提升学生实践能力的卓越课程《交通规划》教学改革研究

列入"卓越工程师计划"的交通工程专业本科生专业核心课程的教学方法探索对于培养卓越工程师综合能力具有重要作用。本文根据《交通规划》课程多年的教学经验,提出切合卓越工程师人才培养目标——"知识、能力、人格"的具体教学实施方法。在资深教授正确、完整传授本学科基本知识体系的前提下,通过小班化教学方式,由副教授、讲师组成的青年教师团队引导学生分析实际案例,增强互动讨论环节,充分调动学生积极性,鼓励学生提出自己对于交通问题的见解;通过"交通规划"与"交通规划课程设计"18个实践学时的捆绑教学,增强对学生理论与实践结合的专业训练,切实提高学生学习的主动性,获得良好教学效果。

《交通规划与管理丛书》由科学出版社出版发行

东南大学交通运输规划与管理国家重点学科通过对该学科所承担的多项国家自然科学基金项目及国家科技攻关项目的研究成果进行总结，由科学出版社以“交通规划与管理丛书’的形式出版了一套(五本)系列学术专著。该系列专著具有以下主要特点：

Research on a non-linear chaotic prediction model for urban traffic flow

In order to solve serious urban transport problems, according to the proved chaotic characteristic of traffic flow, a non linear chaotic model to analyze the time series of traffic flow is proposed. This model reconstructs the time series of traffic flow in the phase space firstly, and the correlative information in the traffic flow is extracted richly, on the basis of it, a predicted equation for the reconstructed information is established by using chaotic theory, and for the purpose of obtaining the optimal predicted results, recognition and optimization to the model parameters are done by using genetic algorithm. Practical prediction research of urban traffic flow shows that this model has famous predicted precision, and it can provide exact reference for urban traffic programming and control.

Alternatives of Strategic Environmental Assessment for Road Traffic Development Planning——Case of Changchun City,China

On analyzing the achievement of the goal in the modem urban road traffic development planning, the alternative of Strategic Environmental Assessment for urban traffic planning should include the basic scheme, the extended scheme and the environmental protection scheme. This study from different perspectives designed the alternatives for Changchun＇s county-level road and urban road system planning, and used the method of System Dynamics to simulate, optimize and analyze those alternatives. Thereafter, some methods including the correlation function method were used to comprehensively assess and rank those alternatives for recommending two best alternatives with the consideration to the indicators, such as the total emission amount of CO, the total emission amount of nitrogen oxides, the noise value, the road construction cost, the fossil oil consumption and the traffic capacity. The result showed that the study would provide substantial supports for decision-makers to make more scientific decisions and promote the sustainable urban traffic in Changchun City.

Air Route Network Generation Based on Traffic Assignment

Air route network is the carrier of air traffic flow,and traffic assignment is a method to verify the rationality of air route network structure.Therefore,air route network generation based on traffic assignment has been becoming the research focus of airspace programming technology.Based on link prediction technology and optimization theory,a bi-level programming model is established in the paper.The model includes an upper level of air route network generation model and a lower level of traffic assignment model.The air route network structure generation incorporates network topology generation algorithm based on link prediction technology and optimal path search algorithm based on preference,and the traffic assignment adopts NSGA-Ⅲalgorithm.Based on the Python platform NetworkX complex network analysis library,a network of 57 airports,383 nodes,and 635 segments within China Airspace Beijing and Shanghai Flight Information Regions and 187975 sorties of traffic are used to simulate the bilevel model.Compared with the existing air route network,the proposed air route network can decrease the cost by 50.624%,lower the flight conflict coefficient by 33.564%,and reduce dynamic non-linear coefficient by 7.830%.

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.

Weighted Time-Based Global Hierarchical Path Planning in Dynamic Environment

A weighted time-based global hierarchical path planning method is proposed to obtain the global optimal path from the starting point to the destination with time optimal control. First, the grid-or graph-based modeling is performed and the environment is divided into a set of grids or nodes. Then two time-based features of time interval and time cost are presented. The time intervals for each grid are built, during each interval the condition of the grid remains stable, and a time cost of passing through the grid is defined and assigned to each interval. Furthermore, the weight is introduced for taking both time and distance into consideration, and thus a sequence of multiscale paths with total time cost can be achieved. Experimental results show that the proposed method can handle the complex dynamic environment, obtain the global time optimal path and has the potential to be applied to the autonomous robot navigation and traffic environment.

One-Dimensional Traffic Model to Consider Priority of the Stochastic Deceleration

A one-dimensional cellular automaton model of traffic flow is proposed to introduce the different delay probabilities in the steps of rules and the stochastic deceleration prior to the deterministic one when the anticipation velocity of vehicle is larger than the headway. The fundamental diagram shows the capacity of road more approaches to the observed data compared with that by the NaSch model. Moreover, the model is able to reproduce the complicated behavior of the real traffic, such as the metastability state, the separation of different phases and the effect of hysteresis.It is concluded that the order arrangement of the stochastic deceleration and deterministic acceleration has indeed remarkable effect on traffic flow and the modification presented in this paper is reasonable and realistic.

