This page has only limited features, please log in for full access.

Dr. Senlai Zhu
School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China

Basic Info


Research Keywords & Expertise

0 Data Analysis
0 travel behaviour
0 Blockchain Technology
0 Tansportation Engineering
0 Intenligent Transportation Systems

Fingerprints

Blockchain Technology

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 26 July 2021 in Sustainability
Reads 0
Downloads 0

Nowadays, blockchain technology is expected to promote the quality control of traditional industry due to its traceability, transparency and non-tampering characteristics. Although blockchain could offer the traditional industry new energy, there are still some predictable difficulties in the early stage of its application, such as the structure of the blockchain-based system, the role of regulators in the system and high transaction fee by block packing. In this paper, we establish a pioneering quality control system for the green composite wind turbine blade supply chain based on blockchain technology. Firstly, the framework of this system is proposed to ensure that the quality of the product could not only be examined and verified by regulator, but also be monitored by other related nodes. Next, we develop a new way to store the data by hash fingerprint and the cost of transaction fees is significantly reduced in the case of a large amount of data. Then, the information on-chain method is developed to realize the data traceability of each node. At last, the tests of this system are carried out to prove its validity, the satisfactory results are obtained and information supervision and sharing role of the regulators are discussed.

ACS Style

Hang Yu; Senlai Zhu; Jie Yang. The Quality Control System of Green Composite Wind Turbine Blade Supply Chain Based on Blockchain Technology. Sustainability 2021, 13, 8331 .

AMA Style

Hang Yu, Senlai Zhu, Jie Yang. The Quality Control System of Green Composite Wind Turbine Blade Supply Chain Based on Blockchain Technology. Sustainability. 2021; 13 (15):8331.

Chicago/Turabian Style

Hang Yu; Senlai Zhu; Jie Yang. 2021. "The Quality Control System of Green Composite Wind Turbine Blade Supply Chain Based on Blockchain Technology." Sustainability 13, no. 15: 8331.

Journal article
Published: 21 July 2021 in Sensors
Reads 0
Downloads 0

In this paper a Bayesian method is proposed to estimate dynamic origin–destination (O–D) demand. The proposed method can synthesize multiple sources of data collected by various sensors, including link counts, turning movements at intersections, flows, and travel times on partial paths. Time-dependent demand for each O–D pair at each departure time is assumed to satisfy the normal distribution. The connections among multiple sources of field data and O–D demands for all departure times are established by their variance-covariance matrices. Given the prior distribution of dynamic O–D demands, the posterior distribution is developed by updating the traffic count information. Then, based on the posterior distribution, both point estimation and the corresponding confidence intervals of O–D demand variables are estimated. Further, a stepwise algorithm that can avoid matrix inversion, in which traffic counts are updated one by one, is proposed. Finally, a numerical example is conducted on Nguyen–Dupuis network to demonstrate the effectiveness of the proposed Bayesian method and solution algorithm. Results show that the total O–D variance is decreasing with each added traffic count, implying that updating traffic counts reduces O–D demand uncertainty. Using the proposed method, both total error and source-specific errors between estimated and observed traffic counts decrease by iteration. Specifically, using 52 multiple sources of traffic counts, the relative errors of almost 50% traffic counts are less than 5%, the relative errors of 85% traffic counts are less than 10%, the total error between the estimated and “true” O–D demands is relatively small, and the O–D demand estimation accuracy can be improved by using more traffic counts. It concludes that the proposed Bayesian method can effectively synthesize multiple sources of data and estimate dynamic O–D demands with fine accuracy.

ACS Style

Hang Yu; Senlai Zhu; Jie Yang; Yuntao Guo; Tianpei Tang. A Bayesian Method for Dynamic Origin–Destination Demand Estimation Synthesizing Multiple Sources of Data. Sensors 2021, 21, 4971 .

