Parameter Sensitivity Analysis of a Cooperative Dynamic Bus Lane System With Connected Vehicles

2021 ◽  
pp. 036119812110357
Author(s):  
Meng Xie ◽  
Michael Winsor ◽  
Tao Ma ◽  
Andreas Rau ◽  
Fritz Busch ◽  
...  
Keyword(s):  
Travel Time ◽  
Transition Period ◽  
Penetration Rate ◽  
Simulation Models ◽  
Driving Behavior ◽  
Connected Vehicles ◽  
Microscopic Simulation ◽  
Communication Range ◽  
Bus Lane ◽  
The Impact

This paper aims to evaluate the sensitivity of the proposed cooperative dynamic bus lane system with microscopic traffic simulation models. The system creates a flexible bus priority lane that is only activated on demand at an appropriate time with advanced information and communication technologies, which can maximize the use of road space. A decentralized multi-lane cooperative algorithm is developed and implemented in a microscopic simulation environment to coordinate lane changing, gap acceptance, and car-following driving behavior for the connected vehicles (CVs) on the bus lane and the adjacent lanes. The key parameters for the sensitivity study include the penetration rate and communication range of CVs, considering the transition period and gradual uptake of CVs. Multiple scenarios are developed and compared to analyze the impact of key parameters on the system’s performance, such as total saved travel time of all passengers and travel time variation among buses and private vehicles. The microscopic simulation models showed that the cooperative dynamic bus lane system is significantly sensitive to the variations of the penetration rate and the communication range in a congested traffic state. With a CV system and a communication range of 150 m, buses obtain maximum benefits with minimal impacts on private vehicles in the study simulation. The safety concerns induced by cooperative driving behavior are also discussed in this paper.

Influence of Autonomous Vehicles on Car-Following Behavior of Human Drivers

2019 ◽  
Vol 2673 (12) ◽  
pp. 367-379 ◽  
Author(s):  
Yalda Rahmati ◽  
Mohammadreza Khajeh Hosseini ◽  
Alireza Talebpour ◽  
Benjamin Swain ◽  
Christopher Nelson
Keyword(s):  
Autonomous Vehicles ◽  
Simulation Models ◽  
Driving Behavior ◽  
Data Driven ◽  
Microscopic Simulation ◽  
Car Following ◽  
The Road ◽  
Human Driver ◽  
Significant Difference ◽  
On The Road

Despite numerous studies on general human–robot interactions, in the context of transportation, automated vehicle (AV)–human driver interaction is not a well-studied subject. These vehicles have fundamentally different decision-making logic compared with human drivers and the driving interactions between AVs and humans can potentially change traffic flow dynamics. Accordingly, through an experimental study, this paper investigates whether there is a difference between human–human and human–AV interactions on the road. This study focuses on car-following behavior and conducted several car-following experiments utilizing Texas A&M University’s automated Chevy Bolt. Utilizing NGSIM US-101 dataset, two scenarios for a platoon of three vehicles were considered. For both scenarios, the leader of the platoon follows a series of speed profiles extracted from the NGSIM dataset. The second vehicle in the platoon can be either another human-driven vehicle (scenario A) or an AV (scenario B). Data is collected from the third vehicle in the platoon to characterize the changes in driving behavior when following an AV. A data-driven and a model-based approach were used to identify possible changes in driving behavior from scenario A to scenario B. The findings suggested there is a statistically significant difference between human drivers’ behavior in these two scenarios and human drivers felt more comfortable following the AV. Simulation results also revealed the importance of capturing these changes in human behavior in microscopic simulation models of mixed driving environments.

scholarly journals Traffic Simulation Analysis on Running Speed in a Connected Vehicles Environment

2019 ◽  
Vol 16 (22) ◽  
pp. 4373 ◽  
Author(s):  
Bin Yu ◽  
Miyi Wu ◽  
Shuyi Wang ◽  
Wen Zhou
Keyword(s):  
Travel Time ◽  
Delay Time ◽  
Traffic Simulation ◽  
Road Traffic ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Connected Vehicles ◽  
Running Speed ◽  
Traffic Characteristics ◽  
The Impact

