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1.	Cao, Danni, et al. (författare) A Platoon Regulation Algorithm to Improve the Traffic Performance of Highway Work Zones 2021 Ingår i: Computer-Aided Civil and Infrastructure Engineering. - : Wiley. - 1093-9687 .- 1467-8667. ; 36:7, s. 941-956 Tidskriftsartikel (refereegranskat)abstract This paper presents a cooperative traffic control strategy to increase the capacity of non-recurrent bottlenecks such as work zones by making full use of the spatial resources upstream of work zones. The upstream area is divided into two zones: the regulation area and the merging area. The basic logic is that a large gap is more efficient in accommodating merging vehicles than several small and scattered gaps with the same total length. In the regulation area, a non-linear programming model is developed to balance both traffic capacity improvements and safety risks. A two-step solving algorithm is proposed for finding optimal solutions. In the merging area, the sorting algorithm is used to design lane changing trajectories based on the regulated platoons. A case study is conducted, and the results indicate that the proposed model is able to significantly improve work zone capacity with minor disturbances to the traffic.
2.	Wang, Liang, et al. (författare) Longitudinal control for person-following robots 2022 Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 5:2, s. 88-98 Tidskriftsartikel (refereegranskat)abstract Purpose: This paper aims to address the longitudinal control problem for person-following robots (PFRs) for the implementation of this technology. Design/methodology/approach: Nine representative car-following models are analyzed from PFRs application and the linear model and optimal velocity model/full velocity difference model are qualified and selected in the PFR control. Findings: A lab PFR with the bar-laser-perception device is developed and tested in the field, and the results indicate that the proposed models perform well in normal person-following scenarios. Originality/value: This study fills a gap in the research on PRFs longitudinal control and provides a useful and practical reference on PFRs longitudinal control for the related research.
3.	Wu, Guohong, et al. (författare) Managing merging from a dedicated CAV lane into a conventional lane considering the stochasticity of connected human-driven vehicles 2024 Ingår i: Physica A: Statistical Mechanics and its Applications. - 0378-4371. ; 652 Tidskriftsartikel (refereegranskat)abstract Connected and automated vehicle (CAV) provides a new promising solution for transportation system. Despite the promising future of CAV, fully deployment of CAV on current road systems is still challenging and the coexistence of CAV and human-driven vehicle (HDV) is inevitable. Furthermore, most studies for trajectory planning under mixed traffic ignore the stochasticity of human-driven vehicle (HDV), which is unrealistic and causes infeasible planned trajectory. In this study, we investigate merging control from a dedicated CAV lane into a conventional lane. The stochastic mixed traffic cooperative merging problem is formulated as a mixed integer quadratic constraint programming, which optimizes vehicle longitudinal trajectories and lane-changing maneuvers in a centralized way. Rolling horizon framework coupled with car-following and lane-changing execution algorithms is used to address the stochasticity of connected human-driven vehicle (CHV). Simulation results validate our proposed control strategy outperforms the rule-based control strategy from the perspective of traffic efficiency, lane-changing efficiency, fuel economy and driving comfort. The robustness of rolling horizon framework and sensitivity analysis are also conducted. Finally, the vehicle trajectory comparison intuitively shows the difference between 2 control strategies.
4.	Cai, Xuelian, et al. (författare) Safety-Oriented Personalized Service Strategy in Air-Ground Integrated Mobility 2024 Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 73:2, s. 2564-2577 Tidskriftsartikel (refereegranskat)abstract Air-ground Integrated Mobility (AIM) can effectively alleviate the current urban traffic pressure by expanding transportation resources in the near-ground field. However, the following problems in AIM need to be addressed urgently: 1) The high mobility of Personal Aerial Vehicles (PAVs) in low-altitude airspace leads to a sharp increase in risk factors; 2) Due to the limited communication distance, antenna direction angle, and frequent handover caused by high-speed movement, the communication quality in the air is unreliable; 3) AIM incorporates vehicles on the ground and PAVs in the air leading to the high variability of user requirements. Confronted with the personalized resource requirements of high-speed mobile PAVs in airspace with unreliable communication quality, traditional resource allocation strategies struggle to guarantee service quality. Therefore, we propose a safety-oriented personalized resource allocation strategy in AIM, which jointly considers the user requirements and resource distribution. Specifically, we first build a three-dimensional (3D) safety distance model by analyzing the motion process of PAVs with the help of a kinematics model. Then, according to the location, speed, and environmental information of the PAVs, the communication and computing resources required by each PAV under the premise of maintaining the optimal safety distance are obtained through the transmission model. Furthermore, the 3D safety distance and resources are jointly optimized, and an on-demand resource allocation algorithm enabled by Deep Reinforcement Learning (DRL) is constructed to provide the resource allocation strategy based on the personalized requirements of the users.
