scholarly journals Cruising for Parking with Autonomous and Conventional Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mehdi Nourinejad ◽  
Matthew J. Roorda
Keyword(s):  
Traffic Flow ◽  
Conventional Method ◽  
Autonomous Vehicles ◽  
Search Time ◽  
Walking Distance ◽  
Travel Costs ◽  
Final Destination ◽  
Parking Spot ◽  
The Impact ◽  
Near Future

Parking is a cumbersome part of auto travel because travelers have to search for a spot and walk from that spot to their final destination. This conventional method of parking will change with the arrival of autonomous vehicles (AV). In the near future, users of AVs get dropped off at their final destination and the occupant-free AVs search for the nearest and most convenient parking spot. Hence, individuals no longer bear the discomfort of cruising for parking while sitting in their vehicle. This paper quantifies the impact of AVs on parking occupancy and traffic flow on a corridor that connects a home zone to a downtown zone. The model considers a heterogeneous group of AVs and conventional vehicles (CV) and captures their parking behavior as they try to minimize their generalized travel costs. Insights are obtained from applying the model to two case studies with uniform and linear parking supply along the corridor. We show that (i) CVs park closer to the downtown zone in order to minimize their walking distance, whereas AVs park farther away from the downtown zone to minimize their parking search time, (ii) AVs experience a lower search time than CVs, and (iii) higher AV penetration rates reduce travel costs for both AVs and CVs.

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 A data-driven approach to characterize the impact of connected and autonomous vehicles on traffic flow

2020 ◽  
pp. 1-9
Author(s):  
Amir Bahador Parsa ◽  
Ramin Shabanpour ◽  
Abolfazl (Kouros) Mohammadian ◽  
Joshua Auld ◽  
Thomas Stephens
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Data Driven ◽  
Data Driven Approach ◽  
The Impact

Effect of connected and autonomous vehicles on traffic flow at a bidirectional road

2021 ◽  
Author(s):  
H. Echab ◽  
A. Khallouk ◽  
H. Ez-Zahraouy
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Negative Influence ◽  
Conventional Vehicle ◽  
Cooperative Driving ◽  
Moving Vehicles ◽  
Penetration Ratio ◽  
Slow Moving ◽  
The Impact ◽  
Cv Model

The objective of this study was to investigate the impact of connected and autonomous vehicles (CAVs) on traffic flow under various parameters. For this purpose, we propose a mixed CAV and conventional vehicle (CV) model to investigate a bidirectional two-lane traffic flow under the periodic boundary condition. The traffic flux and the phase diagrams of the system in the ([Formula: see text]) area are constructed in both cases: with and without CAVs. The overtaking frequency is also calculated. The simulation findings show that the traffic capacity is greatly enhanced with the increase in the CAV penetration ratio. Owing to the cooperative driving strategy, with the increase in penetration ratio of the CAV, the portion of smooth overtaking is boosted. Furthermore, it is found that the traffic throughput is positively correlated to the speed limit of the fast vehicle where the flux increases as [Formula: see text] increases. Also, even if there is a low rate of slow moving vehicles in the system, it will have an appreciable and a significant negative influence.

scholarly journals Impacts of Autonomous Vehicles on Traffic Flow Characteristics under Mixed Traffic Environment: Future Perspectives

2021 ◽  
Vol 13 (19) ◽  
pp. 11052
Author(s):  
Mohammed Al-Turki ◽  
Nedal T. Ratrout ◽  
Syed Masiur Rahman ◽  
Imran Reza
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Flow Characteristics ◽  
Driving Behavior ◽  
Mixed Traffic ◽  
Traffic Characteristics ◽  
Traffic Environment ◽  
Traffic Flow Characteristics ◽  
The Impact

Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses on reviewing the expected impacts under a mixed traffic environment of AVs and regular vehicles (RVs) considering different AV characteristics. The paper includes a policy implication discussion for possible actual future practice and research interests. The AV implementation has positive impacts on the traffic flow, such as improved traffic capacity and stability. However, the impact depends on the factors including penetration rate of the AVs, characteristics, and operational settings of the AVs, traffic volume level, and human driving behavior. The critical penetration rate, which has a high potential to improve traffic characteristics, was higher than 40%. AV’s intelligent control of operational driving is a function of its operational settings, mainly car-following modeling. Different adjustments of these settings may improve some traffic flow parameters and may deteriorate others. The position and distribution of AVs and the type of their leading or following vehicles may play a role in maximizing their impacts.