Connected vehicles (CVs) exchange a variety of information instantly with surrounding vehicles and traffic facilities, which could smooth traffic flow significantly. The objective of this paper is to analyze the effect of CVs on running speed. This study compared the delay time, travel time, and running speed in the normal and the connected states, respectively, through VISSIM (a traffic simulation software developed by PTV company in German). The optimization speed model was established to simulate the decision-makings of CVs in MATLAB, considering the parameters of vehicle distance, average speed, and acceleration, etc. After the simulation, the vehicle information including speed, travel time, and delay time under the normal and the connected states were compared and evaluated, and the influence of different CV rates on the results was analyzed. In a two-lane arterial road, running speed in the connected state increase by 4 km/h, and the total travel time and delay time decrease by 5.34% and 16.76%, respectively, compared to those in the normal state. The optimal CV market penetration rate related to running speed and delay time is 60%. This simulation-based study applies user-defined lane change and lateral behavior rules, and takes different CV rates into consideration, which is more reliable and practical to estimate the impact of CV on road traffic characteristics.

scholarly journals Modeling and simulation of intersection quasi-moving block speed guidance based on connected vehicles

2020 ◽  
Vol 3 (2) ◽  
pp. 67-78
Author(s):  
Qing Xu ◽  
Jiangfeng Wang ◽  
Botong Wang ◽  
Xuedong Yan
Keyword(s):  
Traffic Congestion ◽  
High Speed ◽  
Connected Vehicles ◽  
Content Type ◽  
Communication Range ◽  
Proposed Model ◽  
Simulation Results ◽  
The Impact ◽  
Block Section ◽  
Guidance Model

Purpose This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency. By introducing the theory of moving block section for high-speed train control, a speed guidance model based on the quasi-moving block speed guidance (QMBSG) is proposed to direct platoon including human-driven vehicles and connected vehicles (CV) through the intersection coordinately. Design/methodology/approach In this model, the green time of the intersection is divided into multiple block intervals according to the minimal safety headway. Connected vehicles can pass through the intersection by following the block interval using the QMBSG model. The block interval is assigned dynamically according to the traveling relation of HV and CV, when entering the communication range of the intersection. To validate the comprehensive guidance effect of the proposed model, a general evaluation function (GEF) is established. Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Findings Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Also, compared to the single intersection speed guidance model, the GEF value of the QMBSG model improves over 17.1%. To further explore the guidance effect, the impact of sensitivity factors of the CVs’ environment, such as intersection environment, communication range and penetration rate (PR) is analyzed. When the PR reaches 75.0%, the GEF value will change suddenly and the model guidance effect will be significantly improved. This paper also analyzes the impact of the length of block interval under different PR and traffic demands. It is found that the proposed model has a better guidance effect when the length of the block section is 2 s, which facilitates traffic congestion alleviation of the intersection in practice. Originality/value Based on the aforementioned discussion, the contributions of this paper are three-fold. Based on the traveling information of HV/CV and the signal phase and timing plans, the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately, by following the block interval assigned dynamically. Considering comprehensively the indexes of mobility, safety and environment, a GEF is provided to evaluate the guidance effect of vehicles through the intersection. Sensitivity analysis is carried out on the QMBSG model. The key communication and traffic parameters of the CV environment are analyzed, such as path attenuation, PR, etc. Finally, the effect of the length of block interval is explored.

scholarly journals Identifying Optimum Taper Lengths for Zipper Merging Applications using Real Data and Microscopic Simulation

2019 ◽  
Vol 48 (3) ◽  
pp. 210-220
Author(s):  
Wakeel Idewu ◽  
Pattanun Chanpiwat ◽  
Hana Naghawi
Keyword(s):  
Travel Time ◽  
Simulation Models ◽  
Real Data ◽  
Microscopic Simulation ◽  
Construction Sites ◽  
Design Guideline ◽  
Traffic Volumes ◽  
Unique Approach ◽  
Transition Length ◽  
Lane Closures