AMA Style

Hang Yu, Senlai Zhu, Jie Yang, Yuntao Guo, Tianpei Tang. A Bayesian Method for Dynamic Origin–Destination Demand Estimation Synthesizing Multiple Sources of Data. Sensors. 2021; 21 (15):4971.

Chicago/Turabian Style

Hang Yu; Senlai Zhu; Jie Yang; Yuntao Guo; Tianpei Tang. 2021. "A Bayesian Method for Dynamic Origin–Destination Demand Estimation Synthesizing Multiple Sources of Data." Sensors 21, no. 15: 4971.

Journal article
Published: 24 May 2020 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

The popularity of electric bicycles in China makes them a common transportation mode for people to commute and move around. However, with the increase in traffic volumes for both vehicles and electric bicycles, urban traffic safety and congestion problems are rising due to traffic conflicts between these two modes. To regulate travel behavior, it is essential to analyze the mode choice and route choice behaviors of travelers. This study proposes a combined modal split and multiclass traffic user equilibrium model formulated as a complementarity problem (CP) to simultaneously characterize the mode choice behavior and route choice behavior of both vehicle and electric bicycle users. This model captures the impacts of route travel time and out-of-pocket cost on travelers’ route choice behaviors. Further, modified Bureau of Public Roads (BPR) functions are developed to model the travel times of links with and without physical separation between vehicle lanes and bicycle lanes. This study also analyzes the conditions for uniqueness of the equilibrium solution. A Newton method is developed to solve the proposed model. Numerical examples with different scales are used to validate the proposed model. The results show that electric bicycles are more favored by travelers during times of high network congestion. In addition, total system travel time can be reduced significantly through physical separation of vehicle lanes from electric bicycle lanes to minimize their mutual interference.

ACS Style

Senlai Zhu; Jie Ma; Tianpei Tang; Quan Shi. A Combined Modal and Route Choice Behavioral Complementarity Equilibrium Model with Users of Vehicles and Electric Bicycles. International Journal of Environmental Research and Public Health 2020, 17, 3704 .

AMA Style

Senlai Zhu, Jie Ma, Tianpei Tang, Quan Shi. A Combined Modal and Route Choice Behavioral Complementarity Equilibrium Model with Users of Vehicles and Electric Bicycles. International Journal of Environmental Research and Public Health. 2020; 17 (10):3704.

Chicago/Turabian Style

Senlai Zhu; Jie Ma; Tianpei Tang; Quan Shi. 2020. "A Combined Modal and Route Choice Behavioral Complementarity Equilibrium Model with Users of Vehicles and Electric Bicycles." International Journal of Environmental Research and Public Health 17, no. 10: 3704.

Journal article
Published: 01 April 2019 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts' judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015⁻2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

ACS Style

Tianpei Tang; Senlai Zhu; Yuntao Guo; Xizhao Zhou; Yang Cao. Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method. International Journal of Environmental Research and Public Health 2019, 16, 1166 .

AMA Style

Tianpei Tang, Senlai Zhu, Yuntao Guo, Xizhao Zhou, Yang Cao. Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method. International Journal of Environmental Research and Public Health. 2019; 16 (7):1166.

Chicago/Turabian Style

Tianpei Tang; Senlai Zhu; Yuntao Guo; Xizhao Zhou; Yang Cao. 2019. "Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method." International Journal of Environmental Research and Public Health 16, no. 7: 1166.

Journal article
Published: 30 January 2019 in Sustainability
Reads 0
Downloads 0

The adaptive traffic signal control system is a key component of intelligent transportation systems and has a primary role in effectively reducing traffic congestion. The high costs of implementation and maintenance limit the applicability of the adaptive traffic signal control system, especially in developing countries. This paper proposes a low-cost adaptive signal control method that is easy to implement. Two detectors are installed in each vehicle lane at an optimal location determined by the proposed method to detect green and red redundancy time, based on which the original signal timing is adjusted through a signal controller. The proposed method is evaluated through case studies with low and high volume-to-capacity ratio intersections. The results show that the proposed adaptive signal control method can significantly reduce total traffic delay at intersections.

