| 1. |
- Fang, Shan, et al.
(författare)
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A Dynamic Transformation Car-Following Model for the Prediction of the Traffic Flow Oscillation
- 2024
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Ingår i: IEEE Intelligent Transportation Systems Magazine. - 1939-1390 .- 1941-1197. ; 16:1, s. 174-198
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Tidskriftsartikel (refereegranskat)abstract
- Car-following (CF) behavior is a fundamental of traffic flow modeling; it can be used for the virtual testing of connected and automated vehicles and the simulation of various types of traffic flow, such as free flow and traffic oscillation. Although existing CF models can replicate the free flow well, they are incapable of simulating complicated traffic oscillation, and it is difficult to strike a balance between accuracy and efficiency. This article investigates the error variation when the traffic oscillation is simulated by the intelligent driver model (IDM). Then, it divides the traffic oscillation into four phases (coasting, deceleration, acceleration, and stationary) by using the space headway of multiple steps. To simulate traffic oscillation between multiple human-driven vehicles, a dynamic transformation CF model is proposed, which includes the long-time prediction submodel [modified sequence-to-sequence (Seq2seq)] model, short-time prediction submodel (Transformer), and their dynamic transformation strategy]. The first submodel is utilized to simulate the coasting and stationary phases, while the second submodel is utilized to simulate the acceleration and deceleration phases. The results of experiments indicated that compared to K-nearest neighbors, IDM, and Seq2seq CF models, the dynamic transformation CF model reduces the trajectory error by 60.79–66.69% in microscopic traffic flow simulations, 7.71–29.91% in mesoscopic traffic flow simulations, and 1.59–18.26% in macroscopic traffic flow simulations. Moreover, the runtime of the dynamic transformation CF model (Inference) decreased by 14.43–66.17% when simulating the large-scale traffic flow.
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| 2. |
- He, Yixu, et al.
(författare)
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Exploring the design of reward functions in deep reinforcement learning-based vehicle velocity control algorithms
- 2024
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Ingår i: Transportation Letters. - 1942-7867 .- 1942-7875. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- The application of deep reinforcement learning (DRL) techniques in intelligent transportation systems garners significant attention. In this field, reward function design is a crucial factor for DRL performance. Current research predominantly relies on a trial-and-error approach for designing reward functions, lacking mathematical support and necessitating extensive empirical experimentation. Our research uses vehicle velocity control as a case study, build training and test sets, and develop a DRL framework for speed control. This framework examines both single-objective and multi-objective optimization in reward function designs. In single-objective optimization, we introduce “expected optimal velocity” as an optimization objective and analyze how different reward functions affect performance, providing a mathematical perspective on optimizing reward functions. In multi-objective optimization, we propose a reward function design paradigm and validate its effectiveness. Our findings offer a versatile framework and theoretical guidance for developing and optimizing reward functions in DRL, particularly for intelligent transportation systems.
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| 3. |
- Li, Zongbao, et al.
(författare)
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Upconversion Luminescence of Graphene Oxide through Hybrid Waveguide
- 2018
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Ingår i: The Journal of Physical Chemistry C. - : AMER CHEMICAL SOC. - 1932-7447 .- 1932-7455. ; 122:29, s. 16866-16871
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Tidskriftsartikel (refereegranskat)abstract
- Phonon-assisted upconversion is a promising way to generate short-wavelength emissions under excitation of long wavelength based on unique anti-Stokes luminescence properties. Graphene oxide nanosheets (GONs) exhibit excellent optical properties owing to quantum confinement and edge effects, which have driven research into fundamental principles and potential applications. Here, we experimentally demonstrate upconversion emission by exciting an easily fabricated GON hybrid waveguide (GHVV) with enhanced photothermal effects. The results reveal different origins of short-wavelength range and long-wavelength range in the upconversion spectra, whereas the emissive surface defects of GONs and GHW structure play significant roles in the behavior of photoluminescence. Introducing other upconversion materials to promote emission efficiency, the hybrid waveguide system might readily provide the possibility for the construction of upconversion fiber lasers and remote control of the upconversion luminescence.
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| 4. |
- Cao, Danni, et al.