An optimization model of UAV route planning for road segment surveillance

Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization model of planning UAV route for road segment surveillance was proposed,which aimed to minimize UAV cruise distance and minimize the number of UAVs used.Then,an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem.At last,a UAV flight experiment was conducted to test UAV route planning effect,and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning.The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%,respectively.Additionally,shortening or extending the length of road segments has different impacts on UAV route planning.

Multi-objective evolutionary approach for UAV cruise route planning to collect traffic information

Unmanned aerial vehicle(UAV)was introduced as a novel traffic device to collect road traffic information and its cruise route planning problem was considered.Firstly,a multi-objective optimization model was proposed aiming at minimizing the total cruise distance and the number of UAVs used,which used UAV maximum cruise distance,the number of UAVs available and time window of each monitored target as constraints.Then,a novel multi-objective evolutionary algorithm was proposed.Next,a case study with three time window scenarios was implemented.The results show that both the total cruise distance and the number of UAVs used continue to increase with the time window constraint becoming narrower.Compared with the initial optimal solutions,the optimal total cruise distance and the number of UAVs used fall by an average of 30.93% and 31.74%,respectively.Finally,some concerns using UAV to collect road traffic information were discussed.

Public Transit Connectivity Measures and Analysis of Weak Segments

Bus and any other public transit connectivity issues facilitate an understanding of the importance of transit planning in enhancing existing or new transit services. Improving transit connectivity is one of the most vital tasks in transit-operations planning. A poor connection can cause some passengers to stop using the transit service. Service-design criteria always contain postulates to improve routing and scheduling coordination （intra- and inter-agency transfer centers/points and synchronized/timed transfers）. Ostensibly the lack of well-defined connectivity measures precludes the weighing and quantifying of the result of any coordination effort. This work provides an initial methodological framework and concepts for （1） quantifying transit connectivity measures and （2） directions and tools for detecting weak segments in inter-route and inter-modal chains （paths） for possible revisions/changes.

Management Procedures for Data Collected via Intelligent Transportation Systems

Addressing transportation planning, operation and investment challenges requires increasingly sophisticated data and information management strategies. ITS （intelligent transportation systems） and CV （connected vehicle） technologies represent a new approach to capturing and using needed transportation data in real time or near real time. In the case of Michigan, several ITS programs have been launched successfully, but independently of each other. The objective of this research is to evaluate and assess all important factors that will influence the collection, management and use of ITS data, and recommend strategies to develop integrated, dynamic and adaptive data management systems for state transportation agencies.

Pedestrianisation and Parking Policy as a Solution towards Green Transport Plan： A Case Study of Zagreb

Strategy of development trends in this moment and at this stage of the traffic comes from understanding the possibilities of the implementation of measures to raise the quality of movement and life in the city. It also includes planning and implementation of targeted interventions in the transport network or facilities. Mobility is a complex process in the area, starting from the departure from the apartment, using various means of transportation, a number of activities in different goals until to return to the location of the apartment. It thus requires extensive transport infrastructure in the form of walkways, bicycle paths, street and railway network. At the same time, reshaping of public transport facilities is needed in which the pedestrian, biker and green concept shall be the main elements of the new spatial conditions. Pedestrian zones development in the city means to create pedestrian areas and green islands in all the places in the city where possible. This process is essential for the transformation of public spaces, in particular, transport corridors. To accomplish the concept of the green transport plan, the need for change in the parking policy is emphasized. This should be an integral part of the city planning and should go hand in hand with the traffic policy.

Optimal paths planning in dynamic transportation networks with random link travel times

A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area,China

Road network is a corridor system that interacts with surrounding landscapes,and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use.This study investigates the relationships between road centrality and landscape patterns in the Wuhan Metropolitan Area,China.The densities of centrality measures,including closeness,betweenness,and straightness,are calculated by kernel density estimation(KDE).The landscape patterns are characterized by four landscape metrics,including percentage of landscape(PLAND),Shannon′s diversity index(SHDI),mean patch size(MPS),and mean shape index(MSI).Spearman rank correlation analysis is then used to quantify their relationships at both landscape and class levels.The results show that the centrality measures can reflect the hierarchy of road network as they associate with road grade.Further analysis exhibit that as centrality densities increase,the whole landscape becomes more fragmented and regular.At the class level,the forest gradually decreases and becomes fragmented,while the construction land increases and turns to more compact.Therefore,these findings indicate that the ability and potential applications of centrality densities estimated by KDE in quantifying the relationships between roads and landscapes,can provide detailed information and valuable guidance for transportation and land-use planning as well as a new insight into ecological effects of roads.