ACS Style

Senlai Zhu; Ke Guo; Yuntao Guo; Huairen Tao; Quan Shi. An Adaptive Signal Control Method with Optimal Detector Locations. Sustainability 2019, 11, 727 .

AMA Style

Senlai Zhu, Ke Guo, Yuntao Guo, Huairen Tao, Quan Shi. An Adaptive Signal Control Method with Optimal Detector Locations. Sustainability. 2019; 11 (3):727.

Chicago/Turabian Style

Senlai Zhu; Ke Guo; Yuntao Guo; Huairen Tao; Quan Shi. 2019. "An Adaptive Signal Control Method with Optimal Detector Locations." Sustainability 11, no. 3: 727.

Journal article
Published: 12 March 2018 in Future Internet
Reads 0
Downloads 0

This paper presents a mixed-integer linear programming model for demand-responsive feeder transit services to assign vehicles located at different depots to pick up passengers at the demand points and transport them to the rail station. The proposed model features passengers’ one or several preferred time windows for boarding vehicles at the demand point and their expected ride time. Moreover, passenger satisfaction that was related only to expected ride time is fully accounted for in the model. The objective is to simultaneously minimize the operation costs of total mileage and maximize passenger satisfaction. As the problem is an extension of the nondeterministic polynomial problem with integration of the vehicle route problem, this study further develops an improved bat algorithm to yield meta-optimal solutions for the model in a reasonable amount of time. When this was applied to a case study in Nanjing City, China, the mileage and satisfaction of the proposed model were reduced by 1.4 km and increased by 7.1%, respectively, compared with the traditional model. Sensitivity analyses were also performed to investigate the impact of the number of designed bus routes and weights of objective functions on the model performance. Finally, a comparison of Cplex, standard bat algorithm, and group search optimizer is analyzed to verify the validity of the proposed algorithm.

ACS Style

Bo Sun; Ming Wei; Senlai Zhu. Optimal Design of Demand-Responsive Feeder Transit Services with Passengers’ Multiple Time Windows and Satisfaction. Future Internet 2018, 10, 30 .

AMA Style

Bo Sun, Ming Wei, Senlai Zhu. Optimal Design of Demand-Responsive Feeder Transit Services with Passengers’ Multiple Time Windows and Satisfaction. Future Internet. 2018; 10 (3):30.

Chicago/Turabian Style

Bo Sun; Ming Wei; Senlai Zhu. 2018. "Optimal Design of Demand-Responsive Feeder Transit Services with Passengers’ Multiple Time Windows and Satisfaction." Future Internet 10, no. 3: 30.

Original articles
Published: 27 November 2017 in Transportation Planning and Technology
Reads 0
Downloads 0

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.

ACS Style

Zhaoming Chu; Hui Chen; Lin Cheng; Senlai Zhu; Chao Sun. A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria. Transportation Planning and Technology 2017, 41, 211 -228.

AMA Style

Zhaoming Chu, Hui Chen, Lin Cheng, Senlai Zhu, Chao Sun. A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria. Transportation Planning and Technology. 2017; 41 (2):211-228.

Chicago/Turabian Style

Zhaoming Chu; Hui Chen; Lin Cheng; Senlai Zhu; Chao Sun. 2017. "A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria." Transportation Planning and Technology 41, no. 2: 211-228.