(författare)
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Quantification of the impact of traffic incidents on speed reduction: A causal inference based approach
- 2021
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 157
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Tidskriftsartikel (refereegranskat)abstract
- This paper designs a systemic framework to quantify speed reduction induced by traffic incidents using a causal inference framework. The results can provide a reference to traffic managers for evaluating incident severities, thus take proper control measures after the incident in order not to underestimate or overestimate the negative impact. A two-phase scheme is proposed, including impacted region determination and speed reduction quantification. We first propose a Frame Region (FR) method, based on the shockwave propagation, to determine the spatiotemporal impacted region (SIR) using speed map. It is worth-noting that we design a statistical experiment to prove the rationality of congestion threshold selection. Secondly, we introduce a causal inference method for identifying the matched freeway segments. The traffic condition of finally matched freeway segments can be served as non-incident traffic condition of the incident occurred location, which contributes to quantifying the incident impact on speed reduction. We further demonstrate the proposed method in a case study by taking advantage of an incident record and related real freeway speed data in China. An interesting observation is that, along with the freeway segments away from the incident location, the congestion duration time of different freeway segments firstly rises and then decreases. The case study also illustrates the impact of incident on speed lasts almost 3 h and the congestion caused by the incident spreads 11 km, while the average causal effect of incident on all the impacted freeway segments is 42.3 km/h.
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| 5. |
- Cao, Qi, et al.
(författare)
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Jointly estimating the most likely driving paths and destination locations with incomplete vehicular trajectory data
- 2023
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Ingår i: Transportation Research, Part C: Emerging Technologies. - 0968-090X. ; 155
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Tidskriftsartikel (refereegranskat)abstract
- With an ever-increasing deployment density of probe and fixed sensors, massive vehicular trajectory data is available and show a promising foundation to improve the observability of dynamic traffic demand pattern. However, due to technical and privacy issues, the raw trajectories are not always complete and the paths and destinations between discontinuous trajectory nodes are usually missing. This paper proposes a probabilistic method to jointly reconstruct the missing driving path and destination location of vehicles with incomplete trajectory data. One problem-specific HMM-structured model incorporating spatial and temporal analysis (ST-HMM) is constructed to define the matching probability between observed data and possible movement. Two algorithms, namely candidate set generation and best-match search algorithms, are developed to seek the most possible one as matching result. It can implement end-to-end processing from incomplete trajectory data to complete and connective paths and destinations for the target vehicle. The proposed method is tested based on field-test data and city-wide road network. Compared with two benchmark methods, the proposed method improved the matching accuracy in terms of both path identification and destination inference. Additionally, sensitivity analyses on the size of training dataset and candidate set were performed. We believe that experiment results of these sensitivity analyses can help to provide guidance on data sensing and candidate generation.
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| 6. |
- Chen, Peilin, et al.
(författare)
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Fabrication of a silver nanoparticle-coated collagen membrane with anti-bacterial and anti-inflammatory activities for guided bone regeneration
- 2018
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Ingår i: Biomedical materials. - 1748-6041. ; 13:6
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Tidskriftsartikel (refereegranskat)abstract
- Alveolar bone loss is a common problem that affects dental implant placement. A barrier between the bone substitute and gingiva that can prevent fibro-tissue ingrowth, bacterial infection and induce bone formation is a key factor in improving the success of alveolar ridge reconstruction. This study aims to develop a bioactive collagen barrier material for guided bone regeneration, that is coupled with anti-bacterial and anti-inflammatory properties. We have evaluated two silver coating methods and found controllable and precise coating achieved by sonication compared with sputtering. The optimized AgNP-coated collagen membrane exhibited excellent anti-bacterial effects against Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa) with limited cellular toxicity. It also displayed effective anti-inflammatory effects by reducing the expression and release of inflammatory cytokines including IL-6 and TNF-alpha. Additionally, AgNP-coated collagen membranes were able to induce osteogenic differentiation of mesenchymal stem cells that guide bone regeneration. These findings demonstrate the potential application of AgNP-coated collagen membranes to prevent infection after bone graft introduction in alveolar ridge reconstruction.
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| 7. |
- Gao, Kun, 1993, et al.
(författare)
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Cumulative prospect theory coupled with multi-attribute decision making for modeling travel behavior
- 2021
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Ingår i: Transportation Research Part A: Policy and Practice. - : Elsevier BV. - 0965-8564. ; 148, s. 1-21
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Tidskriftsartikel (refereegranskat)abstract
- This study proposes an approach for modeling travel behavior under uncertainty coupling Cumulative Prospect Theory (CPT) with Multi-attribute Decision Making (MADM) theory. CPT is utilized to depict travelers’ evaluations of each attribute, and MADM describes the process of making tradeoffs among multiple conflicting criteria. Divergent perception principles for different attributes are considered in the proposed framework. The proposed approach is utilized for an empirical analysis concerning mode shift behavior for commuting in Shanghai of China, based on data collected by stated preference surveys. Results show that the proposed approach outperforms conventional methods in terms of model performances and behavioral revelations. Empirical results demonstrate that sensitivity to gains and losses in cost and travel time are divergent in mode shift behavior. More importantly, it is found that travelers underestimate the occurrence chances of low-probability travel time and overestimate the occurrence changes of high-probability travel time in mode shift behavior, which is contrary to the findings from economics. Travelers show substantial loss aversion features as well. The heterogeneity in the value functions of CPT is investigated to shed light on differences in the evaluation process among individuals. Results reveal quite different empirical CPT parameters and behavioral mechanisms in mode shift behavior as compared to monetary experiments in economics. It highlights the importance of empirical estimations in various travel choice contexts to essentially understand travel behavior mechanisms, rather than arbitrary usage of findings from economics.
