Qixin Shi

Integrated quay crane and yard truck schedule problem in container terminals

Abstract Quay crane and yard truck scheduling are two important subproblems in container terminal operations which have been studied separately in previous research. This paper proposes a new problem for the integrated quay crane and yard truck scheduling for inbound containers. The problem is formulated as a mixed integer programming (MIP) model. Due to the intractability, a genetic algorithm (GA) and a modified Johnsons Rule-based heuristic algorithm (MJRHA) are used for the problem solution. In addition, two closed form lower bounds are given to evaluate the solution accuracy. Computational experiments show that the solution algorithm can efficiently handle the scheduling problem and that the integrated methods are very useful.

A Decision Support Method for Truck Scheduling and Storage Allocation Problem at Container

Truck scheduling and storage allocation, as two separate subproblems in port operations, have been deeply studied in past decades. However, from the operational point of view, they are highly interdependent. Storage allocation for import containers has to balance the travel time and queuing time of each container in yard. This paper proposed an integer programming model handling these two problems as a whole. The objective of this model is to reduce congestion and waiting time of container trucks in the terminal so as to decrease the makespan of discharging containers. Due to the inherent complexity of the prob-lem, a genetic algorithm and a greedy heuristic algorithm are designed to attain near optimal solutions. It shows that the heuristic algorithm can achieve the optimal solution for small-scale problems. The solutions of small-and large-scale problems obtained from the heuristic algorithm are better than those from the genetic algorithm.

Synchronization of yard truck scheduling and storage allocation in container terminals

Yard truck scheduling and storage allocation, as two separate subproblems in port operations, have been extensively studied in the past decades. However, from the operational point of view, they are highly interdependent. This article proposes an integer programming model in which yard truck scheduling and storage allocation problems are formulated as a whole for heterogeneous import containers. Different stacking times at yard blocks is modelled as well. The objective of the proposed model is to reduce the congestion and waiting time of yard trucks in the terminal so as to decrease the makespan of discharging containers. Owing to the inherent computational complexity, a genetic algorithm and a greedy heuristic algorithm have been designed. Computational experiments show that the proposed genetic algorithm and greedy algorithm are both effective in solving the studied problem.

Characterising scattering features in flow–density plots using a stochastic platoon model

The scattering features of points in flow–density plot remain as an attractive topic in the last several decades. Some previous studies either assumed that the points of congested traffic flows were completely random or that the implicit rules of hidden distribution were difficult to describe. Although the scattering features are influenced by various factors (e.g. lane-changing manoeuvers, merging behaviours and driver heterogeneity), we believe that they are mainly dominated by the microscopic headway/spacing distributions. In this paper, we relax the assumption of deterministic headway/spacing in Newells simplified car-following model and allow random headways/spacings in a homogeneous platoon (vehicles run closely at the same velocity). Further extending the conventional deterministic reciprocal relationship between flow rate and headway, we find that the reciprocal of average headway of a homogeneous platoon and the corresponding flow rate should follow the same distribution. Based on these two extensions, we can link the conditional distributions of average headway in a homogeneous platoon and the conditional distributions of flow rate, all with respect to velocity. When the aggregation time interval is small enough (e.g. 30 s), tests on Performance Measurement System (PeMS) data reveal that the seemingly disorderly scattering points in the macroscopic flow–density plot follow the estimated flow rate distributions from Next Generation Simulation vehicular trajectories. While if the aggregation time interval increases (e.g. to 5 min), the measured vehicles probably pass the loop detectors at different velocities and form heterogeneous platoons. It becomes difficult to find a definite distribution model that can fit average headway/spacing for heterogeneous platoons. However, most points in flow–velocity plot still locate within a certain 2D region, whose boundaries can be obtained from the homogeneous platoon model. Finally, tests on PeMS data verify the estimated boundaries.

Study on integration of urban traffic control and route guidance based on multi-agent technology

The integration of urban traffic signal control (TSC) system and dynamic route guidance (DRG) system became a development trend of intelligent transportation system (ITS). This paper firstly describes the characters of integration of the two systems and the theory of multi-agent system. Based on the multi-agent system theory, we present a system architecture of the integration system of TSC and DRG with two kinds interactive agent model architecture: traffic signal control agent model and dynamic route guidance agent model. We then use the TSC agent model as an example to discuss the architecture and interactive mechanism of the agent models. The multi-agent system provides a possible means for the integration of TSC and DRG. Finally this paper studies the coordination model, indicates how these agent models coordinate.

