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University of California – Irvine
1.
Luong, Elaine.
Microscopic Car Following Models Simulation Study.
Degree: Civil Engineering, 2018, University of California – Irvine
URL: http://www.escholarship.org/uc/item/8tx731bq 
► This study aims to provide a comparison of different car following models in terms of safe distance, stability, and velocity. Although initially developed to model…
(more)
▼ This study aims to provide a comparison of different car following models in terms of safe distance, stability, and velocity. Although initially developed to model traffic, these algorithms can be applied to autonomous vehicles as a way to control following speed and acceleration. Each model was judged based on their performance in a theoretical ring road simulation. For the simulation, 22 vehicles were initially evenly spaced on a 230 meter length ring road. Every vehicle was assumed to follow the same car following algorithm and be connected to the leading vehicle in terms of information sharing. The following vehicle adjusted its acceleration and velocity based on stimuli such as relative velocity and spacing to the leading vehicle according to a car following algorithm. Most of the algorithms were able to produce adequate spacing between vehicles. The major differences between models were the average velocities and stability.
Subjects/Keywords: Transportation; autonomous; car-following; connected; models; simulation
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APA (6th Edition):
Luong, E. (2018). Microscopic Car Following Models Simulation Study. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/8tx731bq
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Luong, Elaine. “Microscopic Car Following Models Simulation Study.” 2018. Thesis, University of California – Irvine. Accessed February 26, 2021.
http://www.escholarship.org/uc/item/8tx731bq.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Luong, Elaine. “Microscopic Car Following Models Simulation Study.” 2018. Web. 26 Feb 2021.
Vancouver:
Luong E. Microscopic Car Following Models Simulation Study. [Internet] [Thesis]. University of California – Irvine; 2018. [cited 2021 Feb 26].
Available from: http://www.escholarship.org/uc/item/8tx731bq.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Luong E. Microscopic Car Following Models Simulation Study. [Thesis]. University of California – Irvine; 2018. Available from: http://www.escholarship.org/uc/item/8tx731bq
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Texas – Austin
2.
-9138-510X.
The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models.
Degree: PhD, Civil Engineering, 2019, University of Texas – Austin
URL: http://dx.doi.org/10.26153/tsw/2642
► Car-following behavior has been studied since the 1940s. However, complex calibration requirements and challenges with collecting high-resolution data have stunted advancements in this domain. Thus,…
(more)
▼ Car-
following behavior has been studied since the 1940s. However, complex calibration requirements and challenges with collecting high-resolution data have stunted advancements in this domain. Thus, methodologies to adequately capture naturalistic behavioral heterogeneity are largely missing from the literature.
For this dissertation, a sample from the second Strategic Highway Research Program Naturalistic Driving Study was analyzed. This sample contains 665 trips completed on freeways in clear weather conditions. Driver demographics, vehicle CAN bus, and external sensor data are available for each trip. The trajectories in this sample were processed and used to calibrate the Gipps, Intelligent Driver Model, and Wiedemann 99
car-
following models.
This dissertation seeks to improve how inter-driver heterogeneity in
car-
following behavior is accounted for in microsimulation
models. This dissertation has three primary objectives. Objective 1 identifies which driver attributes are sources of inter-driver heterogeneity. Objective 2 explores the viability of using census-level data to calibrate microsimulation
models. Objective 3 develops and evaluates a new mechanism for properly capturing inter-driver heterogeneity in microsimulation: an ensemble
car-
following model.
To achieve these objectives, first, Kruskal-Wallis one-way analysis of variance tests were applied to show statistically significant differences in both the estimated
car-
following model calibration coefficients and the overall model performance across groups of drivers categorized by commonalities in their driver attributes.
Next, the Expectation Maximization clustering algorithm was applied to show that, despite differences in driver behavior, homogeneous driver groups, or groups of drivers that behave similarly, exist in the dataset. Moreover, this dissertation shows that drivers can be classified into their proper homogeneous driver group only knowing their driver specific attributes.
Finally, VISSIM was used to implement the homogeneous driver groups in microsimulation. This case study illustrated that when inter-driver differences in driving behavior are explicitly modeled, there are notable impacts on the performance metrics collected from the microsimulation
models. These performance metrics are ultimately used by decision makers to evaluate alternatives for transportation funding. Thus, this dissertation provides evidence of the importance of appropriately modeling inter-driver differences to improve the quality of the microsimulation model results and inform better funding allocation decisions.
Advisors/Committee Members: Boyles, Stephen David, 1982- (advisor), Machemehl, Randy (committee member), Waller, Travis (committee member), Zhang, Zhanmin (committee member).
Subjects/Keywords: Naturalistic data; Behavioral heterogeneity; Car-following models; Calibration
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APA (6th Edition):
-9138-510X. (2019). The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2642
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Chicago Manual of Style (16th Edition):
-9138-510X. “The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed February 26, 2021.
http://dx.doi.org/10.26153/tsw/2642.