5.	Gao, Jianqiang, et al. (författare) Investigating the Influence of ADAS on Drivers’ Evasive Behaviors During Car-Following on Highways 2022 Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Nature Singapore. - 2190-3026 .- 2190-3018. ; 304 SIST, s. 22-31 Konferensbidrag (refereegranskat)abstract Various advanced driving assistance systems (ADAS) are designed to help drivers make reasonable evasive decisions in emergency conditions. However, different drivers have different perceptions of driving risks, resulting in differences in the choice of evasive behaviors (e.g., car-following, overtaking, etc.). To explorer the impact of ADAS on vehicle interaction behaviors under dangerous conditions, this study objectively assessed how ADAS affected drivers’ choice of evasive behaviors in near-crash events (NCEs). An on-road experiment was conducted on public highways in real traffic. The dangerous driving data of NCEs in different working states of ADAS (i.e., activated or not) were collected and combined to classify NCEs’ risk levels: lower, medium, and higher based on the K-means clustering results. Drivers’ evasive behaviors during ADAS engagement (i.e., during the use of the forward collision warning system) were then found closely associated with NCEs’ risk levels. Differences of probabilities for evasive behaviors were further compared within and across the three risk groups. Results showed that ADAS engagement has a positive impact on reducing the occurrence of NCEs and reduces the probability that drivers in medium and high-risk groups choose overtaking behavior. ADAS engagement can help drivers maintain a greater time headway (THW) when taking evasive action. Findings in this study could optimize ADAS intervention strategies and further enhance the ability of safe driving assistance.
6.	Jiang, Jiwan, et al. (författare) A Personalized Human Drivers' Risk Sensitive Characteristics Depicting Stochastic Optimal Control Algorithm for Adaptive Cruise Control 2020 Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8, s. 145056-145066 Tidskriftsartikel (refereegranskat)abstract This paper presents a personalized stochastic optimal adaptive cruise control (ACC) algorithm for automated vehicles (AVs) incorporating human drivers' risk-sensitivity under system and measurement uncertainties. The proposed controller is designed as a linear exponential-of-quadratic Gaussian (LEQG) problem, which utilizes the stochastic optimal control mechanism to feedback the deviation from the design car-following target. With the risk-sensitive parameter embedded in LEQG, the proposed method has the capability to characterize risk preference heterogeneity of each AV against uncertainties according to each human drivers' preference. Further, the established control theory can achieve both expensive control mode and non-expensive control mode via changing the weighting matrix of the cost function in LEQG to reveal different treatments on input. Simulation tests validate the proposed approach can characterize different driving behaviors and its effectiveness in terms of reducing the deviation from equilibrium state. The ability to produce different trajectories and generate smooth control of the proposed algorithm is also verified.
7.	Kong, Xiangyu, et al. (författare) An Online Processing Method for the Cooperative Control of Connected and Automated Vehicle Platoons 2021 Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Singapore. - 2190-3026 .- 2190-3018. ; 231, s. 133-139 Konferensbidrag (refereegranskat)abstract The recent development of connected and autonomous vehicles (CAVs) makes it increasingly realistic to develop the next generation of transportation systems with the potential to improve operational performance and flexibility. The cooperative control of CAV platoons remains one of the most crucial yet challenging problems before the CAVs can be widely implemented in practice. The present study focuses on an application of CAVs at signalized intersections to realize a well-organized CAV permutation as well as improving the performance of the intersection. An online processing A* (OPA) algorithm is developed to improve the optimality and computation performance. A comparative analysis between the proposed OPA algorithm and an existing A* method is made. In summary, the OPA* could result in stable and scalable results which makes it possible for widely industrial usage.
8.	Li, Kuan, et al. (författare) Dynamic Programming-Based Optimal Charging Scheduling for Electric Vehicles 2022 Ingår i: 2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022. ; , s. 545-550 Konferensbidrag (refereegranskat)abstract The charging scheduling of electric vehicles not only affects the operation of the grid system, but also affects the charging cost of vehicle users. This paper studies the charging scheduling problem of electric vehicles from the user's perspective by considering the grid's as well as the user's needs. On the basis of real-time electricity prices, an electric vehicle charging scheduling system aiming at the lowest charging cost is designed and an optimal charging scheduling method based on dynamic programming is established. In order to reduce the unnecessary computational expenses, this paper optimizes the dynamic programming algorithm, and defines the state transition limit of the dynamic programming search space according to the actual constraints, which reduces the computational complexity. The simulation results show that, on the premise of satisfying the power constraints and user charging demands, the electric vehicles charging scheduling system can effectively reduce the charging cost and time. In addition, the charging process has little impact on the power system from the perspective of grid fluctuation.