Journal article
Published: 02 August 2017 in Sensors
Reads 0
Downloads 0

Most existing network sensor location problem (NSLP) models are designed to identify the number of sensors with fixed costs and installation locations, and sensors are assumed to be installed permanently. However, sometimes sensors are carried by individuals to collect traffic data measurements manually at fixed locations. Hence, their duration of operation for which traffic data measurements are collected is limited, and their costs are not fixed as they are correlated with the duration of operation. This paper proposes a NSLP model that integrates optimal heterogeneous sensor deployment and operation strategies for the dynamic O-D demand estimates under budget constraints. The deployment strategy consists of the numbers of link and node sensors and their installation locations. The operation strategy includes sensors’ start time and duration of operation, which has not been addressed in previous studies. An algorithm is developed to solve the proposed model. Numerical experiments performed on a network from a part of Chennai, India show that the proposed model can identify the optimal heterogeneous sensor deployment and operation strategies with the maximum dynamic O-D demand estimation accuracy.

ACS Style

Senlai Zhu; Yuntao Guo; Jingxu Chen; Dawei Li; Lin Cheng. Integrating Optimal Heterogeneous Sensor Deployment and Operation Strategies for Dynamic Origin-Destination Demand Estimation. Sensors 2017, 17, 1767 .

AMA Style

Senlai Zhu, Yuntao Guo, Jingxu Chen, Dawei Li, Lin Cheng. Integrating Optimal Heterogeneous Sensor Deployment and Operation Strategies for Dynamic Origin-Destination Demand Estimation. Sensors. 2017; 17 (8):1767.

Chicago/Turabian Style

Senlai Zhu; Yuntao Guo; Jingxu Chen; Dawei Li; Lin Cheng. 2017. "Integrating Optimal Heterogeneous Sensor Deployment and Operation Strategies for Dynamic Origin-Destination Demand Estimation." Sensors 17, no. 8: 1767.

Journal article
Published: 01 February 2017 in Physica A: Statistical Mechanics and its Applications
Reads 0
Downloads 0
ACS Style

Jingxu Chen; Zhibin Li; Hang Jiang; Senlai Zhu; Wei Wang. Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation. Physica A: Statistical Mechanics and its Applications 2017, 468, 880 -891.

AMA Style

Jingxu Chen, Zhibin Li, Hang Jiang, Senlai Zhu, Wei Wang. Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation. Physica A: Statistical Mechanics and its Applications. 2017; 468 ():880-891.

Chicago/Turabian Style

Jingxu Chen; Zhibin Li; Hang Jiang; Senlai Zhu; Wei Wang. 2017. "Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation." Physica A: Statistical Mechanics and its Applications 468, no. : 880-891.

Research article
Published: 05 December 2016 in Discrete Dynamics in Nature and Society
Reads 0
Downloads 0