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
MLA Handbook (7th Edition):
-9138-510X. “The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models.” 2019. Web. 26 Feb 2021.
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Vancouver:
-9138-510X. The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Feb 26].
Available from: http://dx.doi.org/10.26153/tsw/2642.
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Council of Science Editors:
-9138-510X. The development of a holistic approach to modeling driver behavior : accounting for driver heterogeneity in car-following models. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2642
Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Delft University of Technology
3.
Echaniz Soldevila, Ignasi (author).
Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection.
Degree: 2017, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0
► This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model…
(more)
▼ This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid
car-
following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine learning techniques such as Gaussian process regression (GPR) to make predictions when there exist correlation between new input and the training dataset. On the other hand, it uses existent traditional parametric CF
models to predict acceleration when no similar situations are found in the training dataset. This formulation guarantees a complete and continues model and deals with the challenges of new available types of dataset in the transport field: noisy and incomplete yet with large amount of data. Multiple
models have been trained using the Optimal Velocity Model (OVM) as a basis parametric model and a dataset collected in the PPA project in Amsterdam by traffic radar detection in stop and go traffic conditions. The other main innovation of this thesis is that variables rarely included in any CF model such as the status and the distance of drivers to the traffic light are also analyzed. Results show that the GPR model formulation is robust as the model performs better than OVM alone according to the main KPI, but still collisions occasionally occur. Moreover, results depict that traffic light status actively influences driver behavior. Overall, this thesis gives insights into new powerful mathematical techniques that can be applied to describe longitudinal driving behavior or any modeled process.
Advisors/Committee Members: Hoogendoorn, Serge (mentor), Knoop, Victor (graduation committee), Steenbakkers, Jeroen (graduation committee), Alonso Mora, Javier (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Car-Following models; Longitudinal driver behavior; Machine Learning; Gausssian Process Regression; Non-parametric models; Urban signalized intersections; Traffic light
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APA (6th Edition):
Echaniz Soldevila, I. (. (2017). Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0
Chicago Manual of Style (16th Edition):
Echaniz Soldevila, Ignasi (author). “Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection.” 2017. Masters Thesis, Delft University of Technology. Accessed February 26, 2021.
http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0.
MLA Handbook (7th Edition):
Echaniz Soldevila, Ignasi (author). “Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection.” 2017. Web. 26 Feb 2021.
Vancouver:
Echaniz Soldevila I(. Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Feb 26].
Available from: http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0.
Council of Science Editors:
Echaniz Soldevila I(. Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:6f864003-8f63-4be3-8837-77656ed620d0
Delft University of Technology
4.
Blauw, Mathieu (author).
Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8
► The Dutch governmental organisation Rijkswaterstaat contributes to the smooth and safe flow of traffic, as both traffic jams and accidents cost society large amounts of…
(more)
▼ The Dutch governmental organisation Rijkswaterstaat contributes to the smooth and safe flow of traffic, as both traffic jams and accidents cost society large amounts of money each day. Roads are designed for the current traffic composition. Due to the promotion of Adaptive Cruise Control (ACC) systems, utilisation of these systems is expected to increase. Society benefits from insights into the effects these systems have on traffic flow, as they can help to reduce traffic jams and accidents. ACC systems are designed to increase driving comfort by taking over throttling and braking from the human driver. For optimal driver acceptance, these systems show similar driving behaviour to that of human drivers. However, this is not entirely possible due to limited anticipation. To predict how differences in driving behaviour affect traffic flows, researchers usually perform simulations using parametric
car-
following models. However, research shows contradictory findings. The goal of this research was to gain insights into the performance of commonly applied parametric
car-
following models on representing the driving behaviour of ACC systems. Optimal model calibration was obtained by investigating the sensitivity of the model calibration to synthetic data. Investigated were the calibration methodology and the quality and quantity of calibration data.
Models are calibrated to real-world driving data from an Audi A4 from 2017. These
models were used to assess the capability of representing typical highway scenarios: steady-state
car-
following, cut-in, cut-out, hard-braking and stop-and-go scenarios. The considered
models were the Intelligent Driver Model (IDM) model, which has previously been applied to model the driving behaviour of human drivers, the newly developed simplified ACC (sACC) model and a variant on this model. Insights in the sensitivity of the model calibration were obtained by performing a sensitivity analysis on synthetic data. Essential factors in achieving an optimal model calibration are: 1) the model closely matches the driving behaviour in the data, 2) noise levels are as low as possible and 3) the data should contain as many situations as possible that are also included in the model. The dataset must be sufficiently long to include all these situations and to allow the model to develop its dynamics entirely. Using these insights, a calibration was performed on real-world ACC driving data from an Audi A4 (2017). For the ACC system, it was found: 1) the ACC system exhibits non-linear driving behaviour, 2) the acceleration depends on the current velocity and distance to the desired velocity, 3) the system does not consider an intelligent braking strategy and is thus not able of handling safety-critical driving situations and 4) the model includes a sub-controller which ensures comfortable driving behaviour. Except for the comfortable sub-controller, the non-linear IDM model considers all of these factors and thus best represents the driving behaviour. The linear sACC model cannot represent standing…
Advisors/Committee Members: Happee, Riender (mentor), Knoop, Victor (mentor), Wang, Meng (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: ACC; Adaptive Cruise Control; Car-Following Models; Model Calibration; Calibration; Parametric; Rijkswaterstaat; IDM; Intelligent Driver Model
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APA (6th Edition):
Blauw, M. (. (2019). Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8
Chicago Manual of Style (16th Edition):
Blauw, Mathieu (author). “Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.” 2019. Masters Thesis, Delft University of Technology. Accessed February 26, 2021.