9.	Li, Meng, et al. (författare) A cooperative energy efficient truck platoon lane-changing model preventing platoon decoupling in a mixed traffic environment 2024 Ingår i: Journal of Intelligent Transportation Systems. - : Informa UK Limited. - 1547-2442 .- 1547-2450. ; 28:2, s. 174-188 Tidskriftsartikel (refereegranskat)abstract Truck platooning has gained increasing attention due to the benefits in energy and operation efficiency in freight transportation. One significant challenge for deploying truck platoons is the safe and efficient interaction with surrounding traffic, especially at freeway discontinuities where mandatory lane changes usually lead to the decoupling of truck platoons. This study proposes a cooperative truck platoon lane-changing model (CTPLC) to prevent the decoupling of truck platoons in a mixed traffic environment. Specifically, a two-step control strategy is presented, where vehicles in the target lane firstly cooperatively adjust speeds to create an appropriate gap for a truck platoon, and then trucks within the truck platoon conduct lane change sequentially. The cooperative speed profiles are generated by solving an optimization problem considering the lane-changing influence and energy consumption. Based on that, a two-dimensional nonlinear model predictive control (MPC) algorithm is employed to generate vehicular acceleration and steering angle for each truck. A series of numerical simulation experiments were conducted to validate the proposed strategy. As shown by the results, our proposed method truck platoon could conduct a lane change in a traffic-efficient and safe manner, and meanwhile, our method was more energy-efficient than a benchmark strategy.
10.	Meng, Zhiwei, 1996, et al. (författare) GIVA: Interaction-aware trajectory prediction based on GRU-Improved VGG-Attention Mechanism model for autonomous vehicles 2023 Ingår i: Proceedings of the Institution of Mechanical Engineers. Part D, Transport engineering. - 2041-2991 .- 0954-4070. ; In Press Tidskriftsartikel (refereegranskat)abstract Predicting future trajectories is crucial for autonomous vehicles, as accurate predictions enhance safety and inform subsequent decision-making and planning modules. This is however a challenging task due to the complex interactions between surrounding vehicles. Existing methods struggled to extract deep representations and often overlook spatial dependence. To address this problem, this paper introduces GIVA, an interaction-aware trajectory prediction method based on the Gated Recurrent Unit (GRU)-Improved Visual Geometry Group (VGG)-Attention Mechanism model. GIVA first encodes the historical trajectories of the target vehicle and its surrounding vehicles using a GRU Encoder. Next, an Interaction Module, which combines the Improved VGG Pooling Module and the Attention Mechanism Pooling Module, effectively captures spatial interaction features between vehicles. The Improved VGG Pooling Module extracts more detailed and effective interaction information, while the Attention Mechanism Pooling Module emphasizes the importance of surrounding vehicles for the target vehicle’s future trajectory. Lastly, the dynamic encoding feature of the target vehicle and the fused interaction feature are concatenated and input into a GRU Decoder to generate the future trajectory. Experiments on the public Next Generation Simulation (NGSIM) dataset showcase the effectiveness of GIVA compared to existing prediction approaches, demonstrating its potential for improving autonomous vehicle performance.
11.	Meng, Zhiwei, 1996, et al. (författare) Interaction-Aware Trajectory Prediction for Autonomous Vehicle Based on LSTM-MLP Model 2023 Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 356, s. 91-99 Konferensbidrag (refereegranskat)abstract Trajectory prediction is one of the core functions of the autonomous vehicle, it greatly affects the rationality and safety of the decision-making module and the planning module. This is challenging because the motion of the target vehicle is affected by the interactive behavior of its surrounding vehicles. In this paper, we propose the interaction-aware trajectory prediction model for autonomous vehicles based on LSTM-MLP model. The encoder module encoded the history trajectories to extract the dynamic feature of each vehicle in the scenarios by the LSTM model, and then the interaction module captures the interactive feature using the MLP-Max Pooling model. In the end, the decoder module decodes the fusion feature which consists of the dynamic feature of the target vehicle and the interactive feature to output the future trajectory based on the LSTM model. The experiments are carried out on the publicly available NGSIM dataset, and the results show that the proposed model outperforms prior works in terms of RMSE value.