A boundedly rational user equilibrium model with restricted unused routes (R-BRUE) considering the restrictions of both used route cost and unused route cost is proposed. The proposed model hypothesizes that for each OD pair no traveler can reduce his/her travel time by an indifference band by unilaterally changing route. Meanwhile, no route is unutilized if its travel time is lower than sum of indifference band and the shortest route cost. The largest and smallest used route sets are defined using mathematical expression. We also show that, with the increase of the indifference band, the largest and smallest used route sets will be augmented, and the critical values of indifference band to augment these two path sets are identified by solving the mathematical programs with equilibrium constraints. Based on the largest and smallest used route sets, the R-BRUE route set without paradoxical route is generated. The R-BRUE solution set can then be obtained by assigning all traffic demands to the corresponding generated route set. Various numerical examples are also provided to illustrate the essential ideas of the proposed model and structure of R-BRUE route flow solution set.1. IntroductionPerfect rationality is widely used in studying traditional transportation network models in which traveler always chooses the shortest (i.e., least utility) route, such as user equilibrium (UE [1]) and stochastic user equilibrium (SUE [2]) traffic assignment models. However, travelers may not always choose shortest route due to lack of perfect travel information; incapability of obtaining the shortest route with the complex traffic situations; and certain “inertia” in decision making. Therefore people do not always choose the route with the maximum utility. They tend to seek a satisfactory route instead.In the literature of evaluating habitual routes in route choice behavior, only 30% of respondents from Boston [3], 59% from Cambridge, Massachusetts [4], and 86.8% from Turin, Italy [5] chose the shortest routes. Based on GPS studies, Zhu [6] found that 90% of subjects in the Minneapolis-St. Paul region choose routes one-fifth longer than average commute time. All findings above revealed that people do not usually take the shortest routes and the used routes generally have higher costs than shortest ones.It is more practical that traveler is boundedly rational (BR); traveler will not change his/her route if his/her travel time is a little longer than the shortest route. A series of experiments were conducted to empirically validate bounded rationality [7–13]. The results showed that, in the repeated learning process, commuters would not change their routes unless the difference between preferred arrival time and actual arrival time exceeded a threshold. And boundedly rational route choice modeling observed from experiments provided a valid description of actual commuter daily behavior.Simon, in 1957 [14], first proposed the notion of bounded rationality. And in 1987 [7], Mahmassani and Chang introduced it to traffic modeling. Since then, bounded rationality has received considerable attention in various transportation models, such as traffic safety [15], transportation planning [16, 17], traffic policy making [18–20], traffic assignment, and network design [21–28]. All these studies indicated that traveler is boundedly rational in his/her decision-making process.Boundedly rational user equilibrium (BRUE) is a network state such that travelers can take any route whose travel time is within a threshold of the shortest route time [22, 23, 25–28]. Such a threshold is phrased by Mahmassani and Chang [7] as “indifference band.” In other words, no one can reduce his/her travel time by an indifference band by unilaterally changing his/her route. The indifference band is estimated from either laboratory experiment data or a behavioral study of road users (e.g., by surveys [7, 29]). By introducing indifference band for each OD pair, the BRUE relaxes UE assumption that travelers only take the shortest routes at equilibrium.However, unlike the conventional UE model, the traffic flow under BRUE may not utilize any shortest or least-cost route; in another word the unused route cost may be lower than the used one. For example, the route flows are 0, 5, and 7 for three different routes on one OD pair, and the travel times are 10, 12, and 13, respectively. If the indifference band is 3, the above route flow solution is a BRUE solution. From the behavioral point of view, one might question the plausibility of this that the least travel time route has no traffic on it. Therefore, to make the model become behavioral more defensible, not only the used route cost should be restricted, but also the unused route cost should be restricted.Uncertainties are unavoidable in transportation systems and make people become boundedly rational. Travelers do not know exactly the time that they arrive at the destination due to the travel time variability which is made by uncertainties. However, in many cases (such as going to work, having a meeting, and catching the train), travelers care more about arrive time than travel time; no one wants to be late; thus the largest and smallest route sets exist in travels’ trip process.This paper makes contributions in three major areas: considering both the restrictions of used route cost and unused route cost in the route decision process, we present a boundedly rational user equilibrium model with restricted unused routes (R-BRUE). This new model hypothesizes that for each OD pair no traveler can reduce his/her travel time by an indifference band by unilaterally changing route. Meanwhile, no route is unutilized if its travel time is lower than sum of indifference band and the shortest route cost. We propose the largest and smallest used route sets which can be used to generate the used route set of R-BRUE model. These two used route sets are defined as the union and intersection of all R-BRUE solution set patterns, respectively. And we develop two mathematical programs (MP) with equilibrium constraint to solve the critical values which is used to augment the largest and smallest used route sets.The remainder of the paper is organized as follows. In Section 2, -R-BRUE ( denotes the indifference band) is defined and its mathematical formulation is established. In Section 3, the largest and smallest -used route sets are defined, and their properties are studied. In Section 4, -R-BRUE route set without paradoxical route is generated. In Section 5, -R-BRUE route flow set without paradoxical route is constructed, and some examples are presented to illustrate the essential ideas of proposed model and the structure of R-BRUE route flow solution set. Finally, some conclusions and future work are provided.2. Definition of ε-R-BRUE and Mathematical FormulationIn this section, we propose -boundedly rational user equilibrium model with restricted unused routes (R-BRUE) and the mathematical formulation of proposed model.2.1. Definition of ε-R-BRUEConsider a transportation network , where and denote the sets of nodes and links, respectively. Let denote the set of OD pairs for which travel demand is generated between OD pair , and let denote the traffic flow on route , where is the set of routes connecting OD pair and all constitute . The feasible route flow set is to assign the traffic demand on the feasible routes: . Below is formal definition of -boundedly rational user equilibrium with restricted unused routes (R-BRUE).Definition 1. -boundedly rational user equilibrium with restricted unused routes (-R-BRUE) is a network state such that the travel cost of all used route is less than or equal to the sum of given indifference band and the shortest route cost; meanwhile, the travel cost of the unused route is greater than or equal to the sum of and the shortest route cost; that is,where is the vector form of traffic flow and is the route cost function on route between OD pair .We should point out that boundedly rational user equilibrium (BRUE) model only considers which do not take the cost of unused route into consideration. We first use to restrict the “irrational solutions.”Equation (1) gives a necessary condition judging whether a flow pattern is R-BRUE and is equivalent to the following condition:In other words, a used route has lower cost than an unused one, which is the same as that in the UE (user equilibrium) setting. When for each , the R-BRUE definition is reduced to the UE problem.Theorem 2. Any -R-BRUE solution is also a -BRUE solution. -BRUE solution may not, however, necessarily fulfill -R-BRUE conditions.Proof. let be a route flow pattern to -R-BRUE model. Then, for , hold for all and ; that is, , , , which satisfies -BRUE model.For the converse situation, suppose that a flow allocation satisfies -BRUE conditions and in addition has an unused route which has a cost less than the sum of and the shortest route. Then -R-BRUE conditions are violated.Usually -R-BRUE is nonunique. Denote a set containing all route flow patterns satisfying Definition 1 as -R-BRUE route flow solution set:Theorem 3. If the link cost function is continuous, -R-BRUE solution is nonempty.Proof. First, Patriksson [30] showed that, when the link cost function is continuous, UE solution exists. Let be one UE route flow pattern, and set , , where is a very small positive parameter. Let , when ,So is -R-BRUE solution (); that is, . Given the continuous link cost function, at least one -R-BRUE flow pattern exists, and therefore .2.2. R-BRUE Mathematical FormulationWe use slack variables to define R-BRUE mathematically. is a R-BRUE distribution if and only if there exists whose physical meaning is the minimum route cost for every such thatwhere is the traffic demand between OD pair . Note that when for all , (5) reduces to , which is the conventional UE conditions.3. Largest and Smallest ε-Used Route SetsIn this section, we give the definition of the large

