
Autonomous Vehicles ◽  
Social Acceptance ◽  
New Technologies ◽  
Consumer Preferences ◽  
Autonomous Vehicle ◽  
Developed Countries ◽  
Automotive Market ◽  
Advantages And Disadvantages ◽  
Autonomous Cars ◽  
The Impact

New technologies reaching out for meeting the needs of an aging population in developed countries have given rise to the development and gradual implementation of the concept of an autonomous vehicle (AV) and have even made it a necessity and an important business paradigm. However, in parallel, there is a discussion about consumer preferences and the willingness to pay for new car technologies and intelligent vehicle options. The main aim of the study was to analyze the impact of selected factors on the perception of the future of autonomous cars by respondents from the area of Southeastern Poland in terms of a comparison with traditional cars, with particular emphasis on the advantages and disadvantages of this concept. The research presented in this study was conducted in 2019 among a group of 579 respondents. Data analysis made it possible to identify potential advantages and disadvantages of the concept of introducing autonomous cars. A positive result of the survey is that 68% of respondents stated that AV will be gradually introduced to our market, which confirms the high acceptance of this technology by Poles. The obtained research results may be valuable information for governmental and local authorities, but also for car manufacturers and their future users. It is an important issue in the area of shaping the strategy of actions concerning further directions of development on the automotive market.

scholarly journals The Impact of Social Influence, Technophobia, and Perceived Safety on Autonomous Vehicle Technology Adoption

2019 ◽  
Vol 48 (2) ◽  
pp. 133-142
Author(s):  
Sahil Koul ◽  
Ali Eydgahi
Keyword(s):  
Technology Adoption ◽  
Social Influence ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Negative Relationship ◽  
Future Research ◽  
Intention To Use ◽  
Perceived Safety ◽  
Vehicle Technology ◽  
The Impact

The objective of this study was to determine whether there was a relationship between social influence, technophobia, perceived safety of autonomous vehicle technology, number of automobile-related accidents and the intention to use autonomous vehicles. The methodology was a descriptive, cross-sectional, correlational study. Theory of Planned Behavior provided the underlying theoretical framework. An online survey was the primary method of data collection. Pearson’s correlation and multiple linear regression were used for data analysis. This study found that both social influence and perceived safety of autonomous vehicle technology had significant, positive relationships with the intention to use autonomous vehicles. Additionally, a significant negative relationship was found among technophobia and intention to use autonomous vehicles. However, no relationship was found between the number of automobile-related accidents and intention to use autonomous vehicles. This study presents several original and significant findings as a contribution to the literature on autonomous vehicle technology adoption and proposes new dimensions of future research within this emerging field.

scholarly journals An attempt to evaluate the influence of automated vehicles on traffic flow and design of road infrastructure

2019 ◽  
Vol 2019 (9) ◽  
pp. 29-38
Author(s):  
Nina Kozaczka ◽  
Stanisław Gaca
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Communication Systems ◽  
Road Traffic ◽  
Negative Impact ◽  
Automated Vehicles ◽  
Road Infrastructure ◽  
The Road ◽  
Self Driving Cars ◽  
The Impact

The article evaluates the impact of autonomous vehicles on road infrastructure de- sign, road traffic conditions and safety based on a review of existing literature. Levels of driv- ing automation and equipment of self-driving vehicles were presented. Attention was drawn to the benefits of developing communication systems between vehicle and the environment. The possible negative impact of autonomous vehicles on mixed traffic capacity was noted. The potential needs to adapt the road infrastructure to the traffic flow of automated vehicles were also presented. Separation of the lane, dedicated to self-driving vehicles, with a high share of these vehicles was presented as an element that improves the flow of traffic and safe- ty. Keywords: Autonomous vehicles; Road infrastructure; Self-driving cars

scholarly journals Vehicle Electrification Impacts on Energy Consumption for Different Connected-Autonomous Vehicle Scenario Runs

2019 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Ehsan Sabri Islam ◽  
Ayman Moawad ◽  
Namdoo Kim ◽  
Aymeric Rousseau
Keyword(s):  
Energy Consumption ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Transportation System ◽  
Regional Energy ◽  
Energy Impact ◽  
Potential Factors ◽  
The Impact ◽  
The City

Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.

scholarly journals The iconography of vehicle automation—a focus group study

2021 ◽  
Author(s):  
Joy Richardson ◽  
Kirsten M. A. Revell ◽  
Jisun Kim ◽  
Neville A. Stanton
Keyword(s):  
Focus Group ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
International Markets ◽  
Cultural Barriers ◽  
Focus Group Study ◽  
Complex Information ◽  
Vehicle Automation ◽  
The Impact ◽  
Level 2

AbstractSAE level 2 and 3 semi-autonomous vehicles are widely available but, due to the nature of automation, their in-vehicle displays are required to communicate more complex information to the driver. Examination of interfaces from a variety of manufacturers revealed a clear lack of consistency in the way key information is displayed. Different manufacturers have adopted icons varying in shape and colour to convey the same message. When driving a semi-autonomous vehicle, mode awareness is critical for trust, performance and safety. Standardisation of icons has been shown to have many benefits including opening products up to wider international markets by helping overcome language and cultural barriers, by providing a method of communication which can surpass them. However, the current lack of standardisation in icon design could cause mode confusion and has little cross-vehicle compatibility. To understand the impact of mode confusion on users, a focus group was held in which participants were asked to interpret the meaning of icons from a variety of different driver interfaces. Ambiguity in user interpretations makes the case for the introduction of new ISO standard icons to better support drivers in SAE level 2 and 3 automated vehicles.