12.	Olovsson, Tomas, 1959, et al. (författare) Future connected vehicles: Communications demands, privacy and cyber-security 2022 Ingår i: Communications in Transportation Research. - : Elsevier BV. - 2772-4247. ; 2 Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
13.	Ouyang, Pengying, et al. (författare) Safety effects of road pavement resurfacing: A case study of city-wide scale projects in China 2020 Ingår i: Journal of Transportation Safety and Security. - : Informa UK Limited. - 1943-9962 .- 1943-9970. ; In Press, s. 1-20 Tidskriftsartikel (refereegranskat)abstract This study explores the influence of resurfacing projects on traffic safety. A case study of city-wide road resurfacing projects conducted from July 2014 to February 2015 in China was adopted to carry out the analysis. The crash data of two years before and after the treatment were collected. Firstly, the safety performance function, generalized linear regression, and Gaussian Process centered on Poisson regression were applied to predict the expected number of crashes in the after period if the resurfacing was not applied. Then, the observational before-after study was applied to compare the safety performance of the before and after period of resurfacing projects. Finally, crash modification factors for various target accidents in different time durations were calculated to evaluate the influence of the resurfacing projects on traffic safety. The results show that the resurfacing projects along with some minor changes, such as widen shoulders and optimized lane markings have remarkably good effects on reducing both the crashes counts and the level of severity. The degree of good effects of the resurfacing projects on different types of crashes is ranked as follows: road crashes with slight consequences > total crashes > road crashes with severe consequences > intersection crashes.
14.	Ouyang, Pengying, et al. (författare) Traffic safety analysis of inter-tunnel weaving section with conflict prediction models 2022 Ingår i: Journal of Transportation Safety and Security. - : Informa UK Limited. - 1943-9962 .- 1943-9970. ; 14:4, s. 630-654 Tidskriftsartikel (refereegranskat)abstract With increasing traffic demand in urban areas of metropolises, many tunnels have been constructed to improve road capacity and traffic mobility. The distance between two consecutive tunnels is relatively short which usually forms a weaving section, leading to considerable traffic conflicts. The objective of this study is to evaluate the safety performance of such inter-tunnel sections. Conflict prediction models based on negative binomial regression were developed to identify influential factors. Field data were collected at ten selected sites in Nanjing, China, and used for calibrating and validating the proposed models. Two types of inter-tunnel weaving sections (type 1 and type 2) were found in the field with distinct lane markings and operation rules. The unique lane markings in type 1 weaving sections are designed to isolate weaving traffic flows and thus reduce conflicts, but in practice, contradictory to its design intention, lead to more traffic conflicts compared with type 2 weaving sections. In addition, the length of the diverging section, merging section, and whole weaving section are found to be significant influencing factors on the conflict occurrence. The findings in the present study are expected to help engineers better design inter-tunnel sections.
15.	Wang, Lichao, et al. (författare) Guidance Method of Connected Autonomous Vehicles Under Automatic Control Intersections 2023 Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 356, s. 35-43 Konferensbidrag (refereegranskat)abstract In this study, a guidance method for connected autonomous vehicles (CAVs) passing through automatic control intersections (ACI) is proposed. The approach favors a new mode of intersection control in an autonomous driving environment. Based on the modeling of automatic control intersections, the functional delineation of the approach lanes was eliminated, and a conflict resolution method for CAVs within the intersections was established considering the objectives of safety and efficiency, and pre-assignment of lanes for CAVs through ACI was realized. Based on the lane pre-assignment results to achieve space–time resource allocation among CAVs, the final passing strategy is determined and back to each CAV. The simulation results show that the method proposed in this study can ensure the safe and efficient passing of CAV through ACI.
16.	Wang, Yuxuan, et al. (författare) A deep learning approach to real-time CO concentration prediction at signalized intersection 2020 Ingår i: Atmospheric Pollution Research. - : Elsevier BV. - 1309-1042. ; 11:8, s. 1370-1378 Tidskriftsartikel (refereegranskat)abstract Vehicle exhaust emissions at signalized intersections are the essential source of traffic-related pollution to pedestrians. Therefore, it is critical to predicting traffic emissions, especially the hazardous CO gas, with practical and accurate methods. However, the CO emission and concentration at crosswalks can be influenced by the complex traffic conditions in a complicated way, making the prediction of CO concentration a challenging task for traditional statistical models. To this end, a hybrid machine learning framework is proposed in this study to investigate the concentration of CO emissions at pedestrian crosswalks. The proposed method firstly ranks key influencing factors with a random forest approach. Then a prediction model with Multi-Variate Long Short-Term Memory (LSTM) neural networks based on the selected factors is developed. Data is collected at the field intersection for model training and validation. The autoregressive integrated moving average (ARIMA), support vector machines (SVM), radial basis functions network (RBFN), nonlinear vector autoregressive (VAR) and gated recurrent unit ( GRU) neural network are selected as the benchmark models to verify the performance of the proposed model. The Root Mean Square Errors (RMSE), Mean Absolute Error (MAE) and R square are calculated to evaluate the performance of models comprehensively. The results indicated that the proposed model overwhelms the benchmark models in terms of prediction accuracy.
