Article
Mathematics, Applied
Guy Fayolle, Jean-Marc Lasgouttes, Carlos Flores
Summary: We investigate the transfer function resulting from the linearization of a car-following model for human drivers, considering their reaction time. The findings reveal nontrivial stability conditions and distinguish between stability, string stability, and partial string stability.
SIAM JOURNAL ON APPLIED MATHEMATICS
(2022)
Article
Physics, Multidisciplinary
Lin Hou, Yulong Pei, Qingling He
Summary: In this study, a Multi-Lane MultiVehicle State Information Index Smoothing Fusion (MLMVISF) model is proposed to enhance the stability of heterogeneous traffic flow in smart grids. Through linear stability analysis and numerical simulation, the model shows a significant improvement in stability compared to other models.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Shuang Han, Jing Zhang, Quanyue Yang, Zijian Yuan, Shubin Li, Fengying Cui, Chuntang Zhang, Tao Wang
Summary: This paper introduces the PID control strategy into the classical car-following system, enhancing the stability of the system and providing an efficient method for optimizing the traffic flow system.
ENGINEERING COMPUTATIONS
(2022)
Article
Mathematics, Applied
Paul Petersik, Debabrata Panja, Henk A. Dijkstra
Summary: In this study, an equation-free method was used to perform bifurcation analyses of various artificial neural network (ANN) based car-following models. The ANN-m model demonstrated good detail in capturing the behavior of the MCF model, while the ANN-r model showed better simulation of traffic jams with more input information.
PHYSICA D-NONLINEAR PHENOMENA
(2021)
Article
Physics, Multidisciplinary
Zijian Yuan, Tao Wang, Jing Zhang, Shubin Li
Summary: This study developed a new car-following model that utilizes dynamic safe headway to prevent collisions, improve driving performance, and smooth traffic flow. The model achieved quantitative agreement with empirical data.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Multidisciplinary
Ziwei Yi, Wenqi Lu, Xu Qu, Jing Gan, Linheng Li, Bin Ran
Summary: This paper presents a bidirectional distance balanced model (BDBM) for car-following in a connected environment, which balances the distance between the host vehicle and its preceding and following vehicles. The model is shown to improve traffic stability while maintaining traffic efficiency through theoretical analysis and simulations.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Engineering, Civil
Ehsan Kamjoo, Ramin Saedi, Ali Zockaie, Mehrnaz Ghamami, Timothy Gates, Alireza Talebpour
Summary: This study investigates the impact of snowplows on car-following behavior and compares car-following models with and without a collision avoidance system. The results show that snowplows significantly affect car-following behavior, while the improvement in behavior from the collision avoidance system is not statistically significant. Additionally, considering driving behavior heterogeneity leads to more accurate prediction of car-following behavior. Developing specific models for winter maintenance operations helps in the development of microsimulation models for adverse weather conditions.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Physics, Multidisciplinary
Ziyu Cui, Xiaoning Wang, Yusheng Ci, Changyun Yang, Jia Yao
Summary: In the foreseeable future, as Connected and Autonomous Vehicles (CAVs) coexist with Human-driven Vehicles (HDVs), a complex heterogeneous traffic environment will emerge. This research proposes an improved car-following model based on the Intelligent Driver Model (IDM) to analyze the impact of CAVs on car-following behavior and the operational characteristics of heterogeneous traffic flow. The results indicate that the improved model significantly improves traffic flow stability and reduces the start-up time of vehicles at signalized intersections.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Chemistry, Analytical
Ziwei Yi, Wenqi Lu, Xu Qu, Linheng Li, Peipei Mao, Bin Ran
Summary: Connected vehicle (CV) technologies are transforming traditional traffic models, with the proposal of bidirectional vehicle information structure (BDVIS) and derived multiple vehicles information structure (DMVIS) to enhance car-following models using acceleration information of preceding and following vehicles. Both BDVIS and DMVIS demonstrate better performance in improving traffic flow stability compared to the original car-following model, and provide advantages for differently positioned vehicles within a platoon.
Article
Physics, Multidisciplinary
Weixiu Pan, Jing Zhang, Junfang Tian, Fengying Cui, Tao Wang
Summary: This paper proposes a combination car-following model that integrates a theory-driven model with a data-driven model. By optimizing parameters and integrating prediction outcomes, the model improves accuracy and controllability, and achieves significant error reduction in numerical simulations.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Transportation Science & Technology
Jie Sun, Zuduo Zheng, Anshuman Sharma, Jian Sun
Summary: This study investigates the stability characteristics of human-driven connected vehicles (CV) and extends a recently-developed car-following (CF) model by considering human factors. The results show that the connected environment improves CF stability and reduces traffic congestion, and higher compliance to information benefits traffic flow stability, except in situations with large time delays.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Mechanical
Ziyu Song, Haitao Ding
Summary: In this study, a car-following model is proposed to explain the car-following behavior of HDVs, AVs, and CAVs in mixed traffic. The model incorporates the velocity of surrounding vehicles, the difference in velocity, and the headway between each pair of vehicles. The model's parameters are optimized based on real road test data, and its accuracy is verified through simulation. The results show that the proposed model outperforms the IDM, ACC, and CACC models in simulating car-following behavior of HDVs, AVs, and CAVs.
