Modeling the Trip Distributions of Tourists Based on Trip Chain and Entropy-Maximizing Theory

Suburban tourist railway is an emerging transportation mode for tourism. Knowing the travel demand and trip distribution patterns of tourists is an important prerequisite to the planning and construction of suburban tourist railways. However, this issue has attracted very little research attention so far. Therefore, this paper proposes a forecasting model focused on the trip distribution of tourists who travel with the suburban tourist railway. Based on the analysis of the characteristics of tourists’ trips and the use of the trip chain method, the frequency, order, distance, and visiting volume of stay points of the trips of tourists have been intensively studied. Then, a tourist trip distribution forecasting model was built in this paper. It uses the Entropy-Maximizing theory to predict trip chain distribution probability and obtain the distribution of tourists within the city. A case study that takes the H city as an example was conducted to test the proposed model. The results of this case show that the output of the model can reflect the real trip distribution characteristics of tourists very well, which demonstrates the applicability and effectiveness of the proposed model.

Modelling Trip Distribution Using the Gravity Model and Fratar's Method

Trip Distribution is a difficult and significant model in the urban transportation planning process. This paper creates and assesses a satisfactory model of the trip distribution stage for the Nasiriyah city by using two models, Gravity and Fratar methods. A large sample was used for developing the model. The research methodology depends on discussing the theoretical fundamentals of the various methods for estimating the trips distribution and examining the suitability of these fundamentals for the conditions of the selected study area. Two different models had been used, namely; Frater and Gravity model. These models were calibrated using real data. The study tests the accuracy of the models, including overall statistical assessments of the predicted movements. Finally, the study recommended to use Fratar Method. These results had been confirmed to the literature that, if the area is a homogenous growth, the best model is the growth factor (Fratar's method) and if the area is experiencing rapid changes. The gravity model will produce satisfactory results because it takes into account the competition in different land uses.

A causal inference approach to measure the vulnerability of urban metro systems

Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inference approach for estimating station-level vulnerability in metro systems. The empirical analysis is based on large-scale data on historical incidents and population-level passenger demand. This analysis thus obviates the need for assumptions made by previous studies on human behaviour and disruption scenarios. We develop four empirical vulnerability metrics based on the causal impact of disruptions on travel demand, average travel speed and passenger flow distribution. Specifically, the proposed metrics based on the irregularity in passenger flow distribution extends the scope of vulnerability measurement to the entire trip distribution, instead of just analysing the disruption impact on the entry or exit demand (that is, moments of the trip distribution). The unbiased estimates of disruption impact are obtained by adopting a propensity score matching method, which adjusts for the confounding biases caused by non-random occurrence of disruptions. An application of the proposed framework to the London Underground indicates that the vulnerability of a metro station depends on the location, topology, and other characteristics. We find that, in 2013, central London stations are more vulnerable in terms of travel demand loss. However, the loss of average travel speed and irregularity in relative passenger flows reveal that passengers from outer London stations suffer from longer individual delays due to lack of alternative routes.

Estimating Public Bicycle Trip Characteristics with Consideration of Built Environment Data

A reliable estimation of public bicycle trip characteristics, especially trip distribution and duration, can help decision-makers plan for the relevant transport infrastructures and assist operators in addressing issues related to bicycle imbalance. Past research studies have attempted to understand the relationship between public bicycle trip generation, trip attraction and factors such as built environment, weather, population density, etc. However, these studies typically did not include trip distribution, duration, and detailed information on the built environment. This paper aims to estimate public bicycle daily trip characteristics, i.e., trip generation, trip attraction, trip distribution, and duration using points of interest and smart card data from Nanjing, China. Negative binomial regression models were developed to examine the effect of built environment on public bicycle usage. Totally fifteen types of points of interest (POIs) data are investigated and factors such as residence, employment, entertainment, and metro station are found to be statistically significant. The results showed that 300 m buffer POIs of residence, employment, entertainment, restaurant, bus stop, metro station, amenity, and school have significantly positive effects on public bicycle generation and attraction, while, counterintuitively, 300 m buffer POIs of shopping, parks, attractions, sports, and hospital have significantly negative effects. Specifically, an increase of 1% in the trip distance leads to a 2.36% decrease in the origin-destination (OD) trips or a 0.54% increase of the trip duration. We also found that a 1% increase in the number of other nearby stations can help reduce 0.19% of the OD trips. The results from this paper can offer useful insights to operators in better estimating public bicycle usage and providing reliable services that can improve ridership.

