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Connected automated vehicles (CAVs) rely heavily on intelligent algorithms and remote sensors. If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication, it can cause significant damage to CAVs or passengers. The primary objective of this study is to model cyber-attacked traffic flow and evaluate the impacts of cyber-attack on the traffic system filled with CAVs in a connected environment. Based on the analysis on environmental perception system and possible cyber-attacks on sensors, a novel lane-changing model for CAVs is proposed and multiple traffic scenarios for cyber-attacks are designed. The impact of the proportion of cyber-attacked vehicles and the severity of the cyber-attack on the lane-changing process is then quantitatively analyzed. The evaluation indexes include spatio-temporal evolution of average speed, spatial distribution of selected lane-changing gaps, lane-changing rate distribution, lane-changing preparation search time, efficiency and safety. Finally, the numerical simulation results show that the freeway traffic near an off-ramp is more sensitive to the proportion of cyber-attacked vehicles than to the severity of the cyber-attack. Also, when the traffic system is under cyber-attack, more unsafe back gaps are chosen for lane-changing, especially in the center lane. Therefore, more lane-changing maneuvers are concentrated on approaching the off-ramp, causing severe congestions and potential rear-end collisions. In addition, as the number of cyber-attacked vehicles and the severity of cyber-attacks increase, the road capacity and safety level will rapidly decrease. The results of this study can provide a theoretical basis for accident avoidance and efficiency improvement for the design of CAVs and management of automated highway systems.

Behaviour modelling has been widely explored using both statistical and machine learning techniques, primarily relying on analyzing correlations to understand passenger responses under different conditions and scenarios. However, correlation alone does not imply causation. This paper introduces a data-driven causal behaviour modelling approach, comprising two phases: causal discovery and causal inference. Causal discovery phase uses Peter-Clark (PC) algorithm to learn a directed acyclic graph that captures the causal relationships among variables. Causal inference phase estimates the corresponding model parameters and infers (conditional) causal effects of interventions designed to influence user behaviour. The method is validated by comparing the results with those from conventional modelling approaches (logistic regression and expert knowledge) using smart card data from a real-world use case on a pre-peak fare discount incentive program in the Hong Kong Mass Transit Railway system. The results highlight that the purely data-driven causal discovery method can produce reasonable causal graph. The method can also quantify the behavioural impacts of the incentive, identify key influencing factors, and estimate the corresponding causal effects. The overall causal effect of the incentive is approximately 0.7 %, with about 3 % of the population changing behaviour from previous statistical analysis. Interestingly, passengers with the highest flexibility exhibit a negative response, while those with medium-to-high flexibility demonstrate 3 times of the general level of responsiveness. The approach initiates the data-driven, causal modelling of human behaviour dynamics to support policy developments and managerial interventions.

Abstract Reinforcement learning (RL)‐based models have been widely studied for traffic signal control with objectives, such as minimizing vehicle delay and queue length, maximizing vehicle throughput, and improving road safety, through tailored reward designs. Despite the advancements in RL‐based signal control models for car traffic, limited research focused on multimodal traffic (e.g. car, bus, pedestrian). The simplified environment of unimodal traffic restrains these models from applications in real‐world cases. In this paper, the authors propose an RL‐based human‐centric multimodal deep (HMD) traffic signal control method to coordinate multimodal traffic at an intersection, with the objective of minimizing the waiting time per capita for multiple traffic modes by taking consideration of the mode capacity to ensure social equity. The method is validated in the simulation of urban mobility (SUMO) simulation environment using real traffic data. The results show the superior performance of HMD over vehicle‐centric (VC) RL‐based methods and traditional signal control schemes. HMD reduces the waiting time per capita by up to 19.2% and 6.3% compared with the fixed timing and VC RL‐based methods. In addition, the experiment results show that the HMD method assigns a higher priority to public transport over low‐occupancy travel modes in passing through intersections compared with unimodal traffic signal control strategies.

To select reasonable excavating and crushing process parameters and nozzle structure parameters is one of the key factors to realize commercial excavation of marine natural gas hydrate (hereinafter “hydrate” for short) in solid fluidization exploitation. For analyzing the factors influencing jet crushing efficiency of hydrate in actual engineering, nozzle diameter, pump pressure and other parameters were simulated and analyzed in k–ε turbulence model based on the laboratory experiments and the field production test data at Liwan 3 Station in the northern South China Sea with a gas production rate of 120 thousand m3/d as the target of commercial hydrate exploitation. And the following research results were obtained. First, the relationship curves of nozzle diameter, pump pressure and displacement are determined when the critical jet speed for crushing hydrate is 24 m/s. Second, the crushing rate to satisfy the daily hydrate sediment excavation of commercial exploitation is 2.48 m3/min and its corresponding jet crushing diameter is 800 mm. Third, when the nozzle diameter is fixed, other parts in the process will be damaged if jet displacement and pump pressure are increased directly. In conclusion, these selected design parameters for commercially excavating and crushing marine non-diagenetic hydrate by means of solid fluidization are conducive to the optimal design of crushing parameters of hydrate in solid fluidization exploitation. Keywords: Natural gas hydrate, Solid fluidization, Nozzle, Fluent, Water jet, Critical crushing rate, Pump pressure, Displacement, Optimal design

