| 1. |
- Fan, Jieyu, et al.
(författare)
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Evaluating the Impact of Signal Control on Emissions at Intersections
- 2022
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Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Nature Singapore. - 2190-3026 .- 2190-3018. ; 304 SIST, s. 104-111
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Konferensbidrag (refereegranskat)abstract
- Transport emission has become an increasingly serious problem, and it is an urgent issue in sustainable transport. In this study, by constructing traffic emission models for different vehicle types and operating conditions, the changes in CO, HC, and NOx emissions of light-duty and heavy-duty vehicles before and after signal control optimization were quantified based on VISSIM simulation. The OBEAS-3000 vehicle emission testing device was used to collect data on the micro-operational characteristics of different vehicles under different operating conditions as well as traffic emission data. Based on the data collected, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to calculate the emissions of light and heavy vehicles in the mixed traffic flow before and after intersection signal optimization. It is known from the study that signal control optimization has a greater impact on heavy vehicles than on light vehicles. Emissions of CO, HC, and NOx from heavy vehicles and light vehicles are all reduced, but NOx emissions from light vehicles remain largely unchanged. The research results reveal the emission patterns of light and heavy vehicles in different micro-operating conditions and establish a traffic emission model. It provides a theoretical basis for accurate traffic emission analysis and traffic flow optimization, as well as a scientific basis for the formulation of traffic management measures and emission reduction in large city transport systems.
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| 2. |
- Peci, Gentrina, et al.
(författare)
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Usage Pattern Analysis of e-scooter Sharing System: A Case Study in Gothenburg, Sweden
- 2022
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Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Nature Singapore. - 2190-3026 .- 2190-3018. ; 304 SIST, s. 123-132
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Konferensbidrag (refereegranskat)abstract
- Swedish cities are embracing shared micro-mobility systems (SMMS) such as e-scooters sharing systems to promote sustainable travel behavior in urban contexts with corresponding infrastructure planning. SMMS is associated with various social, environmental, and economic benefits, as well as providing solutions for the first- and the last-mile problem of using public transit. This study analyzes the usage patterns of e-scooter systems, based on the scooter operation data of VOI company in Gothenburg, Sweden. The used data cover the transaction data of two and half months during the summer and include over five hundred thousand valid trip records. The result shows that most trips travel a distance between 0.5–1.8 km while the duration lasts between 4–7 min. Fridays and Saturdays are the most popular days while Sunday is the least popular day. The number of trips on Sundays decreases by about 60% compared to Fridays and Saturdays. Moreover, the e-scooters are used to varying degrees in the different areas of Gothenburg. The e-scooters are used at a much higher extent in central Gothenburg compared to areas outside the city center. This can be due to several different factors such as location, land use, and accessibility. Lastly, the results show that the e-scooters are not primarily used for commuting but rather for leisure, which can be seen in the average distance and duration of the entire zone as well as the temporal distribution.
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| 3. |
- Yu, Yang, et al.
(författare)
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To Investigate the Hidden Gap between Traffic Flow Fundamental Diagrams and the Derived Microscopic Car Following Models: A Theoretical Analysis
- 2020
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Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Singapore. - 2190-3026 .- 2190-3018. ; 185, s. 89-98
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Konferensbidrag (refereegranskat)abstract
- Traffic flow fundamental diagram, or simply speed–density relationship and/or flow–density relationship, is the basis of traffic flow theories and road performance studies since it depicts the mathematical relationship among three traffic flow fundamental parameters—density, speed, and traffic flow. In this paper, through mathematical analyses and simulations, we find that for all existing fundamental diagram models, their derived microscopic car following models do not perform well and cannot reproduce the status of the stable flow described by the corresponding fundamental diagrams. The results indicate that there seems to exist a hidden gap between existing traffic flow fundamental diagrams and the corresponding microscopic car following models. We further discuss about the fundamental causes behind such gap and propose a simple yet incomplete solution at the end of this paper.
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| 4. |
- Yuan, Ye, et al.
(författare)
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Smart Pavement: An Attention-Based Classification Model for Road Pavement Material
- 2022
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Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Nature Singapore. - 2190-3026 .- 2190-3018. ; 304 SIST, s. 133-140
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Konferensbidrag (refereegranskat)abstract
- Intelligent recognition of traffic road damage is essential for realizing smart vehicles and intelligent transportation systems. The classification of road material types before recognition is a challenge for traffic road damage recognition due to differences in features such as concrete and asphalt. In addition, the widely distributed roads make environmental factors a critical factor affecting the classification. In this paper, we propose a deep learning-based road material classification method that introduces an attention mechanism to deal with the influence of different environments on road material recognition. We acquired tens of thousands of road surface images for training and testing and performed practical validation in real roads. The experiments show that our method has high accuracy and recall in road material classification.
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| 5. |
- Zhu, Jie, 1990, et al.
(författare)
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Bi-level ramp merging coordination for dense mixed traffic conditions
- 2024
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Ingår i: Fundamental Research. - 2096-9457 .- 2667-3258. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- Connected and Autonomous Vehicles (CAVs) hold great potential to improve traffic efficiency, emissions and safety in freeway on-ramp bottlenecks through coordination between mainstream and on-ramp vehicles. This study proposes a bi-level coordination strategy for freeway on-ramp merging of mixed traffic consisting of CAVs and human-driven vehicles (HDVs) to optimize the overall traffic efficiency and safety in congested traffic scenarios at the traffic flow level instead of platoon levels. The macro level employs an optimization model based on fundamental diagrams and shock wave theories to make optimal coordination decisions, including optimal minimum merging platoon size to trigger merging coordination and optimal coordination speed, based on macroscopic traffic state in mainline and ramp (i.e., traffic volume and penetration rates of CAVs). Furthermore, the micro level determines the real platoon size in each merging cycle as per random arrival patterns and designs the coordinated trajectories of the mainline facilitating vehicle and ramp platoon. A receding horizon scheme is implemented to accommodate human drivers’ stochastics as well. The developed bi-level strategy is tested in terms of improving efficiency and safety in a simulation-based case study under various traffic volumes and CAV penetration rates. The results show the proposed coordination addresses the uncertainties in mixed traffic as expected and substantially improves ramp merging operation in terms of merging efficiency and traffic robustness, and reducing collision risk and emissions, especially under high traffic volume conditions.
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| 6. |
- Zhu, Jie, 1990
(författare)
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Coordination and Analysis of Connected and Autonomous Vehicles in Freeway On-Ramp Merging Areas
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Freeway on-ramps are typical bottlenecks in the freeway network, where the merging maneuvers of ramp vehicles impose frequent disturbances on the traffic flow and cause negative impacts on traffic safety and efficiency. The emerging Connected and Autonomous Vehicles (CAVs) hold the potential for regulating the behaviors of each individual vehicle and are expected to substantially improve the traffic operation at freeway on-ramps. The aim of this research is to explore the possibilities of optimally facilitating freeway on-ramp merging operation through the coordination of CAVs, and to discuss the impacts of CAVs on the traffic performance at on-ramp merging. In view of the existing research efforts and gaps in the field of CAV on-ramp merging operation, a novel CAV merging coordination strategy is proposed by creating large gaps on the main road and directing the ramp vehicles into the created gaps in the form of platoon. The combination of gap creation and platoon merging jointly facilitates the mainline and ramp traffic and targets at the optimal performance at the traffic flow level. The coordination consists of three components: (1) mainline vehicles proactively decelerate to create large merging gaps; (2) ramp vehicles form platoons before entering the main road; (3) the gaps created on the main road and the platoons formed on the ramp are coordinated with each other in terms of size, speed, and arrival time. The coordination is analytically formulated as an optimization problem, incorporating the macroscopic and microscopic traffic flow models. The model uses traffic state parameters as inputs and determines the optimal coordination plan adaptive to real-time traffic conditions. The impacts of CAV coordination strategies on traffic efficiency are investigated through illustrative case studies conducted on microscopic traffic simulation platforms. The results show substantial improvements in merging efficiency, throughput, and traffic flow stability. In addition, the safety benefits of CAVs in the absence of specially designed cooperation strategies are investigated to reveal the CAV’s ability to eliminate critical human factors in the ramp merging process.
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| 7. |
- Zhu, Jie, 1990, et al.
(författare)
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Flow-level coordination of connected and autonomous vehicles in multilane freeway ramp merging areas
- 2022
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Ingår i: Multimodal Transportation. - : Elsevier BV. - 2772-5863. ; 1:1
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Tidskriftsartikel (refereegranskat)abstract
- On-ramp merging areas are deemed to be typical bottlenecks for freeway networks due to the intensive disturbances induced by the frequent merging, weaving, and lane-changing behaviors. The Connected and Autonomous Vehicles (CAVs), benefited from their capabilities of real-time communication and precise motion control, hold an opportunity to promote ramp merging opera- tion through enhanced cooperation. The existing CAV cooperation strategies are mainly designed for single-lane freeways, although multilane configurations are more prevailing in the real-world. In this paper, we present a flow-level CAV coordination strategy to facilitate merging operation in multilane freeways. The coordination integrates lane-change rules between mainstream lanes, proactive creation of large merging gaps, and platooning of ramp vehicles for enhanced benefits in traffic flow stability and efficiency. The strategy is formulated under an optimization framework, where the optimal control plan is determined based on real-time traffic conditions. The impacts of tunable model parameters on the produced control plan are discussed in detail. The efficiency of the proposed multilane strategy is demonstrated in a micro-simulation environment. The results show that the coordination can substantially improve the overall ramp merging efficiency and prevent recurrent traffic congestions, especially under high traffic volume conditions.