ACS Style

Chao Sun; Menghui Li; Lin Cheng; Senlai Zhu; Zhaoming Chu. Boundedly Rational User Equilibrium with Restricted Unused Routes. Discrete Dynamics in Nature and Society 2016, 2016, 1 -11.

AMA Style

Chao Sun, Menghui Li, Lin Cheng, Senlai Zhu, Zhaoming Chu. Boundedly Rational User Equilibrium with Restricted Unused Routes. Discrete Dynamics in Nature and Society. 2016; 2016 ():1-11.

Chicago/Turabian Style

Chao Sun; Menghui Li; Lin Cheng; Senlai Zhu; Zhaoming Chu. 2016. "Boundedly Rational User Equilibrium with Restricted Unused Routes." Discrete Dynamics in Nature and Society 2016, no. : 1-11.

Conference paper
Published: 29 June 2016 in CICTP 2016
Reads 0
Downloads 0

There are many uncertain factors in the demand and supply of urban traffic network. Transportation network flexibility can describe the road network’s ability to process or absorb changes caused by uncertainty, and can be used for transportation network performance evaluation. Based on the concept of reserve capacity, two assessment methods of transportation network capacity flexibility were analyzed. The first method only considers the link capacity constraints; the second method, on the basis of the first method, considers the influence of level of service, this method has more application value because it cannot only get the network biggest reserve capacity flexibility like the first method, but also get the network capacity flexibility of each level of service. Finally, a specific example of the two methods for validation and analysis was given.