http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8.
MLA Handbook (7th Edition):
Blauw, Mathieu (author). “Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models.” 2019. Web. 26 Feb 2021.
Vancouver:
Blauw M(. Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 26].
Available from: http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8.
Council of Science Editors:
Blauw M(. Representing the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:c478714c-6449-4240-ab6d-154017e68dd8
5.
Henclewood, Dwayne A.
The Development of a Dynamic-Interactive-Vehicle Model for Modeling Traffic Beyond the Microscopic Level.
Degree: MS, Civil Engineering, 2007, University of Massachusetts
URL: https://scholarworks.umass.edu/theses/41
► The state-of-the-art traffic simulation packages model traffic on a microscopic level. This includes the use of several sets of models that dictate how traffic moves…
(more)
▼ The state-of-the-art traffic simulation packages model traffic on a microscopic level. This includes the use of several sets of
models that dictate how traffic moves within a transportation network. These
models include
car-
following, gap acceptance, lane-changing and route choice
models. The aim of this thesis is to improve the treatment of vehicle dynamics in traffic simulation and, as a result, special attention was paid to
car-
following models. These
models were highlighted because they are largely responsible
for capturing a vehicle’s motion and its relevant dynamics in traffic simulation. In order to improve the treatment of vehicle dynamics in traffic simulation, a Dynamic-Interactive-Vehicle (DIV) model was developed.
This vehicle model is calibrated with the use of essential vehicle performance specifications that are responsible for the movement of a vehicle in a transportation network. After the calibration process the model is able to accept three inputs from a driver – gas pedal, brake pedal and steering wheel positions. The model then outputs the corresponding longitudinal and latitudinal values which represent the movement of a vehicle along a roadway. The vehicle model will also account for most of the dominant external forces that affect an automobile’s performance along a roadway. This thesis will validate the proposed model by comparing its output from a few performance tests with the performance test results of three passenger cars. The DIV model was validated by comparing the acceleration, braking and steering performance test results of three passenger cars with the output from the DIV model upon performing similar tests. It was found that the DIV model was successful at replicating the two-dimensional vehicle motion.
Advisors/Committee Members: Daiheng Ni.
Subjects/Keywords: Traffic Simulation; Vehicle Dynamics; Car Following Models; Engine Model
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APA (6th Edition):
Henclewood, D. A. (2007). The Development of a Dynamic-Interactive-Vehicle Model for Modeling Traffic Beyond the Microscopic Level. (Masters Thesis). University of Massachusetts. Retrieved from https://scholarworks.umass.edu/theses/41
Chicago Manual of Style (16th Edition):
Henclewood, Dwayne A. “The Development of a Dynamic-Interactive-Vehicle Model for Modeling Traffic Beyond the Microscopic Level.” 2007. Masters Thesis, University of Massachusetts. Accessed February 26, 2021.
https://scholarworks.umass.edu/theses/41.
MLA Handbook (7th Edition):
Henclewood, Dwayne A. “The Development of a Dynamic-Interactive-Vehicle Model for Modeling Traffic Beyond the Microscopic Level.” 2007. Web. 26 Feb 2021.
Vancouver:
Henclewood DA. The Development of a Dynamic-Interactive-Vehicle Model for Modeling Traffic Beyond the Microscopic Level. [Internet] [Masters thesis]. University of Massachusetts; 2007. [cited 2021 Feb 26].
Available from: https://scholarworks.umass.edu/theses/41.
Council of Science Editors:
Henclewood DA. The Development of a Dynamic-Interactive-Vehicle Model for Modeling Traffic Beyond the Microscopic Level. [Masters Thesis]. University of Massachusetts; 2007. Available from: https://scholarworks.umass.edu/theses/41
Queensland University of Technology
6.
Bevrani, Kaveh.
The development of a naturalistic car following model for assessing managed motorway systems' safety effects.
Degree: 2013, Queensland University of Technology
URL: https://eprints.qut.edu.au/61499/
► This thesis highlights the limitations of the existing car following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of…
(more)
▼ This thesis highlights the limitations of the existing car following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car following models emulating driver behaviour precise parameters such as headways and Time to Collisions. The comparison evaluates the robustness of each car following model for safety metric reproductions. A new car following model, based on the personal space concept and fish school model is proposed to simulate more precise traffic metrics. This new model is capable of reflecting changes in the headway distribution after imposing the speed limit form VSL systems. This research facilitates assessing Intelligent Transportation Systems on motorways, using microscopic simulation.
Subjects/Keywords: Microscopic simulation models; Managed Motorway Systems (MMS); Driver behavioural models; Car following models; Motorways; VSL; Safety indicators; Time to Collision; headways distribution
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APA (6th Edition):
Bevrani, K. (2013). The development of a naturalistic car following model for assessing managed motorway systems' safety effects. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/61499/
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Bevrani, Kaveh. “The development of a naturalistic car following model for assessing managed motorway systems' safety effects.” 2013. Thesis, Queensland University of Technology. Accessed February 26, 2021.
https://eprints.qut.edu.au/61499/.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Bevrani, Kaveh. “The development of a naturalistic car following model for assessing managed motorway systems' safety effects.” 2013. Web. 26 Feb 2021.
Vancouver:
Bevrani K. The development of a naturalistic car following model for assessing managed motorway systems' safety effects. [Internet] [Thesis]. Queensland University of Technology; 2013. [cited 2021 Feb 26].
Available from: https://eprints.qut.edu.au/61499/.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Bevrani K. The development of a naturalistic car following model for assessing managed motorway systems' safety effects. [Thesis]. Queensland University of Technology; 2013. Available from: https://eprints.qut.edu.au/61499/
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
7.
Nezafat, Reza Vatani.
Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies.
Degree: MS, Civil/Environmental Engineering, 2019, Old Dominion University
URL: 9781085623971
;
https://digitalcommons.odu.edu/cee_etds/82
► Connected vehicles (CVs) will enable new applications to improve traffic flow. This study’s focus is to investigate how potential implementation of variable speed limit…
(more)
▼ Connected vehicles (CVs) will enable new applications to improve traffic flow. This study’s focus is to investigate how potential implementation of variable speed limit (VSL) through different types of communication and sensing technologies on CVs may improve traffic flow at a sag curve. At sag curves, the gradient changes from negative to positive values which causes a reduction in the roadway capacity and congestion. A VSL algorithm is developed and implemented in a simulation environment for controlling the inflow of vehicles to a sag curve on a freeway to minimize delays and increase throughput. Both vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) options for CVs are investigated while implementing the VSL control strategy in a simulation environment. Through a feedback control algorithm, the speed of CVs are manipulated in the upstream of the sag curve to avoid the formation of bottlenecks caused by the change in longitudinal driver behavior. A modified version of the intelligent driver model (IDM) is used to simulate driving behavior on the sag curve. Depending on the traffic density at a sag curve, the feedback control algorithm adjusts the approach speeds of CVs so that the throughput of the sag curve is maximized. A meta-heuristic algorithm is employed to determine the critical control parameters. Various market penetration rates for CVs are considered in the simulations for three alternative communications and sensing technologies. It is demonstrated that for higher Market Penetration Rates (MPR) the performance is the same for all three scenarios which means there is no need for infrastructure-based sensing when the MPR is high enough. The results demonstrate that not only the MPR of CVs but also how CVs are distributed in the traffic stream is critical for system performance. While MPR could be high, uneven distribution of CVs and lack of CVs at the critical time periods as congestion is building up may cause a deterioration in system performance.
Advisors/Committee Members: Mecit Cetin, Sherif S. Ishak, Hong Yang.
Subjects/Keywords: Car following models; Connected vehicles DSRC; Meta-heuristic algorithm; Sag curve; Artificial Intelligence and Robotics; Civil Engineering; Electrical and Computer Engineering; Transportation Engineering
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APA ·
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APA (6th Edition):
Nezafat, R. V. (2019). Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies. (Thesis). Old Dominion University. Retrieved from 9781085623971 ; https://digitalcommons.odu.edu/cee_etds/82
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Nezafat, Reza Vatani. “Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies.” 2019. Thesis, Old Dominion University. Accessed February 26, 2021.
9781085623971 ; https://digitalcommons.odu.edu/cee_etds/82.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Nezafat, Reza Vatani. “Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies.” 2019. Web. 26 Feb 2021.
Vancouver:
Nezafat RV. Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies. [Internet] [Thesis]. Old Dominion University; 2019. [cited 2021 Feb 26].
Available from: 9781085623971 ; https://digitalcommons.odu.edu/cee_etds/82.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Nezafat RV. Variable Speed Limit Control at SAG Curves Through Connected Vehicles: Implications of Alternative Communications and Sensing Technologies. [Thesis]. Old Dominion University; 2019. Available from: 9781085623971 ; https://digitalcommons.odu.edu/cee_etds/82
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Virginia Tech
8.
Gao, Yu.
Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models.
Degree: MS, Civil Engineering, 2008, Virginia Tech
URL: http://hdl.handle.net/10919/35005
► Microscopic traffic simulation software have gained significant popularity and are widely used both in industry and research mainly because of the ability of these tools…
(more)
▼ Microscopic traffic simulation software have gained significant popularity and are widely used both in industry and research mainly because of the ability of these tools to reflect the dynamic nature of the transportation system in a stochastic fashion. To better utilize these software, it is necessary to understand the underlying logic and differences between them. A
Car-
following model is the core of every microscopic traffic simulation software. In the context of this research, the thesis develops procedures for calibrating the steady-state
car-
following models in a number of well known microscopic traffic simulation software including: CORSIM, AIMSUN, VISSIM, PARAMICS and INTEGRATION and then compares the VISSIM and INTEGRATION software for the modeling of traffic signalized approaches.
The thesis presents two papers. The first paper develops procedures for calibrating the steady-state component of various
car-
following models using macroscopic loop detector data. The calibration procedures are developed for a number of commercially available microscopic traffic simulation software, including: CORSIM, AIMSUN2, VISSIM, Paramics, and INTEGRATION. The procedures are then applied to a sample dataset for illustration purposes. The paper then compares the various steady-state
car-
following formulations and concludes that the Gipps and Van Aerde steady-state
car-
following models provide the highest level of flexibility in capturing different driver and roadway characteristics. However, the Van Aerde model, unlike the Gipps model, is a single-regime model and thus is easier to calibrate given that it does not require the segmentation of data into two regimes. The paper finally proposes that the
car-
following parameters within traffic simulation software be link-specific as opposed to the current practice of coding network-wide parameters. The use of link-specific parameters will offer the opportunity to capture unique roadway characteristics and reflect roadway capacity differences across different roadways.
Second, the study compares the logic used in both the VISSIM and INTEGRATION software, applies the software to some simple networks to highlight some of the differences/similarities in modeling traffic, and compares the various measures of effectiveness derived from the
models. The study demonstrates that both the VISSIM and INTEGRATION software incorporate a psycho-physical
car-
following model which accounts for vehicle acceleration constraints. The INTEGRATION software, however uses a physical vehicle dynamics model while the VISSIM software requires the user to input a vehicle-specific speed-acceleration kinematics model. The use of a vehicle dynamics model has the advantage of allowing the model to account for the impact of roadway grades, pavement surface type, pavement surface condition, and type of vehicle tires on vehicle acceleration behavior. Both
models capture a driverâ s willingness to run a yellow light if conditions warrant it. The VISSIM software incorporates a statistical stop/go probability…
Advisors/Committee Members: Rakha, Hesham A. (committeechair), Trani, Antonio A. (committee member), Abbas, Montasir M. (committee member).
Subjects/Keywords: INTEGRATION; Microscopic Traffic Simulation; VISSIM; Car-following Models; Measurements of Effectiveness
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APA (6th Edition):
Gao, Y. (2008). Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/35005
Chicago Manual of Style (16th Edition):
Gao, Yu. “Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models.” 2008. Masters Thesis, Virginia Tech. Accessed February 26, 2021.
http://hdl.handle.net/10919/35005.
MLA Handbook (7th Edition):
Gao, Yu. “Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models.” 2008. Web. 26 Feb 2021.
Vancouver:
Gao Y. Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models. [Internet] [Masters thesis]. Virginia Tech; 2008. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10919/35005.
Council of Science Editors:
Gao Y. Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models. [Masters Thesis]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/35005
Virginia Tech
9.
Pasumarthy, Venkata Siva Praveen.
Formulations, Issues and Comparison of Car-Following Models.
Degree: MS, Civil Engineering, 2004, Virginia Tech
URL: http://hdl.handle.net/10919/41129
► Microscopic simulation software use car-following models to capture the interaction of a vehicle and the preceding vehicle traveling in the same lane. In the literature,…
(more)
▼ Microscopic simulation software use
car-
following models to capture the interaction of a vehicle and the preceding vehicle traveling in the same lane. In the literature, much research has been carried out in the field of
car-
following and traffic stream modeling. Microscopic
car-
following models have been characterized by using the relationship between a vehicleâ s desired speed and the distance headway (h) between the lead and follower vehicles. On the other hand, macroscopic traffic stream
models describe the motion of a traffic stream by approximating for the flow of a continuous compressible fluid. This research work develops and compares three different formulations of
car-
following models â speed formulation, molecular acceleration, and fluid acceleration formulation. First, four state-of-the-art
car-
following models namely, Van Aerde, Greenshields, Greenberg and Pipes
models, are selected for developing the three aforementioned formulations. Then a comprehensive
car-
following behavior encompassing steady-state conditions and two constraints â acceleration and collision avoidance â is presented. Specifically, the variable power vehicle dynamics model proposed by Rakha and Lucic (2002) is utilized for the acceleration constraint. Subsequently, the thesis describes the issues associated with
car-
following formulations. Recognizing that many different traffic flow conditions exist, three distinct scenarios are selected for comparison purposes. The results demonstrate that the speed formulation ensures that vehicles typically revert to steady-state conditions when vehicles experience a perturbation from steady-state conditions. On the other hand, both acceleration formulations are unable to converge to steady-state conditions when the system experiences a perturbation from a steady-state. The thesis also attempts to address the question of capacity drop associated with vehicles accelerating from congested conditions. Specifically, the capacity drop proposition is analyzed for the case of a backward recovery (typical of a signalized intersection) and stationary shockwave (typical of a capacity drop on a freeway). In the case of the backward recovery shockwave, the acceleration constraint results in a temporally and spatially confined capacity drop as vehicles accelerate to their desired steady-state speed. This temporally and spatially confined capacity drop results in what is typically termed the start loss of a signalized phase. Subsequently, vehicles attain steady-state conditions, in the case of the speed and molecular acceleration formulations, at the traffic signal stop bar after the initial five vehicle departures. The analysis also demonstrates that after attaining steady-state conditions the capacity may drop for the initial vehicle departures as a result of traffic stream dispersion. This traffic dispersion capacity drop…
Advisors/Committee Members: Rakha, Hesham A. (committeechair), Adjerid, Slimane (committee member), Trani, Antoino A. (committee member).
Subjects/Keywords: Car-Following Models; Speed and Acceleration Formulations; Discharge Headways and Capacity Drop; Traffic Stream Models
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APA (6th Edition):
Pasumarthy, V. S. P. (2004). Formulations, Issues and Comparison of Car-Following Models. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/41129
Chicago Manual of Style (16th Edition):
Pasumarthy, Venkata Siva Praveen. “Formulations, Issues and Comparison of Car-Following Models.” 2004. Masters Thesis, Virginia Tech. Accessed February 26, 2021.
http://hdl.handle.net/10919/41129.
MLA Handbook (7th Edition):
Pasumarthy, Venkata Siva Praveen. “Formulations, Issues and Comparison of Car-Following Models.” 2004. Web. 26 Feb 2021.
Vancouver:
Pasumarthy VSP. Formulations, Issues and Comparison of Car-Following Models. [Internet] [Masters thesis]. Virginia Tech; 2004. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10919/41129.
Council of Science Editors:
Pasumarthy VSP. Formulations, Issues and Comparison of Car-Following Models. [Masters Thesis]. Virginia Tech; 2004. Available from: http://hdl.handle.net/10919/41129
10.
Cattin, Johana.
Consideration of dynamic traffic conditions in the estimation of industrial vehicules energy consumption while integrating driving assistance strategies : Prise en compte des conditions de trafic dynamique dans l'évaluation des consommations énergétiques des véhicules industriels en intégrant les stratégies d'aide à la conduite.
Degree: Docteur es, Génie Civil, 2019, Lyon
URL: http://www.theses.fr/2019LYSET003
► Le monde industriel, et en particulier l’industrie automobile, cherche à représenter au mieux le réel pour concevoir des outils et produits les plus adaptés aux…
(more)
▼ Le monde industriel, et en particulier l’industrie automobile, cherche à représenter au mieux le réel pour concevoir des outils et produits les plus adaptés aux enjeux et marchés actuels. Dans cette optique, le groupe Volvo a développé de puissants outils pour la simulation de la dynamique des véhicules industriels. Ces outils permettent notamment l’optimisation de composants véhicules ou de stratégies de contrôle. De nombreuses activités de recherche portent sur des technologies innovantes permettant de réduire la consommation des véhicules industriels et d’accroitre la sécurité de leurs usages dans différents environnements. En particulier, le développement des systèmes d’aide à la conduite automobile ITS et ADAS. Afin de pouvoir développer ces systèmes, un environnement de simulation permettant de prendre en compte les différents facteurs pouvant influencer la conduite d’un véhicule doit être mis en place. L’étude se concentre sur la simulation de l’environnement du véhicule et des interactions entre le véhicule et son environnement direct, i.e. le véhicule qui le précède. Les interactions entre le véhicule étudié et le véhicule qui le précède sont modélisées à l’aide de modèles mathématiques, nommés lois de poursuites. De nombreux modèles existent dans la littérature mais peu concernent le comportement des véhicules industriels. Une étude détaillée de ces modèles et des méthodes de calage est réalisée. L’environnement du véhicule peut être représenté par deux catégories de paramètres : statiques (intersections, nombre de voies…) et dynamiques (état du réseau). A partir d’une base de données de trajets usuels, ces paramètres sont calculés, puis utilisés pour générer de manière automatisée des scénarios de simulation réalistes.
