Case Study of Transportation Planning Based on Land Development Patterns in the Great Chengdu Area

Traffic is a function of land use. Based on the understanding of mutual influences between transportation investment and land development, transportation corridors of various levels in Great Chengdu Area （GCA） were investigated. Trip generation was predicted based on population expansion, and trip attraction was estimated based on land use intensity coefficient. Lane assignment of transportation corridors with case studies is expected with two-way-six-lane routes connecting county-cities, two-way-four-lane routes connecting new towns in plane area, and two-way-two-lane connecting new towns in hilly area and prime villages.

Research on Urban Transportation Planning Strategies in China Under the“New Normal”

In order to explore the development direction and strategy of China’s urban transportation planning,drive the development of urban transportation and urban economic progress,as well as respond to the changing trends and challenges of the market under the“new normal,”this paper first analyzes the current situation of China’s transportation industry under the“new normal,”investigates the relationship between transportation and urban planning,and then proposes strategies for China’s urban transportation development and planning as reference.

Social media as passive geo-participation in transportation planning-how effective are topic modeling&sentiment analysis in comparison with citizen surveys?

We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion.Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city.With such pressures on existing public transportation systems,this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services.This research forms a case study of the use of passively collected forms of big data in cities-focusing on Sydney,Australia.Firstly,it examines social media data(Tweets)related to public transport performance.Secondly,it joins this to longitudinal big data-delay information continuously broadcast by the network over a year,thus forming hundreds of millions of data artifacts.Topics,tones,and sentiment are modeled using machine learning and Natural Language Processing(NLP)techniques.These resulting data,and models,are compared to opinions derived from a citizen survey among users.The validity of such data and models versus the intentions of users,in the context of systems that monitor and improve transport performance,are discussed.As such,key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques.

Using structured systems analysis to design an integrated system for transport planning and environmental analysis

This paper applies Yourdon's (1989) structured systems analysis techniques to transport planning, and the environmental analysis of transport plans. It is usual for planners to treat these activities as separate processes or 'systems'. Six serious shortcomings are identified in prevailing approaches to accounting for the environmental impacts of transport plans. The application of systems analysis has elucidated opportunities for overcoming these problems by integrating the two processes. The paper highlights the benefits of using these methods to direct research into, and development of, an integrated transport planning- environmental analysis system. Techniques applied are data flow diagrams, a Venn diagram and an entity-relationship diagram. Significant potential exists for integration within a geographic information system(GIS), although adoption of integrated methods by transport planners is likely to be incremental. Research confirms the usefulness of systems analysis in guiding the development of a GIS application to accommodate integrated transport planning and environmental analysis. Systems analysis also facilitates more careful and effective design of the databases underlying GIS analysis.

Land development suitability analysis for transport planning evaluation and optimization in mountainous ecological region

Transportation planning is a critical component for creating an orderly,intensive,and sustainable pattern of land development.By comprehensively considering the potential and suitability of transport construction,a comprehensive method combining resources and environmental carrying capacity(RECC)and land development suitability(LDS)was developed by using techniques of GIS,analytic hierarchy process(AHP)and threedimensional magic cube.Taking Aba prefecture in Sichuan Province of Southwest China as a case study,LDS for transportation was analyzed from three aspects,including overall planning layout,different transport modes,and transportation projects.The results showed that the transport planning scales of most counties in Aba were suitable,and the order of LDS of different transport modes was railway>highway=superhighway>tourism track,which already included 42 new transportation projects.We found that two counties(Maoxian County and Jiuzhaigou County)should improve the ecological protection level of transportation,in which the railway network construction should be encouraged,and some transportation projects with low LDS should be postponed or constructed harmlessly.We suggest the combination of RECC and LDS for transportation could enhance the territorial space optimization and sustainable transport construction.

TRANSPORT PLANNING FOR NEW TOWN DEVELOPMENT:EXPERIENCE OF HONG KONG

Since the 1960s, Hong Kongs new towns have been builton the assumption that they could be socially and economically selfcontained entities. A study of the linkage between three new townsand metropolitan area confirms that substantial commuting trips arestill made. The new towns serve as dormitories for people workingin the metropolitan area. The commuters' reliance on publictransport is significant. The towns are thus far from self-containedeven aller 20 years of development. The public transport network,trip rate, peak factor, purpose, mode choice, costs and journey time,are signilicantly different from those originally estimated. Thesemay be related to distance from the metropolitan area,theavailability of modes, the structure of the public transport netwrk,and changs in the economical structure of Hong Kong. lt suggeststhat the direct and indiscriminant importation of Westernplanning practice to plan new towns with an oriental socio-economicsetting deserves critical review.

Accuracy Assessment and Guidelines for Manual Traffic Counts from Pre-Recorded Video Data

Traffic count is the fundamental data source for transportation planning, management, design, and effectiveness evaluation. Recording traffic flow and counting from the recorded videos are increasingly used due to convenience, high accuracy, and cost-effectiveness. Manual counting from pre-recorded video footage can be prone to inconsistencies and errors, leading to inaccurate counts. Besides, there are no standard guidelines for collecting video data and conducting manual counts from the recorded videos. This paper aims to comprehensively assess the accuracy of manual counts from pre-recorded videos and introduces guidelines for efficiently collecting video data and conducting manual counts by trained individuals. The accuracy assessment of the manual counts was conducted based on repeated counts, and the guidelines were provided from the experience of conducting a traffic survey on forty strip mall access points in Baton Rouge, Louisiana, USA. The percentage of total error, classification error, and interval error were found to be 1.05 percent, 1.08 percent, and 1.29 percent, respectively. Besides, the percent root mean square errors (RMSE) were found to be 1.13 percent, 1.21 percent, and 1.48 percent, respectively. Guidelines were provided for selecting survey sites, instruments and timeframe, fieldwork, and manual counts for an efficient traffic data collection survey.

Research on key parameters of the Fatigue Arousal Zone in extra-long tunnels based on natural driving experiments

To effectively mitigate the short-term fatigue effects of driving in extra-long tunnels,this study conducted natural driving experiments in five extra-long tunnels of varying lengths and tunnel group sections.Utilizing data obtained from natural driving fatigue experiments,this study identified perclos P80,variable coefficient of pupil diameter,and acceleration as fatigue sensitivity indicators,determined through significance tests of difference and correlation analysis.This study employed an ordered multi-class Logistic model to investigate the factors that influence driving fatigue in extra-long tunnels.The most significant variable in the model was perclos P80,which served as an indicator for classifying and identifying fatigue levels in extra-long tunnels.Following this,a dimensionless quantitative metric,the Fatigue Driving Degree,was formulated,and the Threshold of Driving Fatigue was established.Using the quantitative framework for driving fatigue,this paper standardized the definition of the fatigue arousal zone in extra-long tunnels.The study analyzed the operational principles and validated the key parameters of the fatigue arousal zone in extra-long tunnels.These parameters encompass the placement location,length,form,and traffic induction design of the fatigue arousal zone.The research findings can serve as a theoretical reference for the development of fatigue arousal technology in extra-long highway tunnels in China.

Scheduling trains on railway network using random walk method

According to random walk, in this paper, we propose a new traffic model for scheduling trains on a railway network. In the proposed method, using some iteration rules for walkers, the departure and the arrival times of trains at each station are determined. We test the proposed method on an assumed railway network. The numerical simulations and the analytical results demonstrate that the proposed method provides an effective tool for scheduling trains. Some characteristic behaviours of train movement can be reproduced, such as train delay.

Building Evacuate Module for Urban Underground Passages: Subway Station in Turkey

The primary goal of crowd evacuation in urban underground passages or subways is to evacuate as many evacuees as possible to safe areas in the shortest time when emergency events occur. This paper chooses the underground passages of one metro in Istanbul, Turkey as research object, and uses a study method which combines by sites investigation, field test and computer simulation of the creating new software. It is called Building Evacuate Module software. We present a depth analysis of the related factors which include the number and width of passage, channelization setting and the number of pedestrians with the evacuation time. And the influential effect of public opinion is explained by using big data technology. In addition, pedestrians evacuation condition are recorded in three evacuation period, the morning peak, common and evening peak by the observation and statistic obtained with video, and build the model to simulate the change of evacuation time with pedestrians. So it reveals when the number of pedestrians reaches to more than 200, evacuation time increases significantly and the field experiment and simulation condition are consistent basically.

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.

Method of Generating Strategic Guidance Information for Driving Evacuation Flows to Approach Safety-Based System Optimal Dynamic Flows: Case Study of a Large Stadium

In previous evacuation flow planning, a system optimal dynamic traffic assignment(SODTA) did not consider the exogenous costs caused by potential traffic accidents. A traffic accident,which might occur as a result of traffic congestion, will impact an evacuation process because of accidentrelated delays experienced by the downstream vehicles. This paper establishes a safety-based SO-DTA linear programming model in which the generalized system cost incorporates both the travel time and the accident-related delay. The goal is to minimize the generalized system cost under the cell transmission setup. Furthermore, the authors provide strategic guidance information that considers both the objective of the decision maker and the route choice behavior of the evacuees. Mathematically,the authors propose an unconstrained non-linear programming model aimed at minimizing the gap between the safety-based flows and the stochastic real-world evacuation flows, to provide strategic travel time information to be published on variable message signs(VMS). In the case study, the authors found that the safety-based SO-DTA model can reduce congestion and improve the evacuation efficiency; the stochastic real-world evacuation flows, guided by strategic information, can approach the safety-based flows.

Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods

Traffic volume is an important parameter in most transportation planning applications. Low volume roads make up about 69% of road miles in the United States. Estimating traffic on the low volume roads is a cost-effective alternative to taking traffic counts. This is because traditional traffic counts are expensive and impractical for low priority roads. The purpose of this paper is to present the development of two alternative means of cost- effectively estimating traffic volumes for low volume roads in Wyoming and to make recommendations for their implementation. The study methodology involves reviewing existing studies, identifying data sources, and carrying out the model development. The utility of the models developed were then verified by comparing actual traffic volumes to those predicted by the model. The study resulted in two regression models that are inexpensive and easy to implement. The first regression model was a linear regression model that utilized pavement type, access to highways, predominant land use types, and population to estimate traffic volume. In verifying the model, an R^2 value of 0.64 and a root mean square error of 73.4% were obtained. The second model was a logistic regression model that identified the level of traffic on roads using five thresholds or levels. The logistic regression model was verified by estimating traffic volume thresholds and determining the percentage of roads that were accurately classified as belonging to the given thresholds. For the five thresholds, the percentage of roads classified correctly ranged from 79% to 88%. In conclusion, the verification of the models indicated both model types to be useful for accurate and cost-effective estimation of traffic volumes for low volume Wyoming roads. The models developed were recommended for use in traffic volume estimations for low volume roads in pavement management and environmental impact assessment studies.

THE SIMPLE BLOCK ITERATIVE ALGORITHM OF AN EXTENDED ENTROPY MODEL AND ITS CONVERGENCE

The paper discusses an extended entropy model for the prediction of trip amount and provides a method to solve it, called the simple block iterative algorithm, from the point of view of the system of nonlinear equations. Because the algorithm gives consideration to the characteristic of the model, it has better effect in our practice. The paper also studies the existence and uniqueness of the solution and convergence of the algorithm.