ACS Style

Senlai Zhu; Lin Cheng; Xiaokun Wang; Yu Zhang; Ying-En Ge; Youfang Huang. Transportation Network Flexibility Assessment Based on Reserve Capacity. CICTP 2016 2016, 2230 -2240.

AMA Style

Senlai Zhu, Lin Cheng, Xiaokun Wang, Yu Zhang, Ying-En Ge, Youfang Huang. Transportation Network Flexibility Assessment Based on Reserve Capacity. CICTP 2016. 2016; ():2230-2240.

Chicago/Turabian Style

Senlai Zhu; Lin Cheng; Xiaokun Wang; Yu Zhang; Ying-En Ge; Youfang Huang. 2016. "Transportation Network Flexibility Assessment Based on Reserve Capacity." CICTP 2016 , no. : 2230-2240.

Journal article
Published: 01 November 2015 in Transportation Research Part E: Logistics and Transportation Review
Reads 0
Downloads 0

This paper develops a mathematical model for the optimal stopping design of limited-stop bus service, which allows each bus vehicle to skip some stops. To better reflect the reality, this paper considers the vehicle capacity and stochastic travel time. Also, vehicles are all allowed to skip stops whereas any stop is not allowed to be skipped by two consecutive vehicles. A hybrid artificial bee colony (ABC) and Monte Carlo method is developed to solve the optimal stopping strategy. Finally, the model and solution method are validated by a numerical example, and a sensitivity analysis is performed on the passenger demand.

ACS Style

Jingxu Chen; Zhiyuan Liu; Senlai Zhu; Wei Wang. Design of limited-stop bus service with capacity constraint and stochastic travel time. Transportation Research Part E: Logistics and Transportation Review 2015, 83, 1 -15.

AMA Style

Jingxu Chen, Zhiyuan Liu, Senlai Zhu, Wei Wang. Design of limited-stop bus service with capacity constraint and stochastic travel time. Transportation Research Part E: Logistics and Transportation Review. 2015; 83 ():1-15.

Chicago/Turabian Style

Jingxu Chen; Zhiyuan Liu; Senlai Zhu; Wei Wang. 2015. "Design of limited-stop bus service with capacity constraint and stochastic travel time." Transportation Research Part E: Logistics and Transportation Review 83, no. : 1-15.

Research article
Published: 22 March 2015 in Mathematical Problems in Engineering
Reads 0
Downloads 0

Public bicycle acts as a seamless feeder mode in combination with the citywide public transit, as well as a competitor for the inner-city short trips. The primary objective of this study is to address the layout planning of public bicycle system within the attracted scope of a metro station. Based on the land use function, population, and bicycle mode share, bicycle rental stations are divided into three types, namely, the metro station, district station, and resident station, and later the quantity of bicycle facilities in each rental station is estimated. Then, the service stations are selected from these bicycle rental stations to provide the service of periodical bicycle redistribution. An improved immune algorithm is proposed to determine the number and locations of service stations and the optimal route options for the implement of redistributing strategy. Finally, a case study of Nanjing Tianyin Road metro station is conducted to illustrate the proposed model and clarify some of its implementation details.

ACS Style

Jingxu Chen; Xuewu Chen; Hang Jiang; Senlai Zhu; Xiaowei Li; Zhibin Li. Determining the Optimal Layout Design for Public Bicycle System within the Attractive Scope of a Metro Station. Mathematical Problems in Engineering 2015, 2015, 1 -8.

AMA Style

Jingxu Chen, Xuewu Chen, Hang Jiang, Senlai Zhu, Xiaowei Li, Zhibin Li. Determining the Optimal Layout Design for Public Bicycle System within the Attractive Scope of a Metro Station. Mathematical Problems in Engineering. 2015; 2015 (2134):1-8.

Chicago/Turabian Style

Jingxu Chen; Xuewu Chen; Hang Jiang; Senlai Zhu; Xiaowei Li; Zhibin Li. 2015. "Determining the Optimal Layout Design for Public Bicycle System within the Attractive Scope of a Metro Station." Mathematical Problems in Engineering 2015, no. 2134: 1-8.

Research article
Published: 22 April 2014 in Discrete Dynamics in Nature and Society
Reads 0
Downloads 0

This paper analyzes the activity-trip chaining behavior of urban low-income populations in Nanjing, China, based on a specific travel survey of low-income residents of Nanjing city (2010), and the database of residents travel survey of Nanjing city (2009). Individual’s information of activity participation and trip chains is extracted from the daily travel diary and matched with individual and household characteristics. On top of correlation analysis and normalization process, using the software AMOS, two structural equation models are formulated to analyze the relationship among individuals’ sociodemographics, activity duration, and trip chains of low-income populations and non-low-income populations, respectively. Seven household characteristics and six individual characteristics are chosen as the exogenous variables, while 4 indices of activity duration and 4 indices of trip chains are sleeted as the endogenous variables. The result shows that the activity-travel behavior of urban low-income populations is quite unique, which offers promising insights into activity-trip chaining behavior of the poor and extends the need to crafting effective transportation policies specifically for urban low-income populations in developing countries.

ACS Style

Zhaoming Chu; Hui Chen; Lin Cheng; Xuewu Chen; Senlai Zhu. Activity-Trip Chaining Behavior of Urban Low-Income Populations in Nanjing, China: A Structural Equations Analysis. Discrete Dynamics in Nature and Society 2014, 2014, 1 -11.

AMA Style

Zhaoming Chu, Hui Chen, Lin Cheng, Xuewu Chen, Senlai Zhu. Activity-Trip Chaining Behavior of Urban Low-Income Populations in Nanjing, China: A Structural Equations Analysis. Discrete Dynamics in Nature and Society. 2014; 2014 (1927):1-11.

Chicago/Turabian Style

Zhaoming Chu; Hui Chen; Lin Cheng; Xuewu Chen; Senlai Zhu. 2014. "Activity-Trip Chaining Behavior of Urban Low-Income Populations in Nanjing, China: A Structural Equations Analysis." Discrete Dynamics in Nature and Society 2014, no. 1927: 1-11.

Research article
Published: 13 April 2014 in Discrete Dynamics in Nature and Society
Reads 0
Downloads 0

This paper presents a Bayesian network model for estimating origin-destination matrices. Most existing Bayesian methods adopt prior OD matrixes, which are always troublesome to be obtained. Since transportation systems normally have stored large amounts of historical link flows, a Bayesian network model using these prior link flows is proposed. Based on some observed link flows, the estimation results are updated. Under normal distribution assumption, the proposed Bayesian network model considers the level of total traffic flow, the variability of link flows, and the violation of the traffic flow conservation law. Both the point estimation and the corresponding probability intervals can be provided by this model. To solve the Bayesian network model, a specific procedure which can avoid matrix inversion is proposed. Finally, a numerical example is given to illustrate the proposed Bayesian network method. The results show that the proposed method has a high accuracy and practical applicability.

ACS Style

Lin Cheng; Senlai Zhu; Zhaoming Chu; Jingxu Cheng. A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows. Discrete Dynamics in Nature and Society 2014, 2014, 1 -9.

AMA Style

Lin Cheng, Senlai Zhu, Zhaoming Chu, Jingxu Cheng. A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows. Discrete Dynamics in Nature and Society. 2014; 2014 (2):1-9.

Chicago/Turabian Style

Lin Cheng; Senlai Zhu; Zhaoming Chu; Jingxu Cheng. 2014. "A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows." Discrete Dynamics in Nature and Society 2014, no. 2: 1-9.