17.	Wang, Yuxuan, et al. (författare) Are shared electric scooters energy efficient? 2021 Ingår i: Communications in Transportation Research. - : Elsevier BV. - 2772-4247. ; 1 Tidskriftsartikel (refereegranskat)abstract Shared electric scooters (e-scooter) are booming across the world and widely regarded as a sustainable mobility service. An increasing number of studies have investigated the e-scooter trip patterns, safety risks, and environmental impacts, but few considered the energy efficiency of e-scooters. In this research, we collected the operational data of e-scooters from a major provider in Gothenburg to shed light on the energy efficiency performance of e-scooters in real cases. We first develop a multiple logarithmic regression model to examine the energy consumption of single trips and influencing factors. With the regression model, a Monte Carlo simulation framework is proposed to estimate the fleet energy consumption in various scenarios, taking into account both trip-related energy usage and energy loss in idle status. The results indicate that 40% of e-scooter battery energy was wasted in idle status in the current practice, mainly due to the relatively low usage rate (0.83) of e-scooters. If the average usage rate drops below 0.5, the wasted energy could reach up to 53%. In the end, we present a field example to showcase how to optimally integrate public transport with e-scooters from the perspective of energy efficiency. We hope the findings of this study could help understand and resolve the current and future challenges regarding the ever-growing e-scooter services.
18.	Wu, Jiaming, 1989, et al. (författare) A Modular, Adaptive, and Autonomous Transit System (MAATS): A In-motion Transfer Strategy and Performance Evaluation in Urban Grid Transit Networks 2021 Ingår i: Transportation Research Part A: General. - : Elsevier BV. - 0965-8564. ; 151, s. 81-98 Tidskriftsartikel (refereegranskat)abstract Dynamic traffic demand has been a longstanding challenge for the conventional transit system design and operation. The recent development of autonomous vehicles (AVs) makes it increasingly realistic to develop the next generation of transportation systems with the potential to improve operational performance and flexibility. In this study, we propose an innovative transit system with autonomous modular buses (AMBs) that is adaptive to dynamic traffic demands and not restricted to fixed routes and timetables. A unique transfer operation, termed as “in-motion transfer”, is introduced in this paper to transfer passengers between coupled modular buses in motion. A two-stage model is developed to facilitate in-motion transfer operations in optimally designing passenger transfer plans and AMB trajectories at intersections. In the proposed AMB system, all passengers can travel in the shortest path smoothly without having to actually alight and transfer between different bus lines. Numerical experiments demonstrate that the proposed transit system results in shorter travel time and a significantly reduced average number of transfers. While enjoying the above-mentioned benefits, the modular, adaptive, and autonomous transit system (MAATS) does not impose substantially higher energy consumption in comparison to the conventional bus system
19.	Wu, Jiaming, 1989, et al. (författare) Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making 2020 Ingår i: Transportation Research Part B: Methodological. - : Elsevier BV. - 0191-2615. ; 141, s. 223-239 Tidskriftsartikel (refereegranskat)abstract Emergency vehicles (EVs) play a crucial role in providing timely help for the general public in saving lives and avoiding property loss. However, very few efforts have been made for EV prioritization on normal road segments, such as the road section between intersections or highways between ramps. In this paper, we propose an EV lane pre-clearing strategy to prioritize EVs on such roads through cooperative driving with surrounding connected vehicles (CVs). The cooperative driving problem is formulated as a mixed-integer nonlinear programming (MINP) problem aiming at (i) guaranteeing the desired speed of EVs, and (ii) minimizing the disturbances on CVs. To tackle this NP-hard MINP problem, we formulate the model in a bi-level optimization manner to address these two objectives, respectively. In the lower-level problem, CVs in front of the emergency vehicle will be divided into several blocks. For each block, we developed an EV sorting algorithm to design optimal merging trajectories for CVs. With resultant sorting trajectories, a constrained optimization problem is solved in the upper-level to determine the initiation time/distance to conduct the sorting trajectories. Case studies show that with the proposed algorithm, emergency vehicles are able to drive at a desired speed while minimizing disturbances on normal traffic flows. We further reveal a linear relationship between the optimal solution and road density, which could help to improve EV routing decision makings when high-resolution data is not available.