Marine natural gas hydrate (NGH) reservoirs in China are characterized by shallow burial depth and weak cementing. In view of these characteristics, it is in an urgent need to develop a series of technologies and support tools to ensure safe, economical, green and efficient NGH exploitation. In this paper, a new technical idea of NGH jet breaking and fluidization exploitation without changing the temperature and pressure conditions of NGH reservoirs was proposed, and the support nozzle tools for NGH jet breaking was designed, experimentally tested and optimized. Then, the relationships between the jet breaking parameters of nozzles (e.g. working pressure drop, flow rate, and lifting and lowering velocity and frequency) and the borehole diameters and breaking rates of broken NGH were investigated based on laboratory tests, and the field construction engineering charts of NGH jet breaking and fluidization exploitation were established. Finally, this method was practically verified at Well Liwan 3 in the South China Sea. And following research results were obtained. First, the NGH jet breaking and fluidization exploitation technology can increase the production efficiency of NGH exploitation, protect the safety of reservoir bottom and reduce the energy consumption of NGH exploitation. Second, by using the nozzle tools of NGH jet breaking, the generated borehole diameters are regular, broken particles can flow back well, and the lowering velocity of jet breaking without pilot holes is less than 7.1 m/h. Third, the engineering charts of NGH jet breaking and fluidization exploitation interpret the influential laws of jet breaking behaviors and construction parameters on the borehole diameters and breaking rates of NGH so as to provide a reference for the selection of NGH production test technology parameters. And fourth, the successful implementation of the NGH jet breaking and fluidization technology in the production tests of Well Liwan 3 verifies the feasibility of NGH jet breaking and fluidization exploitation process, and exhibits its promising application prospects in NGH future commercial exploitation. Keywords: Natural gas hydrate (NGH), Jet breaking, Fluidization exploitation, Multi-functional nozzle, Breaking effect, Technological parameter, Construction chart, Production test, South China sea, Well Liwan 3

Water jet technology is a key technology in the marine natural gas hydrate (NGH) solid fluidization mining method. As an important parameter in water jet breaking NGH sediments technology, the critical breaking velocity of NGH sediments is unknown. In the present research, an orthogonal design experiment is carried out to study the critical velocity of NGH breakage by water jet, using frozen soil and sand as experimental samples. First, the time it takes to reach maximum NGH breaking depth is determined. Then, ultimate breaking distance is studied with respect to the NGH saturation, jet pressure, and nozzle diameter. Following that, the variation of critical velocity with NGH saturation is analyzed. Eventually, a formula to calculate the critical velocity for marine NGH breakage by water jet process is established, and the undetermined coefficient (η) in the formula is calibrated with the experiment data. The results show that the ultimate breaking distance is mostly achieved within 63 s. The three experimental factors in order of the effect on the ultimate breaking depth (from high to low) are NGH saturation, jet pressure, and nozzle diameter. The critical velocities for marine NGH breakage corresponding to the NGH saturations of 20%, 40,%, 6%, and 80% are 5.71 m/s, 7.14 m/s, 9.60 m/s, and 10.85 m/s, respectively. The undetermined coefficient η in critical velocity formula is 1.44 m/s.

The application of a hydrocyclone to recycle NGH and desand during NGH exploitation is a novel idea. The flow field and performance of this hydrocyclone is in the frontier of the research in this field and is unclear so far. This research aimed to reveal the flow field characteristics and performance of NGH downhole hydrocyclones. In this paper, flow field, solid phase particle volume distribution and separation efficiency were investigated according to the two objectives of NGH recovery efficiency and sand removal efficiency with different inlet velocities by computational fluid simulations (CFD)-FLUENT software. The results show that the short circuit flow contributed to the recovery of NGH. Axial velocity is a decisive factor in balancing the two objectives of NGH recovery efficiency and sand removal efficiency. In addition, the same as those in traditional hydrocyclones, the static pressure, tangential velocity and turbulence intensity play key roles in separation performance, hydrocyclone performance can be improved by increasing the inlet velocity. On the other hand, most separation efficiencies were greater than 80%, when the particle size was larger than 15 µm, and the differential pressure was less than 0.6 MPa. Therefore, all the above results confirm that hydrocyclone has good performance in NGH exploitation, and the basis of its structural design and optimization are provided.