Dongfang Ma

Calibration of Platoon Dispersion Parameter Considering the Impact of the Number of Lanes

Microscopic vehicle behaviors, such as car following, overtaking, and lane changing, may occur differently on links with different numbers of lanes. Thus, this paper addresses the impact of the number of lanes on the platoon dispersion of traffic flow in low-friction conditions. A well-adopted dispersion model is used to reflect the platoon dispersion. The platoon dispersion factor of the model is then recalibrated using data on road segments with different numbers of lanes. The data are obtained from a comprehensive survey taken at several locations on the arterial streets of Changchun and Hangzhou city, China, where each direction of road segment has two, three, four, or five lanes. The statistical results verify that the number of lanes does have an evident effect on the platoon dispersion factor α: when the number of lanes grows from two to five, the value of α decreases significantly; meanwhile, the slope of the function curve between α and the normalized flow becomes larger.

A Method of Signal Timing Optimization for Spillover Dissipation in Urban Street Networks

The precise identification and quick dissipation of spillovers are critically important in a traffic control system, especially when heavy congestion occurs. This paper first presents a calculation method for the occupancy per cycle under different traffic conditions and identifies the threshold of occupancy that characterizes the formation of spillovers. Then, capacity adjustments are determined for the incoming and outgoing streams of bottleneck links, with the aim of dissipating the queue to a permissible length within a given period of time, and optimization schemes are defined to calculate splits for the upstream and downstream intersections. Finally, taking average vehicular delay, outputs per cycle, and maximum queue length on the bottleneck link as the evaluation indices, the method of dissipating spillovers proposed in this paper is evaluated using a VISSIM simulation. The results show that the maximum queue length on the bottleneck link and the average vehicular delay at the upstream and downstream intersections decrease significantly under the new signal control plan; meanwhile, the new control schemes have little influence on the outputs of the two intersections per cycle.

A Method for Queue Length Estimation in an Urban Street Network Based on Roll Time Occupancy Data

A method estimating the queue length in city street networks was proposed using the data of roll time occupancy. The key idea of this paper is that when the queue length in front of the queue detector becomes longer, the speeds of the following vehicles to pass through the detector will become smaller, resulting in higher occupancy with constant traffic intensity. Considering the relationship between queue lengths and roll time occupancy affected by many factors, such as link length, lane width, lane number, and bus ratio, twelve different conditions were designed, and the traffic data under different conditions was obtained using VISSIM simulation. Based on the analysis of simulation data, an S-type logistic model was decided to develop for the relationship between queue lengths and roll time occupancy, and the fitting equations were obtained under the twelve simulation situations. The average model for the relationship between queue lengths and roll time occupancy was presented by successive multiple linear regression with the fitting equation parameters and simulation parameters, and the estimation model for queue length was presented through analyzing the equation of the average relation model.

Lane-Based Saturation Degree Estimation for Signalized Intersections Using Travel Time Data

Saturation degree estimation is a vital problem of signal timing optimization. However, classic loop-detector-based algorithms are not capable to capture the severity of oversaturation, since detectors are located in front of stop lines, and also cannot distinguish the saturated degree in different lane groups if detectors are located at an upstream position. In this paper, we present a new method to estimate the lane-based saturation degree using travel times. The method is simple and mainly depends on the parameters of signal cycles and the corresponding virtual cycles. The virtual cycle parameters are extracted by analyzing the data on travel times using the K-mean cluster analysis. Then, two models for the traffic demand saturated degree (TDSD) and the effectively used green time saturation degree (EUGTSD) are presented based on the traffic flow conservation during one signal cycle and the corresponding virtual cycle. The new method can overcome the defects of loop-detector-based algorithms, and it can be used to optimize the TDSD and the EUGTSD simultaneously. Finally, the precision of the two types of models is evaluated using field survey data. The results show that the new method has a higher precision for the TDSD and the same accuracy level for the EUGTSD compared to the existing methods. The findings of this paper have potential applicability to signal control systems.

