Applying an extended prototype willingness model to predict back seat safety belt use in China

The risk of injury and death in traffic accidents for passengers in the back and front seats can be reduced by utilizing safety belts. However, passengers use back seatbelts far less frequently than those in the front. More investigation is therefore required into the psychological constructs that affect individuals\u27 attitudes toward using back seat belts. In this study, four models were used to analyze individual intentions and actual back seat belt use: the standard theory of planned behavior (TPB); the standard prototype willingness model (PWM); a model that integrates the TPB and PWM constructs; and a model that integrates the TPB construct, PWM constructs, descriptive norms and perceived law enforcement. The results showed that the standard PWM has much more explanatory power than the standard TPB in explaining the variance in behavioral intention and behavior. Incorporating perceived behavioral control (PBC) into the standard PWM did not improve the model fit considerably, while incorporating descriptive norms and perceived law enforcement moderately improved the model fit. Attitude greatly impacted behavioral intention and the use of back seat belts, followed by perceived law enforcement and descriptive norms, while subjective norms, prototype favorability, prototype similarity and PBC had no significant effect

Revealing the determinants of the intermodal transfer ratio between metro and bus systems considering spatial variations

Buses and metros are two main public transit modes, and these modes are crucial components of sustainable transportation systems. Promoting reciprocal integration between bus and metro systems requires a deep understanding of the effects of multiple factors on transfers among integrated public transportation transfer modes, i.e., metro-to-bus and bus-to-metro. This study aims to reveal the determinants of the transfer ratio between bus and metro systems and quantify the associated impacts. The transfer ratio between buses and metros is identified based on large-scale transaction data from automated fare collection systems. Meanwhile, various influencing factors, including weather, socioeconomic, the intensity of business activities, and built environment factors, are obtained from multivariate sources. A multivariate regression model is used to investigate the associations between the transfer ratio and multiple factors. The results show that the transfer ratio of the two modes significantly increases under high temperature, strong wind, rainfall, and low visibility. The morning peak hours attract a transfer ratio of up to 57.95%, and the average hourly transfer volume is 0.94 to 1.38 times higher at this time than in other periods. The intensity of business activities has the most significant impact on the transfer ratio, which is approximately 1.5 to 15 times that of the other independent variables. Moreover, an adaptative geographically weighted regression is utilized to investigate the spatial divergences of the influences of critical factors on the transfer ratio. The results indicate that the impact of a factor presents spatial heterogeneity and even shows opposite effects (in terms of positive and negative) on the transfer ratio in different urban contexts. For example, among the related socioeconomic variables, the impact of the housing price on the downtown transfer ratio is larger than that in the suburbs. Crowd density positively influences the transfer ratio at most stations in the northern region, whereas it shows negative results in the southern region. These findings provide valuable insights for public transportation management and promote the effective integration of bus and metro systems to provide enhanced transfer services

Bus timetable optimization model in response to the diverse and uncertain requirements of passengers for travel comfort

Most existing public transit systems have a fixed dispatching and service mode, which cannot effectively allocate resources from the perspective of the interests of all participants, resulting in resource waste and dissatisfaction. Low passenger satisfaction leads to a considerable loss of bus passengers and further reduces the income of bus operators. This study develops an optimization model for bus schedules that considers vehicle types and offers two service levels based on heterogeneous passenger demands. In this process, passenger satisfaction, bus company income, and government subsidies are considered. A bilevel model is proposed with a lower-level passenger ride simulation model and an upper-level multiobjective optimization model to maximize the interests of bus companies, passengers, and the government. To verify the effectiveness of the proposed methodology, a real-world case from Guangzhou is presented and analyzed using the nondominated sorting genetic algorithm-II (NSGA-II), and the related Pareto front is obtained. The results show that the proposed bus operation system can effectively increase the benefits for bus companies, passengers, and the governmen

Real-Time Dispatch of Coupled Transmission and Distribution Systems within a Distributed and Cooperative Framework

This paper presents a real-time dispatch strategy for coupled transmission and distribution systems within a distributed and cooperative control framework to maintain reliable and secure operation with minimum generation costs and maximum renewable energy consumption. The presented strategy transforms each distribution system into a dispatchable active source via an average-consensus-based active power control of renewable distributed energy resources (DERs) at the distribution level and then dispatches the active power reference of conventional generators as well as the distribution systems in a measurement-based way at a transmission level. The voltage fluctuation caused by the DER active power control is smoothened with a distributed voltage control method, which can also reduce the active power loss in the distribution systems. Compared to existing real-time dispatch strategies, the proposed strategy can eliminate security issues in the transmission system in a short time by regulating large amounts of DERs at a distribution level in a simple and easy controlled structure, in which the differences in the communication conditions and privacy requirements between the distribution and transmission systems are adequately considered

Dynamic-decision-based Real-time Dispatch for Reducing Constraint Violations

This paper proposes a dynamic-decision-based real-time dispatch method to coordinate the economic objective with multiple types of security dispatch objectives while reducing constraint violations in the process of adjusting the system operation point to the optimum. In each decision moment, the following tasks are executed in turn: ① locally linearizing the system model at the current operation point with the online model identification by using measurements; ② narrowing down the gaps between unsatisfied security requirements and their security thresholds in order of priority; ③ minimizing the generation cost; ④ minimizing the security indicators within their security thresholds. Compared with the existing real-time dispatch strategies, the proposed method can adjust the deviations caused by unpredictable power flow fluctuations, avoid dispatch bias caused by model parameter errors, and reduce the constraint violations in the dispatch decision process. The effectiveness of the proposed method is verified with the IEEE 39-bus system

Multiple Emergency Vehicle Priority in a Connected Vehicle Environment: A Cooperative Method

Since emergency vehicles (EMVs) in urban transit systems play a crucial role in responding to time-critical events, the quick response of EMVs is essential for improving the success rate of rescue operations and minimizing property loss. Booming connected vehicle (CV) technology provides a new perspective to further enhance the effectiveness of EMV priority. Based on this CV technology, we propose a cooperative multiple EMV priority model in which the speed, acceleration, and lane changing actions of both the EMVs and surrounding ordinary vehicles (OVs) are set as decision variables. This proposed model is rigorously formulated in integer linear programming to maximize the EMV traffic efficiency and find a trade-off between the interference with normal traffic flows and the smoothness of the EMV driving trajectories. Two customized algorithms are developed to reduce the number of decision variables and constraints to obtain the better feasible solution in an acceptable computational time. A numerical experiment based on real-world data is proposed to further verify the utility and effectiveness of the aforementioned mathematical model. The customized algorithms achieve near-exact solutions with significantly faster computation compared to the benchmark solver. The robustness of the proposed model is tested with different parameter settings in the sensitivity analysis

Determination of the number of ψ(3686)\psi(3686) events at BESIII

The numbers of ψ(3686) events accumulated by the BESIII detector for the data taken during 2009 and 2012 are determined to be and , respectively, by counting inclusive hadronic events, where the uncertainties are systematic and the statistical uncertainties are negligible. The number of events for the sample taken in 2009 is consistent with that of the previous measurement. The total number of ψ(3686) events for the two data taking periods is