scholarly journals An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

2020 ◽  
Vol 12 (7) ◽  
pp. 2922 ◽  
Author(s):  
Muhammad Tanveer ◽  
Faizan Ahmad Kashmiri ◽  
Hassan Naeem ◽  
Huimin Yan ◽  
Xin Qi ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Age Groups ◽  
Transportation Systems ◽  
Heterogeneous Traffic ◽  
And Gender ◽  
The Impact

Traffic congestion has become increasingly prevalent in many urban areas, and researchers are continuously looking into new ways to resolve this pertinent issue. Autonomous vehicles are one of the technologies expected to revolutionize transportation systems. To this very day, there are limited studies focused on the impact of autonomous vehicles in heterogeneous traffic flow in terms of different driving modes (manual and self-driving). Autonomous vehicles in the near future will be running parallel with manual vehicles, and drivers will have different characteristics and attributes. Previous studies that have focused on the impact of autonomous vehicles in these conditions are scarce. This paper proposes a new cellular automata model to address this issue, where different autonomous vehicles (cars and buses) and manual vehicles (cars and buses) are compared in terms of fundamental traffic parameters. Manual cars are further divided into subcategories on the basis of age groups and gender. Each category has its own distinct attributes, which make it different from the others. This is done in order to obtain a simulation as close as possible to a real-world scenario. Furthermore, different lane-changing behavior patterns have been modeled for autonomous and manual vehicles. Subsequently, different scenarios with different compositions are simulated to investigate the impact of autonomous vehicles on traffic flow in heterogeneous conditions. The results suggest that autonomous vehicles can raise the flow rate of any network considerably despite the running heterogeneous traffic flow.

Exploring the Potential of Multiagent Learning for Autonomous Intersection Control

2009 ◽  
pp. 280-290 ◽  
Author(s):  
Matteo Vasirani ◽  
Sascha Ossowski
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Coordination Mechanism ◽  
Multiagent Learning ◽  
Average Travel Time ◽  
Promising Application ◽  
Flow Through ◽  
Near Future ◽  
Intersection Control

The problem of advanced intersection control is being discovered as a promising application field for multiagent technology. In this context, drivers interact autonomously with a coordination facility that controls the traffic flow through an intersection, with the aim of avoiding collisions and minimizing delays. This is particularly interesting in the case of autonomous vehicles that are controlled entirely by agents, a scenario that will become possible in the near future. In this chapter, the authors seize the opportunities of multiagent learning offered by such a scenario, by introducing a coordination mechanism where teams of agents coordinate their velocities when approaching the intersection in a decentralized way. They show that this approach enables the agents to improve the intersection efficiency, by reducing the average travel time and so contributing to alleviate traffic congestions.

Traffic Oscillation using Stochastic Lagrangian Dynamics: Simulation and Mitigation via Control of Autonomous Vehicles

2019 ◽  
Vol 2673 (7) ◽  
pp. 1-11
Author(s):  
Fangfang Zheng ◽  
Liang Lu ◽  
Ruijie Li ◽  
Xiaobo Liu ◽  
Youhua Tang
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Control Strategies ◽  
Dynamics Simulation ◽  
Lagrangian Model ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
Sample Paths ◽  
Stop And Go ◽  
The Impact

The phenomenon of stop-and-go waves is frequently observed in congested traffic. With the development of connected and autonomous vehicle (CAV) technologies, it is possible to reduce traffic oscillation via control of CAVs in a mixed traffic flow with both human drivers and autonomous vehicles (AVs). This paper introduces a stochastic Lagrangian model which is capable of simulating stop-and-go traffic considering the heterogeneity of drivers. The sample paths of the stochastic process are smooth without aggressive oscillation. The model is further extended to the mixed traffic flow condition, considering stochastic human driving behavior and deterministic behavior of AVs. With the proposed model, the variation of performance of AV control strategies can be quantified in addition to the average performance. A numerical example with a single lane circular road is used to investigate the impact of the AV control strategy on mitigating stop-and-go waves. Both qualitative and quantitative results show that the phenomenon of stop-and-go waves can be reduced significantly with only one AV, while the increase of AVs from 10% (two AVs) to 50% (10 AVs) offers just marginal improvement in relation to the ensemble-averaged performance and 95% confidence interval of the ensemble-averaged performance. The proposed simulation approach based on the stochastic Lagrangian model can effectively investigate the impact of AV control strategies on traffic oscillation, considering in particular the uncertainty of human driver behavior.