Model and algorithm of optimizing alternate traffic restriction scheme in urban traffic network

An optimization model and its solution algorithm for alternate traffic restriction(ATR) schemes were introduced in terms of both the restriction districts and the proportion of restricted automobiles. A bi-level programming model was proposed to model the ATR scheme optimization problem by aiming at consumer surplus maximization and overload flow minimization at the upper-level model. At the lower-level model, elastic demand, mode choice and multi-class user equilibrium assignment were synthetically optimized. A genetic algorithm involving prolonging codes was constructed, demonstrating high computing efficiency in that it dynamically includes newly-appearing overload links in the codes so as to reduce the subsequent searching range. Moreover,practical processing approaches were suggested, which may improve the operability of the model-based solutions.

Research on Intelligent Transportation System and Its Key Technology based on IOT

This paper presents a design scheme of intelligent transportation system based on the Internet of things. First, the paper elaborated the related technical and functional demand of intelligent traffic system, designed the gateway level model and the overall project. Then, we design gateway hardware circuit according to the overall plan, and design the gateway application software according to the functional requirements. Through the experiment and simulation results show that, the intelligent transportation system gateway based on Internet of things is ability to create ZigBee network through the way of wireless access, GPRS network, Ethernet access based on the wired way, to realizes multimode access, multi-protocol conversion gateway, ad hoc network functions.

Transportation problem: A special case for linear programing problems in mining engineering

In real world applications the supply, the demand and the transportation cost per unit of the quantities in a transportation problem are hardly specified precisely because of the changing economic and environmental conditions. It is also important that the time required for transportation should be minimum. In this paper a method has been proposed for the minimization of transportation costs. Supply and transportation costs per unit of the quantities are also determined. The present study was carried out to evaluate the quality of gravel to know its suitability for aggregate (raw material for concrete and road). The samples of gravel were analyzed for petrographic, physical, mechanical and chemical properties. Samples were categorized as quartzite group and carbonate group according to ASTM standard 295. Among these, samples of quartzite group were found dominant. The petrography examination of gravels which was carried out constituted of opal, tridymite, chalcedony, crystobalite and alkali carbonates rocks. Those minerals react with alkalis in cement leading to expansion and cracking of concrete. Other components such as sulfides, sulfates, halites, iron oxides, clay minerals and anhydrites are examined, which might be present as coating and impurities. The present study indicated that all samples are suitable for concrete making and obtain the optimum solution for transporting these materials from quarries to cities with minimum cost according to Egyptian Code.

A multi-objective model for cordon-based congestion pricing schemes with nonlinear distance tolls

Congestion pricing is an important component of urban intelligent transport system.The efficiency,equity and the environmental impacts associated with road pricing schemes are key issues that should be considered before such schemes are implemented.This paper focuses on the cordon-based pricing with distance tolls,where the tolls are determined by a nonlinear function of a vehicles' travel distance within a cordon,termed as toll charge function.The optimal tolls can give rise to:1) higher total social benefits,2) better levels of equity,and 3) reduced environmental impacts(e.g.,less emission).Firstly,a deterministic equilibrium(DUE) model with elastic demand is presented to evaluate any given toll charge function.The distance tolls are non-additive,thus a modified path-based gradient projection algorithm is developed to solve the DUE model.Then,to quantitatively measure the equity level of each toll charge function,the Gini coefficient is adopted to measure the equity level of the flows in the entire transport network based on equilibrium flows.The total emission level is used to reflect the impacts of distance tolls on the environment.With these two indexes/measurements for the efficiency,equity and environmental issues as well as the DUE model,a multi-objective bi-level programming model is then developed to determine optimal distance tolls.The multi-objective model is converted to a single level model using the goal programming.A genetic algorithm(GA) is adopted to determine solutions.Finally,a numerical example is presented to verify the methodology.

A surrogate-based optimization algorithm for network design problems

Network design problems （NDPs） have long been regarded as one of the most challenging problems in the field of transportation planning due to the intrinsic non-convexity of their bi-level programming form. Furthermore, a mixture of continuous/discrete decision variables makes the mixed network design problem （MNDP） more complicated and difficult to solve. We adopt a surrogate-based optimization （SBO） framework to solve three featured categories of NDPs （continuous, discrete, and mixed-integer）. We prove that the method is asymptotically completely convergent when solving continuous NDPs, guaranteeing a global optimum with probability one through an indefinitely long run. To demonstrate the practical performance of the proposed framework, numerical examples are provided to compare SBO with some existing solving algorithms and other heuristics in the literature for NDP. The results show that SBO is one of the best algorithms in terms of both accuracy and efficiency, and it is efficient for solving large-scale problems with more than 20 decision variables. The SBO approach presented in this paper is a general algorithm of solving other optimization problems in the transportation field.