Location Specific Cell Transmission Model for Freeway Traffic

Abstract This paper describes a location specific cell transmission model of freeway traffic based on the observed variability of fundamental diagrams both along and across freeway segments. This model extends the original cell transmission model (CTM) mechanism by defining various shapes of fundamental diagrams to reproduce more complex traffic phenomena, including capacity drops, lane-by-lane variations, nonhomogeneous wave propagation velocities, and temporal lags. A field test on a Canadian freeway was used to demonstrate the validity of the location specific CTM. The simulated spatio-temporal evolutions of traffic flow show that the model can be used to describe the traffic dynamics near bottlenecks more precisely than the original model.

Evolution and Effect of Transportation Policy on Public Transit: Lessons from Beijing

The United Nations predicts that half the worlds population will live in cities by 2008. Thus, rapid urban sprawl, and especially its traffic congestion, is a global problem. Meeting mobility needs of urban dwellers is critical to sustaining growth and social stability, but many major cities struggle to do so. The evolving situation in Beijing, is examined, and the policy-making process in Beijing is analyzed to understand why transportation problems occur and are intractable and how they can be solved. A structure of policy making is proposed that includes four factors: institutional, travel behavior, ideals, and landmark events. The analysis includes a case study and comparison of transit service in Beijing and other cities, including results from the latest transit level-of-service rider survey in Beijing. It is concluded that an imbalance between transportation supply and demand is the primary cause of traffic congestion. The transportation problem must be solved from two sides: increasing supply and managing demand simultaneously. Public transit, paired with transportation demand management, is an effective approach for sustainable transportation but requires a range of policies.

Perturbation And Stability Analysis Of The Multi-Anticipative Intelligent Driver Model

This paper discusses three kinds of IDM car-following models that consider both the multi-anticipative behaviors and the reaction delays of drivers. Here, the multi-anticipation comes from two ways: (1) the driver is capable of evaluating the dynamics of several preceding vehicles, and (2) the autonomous vehicles can obtain the velocity and distance information of several preceding vehicles via inter-vehicle communications. In this paper, we study the stability of homogeneous traffic flow. The linear stability analysis indicates that the stable region will generally be enlarged by the multi-anticipative behaviors and reduced by the reaction delays. The temporal amplification and the spatial divergence of velocities for local perturbation are also studied, where the results further prove this conclusion. Simulation results also show that the multi-anticipative behaviors near the bottleneck will lead to a quicker backwards propagation of oscillations.

Development of Integrated Information Platform for Intelligent Transportation Systems

Information society requires to establish the Intelligent Integrated Transportation System (IITS). The important approach to integrate many Intelligent Transportation System (ITS) subsystems is the Integrated Transportation Information Platform(ITIP). In this paper, Firstly the significance of ITIP is analyzed. Currently in China research and establishment of ITIP is urgent. After analyzing the functions of ITIP, a Distributed System Architecture of ITIP is presented, which is based on the Data Processing technique. Then the important basic of IIP establishment-Data Processing technique, including data fusing technology, Data warehouse technology, Data compression technology and Data Mining technology is discussed. In the end the advantages of the ITIP and its development in China are analyzed.

Evaluation of Accident-Induced Indirect Costs for Measuring Penalties on Violations of Laws

Traffic accidents cause significant economic losses, which include not only direct costs, such as damage to vehicles and road facilities, but also indirect costs, such as traffic delays for other travelers. For severe accidents involving violations of laws, the direct economic loss is trivial compared with the indirect economic loss resulting from long hours of congestion and large numbers of affected travelers. Drivers who violate transportation laws should be subject to legal liabilities for both direct and indirect economic losses. To calculate the penalties for violating laws related to traffic accidents, it is important to establish a standard for evaluating the indirect costs of accidents. A general framework for estimating accident-induced indirect costs is proposed. As a key component of the estimation procedures, the delay estimation can be conducted by reconstructing the spatial–temporal traffic flow evolutions on the basis of intelligent transportation system sensors or archived data, or both. The proposed evaluation methodology, which measures on-site arrival–departure cumulative flows and speeds, was compared with the spatial–temporal traffic state evolution approach. As a case study, the proposed approach was applied to two severe traffic accidents that occurred on the G6 Highway (Beijing–Tibet Highway). The promising results verify the feasibility and accuracy of the proposed procedures. The analytic study results also support drafting the related national standard in China.