The industrial world, and in particular the automotive industry, is seeking to best represent the real world in order to design tools and products that are best adapted to current challenges and markets, by reducing development times and prototyping costs. With this in mind, the Volvo Group has developed powerful tools to simulate the dynamics of industrial vehicles. These tools allow the optimization of vehicle components or control strategies. Many research activities focus on innovative technologies to reduce the consumption of industrial vehicles and increase the safety of their use in different environments. Particularly, the development of ITS and ADAS is booming. In order to be able to develop these systems, a simulation environment must be set up to take into account the various factors that can influence the driving of a vehicle. The work focuses on simulating the vehicle environment and the interactions between the vehicle and its direct environment, i.e. the vehicle in front of it. The interactions between the vehicle under study and the vehicle in front of it are modelled using mathematical models, called car-following models. Many models exist in the literature, but few of them deals specifically with heavy duty vehicles. A specific focus on these models and their calibration…
Advisors/Committee Members: Faouzi, Nour-Eddin el-Faouzi (thesis director), Leclercq, Ludovic (thesis director).
Subjects/Keywords: Consommation énergiétiques; Poids lourd; Lois de poursuite; Calibration / Optimisation; Statistiques d'usage; Système de Transport Intelligent (STI); Système d'aide à a conduite automobile (ADAS); Energy consumption; Heavy Duty Vehicles; Car-following models; Calibration / Optimization; Statistics of use; Intelligent Transportation Systems (ITS); Advanced Driver Assistance Systems (ADAS)
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APA ·
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APA (6th Edition):
Cattin, J. (2019). Consideration of dynamic traffic conditions in the estimation of industrial vehicules energy consumption while integrating driving assistance strategies : Prise en compte des conditions de trafic dynamique dans l'évaluation des consommations énergétiques des véhicules industriels en intégrant les stratégies d'aide à la conduite. (Doctoral Dissertation). Lyon. Retrieved from http://www.theses.fr/2019LYSET003
Chicago Manual of Style (16th Edition):
Cattin, Johana. “Consideration of dynamic traffic conditions in the estimation of industrial vehicules energy consumption while integrating driving assistance strategies : Prise en compte des conditions de trafic dynamique dans l'évaluation des consommations énergétiques des véhicules industriels en intégrant les stratégies d'aide à la conduite.” 2019. Doctoral Dissertation, Lyon. Accessed February 26, 2021.
http://www.theses.fr/2019LYSET003.
MLA Handbook (7th Edition):
Cattin, Johana. “Consideration of dynamic traffic conditions in the estimation of industrial vehicules energy consumption while integrating driving assistance strategies : Prise en compte des conditions de trafic dynamique dans l'évaluation des consommations énergétiques des véhicules industriels en intégrant les stratégies d'aide à la conduite.” 2019. Web. 26 Feb 2021.
Vancouver:
Cattin J. Consideration of dynamic traffic conditions in the estimation of industrial vehicules energy consumption while integrating driving assistance strategies : Prise en compte des conditions de trafic dynamique dans l'évaluation des consommations énergétiques des véhicules industriels en intégrant les stratégies d'aide à la conduite. [Internet] [Doctoral dissertation]. Lyon; 2019. [cited 2021 Feb 26].
Available from: http://www.theses.fr/2019LYSET003.
Council of Science Editors:
Cattin J. Consideration of dynamic traffic conditions in the estimation of industrial vehicules energy consumption while integrating driving assistance strategies : Prise en compte des conditions de trafic dynamique dans l'évaluation des consommations énergétiques des véhicules industriels en intégrant les stratégies d'aide à la conduite. [Doctoral Dissertation]. Lyon; 2019. Available from: http://www.theses.fr/2019LYSET003
11.
Lanka, Venkata Raghava Ravi Teja, Lanka.
VEHICLE RESPONSE PREDICTION USING PHYSICAL AND MACHINE
LEARNING MODELS.
Degree: MS, Mechanical Engineering, 2017, The Ohio State University
URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1511891682062084
► With sporadic advancement in computer technology, transportation is moving towards autonomy. With rapid increase in production of highly automated vehicles (AVs), validation and safety of…
(more)
▼ With sporadic advancement in computer technology,
transportation is moving towards autonomy. With rapid increase in
production of highly automated vehicles (AVs), validation and
safety of AVs is gaining high importance. The estimation of safety
for AVs is a challenging problem as the AVs mimic human drivers and
it requires an estimate of AVs response at all critical scenarios.
AV response in each scenario, if known, can be used for estimating
its safety.In this work, methods for estimating vehicle response
are proposed by using various
models based on both physics-based
modeling as well as Machine Learning algorithms. Various Machine
Learning algorithms were explored for classifying and predicting
driver’s intention, such as Extremely Randomized Trees and Gaussian
Mixture Model based Hidden Markov Model. Also, physics-based
modeling is done for longitudinal
car-
following conditions using
three
models namely: Spring-Damper model, Time-to-Collision model
and Gazis-Herman-Rothery model.The Machine Learning
models were
fitted using Naturalistic Driving Study dataset (NDS) collected as
a part of Strategic Highway Research Program-2 (SHRP2). The
vehicular data comprising of various vehicular parameters is
processed and analyzed for preparing driver’s behavior model, which
gives an estimate of vehicle’s longitudinal and lateral
acceleration at that given instance. Physics-based
models were
limited to longitudinal acceleration prediction as lateral
acceleration prediction in dynamic traffic conditions is a highly
complex problem for modeling. The physics-based
models were fitted
using both SHRP2 as well as the test track data of AVs collected
from Transportation Research Center Inc.Then, the fitted Machine
Learning and physics-based
models were validated against validation
data. The parameters obtained from physics-based
models were used
for obtaining driving characteristics, which were used to compare
tested AVs among themselves as well as human drivers.