Analisis Jaringan Jalan dengan Metode MKJI 197 pada Kinerja Lalu Lintas di Sekitar Kawasan Perkotaan (Studi Kasus: Perencanaan Tata Guna Lahan Baru di Kawasan Tanrise City Jember)

ABSTRAKTanrise City Jember merupakan kawasan superblock yang akan dibangun di Jalan Hayam Wuruk, Kabupaten Jember. Pembangunan meliputi mall, hotel, depo bangunan, ruko, perumahan, dan convention hall. Pembangunan tersebut akan menimbulkan trip production dan trip atrraction yang berdampak pada kinerja ruas dan simpang di sekitarnya. Analisis kinerja simpang dan ruas akibat pembangunan Tanrise City Jember perlu dilakukan dengan tujuan untuk mengetahui pengaruhnya pada kondisi eksisting, operasional dan 5 tahun mendatang. Analisis kinerja simpang dan ruas dilakukan dengan menggunakan metode MKJI 1997. Volume kendaraan setiap simpang dan ruas didapatkan dari hasil counting dan faktor pertumbuhan. Penentuan trip production dan trip attraction dengan melakukan survei pada bangunan pembanding. Adapun perkiraan lalu lintas didapatkan dengan menggunakan konsep trip generation, trip distribution, trip assignment. Hasil analisis kinerja simpang Mangli, Transmart dan Argopuro pada kondisi eksisting, operasional dan 5 tahun mendatang menggunakan MKJI 1997 didapatkan kinerja simpang mengalami penurunan. Kinerja simpang terburuk terjadi di Simpang Mangli dengan nilai tundaan (D)>1000 det/smp. Hasil analisis kinerja ruas sekitar pada kondisi eksisiting adalah arus stabil dan kinerja terburuk terjadi di Jl. Brawijaya dengan derajat kejenuhan (DS)>0,85 yakni kategori E. Kinerja ruas pada kondisi operasional dan 5 tahun mendatang mengalami penurunan di setiap jam puncaknya.Kata kunci : derajat kejenuhan; MKJI 1997; tundaan ABSTRACTTanrise City is a superblock area that will be built around Hayam Wuruk street, Jember District. This development will give rises to a new mall, hotel, building depo, shop house, housing, and convention hall. The development will lead to the production trip and attraction trip that will impact the intersections and roads in surrounding areas. Intersections and road performance analysis of Jember Tanrise City development impact need to be studied to understand its effects on the existing condition in the present time and 5 (five) years to come. Intersections and road performance analysis use The 1997 Indonesian Highway Capacity Manual (IHCM). The volume of vehicles for each intersection and roads is obtained from the counting result and the growth factor. Determination of trip production and the trip attraction was by surveying the comparison building. The traffic estimate is obtained using the concept of trip generation, trip distribution, trip assignment. The result of intersections performance of the Mangli Intersections, Transmart Intersections, Argopuro Intersection on the existing condition, in the present time, and 5 (five) years to come to use The 1997 Indonesian Highway Capacity Manual (IHCM) showed that the intersection performance has decreased. The worst intersection performance occurred at the Mangli intersection with the delay value (D) is > 1000 sec/pcu. The result of road performance in surrounding areas on the existing condition is stable currents, and the worst road performance occurred in Brawijaya street with the Degree Of Saturation (DS) is > 0,85, which is E category. The road's performance in the present time and 5 (five) years to come has decreased in every peak hour.