scholarly journals The Impact of Bottom-Up Parking Information Provision in a Real-Life Context: The Case of Antwerp

2017 ◽  
Vol 2017 ◽  
pp. 1-15
Author(s):  
Geert Tasseron ◽  
Karel Martens
Keyword(s):  
Transport Model ◽  
Real Life ◽  
Search Time ◽  
Information Provision ◽  
Walking Distance ◽  
Bottom Up ◽  
Life Context ◽  
Smart Cars ◽  
Occupancy Rates ◽  
The Impact

A number of studies have analyzed the possible impacts of bottom-up parking information or parking reservation systems on parking dynamics in abstract simulation environments. In this paper, we take these efforts one step further by investigating the impacts of these systems in a real-life context: the center of the city of Antwerp, Belgium. In our simulation, we assume that all on-street and off-street parking places are equipped with technology able to transmit their occupancy status to so-called smart cars, which can receive information and reserve a parking place. We employ PARKAGENT, an agent-based simulation model, to simulate the behavior of smart and regular cars. We obtain detailed data on parking demand from FEATHERS, an activity-based transport model. The simulation results show that parking information and reservation hardly impact search time but do reduce walking distance for smart cars, leading to a reduction in total parking time, that is, the sum of search time and walking time. Reductions in search time occur only in zones with high occupancy rates, while a drop in walking distance is especially observed in low occupancy areas. Societal benefits of parking information and reservation are limited, because of the low impact on search time and the possible negative health effects of reduced walking distance.

Modeling the Impact of Communications Technologies on Travel Behavior and Land Use

2017 ◽  
Vol 2658 (1) ◽  
pp. 8-16 ◽  
Author(s):  
Rolf Moeckel
Keyword(s):  
Social Networks ◽  
Land Use ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Transport Model ◽  
Work Place ◽  
Communications Technologies ◽  
Housing Search ◽  
The Impact ◽  
Near Future

The widespread use of communications technologies has changed the way people travel. Transport modeling offers the opportunity to analyze this impact and test innovations, policies, and future trends before they actually happen. The impact of smartphones, GPS, and telework has been researched insufficiently, despite the impact of these technologies on travel behavior. Autonomous vehicles are expected to be widely available in the near future, but their impact on travel behavior is largely unknown. Last but not least, social networks have a dominating impact on the activities people pursue, the destinations they choose, the mode they use, and with whom they travel. This paper describes a framework for an integrated land use–transport model for analyzing the impact of communications technologies on travel behavior. Social networks are simulated explicitly. The impact of communications technologies on both land use, such as the impact on a housing search, auto ownership, or work place choice, as well as travel behavior such as activity generation, destination choice, or mode choice, can be simulated with this modeling suite.

Syrian Crisis and Migration

2015 ◽  
Vol 12 (3) ◽  
pp. 181-192 ◽  
Author(s):  
Pinar Yazgan ◽  
Deniz Eroglu Utku ◽  
Ibrahim Sirkeci
Keyword(s):  
Human Mobility ◽  
Special Issue ◽  
Host Countries ◽  
Syrian Crisis ◽  
Mass Migration ◽  
Large Numbers ◽  
And Migration ◽  
Europe Today ◽  
The Impact ◽  
Near Future

With the growing insurrections in Syria in 2011, an exodus in large numbers have emerged. The turmoil and violence have caused mass migration to destinations both within the region and beyond. The current "refugee crisis" has escalated sharply and its impact is widening from neighbouring countries toward Europe. Today, the Syrian crisis is the major cause for an increase in displacement and the resultant dire humanitarian situation in the region. Since the conflict shows no signs of abating in the near future, there is a constant increase in the number of Syrians fleeing their homes. However, questions on the future impact of the Syrian crisis on the scope and scale of this human mobility are still to be answered. As the impact of the Syrian crisis on host countries increases, so does the demand for the analyses of the needs for development and protection in these countries. In this special issue, we aim to bring together a number of studies examining and discussing human mobility in relation to the Syrian crisis.

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