Advisors/Committee Members: Heydinger, Gary (Advisor), Guenther, Dennis (Committee Chair).
Subjects/Keywords: Transportation; Mechanical Engineering; Engineering; Machine Learning, Longitudinal Car-Following Models,
Extremely Randomized Trees, Random Forest, Hidden Markov Models,
Validation
…77
Figure 4.20: Performance of 3 models for Driver # 1 car-following data… …78
Figure 4.21: Performance of 3 models for Driver # 2 car-following data… …79
Figure 4.22: Performance of 3 models for Driver # 3 car-following data… …physical models for longitudinal car-following scenarios were explored in this thesis.
The models… …50
4.3.2 Collection of human driver car-following data…
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APA ·
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APA (6th Edition):
Lanka, Venkata Raghava Ravi Teja, L. (2017). VEHICLE RESPONSE PREDICTION USING PHYSICAL AND MACHINE
LEARNING MODELS. (Masters Thesis). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1511891682062084
Chicago Manual of Style (16th Edition):
Lanka, Venkata Raghava Ravi Teja, Lanka. “VEHICLE RESPONSE PREDICTION USING PHYSICAL AND MACHINE
LEARNING MODELS.” 2017. Masters Thesis, The Ohio State University. Accessed February 26, 2021.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1511891682062084.
MLA Handbook (7th Edition):
Lanka, Venkata Raghava Ravi Teja, Lanka. “VEHICLE RESPONSE PREDICTION USING PHYSICAL AND MACHINE
LEARNING MODELS.” 2017. Web. 26 Feb 2021.
Vancouver:
Lanka, Venkata Raghava Ravi Teja L. VEHICLE RESPONSE PREDICTION USING PHYSICAL AND MACHINE
LEARNING MODELS. [Internet] [Masters thesis]. The Ohio State University; 2017. [cited 2021 Feb 26].
Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1511891682062084.
Council of Science Editors:
Lanka, Venkata Raghava Ravi Teja L. VEHICLE RESPONSE PREDICTION USING PHYSICAL AND MACHINE
LEARNING MODELS. [Masters Thesis]. The Ohio State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1511891682062084
Texas A&M University
12.
Schultz, Grant George.
Developing a methodology to account for commercial motor vehicles using microscopic traffic simulation models.
Degree: PhD, Civil Engineering, 2004, Texas A&M University
URL: http://hdl.handle.net/1969.1/111
► The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future…
(more)
▼ The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation
models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation
models that has received increased attention in recent years is the calibration of these
models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation
models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation
models. The research develops a methodology to model CMVs using microscopic traffic simulation
models and then utilizes the output of these
models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.
Advisors/Committee Members: Rilett, Laurence R. (advisor), Burris, Mark W. (committee member), Spiegelman, Clifford H. (committee member), Lomax, Timothy J. (committee member).
Subjects/Keywords: commercial motor vehicles; microscopic traffic simulation models; weigh-in-motion; WIM; intelligent transportation systems; ITS; car-following; genetic algorithm; automatic vehicle classification; AVC; CORSIM; principal component analysis; recursive partitioning; CART; calibration; emissions
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Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Schultz, G. G. (2004). Developing a methodology to account for commercial motor vehicles using microscopic traffic simulation models. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/111
Chicago Manual of Style (16th Edition):
Schultz, Grant George. “Developing a methodology to account for commercial motor vehicles using microscopic traffic simulation models.” 2004. Doctoral Dissertation, Texas A&M University. Accessed February 26, 2021.
http://hdl.handle.net/1969.1/111.
MLA Handbook (7th Edition):
Schultz, Grant George. “Developing a methodology to account for commercial motor vehicles using microscopic traffic simulation models.” 2004. Web. 26 Feb 2021.
Vancouver:
Schultz GG. Developing a methodology to account for commercial motor vehicles using microscopic traffic simulation models. [Internet] [Doctoral dissertation]. Texas A&M University; 2004. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/1969.1/111.
Council of Science Editors:
Schultz GG. Developing a methodology to account for commercial motor vehicles using microscopic traffic simulation models. [Doctoral Dissertation]. Texas A&M University; 2004. Available from: http://hdl.handle.net/1969.1/111
. 
Open Access Theses and Dissertations
