Assessing the Impact of Automated and Connected Automated Vehicles on Virginia Freeways

This study assesses the impact of the introduction of connected and automated vehicles on Virginia freeway corridors. Three vehicle types: legacy vehicles (LV), automated vehicles (AV), and connected automated vehicles (CAV), were considered in mixed traffic scenarios. Previous relevant studies were reviewed and the proper operating parameters for LV, AV, and CAV identified. AV and CAV driving behavior models were developed in the VISSIM environment. According to the basic freeway test network results, AV and CAV increase road capacity by 29% and 91%. In the merging freeway test network, AV and CAV increase road capacity by 48% and 60% compared with LV, respectively. A model with diverse LV, AV, and CAV market penetration and diverse traffic demand was tested on I-95 in Virginia, where the research team tested the speed and throughput. Under the current traffic demand, the average speed was higher when there were more AV and no CAV in the traffic flow. However, the average speed of CAV in a congested segment is higher than LV. In the case of throughput, CAV shows poor performance under current traffic demand. With increased traffic demand, high penetrations of AV and CAV present better performance because of their short headway and homogeneity. Therefore, the study predicts that in the future, as the traffic demand grows, AV and CAV can reduce traffic congestion.

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Developing an Eco-Driving Application for Semi-Actuated Signalized Intersections and Modeling the Market Penetration Rates of Eco-Driving

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119839960 ◽

2019 ◽

Vol 2673 (5) ◽

pp. 466-477 ◽

Cited By ~ 1

Author(s):

Saleh R. Mousa ◽

Sherif Ishak ◽

Ragab M. Mousa ◽

Julius Codjoe

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Fuel Consumption ◽

Signalized Intersections ◽

Market Penetration ◽

Automated Vehicles ◽

Gas Emissions ◽

Traffic Demand ◽

The Impact ◽

Connected Automated Vehicles

Eco-driving is one of the most effective techniques for making the transportation sector more sustainable in relation to fuel consumption and greenhouse gas emissions. Eco-driving applications guide drivers approaching signalized intersections to optimize the fuel consumption and reduce greenhouse gas emissions. Unlike pre-timed traffic signals, developing eco-driving applications for semi-actuated signals is more challenging because of variations in cycle length as a result of fluctuations in traffic demand. This paper presents a framework for developing an eco-driving application for connected/automated vehicles passing through semi-actuated signalized intersections. The proposed algorithm takes into consideration the queue effects because of traditional and connected/automated vehicles. Results showed that the fuel consumption for vehicles controlled by the developed model was 29.2% less than for the case with no control. A sensitivity analysis for the impact of market penetration (MP) indicated that the savings in fuel consumption increase with higher MP. Furthermore, when MP is greater than 50%, the model provides appreciable savings in travel times. In addition, the estimated acceleration noise for the vehicles controlled by the algorithms was 21.9% less than for the case with no control. These reductions in fuel consumption and acceleration noise demonstrate the ability of the algorithm to provide more environmentally sustainable semi-actuated signalized intersections.

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The Feasibility of Opening Communities -- Based on the Wiedemann Car-Following Model

Computer and Information Science ◽

10.5539/cis.v11n3p57 ◽

2018 ◽

Vol 11 (3) ◽

pp. 57

Author(s):

Xiao-Yan Cao ◽

Bing-Qian Liu ◽

Bao-Ru Pan ◽

Yuan-Biao Zhang

Keyword(s):

Traffic Congestion ◽

Large Scale ◽

Gated Communities ◽

Urban Traffic ◽

Average Delay ◽

Traffic Demand ◽

Car Following ◽

Car Following Model ◽

Urbanization In China ◽

The Impact

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.

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CONGESTION EFFECTS OF AUTONOMOUS TAXI FLEETS

Transport ◽

10.3846/16484142.2017.1347827 ◽

2018 ◽

Vol 33 (4) ◽

pp. 971-980 ◽

Cited By ~ 21

Author(s):

Michal Maciejewski ◽

Joschka Bischoff

Keyword(s):

Traffic Congestion ◽

Autonomous Vehicles ◽

Large Scale ◽

Traffic Volume ◽

City Centre ◽

Conventional Vehicle ◽

Road Capacity ◽

Private Car ◽

The One ◽

The Impact

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.