NONLINEAR DYNAMICS
(2023)
Article
Economics
Marouane Bouadi, Bin Jia, Rui Jiang, Xingang Li, Zi-You Gao
Summary: The presence of stochastic factors destabilizes traffic flow and stimulates concave growth pattern of traffic oscillations. Impact of stochasticity depends on sensitivity to gap and velocity difference. Stochastic car-following models accurately reproduce observed traffic instability and concave growth pattern of traffic oscillations, highlighting significant impact of stochastic factors on traffic dynamics.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Engineering, Civil
Jie Sun, Zuduo Zheng, Jian Sun
Summary: This paper relaxes an unrealistic assumption commonly adopted in the stability analysis of car-following (CF) models, which is the fixed equilibrium state assumption. The influence mechanism of the equilibrium state and its change on the stability of CF models is studied, considering the impact of asymmetry in CF models. The results show significant differences between symmetric and asymmetric CF models: the acceleration process significantly destabilizes the traffic with asymmetric CF models, while the influence of acceleration and deceleration on the stability change is identical and relatively insignificant for symmetric CF models.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Physics, Multidisciplinary
Jun Du, Bin Jia, Rui Jiang, Shi-Teng Zheng
Summary: Understanding the impact of leading speed pattern on traffic oscillation evolution is crucial in traffic flow studies. This paper extends the frequency-domain stability analysis to investigate this impact and provides numerical simulations to validate the analytical findings.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Fluids & Plasmas
Andrew Mellor, Mauro Mobilia, S. Redner, Alastair M. Rucklidge, Jonathan A. Ward
Article
Mathematics, Applied
Peter Grindrod, Desmond J. Higham, Peter Laflin, Amanda Otley, Jonathan A. Ward
EUROPEAN JOURNAL OF APPLIED MATHEMATICS
(2016)
Article
Multidisciplinary Sciences
Jonathan A. Ward, Andrew J. Evans, Nicolas S. Malleson
ROYAL SOCIETY OPEN SCIENCE
(2016)
Article
Mathematics, Applied
Sergey Melnik, Jonathan A. Ward, James P. Gleeson, Mason A. Porter
Article
Chemistry, Physical
A. C. Fowler, J. A. Ward, S. B. G. O'Brien
JOURNAL OF COLLOID AND INTERFACE SCIENCE
(2011)
Article
Mathematics, Applied
Jonathan A. Ward, Peter Grindrod
PHYSICA D-NONLINEAR PHENOMENA
(2014)
Article
Physics, Fluids & Plasmas
James P. Gleeson, Sergey Melnik, Jonathan A. Ward, Mason A. Porter, Peter J. Mucha
Article
Physics, Multidisciplinary
James P. Gleeson, Jonathan A. Ward, Kevin P. O'Sullivan, William T. Lee
PHYSICAL REVIEW LETTERS
(2014)
Article
Multidisciplinary Sciences
Jonathan A. Ward, R. Eddie Wilson
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2011)
Article
Computer Science, Information Systems
Annabel Whipp, Nicolas Malleson, Jonathan Ward, Alison Heppenstall
Summary: This paper critically assesses the utility of conventional and novel data sources for building fine-scale spatio-temporal estimates of the ambient population. It provides a framework of reference for researchers and highlights the implications for national and international applications in urban planning and policy development.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2021)
Article
Multidisciplinary Sciences
Jonathan A. Ward
Summary: The study derived explicit formulas to quantify the Markov chain state-space compression achieved in real-world networks by exploiting redundancies due to symmetries. It found that for most networks, lumping can lead to a state-space compression ratio of up to 107, with the largest compression ratio identified being nearly 1012, many of which are found in animal social networks. The study also presented examples of symmetry types in real-world networks that had not been previously reported.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2021)
Article
Computer Science, Interdisciplinary Applications
Robert Clay, Jonathan A. Ward, Patricia Ternes, Le-Minh Kieu, Nick Malleson
Summary: The paper introduces a new method called RJUKF, which combines the UKF data assimilation algorithm with elements of the RJ Markov chain Monte Carlo method, allowing assimilation of both continuous and categorical parameters. This method demonstrates potential applications in crowd management through simulations.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Social Sciences, Interdisciplinary
Nick Malleson, Kevin Minors, Le-Minh Kieu, Jonathan A. Ward, Andrew A. West, Alison Heppenstall
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION
(2020)
Article
Computer Science, Theory & Methods
Jonathan A. Ward, Martin Lopez-Garcia
APPLIED NETWORK SCIENCE
(2019)
Article
Economics
Stephen Haben, Jonathan Ward, Danica Vukadinovic Greetham, Colin Singleton, Peter Grindrod
INTERNATIONAL JOURNAL OF FORECASTING
(2014)