20.	Wu, Jiaming, 1989, et al. (författare) Intersection control with connected and automated vehicles: a review 2022 Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 5:3, s. 260-269 Forskningsöversikt (refereegranskat)abstract Purpose: This paper aims to review the studies on intersection control with connected and automated vehicles (CAVs). Design/methodology/approach: The most seminal and recent research in this area is reviewed. This study specifically focuses on two categories: CAV trajectory planning and joint intersection and CAV control. Findings: It is found that there is a lack of widely recognized benchmarks in this area, which hinders the validation and demonstration of new studies. Originality/value: In this review, the authors focus on the methodological approaches taken to empower intersection control with CAVs. The authors hope the present review could shed light on the state-of-the-art methods, research gaps and future research directions.
21.	Wu, Jiaming, 1989, et al. (författare) Stationary Condition Based Performance Analysis of the Contraflow Left-Turn Lane Design Considering the Influence of the Upstream Intersection 2021 Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 122 Tidskriftsartikel (refereegranskat)abstract The present study conducted an operational performance analysis of the contraflow left-turn lane (CLL) design considering the influence of the upstream signalized intersection. The arrival distribution was generated using a platoon dispersion model. A stationary condition was defined, in which the performance of the CLL design remained stable in any stationary cycle. It has proved that the CLL system always converges to the stationary condition after a few cycles if the arrival distribution is fixed. In stationary cycles, the CLL design generates either recurrent and constant residual queues or no queues, depending on the arrival distributions of left-turning vehicles. Based on the stationary condition, analytical models were developed to estimate the operational performance for left-turns at signalized intersections with the CLL design. The results show that both the arrival pattern and the length of the contraflow lane can significantly influence the operational performance of the CLL design. The residual queues in the stationary condition could increase control delay significantly, leading to an overlong delay of the left-turning vehicles if the contraflow lane was not carefully designed. To this end, an empirical optimization method was proposed to minimize the control delay by optimizing the length of contraflow lanes and the offset between adjacent intersections. The research results can be directly employed by traffic engineers to optimize the CLL design and to estimate the operational performance of the signalized intersections with the CLL design.
22.	Wu, Jiaming, 1989, et al. (författare) The cooperative sorting strategy for connected and automated vehicle platoons 2021 Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 123 Tidskriftsartikel (refereegranskat)abstract This paper presents a "cooperative vehicle sorting" strategy that seeks to optimally sort connected and automated vehicles (CAVs) in a multi-lane platoon to reach an ideally organized platoon. In the proposed method, a CAV platoon is firstly discretized into a grid system, where a CAV moves from one cell to another in discrete time-space domain. Then, the cooperative sorting problem is modeled as a path-finding problem in the graphic domain. The problem is solved by the deterministic A* algorithm with a stepwise strategy, where only one vehicle can move within a movement step. The resultant shortest path is further optimized with an integer linear programming algorithm to minimize the sorting time by allowing multiple movements within a step. To improve the algorithm running time and address multiple shortest paths, a distributed stochastic A* algorithm (DSA) is developed by introducing random disturbances to the edge costs to break uniform paths (with equal path cost). Numerical experiments are conducted to demonstrate the effectiveness of the proposed DSA method. The results report shorter sorting time and significantly improved algorithm running time due to the use of DSA*. In addition, we find that the optimization performance can be further improved by increasing the number of processes in the distributed computing system.
23.	Wu, Jiaming, 1989, et al. (författare) Why is your paper rejected? Lessons learned from over 5000 rejected transportation papers 2024 Ingår i: Communications in Transportation Research. - 2772-4247. ; 4 Tidskriftsartikel (refereegranskat)abstract Academic papers are the cornerstone of knowledge dissemination and crucial for researchers’ career development. This is particularly true for rapidly evolving research domains such as transportation, as evidenced by the surge of journals and papers in the past decade. While abundant literature offers guidance on successful publication strategies, insights into the reasons for rejection are rare. This study fills in this gap by examining why papers are rejected in the area of transportation. We present concrete evidence based on data from over 5,000 rejected transport papers. Quantitative analyses are conducted to reveal the impacts of similarity rate, duplication submission rate, and topic on desk rejections. Additionally, we shed light on the distinct focus reviewers have when serving different journals. We hope the results could equip transport researchers with a deeper comprehension of publication criteria and a better awareness of common but avoidable mistakes.