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Multi-lane Changing Model with Coupling Driving Intention and Inclination

PROMET - Traffic&Transportation ◽

10.7307/ptt.v29i2.2085 ◽

2017 ◽

Vol 29 (2) ◽

pp. 185-192 ◽

Cited By ~ 4

Author(s):

Jiangfeng Wang ◽

Chang Gao ◽

Zhouyuan Zhu ◽

Xuedong Yan

Keyword(s):

Risk Factor ◽

Lane Changing ◽

Traffic Demand ◽

Average Speed ◽

Slowing Down ◽

Behavioural Characteristics ◽

Proposed Model ◽

Density Flow ◽

The Impact ◽

The Relationship

Considering the impact of drivers’ psychology and behaviour, a multi-lane changing model coupling driving intention and inclination is proposed by introducing two quantitative indices of intention: strength of lane changing and risk factor. According to the psychological and behavioural characteristics of aggressive drivers and conservative drivers, the safety conditions for lane changing are designed respectively. The numerical simulations show that the proposed model is suitable for describing the traffic flow with frequent lane changing, which is more consistent with the driving behaviour of drivers in China. Compared with symmetric two-lane cellular automata (STCA) model, the proposed model can improve the average speed of vehicles by 1.04% under different traffic demands when aggressive drivers are in a higher proportion (the threshold of risk factor is 0.4). When the risk factor increases, the average speed shows the polarization phenomenon with the average speed slowing down in big traffic demand. The proposed model can reflect the relationship among density, flow, and speed, and the risk factor has a significant impact on density and flow.

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FCG-ASpredictor: An Approach for the Prediction of Average Speed of Road Segments with Floating Car GPS Data

Sensors ◽

10.3390/s19224967 ◽

2019 ◽

Vol 19 (22) ◽

pp. 4967 ◽

Cited By ~ 1

Author(s):

Difeng Zhu ◽

Guojiang Shen ◽

Duanyang Liu ◽

Jingjing Chen ◽

Yijiang Zhang

Keyword(s):

Predictive Model ◽

Traffic Congestion ◽

Predictive Accuracy ◽

Least Squares Method ◽

Recursive Least Squares ◽

Road Segment ◽

Average Speed ◽

Floating Car Data ◽

The Impact ◽

Road Segments

The average speed (AS) of a road segment is an important factor for predicting traffic congestion, because the accuracy of AS can directly affect the implementation of traffic management. The traffic environment, spatiotemporal information, and the dynamic interaction between these two factors impact the predictive accuracy of AS in the existing literature, and floating car data comprehensively reflect the operation of urban road vehicles. In this paper, we proposed a novel road segment AS predictive model, which is based on floating car data. First, the impact of historical AS, weather, and date attributes on AS prediction has been analyzed. Then, through spatiotemporal correlations calculation based on the data from Global Positioning System (GPS), the predictive method utilizes the recursive least squares method to fuse the historical AS with other factors (such as weather, date attributes, etc.) and adopts an extended Kalman filter algorithm to accurately predict the AS of the target segment. Finally, we applied our approach on the traffic congestion prediction on four road segments in Chengdu, China. The results showed that the proposed predictive model is highly feasible and accurate.

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Impact of Accurate Detection of Freeway Traffic Conditions on the Dynamic Pricing: A Case Study of I-95 Express Lanes

Sensors ◽

10.3390/s21185997 ◽

2021 ◽

Vol 21 (18) ◽

pp. 5997

Author(s):

Suhaib Alshayeb ◽

Aleksandar Stevanovic ◽

Nikola Mitrovic ◽

Branislav Dimitrijevic

Keyword(s):