Modeling Mixed Bicycle Traffic Flow: A Comparative Study on the Cellular Automata Approach

Simulation, as a powerful tool for evaluating transportation systems, has been widely used in transportation planning, management, and operations. Most of the simulation models are focused on motorized vehicles, and the modeling of nonmotorized vehicles is ignored. The cellular automata (CA) model is a very important simulation approach and is widely used for motorized vehicle traffic. The Nagel-Schreckenberg (NS) CA model and the multivalue CA (M-CA) model are two categories of CA model that have been used in previous studies on bicycle traffic flow. This paper improves on these two CA models and also compares their characteristics. It introduces a two-lane NS CA model and M-CA model for both regular bicycles (RBs) and electric bicycles (EBs). In the research for this paper, many cases, featuring different values for the slowing down probability, lane-changing probability, and proportion of EBs, were simulated, while the fundamental diagrams and capacities of the proposed models were analyzed and compared between the two models. Field data were collected for the evaluation of the two models. The results show that the M-CA model exhibits more stable performance than the two-lane NS model and provides results that are closer to real bicycle traffic.

A Novel Speed–Density Relationship Model Based on the Energy Conservation Concept

This paper makes a basic assumption that energy conservation exists, between psychological potential and a vehicles kinetic energy, in the drivers psychological field based on the drivers mental activities. A virtual spring is used to describe the storage and release of psychological potential energy. Under the aforementioned conditions, we established a macroscopic traffic flow model with conservation law. Each parameter in the new model is physically meaningful and explicit. Additionally, the model can fit field data consistently well, both in free-flow and congested situations. The results of this paper prove the rationality of the energy conservation concept in traffic flow, which improves the understanding of traffic flow and provides a new theoretical foundation.

Development of Correlation Degree Model between Adjacent Signal Intersections for Subarea Partition

The correlation degree model between adjacent signal intersections is the most important component of subarea partition algorithms. In this article, factors that affect partition are classified into static factors and dynamic factors. The authors mainly focus on the two dynamic factors, which are cycle length and platoon length. The cycle length correlation model is established by considering the cycle length difference between seed intersection and non-seed intersection. Then by adopting platoon dispersion and the ratio of platoon length to phase green time, the platoon correlation model is developed to depict the benefits of signal coordination control. Based on the two above models, an integrated correlation model is developed to quantify the correlation degree of adjacent intersections. At last, Changs model, which is a representative achievement in subarea partition cited by the Traffic Control Systems Handbook, is compared with the authors model by way of examples. The results show that the authors model outperforms Changs model in depicting correlation degree between intersections. This research can provide theoretical support for subarea partition and signal control.

Policy-Combination Oriented Optimization for Public Transportation Based on the Game Theory

This research aims at detecting the interactions between policy maker and travelers when making public transport policy and strategies to optimize relevant policy combination. In the two scenarios of whether to set a bus lane or not, travel cost functions of bus and car are proposed, respectively, with the in-vehicle comfort level of passengers considered. By introducing the bottleneck model and transit assignment model, travelers’ behaviors are revealed according to different travel mode. Focusing on minimizing the total cost of the system (TSC), Stackelberg game model is built to describe the dynamic interactions between the government, the bus company, and travelers. Finally, kriging surrogate method is proposed on account of numerical simulation to find solution to the game model and propose the optimal policy combination and resource allocation. The results show an effective performance: under the assumption that the travel distance is 20km, the optimized policy combination can reduce TSC by 8.59% and 9.82% in two scenarios, respectively, and reduce travel cost per person by 10.28% and 15.85%, respectively.

Travel time estimation method for urban road based on traffic stream directions

ABSTRACT Traffic flow on a given link in an urban road network can be divided into several traffic streams, depending on their turning manoeuvres when entering and leaving the link. These traffic streams may experience various travel times due to multiple reasons, such as fluctuations in traffic demand/supply and stochastic arrivals/departures at signalised intersections. However, the current travel time estimation methods take traffic flow as a whole and produce a single estimation value. This approach can produce large errors. Furthermore, given the travel time information of each traffic stream, the results of dynamic traffic assignment models can be made much more accurate and the effect of signal controls improved. In this paper, a comparison analysis is conducted to verify the significant difference in link travel times of different traffic streams. Then, link travel time is redefined in consideration of traffic stream directions. This process is also successful in filtering noise, as shown in the numerical experiments. In addition, existing estimation methods cannot reflect real values or fluctuations of travel times in sampling intervals without any valid observational data. To solve this problem, a regression model is built and integrated into the travel time estimation model. Error analysis of several links on two different days demonstrates the improvements made by the model.

A Discrete-Flow Form of the Point-Queue Model

This paper proposes a discrete-flow form of the well-known point-queue model. Different from the traditional continuous-flow form with non-integral flow, the discrete-flow form treats a vehicle as its basic unit. The treatment simplifies the measurements of link travel times, and expands the applications of the point-queue model, such as into agent-based applications.