24.	Xie, Jian, et al. (författare) On the Impact Analysis of Emergency Vehicles Preemption on Signalized Intersections with Connected Vehicles 2022 Ingår i: Smart Innovation, Systems and Technologies. - Singapore : Springer Nature Singapore. - 2190-3026 .- 2190-3018. ; 304 SIST, s. 151-160 Konferensbidrag (refereegranskat)abstract In recent years, vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication are the leading technologies in intelligent transportation systems. With V2I and V2V, new strategies are enabled to better facilitate emergency rescue and traffic emergency management. Since signalized intersection is the major source of delay and congestion, how to prioritize emergency vehicles (EVs) at intersections becomes an indispensable research topic and has drawn extensive studies. Albeit that emergency vehicles should be granted absolute priority, the influence of EVs on the intersection was rarely studied, especially when aggressive preemption strategies are adopted. To this end, this paper is devoted to evaluating the impacts of EVs on the control of signalized intersections, as an effort to better emergency management. Mixed-integer linear programming models are developed to optimize the intersection control before and after the pass of EVs, respectively. Case studies indicate that, by assuming the EV will take exclusively one lane at the intersection, the average delay could increase by 11.28% along with a capacity decrease of 6.63%.
25.	Xu, Liang, et al. (författare) Traffic signal coordination control for arterials with dedicated CAV lanes 2022 Ingår i: Journal of Intelligent and Connected Vehicles. - 2399-9802. ; 5:2, s. 72-87 Tidskriftsartikel (refereegranskat)abstract Purpose: This study aims to make full use of the advantages of connected and autonomous vehicles (CAVs) and dedicated CAV lanes to ensure all CAVs can pass intersections without stopping. Design/methodology/approach: The authors developed a signal coordination model for arteries with dedicated CAV lanes by using mixed integer linear programming. CAV non-stop constraints are proposed to adapt to the characteristics of CAVs. As it is a continuous problem, various situations that CAVs arrive at intersections are analyzed. The rules are discovered to simplify the problem by discretization method. Findings: A case study is conducted via SUMO traffic simulation program. The results show that the efficiency of CAVs can be improved significantly both in high-volume scenario and medium-volume scenario with the plan optimized by the model proposed in this paper. At the same time, the progression efficiency of regular vehicles is not affected significantly. It is indicated that full-scale benefits of dedicated CAV lanes can only be achieved with signal coordination plans considering CAV characteristics. Originality/value: To the best of the authors’ knowledge, this is the first research that develops a signal coordination model for arteries with dedicated CAV lanes.
26.	Yue, Wenwei, et al. (författare) A Channel Knowledge Map-Aided Personalized Resource Allocation Strategy in Air-Ground Integrated Mobility 2024 Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; In Press Tidskriftsartikel (refereegranskat)abstract Air-ground Integrated Mobility (AIM), as a disruptive mode of travel, has the tremendous potential to alleviate ground traffic congestion issues substantially. However, the primary challenge in achieving this leapfrog development lies in ensuring driving safety. Receiving collision warnings in time within a limited distance can significantly reduce collision risks, which is crucial for ensuring driving safety in AIM. However, due to challenges in aerial network coverage, ensuring the communication quality of aerial Personal Aerial Vehicles (PAVs) remains difficult, thereby affecting the effective transmission of messages. Furthermore, the integration of ground Connected and Automated Vehicles (CAVs) with aerial PAVs in AIM results in significant differences in user resource requirements. Given the complexity of the AIM environment and the high mobility of PAVs, it is challenging to rapidly and accurately capture user communication quality. Therefore, addressing the differential resource requirements of users in this environment is particularly challenging. To this end, we propose a personalized resource allocation strategy assisted by a Channel Knowledge Map (CKM) in AIM. This strategy aims to meet the personalized resource requirements of users while maintaining the maximum Perception Response Time (PRT), thereby ensuring driving safety. Specifically, the CKM in AIM is constructed to obtain channel states through environment-aware communication. Next, a 3D collision warning system is designed to analyze rigorously the maximum PRT of vehicles under different motion states in avoiding collisions. On this basis, with the help of CKM, the channel knowledge of the user’s location is obtained to quantify the communication and computing resources required by each user to maintain the maximum PRT. Finally, we establish the PRT-driven resource optimization problem and employ Deep Reinforcement Learning (DRL) to seek the optimal resource allocation strategy. Simulation results indicate that the proposed method effectively enhances safety and resource utilization in AIM under resource constraints and uneven distribution.