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| 8. |
- Zhu, Jie, 1990, et al.
(författare)
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Improving Freeway Merging Efficiency via Flow-Level Coordination of Connected and Autonomous Vehicles
- 2024
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- Freeway on-ramps are typical bottlenecks in the freeway network due to the frequent disturbances caused by their associated merging, weaving, and lane-changing behaviors. With real-time communication and precise motion control, Connected and Autonomous Vehicles (CAVs) provide an opportunity to substantially enhance the traffic operational performance of on-ramp bottlenecks. In this paper, we propose an upper-level control strategy to coordinate the two traffic streams at on-ramp merging through proactive gap creation and platoon formation. The coordination consists of three components: 1) mainline vehicles proactively decelerate to create large merging gaps; 2) ramp vehicles form platoons before entering the main road; 3) the gaps created on the main road and the platoons formed on the ramp are coordinated with each other in terms of size, speed, and arrival time. The coordination is formulated as a constrained optimization problem, incorporating both macroscopic and microscopic traffic flow models. The model uses traffic state parameters as inputs and determines the optimal coordination plan adaptive to real-time traffic conditions. The benefits of the proposed coordination are demonstrated through an illustrative case study. Results show that the coordination is compatible with real-world implementation and can substantially improve the overall efficiency of on-ramp merging, especially under high traffic volume conditions, where recurrent traffic congestion is prevented, and merging throughput increased.
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| 9. |
- Zhu, Jie, 1990, et al.
(författare)
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Merging control strategies of connected and autonomous vehicles at freeway on-ramps: a comprehensive review
- 2022
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Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 5:2, s. 99-111
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Forskningsöversikt (refereegranskat)abstract
- Purpose – On-ramp merging areas are typical bottlenecks in the freeway network since merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and lead to various negative impacts on traffic efficiency and safety. The connected and autonomous vehicles (CAVs), with their capabilities of real-time communication and precise motion control, hold a great potential to facilitate ramp merging operation through enhanced coordination strategies. This paper aims to present a comprehensive review of the existing ramp merging strategies leveraging CAVs, focusing on the latest trends and developments in the research field. Design/methodology/approach – The review comprehensively covers 44 papers recently published in leading transportation journals. Based on the application context, control strategies are categorized into three categories: merging into sing-lane freeways with total CAVs, merging into singlane freeways with mixed traffic flows and merging into multilane freeways. Findings – Relevant literature is reviewed regarding the required technologies, control decision level, applied methods and impacts on traffic performance. More importantly, the authors identify the existing research gaps and provide insightful discussions on the potential and promising directions for future research based on the review, which facilitates further advancement in this research topic. Originality/value – Many strategies based on the communication and automation capabilities of CAVs have been developed over the past decades, devoted to facilitating the merging/lane-changing maneuvers at freeway on-ramps. Despite the significant progress made, an up-to-date review covering these latest developments is missing to the authors’ best knowledge. This paper conducts a thorough review of the cooperation/ coordination strategies that facilitate freeway on-ramp merging using CAVs, focusing on the latest developments in this field. Based on the review, the authors identify the existing research gaps in CAV ramp merging and discuss the potential and promising future research directions to address the gaps.
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| 10. |
- Zhu, Jie, 1990, et al.
(författare)
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Safety analysis of freeway on-ramp merging with the presence of autonomous vehicles
- 2021
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 152
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Tidskriftsartikel (refereegranskat)abstract
- Freeway on-ramp merging areas are high-risk areas for motor vehicle crashes and conflicts due to the variety of driving styles, the difference in mainline and ramp traffic states, and factors related to roadway design and traffic control. The emerging Autonomous Vehicle (AV) technologies are expected to bring substantial improvements in ramp merging operations in general, including the possibility to reduce traffic conflicts and crashes by partially or fully eliminating the critical factors related to the human drivers. In order to investigate the potential safety impacts of AVs at on-ramp merging, this study first proposes a novel conflict index in theory as a specific indicator for ramp merging safety. Then, a merging conflict model is introduced to estimate the index value in various cases by considering the interactions between the mainline and ramp vehicles. In order to account for real-world uncertainties and variations in various crash-contributing factors, the proposed approach incorporates Monte-Carlo method and probabilistic distributions calibrated on the empirical freeway data. The developed approach is later applied in a case study with incremental AV market penetration rates to investigate AV safety impacts at on-ramp merging. The results show clear benefits of AVs in reducing the frequency and severity of the critical merging events. In addition, a sensitivity analysis on essential model parameters shows that the merging safety of AVs is closely related to their gap acceptance policy and the proper functioning of the driving systems, providing further insights into the future development of AVs.
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