Accurate prediction of passenger demand is essential for the efficient operation and management metro systems. In practical scenarios, strategies to enhance service quality often require information on multiple fronts, such as inflow a station, outflow from well transition flow between entry/exit stations. While predictions single type have been extensively studied, limited attention was paid jointly predicting demands. This problem challenging due complex relationships among demands (e.g.,...

This paper proposes an integrated optimization model for vessel scheduling and routing. The objective is to maximize shipping company profits while considering profit volatility using the Conditional Value-at-Risk metric master risks from demand fluctuations. Simultaneously, balances spot contract container allocation by optimally adjusting speeds so as minimize carbon emissions. We account deployment, chartering costs, delay penalties, fuel expenses, weather conditions ensure model’s...

Abstract An efficient ferrocene‐derived bifunctional phosphine‐catalyzed enantioselective oxa‐[4+2] cycloaddition of α‐substituted allenones with a broad range enones is investigated for the preparation stereodefined dihydropyrans in good to excellent yields (up 99 %) and enantioselectivity % ee ). Furthermore, series valuable chiral polyheterocyclic frameworks can be efficiently achieved enantioselectivities.

Connected and autonomous vehicles (CAVs) have the capability to acquire real‐time information from each other while human‐driven (HVs) are standalone in vehicle roadway navigation system. The asymmetry poses significant challenges managing controlling mixed traffic. To address such challenges, this study first customises intelligent driver model describe car‐following behaviour of CAVs. Furthermore, raise traffic efficiency flow, a new lane‐changing decision support algorithm is proposed,...

In order to improve the accuracy of short-term travel time prediction in an urban road network, a hybrid model for spatio-temporal feature extraction and network is proposed this research, which combines empirical dynamic modeling (EDM) complex networks (CN) with XGBoost model. Due highly nonlinear nature series, it necessary consider dependence spatial reliance series predicting networks. The can be revealed by EDM method, approach based on Chaos theory. Further, characteristic traffic...

A transportation digital twin represents a version of physical object or process, such as traffic signal controller, and thereby two-way real-time data exchange between the twin. This paper introduces approach for adaptive control (ATSC) to improve traveler's driving experience by reducing redistributing waiting time at an intersection. While ATSC combined with connected vehicle concept can reduce intersection travel in signalized corridor, it is nearly impossible delay congested conditions....

The ability to make informed decisions in complex scenarios is crucial for intelligent automotive systems. Traditional expert rules and other methods often fall short contexts. Recently, reinforcement learning has garnered significant attention due its superior decision-making capabilities. However, there exists the phenomenon of inaccurate target network estimation, which limits scenarios. This paper mainly focuses on study underestimation phenomenon, proposes an end-to-end autonomous...

The presence of demand uncertainty brings challenges to network design problems (NDP), because fluctuations in origin-destination (OD) have a prominent effect on the corresponding total travel time, which is usually adopted as an index evaluate problem. Fortunately, macroscopic fundamental diagram (MFD) has been proved be property road itself, independent demand. Such characteristics MFD provide new theoretical basis assess traffic performance and further appraise quality strategies....

Abstract Network‐wide short‐term passenger flow prediction is critical for the operation and management of metro systems. However, it challenging due to inherent non‐stationarity, nonlinearity, spatial–temporal dependencies within flow. To tackle these challenges, this paper introduces a hybrid model called multi‐scale dynamic propagation network (MSDPSTN). Specifically, employs multivariate empirical mode decomposition jointly decompose into intrinsic functions. Then, set graphs developed...

Advances in connected and autonomous vehicles have the promise to reshape future of transportation system. How when benefits associated with automation connectivity technology will start impact performance an urban corridor is issue interest for traffic operators. This paper proposes analytical capacity model corridors mixed based on concept macroscopic fundamental diagram. The incorporates full spectrum vehicle penetration rates as well reaction times different following patterns. platoon...

Evaluating a regional traffic control system requires understanding both the advantages and disadvantages of schemes as well interrelated characteristics system. To assess efficiency signal in road network, this study, which is based on macroscopic fundamental diagram (MFD) concept, proposes four evaluative indicators: maximum throughput, critical accumulation, gridlock accumulation degree homogeneity. The throughput can be used to reflect network capacity load capacity, respectively....

A hurricane can cause a lot of damage to highway networks and significantly affect the evacuation trip operations on roads. good understanding network vulnerability improve preparedness for an emergency evacuation. This paper presents game theory–based approach analysis under zero-sum was constructed between router, which seeks minimum-cost paths trips, tester, maximizes travel cost by disturbing links. The distribution demand elastic because probability selecting destination determined path...

Planning for a bus-based regional evacuation is essential emergency preparedness, especially hurricane or flood prone urban environments with large numbers of transit-dependent transit-captive populations. This paper develops an optimization-based decision-support model pedestrian–bus planning under bus fleet, pedestrian and routes, network constraints. Aiming to minimize the duration time, optimization proposed determine optimal pickup nodes evacuees assemble using existing allocate...

In order to identify the real-time traffic state of regional road network effectively, this paper proposes a method determine thresholds selected index corresponding different states, which combines macroscopic fundamental diagram (MFD) with K-means clustering. Firstly, in facilitate control traffic, number accumulated vehicles inside is as discriminant index, and cluster K value determined according data characteristics MFD related specifications. Then select algorithm scatter plots get...

The macroscopic fundamental diagram (MFD) is a nonuniversal changing process over network traffic status which indicates different shapes in networks. Hysteresis observed the MFD of some urban It unique phenomenon when remains at low stability level and usually appears around congestion period. This paper analyzed peak through focusing on hysteresis. formation mechanism hysteresis deduced from mathematical method based previous research studies. precondition state can be figured by...