scholarly journals An Investigation of Autonomous Vehicle Roundabout Situation

2019 ◽  
Vol 48 (3) ◽  
pp. 236-241
Author(s):  
Hang Cao ◽  
Máté Zöldy
Keyword(s):  
Fuel Consumption ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Preliminary Test ◽  
Driving Behavior ◽  
Physical Parameters ◽  
Test Scenario ◽  
Vehicle Type ◽  
Fuel Consumption And Emissions ◽  
The Impact

The aim of this paper is to evaluate the impact of connected autonomous behavior in real vehicles on vehicle fuel consumption and emission reductions. Authors provide a preliminary theoretical summary to assess the driving conditions of autonomous vehicles in roundabout, which attempts exploring the impact of driving behavior patterns on fuel consumption and emissions, and including other key factors of autonomous vehicles to reduce fuel consumption and emissions. After summarizing, driving behavior, effective in-vehicle systems, both roundabout physical parameters and vehicle type are all play an important role in energy using. ZalaZONE’s roundabout is selected for preliminary test scenario establishment, which lays a design foundation for further in-depth testing.

scholarly journals Estimating Bounds of Aerodynamic, Mass, and Auxiliary Load Impacts on Autonomous Vehicles: A Powertrain Simulation Approach

2021 ◽  
Vol 13 (22) ◽  
pp. 12405
Author(s):  
Yuche Chen ◽  
Ruixiao Sun ◽  
Xuanke Wu
Keyword(s):  
Autonomous Vehicles ◽  
Steering Wheel ◽  
Power Demand ◽  
Major Power ◽  
Vehicle Performance ◽  
Design Changes ◽  
Energy Economy ◽  
Driving Conditions ◽  
Vehicle Automation ◽  
The Impact

Vehicle automation requires new onboard sensors, communication equipment, and/or data processing units, and may encourage modifications to existing onboard components (such as the steering wheel). These changes impact the vehicle’s mass, auxiliary load, coefficient of drag, and frontal area, which then change vehicle performance. This paper uses the powertrain simulation model FASTSim to quantify the impact of autonomy-related design changes on a vehicle’s fuel consumption. Levels 0, 2, and 5 autonomous vehicles are modeled for two battery-electric vehicles (2017 Chevrolet Bolt and 2017 Nissan Leaf) and a gasoline powered vehicle (2017 Toyota Corolla). Additionally, a level 5 vehicle is divided into pessimistic and optimistic scenarios which assume different electronic equipment integration format. The results show that 4–8% reductions in energy economy can be achieved in a L5 optimistic scenario and an 10–15% increase in energy economy will be the result in a L5 pessimistic scenario. When looking at impacts on different power demand sources, inertial power is the major power demand in urban driving conditions and aerodynamic power demand is the major demand in highway driving conditions.

scholarly journals Shared Autonomous Vehicles Effect on Vehicle-Km Traveled and Average Trip Duration

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Ana T. Moreno ◽  
Andrzej Michalski ◽  
Carlos Llorca ◽  
Rolf Moeckel
Keyword(s):  
Metropolitan Area ◽  
Autonomous Vehicles ◽  
Online Survey ◽  
Travel Demand ◽  
Stated Preference ◽  
Autonomous Vehicle ◽  
Trip Duration ◽  
Conventional Vehicle ◽  
Willingness To Use ◽  
The Impact

Intermediate modes of transport, such as shared vehicles or ride sharing, are starting to increase their market share at the expense of traditional modes of car, public transport, and taxi. In the advent of autonomous vehicles, single occupancy shared vehicles are expected to substitute at least in part private conventional vehicle trips. The objective of this paper is to estimate the impact of shared autonomous vehicles on average trip duration and vehicle-km traveled in a large metropolitan area. A stated preference online survey was designed to gather data on the willingness to use shared autonomous vehicles. Then, commute trips and home-based other trips were generated microscopically for a synthetic population in the greater Munich metropolitan area. Individuals who traveled by auto were selected to switch from a conventional vehicle to a shared autonomous vehicle subject to their willingness to use them. The effect of shared autonomous vehicles on urban mobility was assessed through traffic simulations in MATSim with a varying autonomous taxi fleet size. The results indicated that the total traveled distance increased by up to 8% after autonomous fleets were introduced. Current travel demand can still be satisfied with an acceptable waiting time when 10 conventional vehicles are replaced with 4 shared autonomous vehicles.

scholarly journals A Data-Driven Approach to Characterize the Impact of Connected and Autonomous Vehicles on Traffic Flow

2020 ◽  
Author(s):  
Amir Bahador Parsa ◽  
Ramin Shabanpour ◽  
Abolfazl Mohammadian ◽  
Joshua Auld ◽  
Thomas Stephens
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Gradient Boosting ◽  
Analysis Tool ◽  
Urban Structure ◽  
K Nearest Neighbors ◽  
Network Characteristics ◽  
Extreme Gradient Boosting ◽  
Data Driven Approach ◽  
The Impact

The current study aims to present a model to characterize changes in network traffic flows as a result of implementing connected and autonomous vehicle (CAV) technology based on traffic network and built-environment characteristics. To develop such a model, first, POLARIS agent-based modeling platform is used to predict changes in average daily traffic (ADT) under CAVs scenario in the road network of Chicago metropolitan area as the dependent variable of the model. Second, a comprehensive set of variables and indicators representing network characteristics and urban structure patterns are generated. Three machine learning models namely K-Nearest neighbors, Random Forest, and eXtreme Gradient Boosting are developed and validated to establish the relationship between network characteristics and changes in ADT under CAVs scenario. The estimated models are found to yield acceptable performance. In addition, SHapley Additive exPlanations (SHAP) analysis tool is employed to investigate the impact of important features on changes in ADT, which discloses the most important link properties, network features, and demographic information in predicting change in ADT under the analyzed CAVs scenario.

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