Motorists lack of understanding on the proper way to maneuver through lane closures during congested periods cause driver confusion. This confusion directly and indirectly creates inconsistent flow patterns, forced merges, travel time delays, and crashes. Engineers and developers have tried to improve the merge systems used in construction zones to reduce driver frustration, improve travel time, and increase safety. Encouraging drivers to use the zipper merge approach has been assumed by some to target these issues. When implemented, drivers jointly merge together in an alternating fashion at two-to-one lane closures/reductions. There is a difference in opinion between traffic officials concerning the taper length required to efficiently accommodate these types of merging patterns – particularly those that occur near construction sites. Current practice uses the taper design guideline presented in the MUTCD. However, some believe this unique approach to merging at lane reductions should be accompanied by a shorter/longer taper. This study simulated 192 scenarios consisting of eight different percent truck compositions, six different transition lengths, and four different traffic volumes in VISSIM. The simulation models were calibrated with field data taken while a zipper merge configuration was in operation on a freeway. The main objective was to identify the optimum transition length when placing a zipper merge configuration because it visually and physically promoted alternating merging maneuvers. The results indicated none of the six tested taper lengths had a clear advantage over the other under multiple traffic volumes and truck percentages. Although statistically equal, operational differences in response to taper lengths were present and became more pronounced as volumes and truck percentages increased.

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 Car Following and Microscopic Traffic Simulation Under Distracted Driving

2021 ◽  
pp. 036119812110003
Author(s):  
Sunbola Zatmeh-Kanj ◽  
Tomer Toledo
Keyword(s):  
Traffic Flow ◽  
Coefficient Of Variation ◽  
Driving Simulator ◽  
Traffic Simulation ◽  
Driving Behavior ◽  
Transportation Systems ◽  
Microscopic Simulation ◽  
Microscopic Traffic Simulation ◽  
Car Following ◽  
The Impact

Microscopic simulation models have been widely used as tools to investigate the operation of traffic systems and different intelligent transportation systems applications. The fidelity of microscopic simulation tools depends on the driving behavior models that they implement. However, current models commonly do not consider human-related factors, such as distraction. The potential for distraction while driving has increased rapidly with the availability of smartphones and other connected and infotainment devices. Thus, an understanding of the impact of distraction on driving behavior is essential to improve the realism of microscopic traffic tools and support safety and other applications that are sensitive to it. This study focuses on car-following behavior in the context of distracting activities. The parameters of the well-known GM and intelligent driver models are estimated under various distraction scenarios using data collected with an experiment conducted in a driving simulator. The estimation results show that drivers are less sensitive to their leaders while talking on the phone and especially while texting. The estimated models are implemented in a microscopic traffic simulation model. The average speed, coefficient of variation of speed, acceleration noise and acceleration and deceleration time fractions were used as measures of performance indicating traffic flow and safety implications. The simulation results show deterioration of traffic flow with texting and to some extent talking on the phone: average speeds are lower and the coefficient of variation of speeds are higher. Further experimentation with varying fractions of texting drivers showed similar trends.

scholarly journals Impact of connected vehicle guidance information on network-wide average travel time

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668335 ◽  
Author(s):  
Jiangfeng Wang ◽  
Jiarun Lv ◽  
Qian Zhang ◽  
Xuedong Yan
Keyword(s):  
Travel Time ◽  
Data Exchange ◽  
Positive Impact ◽  
Penetration Rate ◽  
Transportation Systems ◽  
Time Variability ◽  
Connected Vehicle ◽  
Vehicle Guidance ◽  
Average Travel Time ◽  
The Impact