27.	Yue, Wenwei, et al. (författare) Cooperative Incident Management in Mixed Traffic of CAVs and Human-Driven Vehicles 2023 Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 24:11, s. 12462-12476 Tidskriftsartikel (refereegranskat)abstract Traffic incident management in metropolitan areas is crucial for the recovery of road systems from accidents as well as the mobility and safety of the community. With the continuous improvement in computation and communication technologies, connected and automated vehicles (CAVs) exhibit the potential to relieve incident-induced traffic degradation. To understand the benefits of CAVs on traffic incidents, this paper models the impacts of CAVs with joint consideration of microscopic CAV driving behaviors and macroscopic traffic assignment in mixed traffic environment comprising both CAVs and human-driven vehicles (HDVs). Firstly, a generic traffic assignment model with mixed traffic is proposed to analyze the mixed traffic process from the macroscopic perspective. Then, we incorporate the traffic assignment model with bottleneck delays and incident effects from the microscopic perspective, to model the dynamic road system with incident effects in mixed traffic environment. Furthermore, cooperating with the mixed traffic assignment model, dynamic signal control policies are presented according to different incident severities, and the conditions for equilibrium existence, uniqueness and stability of the road system are derived. The analytical results indicate that road system stability with incident effects is closely related to the incident severity, signal control policy as well as penetration rate and spatial distribution of CAVs. Finally, simulation results are conducted to demonstrate the effectiveness of our proposed incident management policy in improving the recovery rate and system stability of road networks.
28.	Zheng, Zhejian, et al. (författare) Capacity of Vehicular Networks in Mixed Traffic With CAVs and Human-Driven Vehicles 2024 Ingår i: IEEE Internet of Things Journal. - 2327-4662. ; 11:10, s. 17852-17865 Tidskriftsartikel (refereegranskat)abstract Connected and Automated Vehicles (CAVs) are characterized by diverse communication attributes, embodying the trajectory of future automotive progress. Meanwhile, the transportation system will be in a mixed stage of CAVs and Human-Driven Vehicles (HDVs) for a long time. The study of communication capacity and strategies for mixed traffic systems is of great significance for the popularization of CAVs and the deployment of communication infrastructures. However, current research mainly focuses on the communication capacity analysis in the scenario with full penetration of CAVs, while the influence caused by HDVs on Vehicle-to-Vehicle (V2V) communications and the capacity analysis of connected vehicles in mixed traffic systems need further understanding. To address this issue, this paper considers the shadow fading caused by HDVs on wireless communication links and analyzes the communication capacity in mixed traffic systems. Specifically, we first synthesize the V2V and Vehicle-to-Infrastructure (V2I) communication modes to propose an analytical framework for vehicular network communication capacity in mixed traffic. Then, a predictive communication strategy is also provided that caches the required content at infrastructure in advance according to predicted vehicle trajectories to improve the capacity of vehicular networks in mixed traffic. Furthermore, the derived capacity analysis theorems reveal the communication capacity of mixed traffic is closely related to the CAV penetration rate, the vehicle arrival rate, and the infrastructure deployment interval. Simulation results prove the effectiveness of the proposed framework, and the proposed predictive communication strategy can increase the mixed traffic communication capacity compared to existing communication strategies. The theoretical results herein can guide the implementation of vehicular network applications and the design of communication strategies in mixed traffic systems.
29.	Zhou, Fangting, 1993, et al. (författare) Collaborative electric vehicle routing with meet points 2024 Ingår i: Communications in Transportation Research. - 2772-4247. Tidskriftsartikel (refereegranskat)abstract In this paper, we develop a profit-sharing-based optimal routing mechanism to incentivize horizontal collaboration among urban goods distributors. The core of this mechanism is based on exchanging goods at meet points, which is optimally planned en route. We propose a Collaborative Electric Vehicle Routing Problem with Meet Points (CoEVRPMP) considering constraints such as time windows, opportunity charging, and meet-point synchronization. The proposed CoEVRPMP is formulated as a mixed-integer nonlinear programming model. We present an exact method via branching and a matheuristic that combines adaptive large neighborhood search with linear programming. The viability and scalability of the collaborative method are demonstrated through numerical case studies, including a real-world case and a large-scale experiment with up to 500 customers. The findings underscore the significance of horizontal collaboration among delivery companies in attaining both higher individual profits and lower total costs. Moreover, collaboration helps to reduce the environmental footprint by decreasing travel distance.

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