Dynamic Pricing ◽

Traffic Congestion ◽

Sensor Failure ◽

Freeway Traffic ◽

Traffic Demand ◽

Traffic Conditions ◽

Toll Pricing ◽

The Impact ◽

Express Lanes

Express lanes (ELs) implementation is a proven strategy to deal with freeway traffic congestion. Dynamic toll pricing schemes effectively achieve reliable travel time on ELs. The primary inputs for the typical dynamic pricing algorithms are vehicular volumes and speeds derived from the data collected by sensors installed along the ELs. Thus, the operation of dynamic pricing critically depends on the accuracy of data collected by such traffic sensors. However, no previous research has been conducted to explicitly investigate the impact of sensor failures and erroneous sensors’ data on toll computations. This research fills this gap by examining the effects of sensor failure and faulty detection scenarios on ELs tolls calculated by a dynamic pricing algorithm. The paper’s methodology relies on applying the dynamic toll pricing algorithm implemented in the field and utilizing the fundamental speed-volume relationship to ‘simulate’ the sensors’ reported data. We implemented the methodology in a case study of ELs on Interstate-95 in Southeast Florida. The results have shown that the tolls increase when sensors erroneously report higher than actual traffic demand. Moreover, it has been found that the accuracy of individual sensors and the number of sensors utilized to estimate traffic conditions are critical for accurate toll calculations.

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EVALUASI KINERJA JALAN NASIONAL TERHADAP KARAKTERISTIK LALU LINTAS PADA RUAS JALAN NASIONAL KOTA PALEMBANG

JURNAL TEKNO GLOBAL UIGM FAKULTAS TEKNIK ◽

10.36982/jtg.v9i1.1082 ◽

2020 ◽

Vol 9 (1) ◽

Author(s):

Sartika Nisumanti ◽

Evina Krisna

Keyword(s):

Traffic Congestion ◽

Traffic Accidents ◽

Road Traffic ◽

Heavy Traffic ◽

Service Level ◽

Traffic Volume ◽

The Road ◽

Road Capacity ◽

On The Road ◽

The Impact

The roads transportation is an important infrastructure as one of the land transportation infrastructures for the movement of social activities and to support economic development, specifically in Palembang City. The population growth of Palembang City has resulted in an increase in the number of vehicles and highway users. As a result, transportation activities in Palembang, especially at Parameswara roads are increasing. The impact of this, there will be heavy traffic volume, resulting in conflicts on the road, which lead to traffic accidents. Therefore, there will be congestion and a decrease in the performance of the road speed.The research is conducted at Parameswara Road in Palembang that visually diminished the ability to accommodate the road traffic volume per day, accordingly the effect of traffic that occurs due to the lack of road capacity as the sequence of large volume traffic. The purpose of this study is to determine the capacity and level of road services to carried out the performance value on this road. The method used in the analysis is the Greenshield model, Greenberg, and Underwood. This study explains the maximum volume at peak hour that develop on Monday is between 1561 smp/hour and 1549 smp/hour. Whereas the lowest is around 1225 smp/hour and 1008 smp/hour that occurs on Sunday. Therefore, the analysis of service level on the research years at Parameswara Road depicts the saturated traffic conditions and low starting speed with D service index category and service level analysis at 10 years of planning time projections, the lpda result is from 2022 to 2026, The Parameswara road conditions at E and F service index categories are the traffic jam circumstances and slight speed. Hence, it necessitates constructing a non-plot way at Parameswara Road intersection to tackle this traffic congestion.Keywords: Greenshield, Greenberg, Underwood, Road Capacity.

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The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks

Journal of Advanced Transportation ◽

10.1155/2021/8404951 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Ji Eun Park ◽

Wanhee Byun ◽

Youngchan Kim ◽

Hyeonjun Ahn ◽

Doh Kyoum Shin

Keyword(s):