With the emergence of connected vehicle technologies, the potential positive impact of connected vehicle guidance on mobility has become a research hotspot by data exchange among vehicles, infrastructure, and mobile devices. This study is focused on micro-modeling and quantitatively evaluating the impact of connected vehicle guidance on network-wide travel time by introducing various affecting factors. To evaluate the benefits of connected vehicle guidance, a simulation architecture based on one engine is proposed representing the connected vehicle–enabled virtual world, and connected vehicle route guidance scenario is established through the development of communication agent and intelligent transportation systems agents using connected vehicle application programming interface considering the communication properties, such as path loss and transmission power. The impact of connected vehicle guidance on network-wide travel time is analyzed by comparing with non-connected vehicle guidance in response to different market penetration rate, following rate, and congestion level. The simulation results explore that average network-wide travel time in connected vehicle guidance shows a significant reduction versus that in non–connected vehicle guidance. Average network-wide travel time in connected vehicle guidance have an increase of 42.23% comparing to that in non-connected vehicle guidance, and average travel time variability (represented by the coefficient of variance) increases as the travel time increases. Other vital findings include that higher penetration rate and following rate generate bigger savings of average network-wide travel time. The savings of average network-wide travel time increase from 17% to 38% according to different congestion levels, and savings of average travel time in more serious congestion have a more obvious improvement for the same penetration rate or following rate.

scholarly journals Underground travel time estimation for macro simulation models, on the example of the first line in Warsaw

2014 ◽  
Vol 13 (4) ◽  
pp. 067-074
Author(s):  
Marek Bauer
Keyword(s):  
Travel Time ◽  
Stopping Time ◽  
Time Estimation ◽  
Simulation Models ◽  
Stopping Times ◽  
Travel Time Estimation ◽  
Travel Time Prediction ◽  
Running Time ◽  
Average Running Time ◽  
The Impact

In this paper, the author’s model of underground travel time prediction was presented. The structure of the model can be used to estimate the travel time of any underground line in the planning phase. The model takes into account the length and the variability of running time between stations and stopping time at these stations. Partial models of average running time depending on the length of the sections – for six periods of the working day, developed on the basis of measurements on the first underground line in Warsaw were presented. Similar models for the estimation of the standard deviation of running time were also presented. Stopping times for three types of stations, varying in terms of the average stopping time and location of the station in relation to the city center were estimated. Paper presents also a practical example of the use of the model: evaluation of the impact of additional stations on the travel time on the underground line in Warsaw.

scholarly journals Using Microscopic Simulation-Based Analysis to Model Driving Behavior: A Case Study of Khobar-Dammam in Saudi Arabia

2019 ◽  
Vol 11 (11) ◽  
pp. 3018 ◽  
Author(s):  
Hassan M. Al-Ahmadi ◽  
Arshad Jamal ◽  
Imran Reza ◽  
Khaled J. Assi ◽  
Syed Anees Ahmed
Keyword(s):  
Saudi Arabia ◽  
Traffic Simulation ◽  
Management Strategies ◽  
Simulation Models ◽  
Driving Behavior ◽  
Transportation Systems ◽  
Simulation Software ◽  
Sustainable Transportation ◽  
Microscopic Simulation

Sustainable transportation systems play a key role in the socio-economic development of a country. Microscopic simulation models are becoming increasingly useful tools in designing, optimizing, and evaluating the sustainability of transportation systems and concerned management strategies. VISSIM, a microscopic traffic simulation software, has gained rapid recognition in the field of traffic simulation. However, default values for different input parameters used during simulation need to be tested to ensure a realistic replication for local traffic conditions. This paper attempts to model driving behavior parameters using the microscopic simulation software VISSIM through a case study in the Khobar-Dammam metropolitan areas in Saudi Arabia. VISSIM default values for different sensitive parameters such as lane change distances, additive and multiplicative parts of desired safety distances, the number of preceding vehicles spotted, amber signal decisions, and minimum headway were identified to be most sensitive and significant parameters to be calibrated to precisely replicate field conditions. The simulation results using default values produced higher link speed, larger queue length, and shorter travel times than those observed in the field. However, measures of effectiveness (MOEs) obtained from calibrated models over desired simulation runs were comparable to those obtained from field surveys. All compared MOEs used to validate the model matched within a range of 5–10% to the field-observed values.

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