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| 8. |
- Gao, Kun, 1993, et al.
(författare)
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Data-driven interpretation on interactive and nonlinear effects of the correlated built environment on shared mobility
- 2023
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Ingår i: Journal of Transport Geography. - 0966-6923. ; 110
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Tidskriftsartikel (refereegranskat)abstract
- Understanding the usage demand of shared mobility systems in different areas of a city and its determinants is crucial for planning, operation and management of the systems. This study leverages an unbiased data-driven approach called accumulated effect analysis for examining the complex (nonlinear and interactive) effects of correlated built environment factors on the usage of shared mobility. Special research emphasis is given to unraveling the complex effects using an unbiased and data-driven approach that can overcome the impacts of correlations among built environment factors. Based on empirical analysis of synthetic data and a field dataset about dockless bike sharing systems (DLBS), results demonstrate that the method of partial dependency analysis prevalent in the relevant literature, will result in biases when investigating the effects of correlated built environment factors. In comparison, accumulated local effect analysis can appropriately interpret the effects of correlated built environment factors. The main effects of many built environment factors on the usage of DLBS present nonlinear and threshold patterns, quantitively revealed by accumulated local analysis. The approach can reveal complex interaction effects between different built environment factors (e.g., commercial service and education facility, and metro station coverage and living facility) on the usage of DLBS as well. The interactions among two built environment factors could even change with the values of the factors rather than invariant. The outcomes offer a new approach for revealing complex influences of different built environment factors with correlations as well as in-depth empirical understandings regarding the usage of DLBS.
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| 9. |
- Gao, Kun, 1993, et al.
(författare)
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Diverging effects of subjective prospect values of uncertain time and money
- 2021
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Ingår i: Communications in Transportation Research. - : Elsevier BV. - 2772-4247. ; 1
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Tidskriftsartikel (refereegranskat)abstract
- Studies from behavioral economics show that the subjective prospect value of money has diminishing sensitivity to losses/gains, represented by an S-shape, and this has been applied in representing the subjective prospect value of time in many transportation studies such as travel behavior modeling and network equilibrium. In this study, we demonstrate that the prospect value of time has an increasing sensitivity to losses/gains and can be represented by an Ϩ-shape, which contrasts that of money. We further explain the rationality of this surprising finding based on psychological and behavioral theories and discuss extensive practical implications. The correlations between sensitivities to gains and losses in terms of magnitude are revealed as well to shed light on potential underlying correlated behavioral principles. Substantial loss-aversion features are observed in the empirical analysis, supporting endowment effects. Implications of the findings on decision-making and other areas that utilize time as a key indicator have been discussed. The findings may revolutionize many research areas that utilize time as a key indicator such as transportation engineering.
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| 10. |
- Gao, Kun, 1993, et al.
(författare)
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Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction
- 2021
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Ingår i: Transportation Research Part D: Transport and Environment. - : Elsevier BV. - 1361-9209. ; 97
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Tidskriftsartikel (refereegranskat)abstract
- Improving passengers’ satisfaction is crucial for airline industry and requires in-depth understandings regarding the complex effects of various factors. This study investigates the importance, complex nonlinear effects and interaction effects of various factors (including passenger characteristics and service attributes) on airline travel satisfaction in data-driven manners leveraging machine-learning (ML) approaches. The results show that ML algorithms such as Random Forest have superiority in modeling airline travel satisfaction as compared to conventional logistic regressions. The quantitative importance of various factors is estimated and compared to reveal key determinants of passengers’ satisfaction using permutation-based importance and accumulated local effect analysis. More importantly, results suggest that the main effects of service attributes present piecewise nonlinear patterns. There are piecewise interaction effects between passenger characteristics and service attributes and among service attributes on airline travel satisfaction. Practical implications on efficient and cost-effective measures of promoting satisfaction are derived and discussed based on the findings.
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