Traffic Flow ◽

Road Network ◽

Traffic Volume ◽

Transport Systems ◽

Automated Vehicles ◽

Average Delay ◽

The Road ◽

Capacity Increase ◽

Road Capacity ◽

The Impact

Automated vehicles (AVs) are believed to have great potential to improve the traffic capacity and efficiency of the current transport systems. Despite positive findings of the impact of AVs on traffic flow and potential road capacity increase for highways, few studies have been performed regarding the impact of AVs on urban roads. Moreover, studies considering traffic volume increase with a mixture of AVs and human-driven vehicles (HDVs) have rarely been conducted. Therefore, this study investigated the impact of gradual increments of AV penetration and traffic volume on urban roads. The study adopted a microsimulation approach using VISSIM with a Wiedmann 74 model for car-following behavior. Parameters for AVs were set at the SAE level 4 of automation. A real road network was chosen for the simulation having 13 intersections in a total distance of 4.5 km. The road network had various numbers of lanes from a single lane to five lanes in one direction. The network consists of a main arterial road and a parallel road serving nearby commercial and residential blocks. In total, 36 scenarios were investigated by a combination of AV penetrations and an increase in traffic volumes. The study found that, as AV penetration increased, traffic flow also improved, with a reduction of the average delay time of up to 31%. Also, as expected, links with three or four lanes had a more significant impact on the delay. In terms of road capacity increase, when the penetration of AVs was saturated at 100%, the road network could accommodate 40% more traffic.

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On the impact of connected automated vehicles in freeway work zones: a cooperative cellular automata model based approach

Journal of Intelligent and Connected Vehicles ◽

10.1108/jicv-11-2017-0001 ◽

2018 ◽

Vol 1 (1) ◽

pp. 1-14 ◽

Cited By ~ 5

Author(s):

Yun Zou ◽

Xiaobo Qu

Keyword(s):

Cellular Automata ◽

Travel Time ◽

Traffic Congestion ◽

High Speed ◽

Work Zones ◽

Automated Vehicles ◽

Cellular Automata Model ◽

Content Type ◽

Freeway Work Zones ◽

The Impact

Purpose Freeway work zones have been traffic bottlenecks that lead to a series of problems, including long travel time, high-speed variation, driver’s dissatisfaction and traffic congestion. This research aims to develop a collaborative component of connected and automated vehicles (CAVs) to alleviate negative effects caused by work zones. Design/methodology/approach The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations. Findings Simulation results show that, with the proposed component and penetration of CAVs, the average performances (travel time, safety and emission) can all be improved and the stochasticity of performances will be minimized too. Originality/value To the best of the authors’ knowledge, this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.

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Subtle Impact of Akt1 and Akt3 on Exploratory Behavior in Gene Targeted Mice

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000218 ◽

2015 ◽

Vol 223 (3) ◽

pp. 173-180 ◽

Cited By ~ 1

Author(s):

Christina Leibrock ◽

Michael Hierlmeier ◽

Undine E. Lang ◽

Florian Lang

Keyword(s):

Forced Swimming Test ◽

Open Field Test ◽

Wild Type ◽

Average Speed ◽

Closed Area ◽

Light Area ◽

Swimming Test ◽

The Impact ◽

Center Area ◽

Dark Transition

Abstract. The present study explored the impact of Akt1 and Akt3 on behavior. Akt1 (akt1-/-) and Akt3 (akt3-/-) knockout mice were compared to wild type (wt) mice. The akt1-/- mice, akt3-/- mice, and wt mice were similar in most parameters of the open-field test. However, the distance traveled in the center area was slightly but significantly less in akt3-/- mice than in wt mice. In the light/dark transition test akt1-/- mice had significantly lower values than wt mice and akt3-/- mice for distance traveled, number of rearings, rearing time in the light area, as well as time spent and distance traveled in the entrance area. They were significantly different from akt3-/- mice in the distance traveled, visits, number of rearings, rearing time in the light area, as well as time spent, distance traveled, number of rearings, and rearing time in the entrance area. In the O-maze the time spent, and the visits to open arms, as well as the number of protected and unprotected headdips were significantly less in akt1-/- mice than in wt mice, whereas the time spent in closed arms was significantly more in akt1-/- mice than in wt mice. Protected and unprotected headdips were significantly less in akt3-/- mice than in wt mice. In closed area, akt3-/- mice traveled a significantly larger distance at larger average speed than akt1-/- mice. No differences were observed between akt1-/- mice, akt3-/- mice and wt-type mice in the time of floating during the forced swimming test. In conclusion, akt1-/- mice and less so akt3-/ mice display subtle changes in behavior.

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