Kejun Long

Bio: Kejun Long is an academic researcher from Changsha University of Science and Technology. The author has contributed to research in topics: Bus network & Traffic flow. The author has an hindex of 6, co-authored 22 publications receiving 158 citations. Previous affiliations of Kejun Long include Changsha University.

Designing Sustainable Public Transportation: Integrated Optimization of Bus Speed and Holding Time in a Connected Vehicle Environment

Abstract: Developing public transportation and giving priority to buses is a feasible solution for improving the level of public transportation service, which facilitates congestion alleviation and prevention, and contributes to urban development and city sustainability. This paper presents a novel bus operation control strategy including both holding control and speed control to improve the level of service of transit systems within a connected vehicle environment. Most previous work focuses on optimization of signal timing to decrease the bus signal delay by assuming that holding control is not applied; the speed of buses is given as a constant input and the acceleration and deceleration processes of buses can be neglected. This paper explores the benefits of a bus operation control strategy to minimize the total cost, which includes bus signal delay, bus holding delay, bus travel delay, acceleration cost due to frequent stops and intense driving. A set of formulations are developed to explicitly capture the interaction between bus holding control and speed control. Experimental analysisand simulation tests have shown that the proposed integrated operational model outperforms the traditional control, speed control only, or holding control only strategies in terms of reducing the total cost of buses. The sensitivity analysis has further demonstrated the potential effectiveness of the proposed approach to be applied in a real-time bus operation control system under different levels of traffic demand, bus stop locations, and speed limits.

Reliability-Aware Joint Optimization for Cooperative Vehicular Communication and Computing

Abstract: This paper comprehensively discusses the cooperative communication and computation of vehicular system. Based on the cooperative transmission, an stochastic model of vehicle-to-vehicle (V2V) communication reliability is established using probability theory. Furthermore, the computation reliability is defined as a new metric for computation offloading, and a vehicle computational performance evaluation model is also established. In order to effectively compute the required data, we combine V2V communication and vehicle computing to further characterize the coupling reliability of cooperative communications and computation systems. In addition, we propose a virtual queue model that combines queue length and vehicle privacy entropy to optimize partitioning. Finally, considering the amount of processing data and cut-off time of vehicle applications, we establish the optimal partition model of vehicle computing with the goal of maximizing the coupling reliability, and propose the coupling-oriented reliability calculation for vehicle collaboration using dynamic programming methods. Simulations show that the proposed scheme outperforms traditional approaches in terms of coupling reliability and completion rate. In addition, the allocation between local computing and data offloading is controlled by the server’s privacy perception of collaboration events.

Urban traffic signal control with connected and automated vehicles: A survey

Abstract: Inefficient traffic control is pervasive in modern urban areas, which would exaggerate traffic congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we systematically review the potential solutions that take advantage of connected and automated vehicles (CAVs) to improve the control performances of urban signalized intersections. We review the methods and models to estimate traffic flow states and optimize traffic signal timing plans based on CAVs. We summarize six types of CAV-based traffic control methods and propose a conceptual mathematical framework that can be specified to each of six three types of methods by selecting different state variables, control inputs, and environment inputs. The benefits and drawbacks of various CAV-based control methods are explained, and future research directions are discussed. We hope that this review could provide readers with a helpful roadmap for future research on CAV-based urban traffic control and draw their attention to the most challenging problems in this important and promising field.

Genetic algorithm and its application

Abstract: The definition,content and application of the Genetic Algorithm were mainly introduced.The identifying of the digital image in the objective function was specialized for the purpose of ensuring the image keeping accurate.The application of option,exchange and variation of operator to the GA was introduced,and the application of GA was forecasted.

Dynamic headway control for high-frequency bus line based on speed guidance and intersection signal adjustment

Abstract: Computer-Aided Civil and Infrastructure Engineering To prevent bus bunching, a dynamic headway control method in the V2I (vehicle to infrastructure) environment for a high-frequency route with bus lane is developed. Bus operating speed guidance on the mid-blocks and intersection signal adjustment are two main strategies in the proposed method. A forecasting model of bus travel time under the dynamic control method is developed. The objective function is set up by taking into account differences between actual bus headways and dispatching headways, and the scaling ratios of intersection cycle lengths. The optimization model is solved using genetic algorithm. The proposed method is applied to a real bus route in Meihekou city, China, and compared with the current control plan as well as holding strategy. Results show that the proposed method can reduce bus headway deviations in all investigating periods; negative impacts on cars can be limited by setting reasonable values for the parameters.

Statistical and Econometric Methods for Transportation Data Analysis

Abstract: You are given vehicle accident data from 337 rural interstate road sections in the state of Indiana for a 5-year period (1995 to 1999). The use of accidents per vehiclemiles traveled has an intuitive appeal in highway safety – providing a standardized measure of the relative safety of roadway segments that is more easily interpreted than the number of accidents per some time period. Because accident rates on specific highway segments are assessed over some finite time period, there is the likelihood that many highway segments will have no accidents reported during the analysis period. Thus, modeling accident rates by standard OLS would result in biased and inconsistent parameter estimates. The solution to this is to consider accident rates as a censored dependent variable (censored at zero) and apply a tobit model. For the accident-rate considered, the data will be left-censored with a clustering at zero (zero accidents per 100-million vehicle miles traveled) because accidents may not be observed on all roadway segments during the period of observation. For model estimation, the accident rate (number of accidents per 100-million VMT) was calculated as: