Keeping Passenger Surveys Up to Date: A Fuzzy Approach

2000 ◽  
Vol 1735 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Markus Friedrich ◽  
Peter Mott ◽  
Klaus Noekel
Keyword(s):  
Travel Demand ◽  
Fuzzy Approach ◽  
Transit System ◽  
Computer Aided ◽  
Traffic Volumes ◽  
Survey Costs ◽  
Essential Prerequisite ◽  
Transport Supply

The knowledge of travel demand is an essential prerequisite for analyzing and planning transport supply. Obtaining travel-demand data for a transit system requires passenger surveys that combine counts and interviews. Passenger surveys have two unpleasant characteristics: they are expensive, and the results of such studies tend to lose their validity fairly rapidly. For these reasons, the development of techniques that reduce survey costs and keep demand matrices up to date is gaining increasing interest. Details of a technique for computer-aided processing of passenger surveys are given, and a method for continuous updating of demand matrices is presented. Because traffic surveys represent only a snapshot situation, the proposed updating method employs a fuzzy approach to consider that traffic volumes vary within a certain bandwidth.

MODEL DISTRIBUSI PERJALANAN PENDUDUK UNTUK PENENTUAN KORIDOR ‘LRT’ DI PULAU BATAM

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Djoko Prijo Utomo
Keyword(s):  
Network Performance ◽  
Travel Demand ◽  
Mass Transit ◽  
Distribution Model ◽  
Economic Activities ◽  
Transit System ◽  
Trip Distribution ◽  
Home Interview ◽  
Interview Survey ◽  
Private Car

In consequence of the increasing of regional economic activities in Pulau Batam, a reliable transportation system is required. Decreasing road network performance as a result of increasing traffic volume needs a strategic planning to anticipate the worsening condition in the future. One of the solutions is by providing mass transit system which is expected to attract private car users. Therefore, determination of potential corridor of mass transit system need to be identified so that the system provide better accessibility. Trip pattern in Pulau Batam must be known by developing trip distribution model. The trip distribution model is calibrated using origin-destination (O-D) data that is based on home interview survey. The validated model will be used to forecast and simulate travel demand onto transport network. Result of model calibration process shows mean trip length difference between model and survey is equal 0.141 %. From simulation of trip assignment is obtained that potential corridor for mass transit system using LRT is Batu Ampar – Batu Aji via Muka Kuning. Passenger forecast in the year 2030 is 193,990 passenger/day (2 directions).

scholarly journals Understanding Users’ Satisfaction Towards Public Transit System in India: A Case-Study of Mumbai

2021 ◽  
Vol 10 (3) ◽  
pp. 155
Author(s):  
Rahul Das
Keyword(s):  
Service Quality ◽  
Public Transport ◽  
Travel Demand ◽  
Resource Constraints ◽  
Public Transit ◽  
Sampling Bias ◽  
Relevant Information ◽  
Transit System ◽  
Transport Services ◽  
Developing Cities

In this work, we present a novel approach to understand the quality of public transit system in resource constrained regions using user-generated contents. With growing urban population, it is getting difficult to manage travel demand in an effective way. This problem is more prevalent in developing cities due to lack of budget and proper surveillance system. Due to resource constraints, developing cities have limited infrastructure to monitor transport services. To improve the quality and patronage of public transit system, authorities often use manual travel surveys. But manual surveys often suffer from quality issues. For example, respondents may not provide all the detailed travel information in a manual travel survey. The survey may have sampling bias. Due to close-ended design (specific questions in the questionnaire), lots of relevant information may not be captured in a manual survey process. To address these issues, we investigated if user-generated contents, for example, Twitter data, can be used to understand service quality in Greater Mumbai in India, which can complement existing manual survey process. To do this, we assumed that, if a tweet is relevant to public transport system and contains negative sentiment, then that tweet expresses user’s dissatisfaction towards the public transport service. Since most of the tweets do not have any explicit geolocation, we also presented a model that does not only extract users’ dissatisfaction towards public transit system but also retrieves the spatial context of dissatisfaction and the potential causes that affect the service quality. It is observed that a Random Forest-based model outperforms other machine learning models, while yielding 0.97 precision and 0.88 F1-score.

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

2017 ◽  
Vol 2650 (1) ◽  
pp. 74-83 ◽  
Author(s):  
Neda Masoud ◽  
Daisik Nam ◽  
Jiangbo Yu ◽  
R. Jayakrishnan
Keyword(s):  
Los Angeles ◽  
Travel Demand ◽  
Decision Support Tool ◽  
Peer To Peer ◽  
Successful Implementation ◽  
Modeling Framework ◽  
Transit System ◽  
Support Tool ◽  
Demand Shifts ◽  
Red Line

Peer-to-peer (P2P) ridesharing is a recently emerging travel alternative that can help accommodate the growth in urban travel demand and at the same time alleviate problems such as excessive vehicular emissions. Prior ridesharing projects suggest that the demand for ridesharing is usually shifted from transit, but its true benefits are realized when the demand shifts from single-occupancy vehicles. This study investigated the potential of shifting demand from private autos to transit by providing a general modeling framework that found routes for private vehicle users that were a combination of P2P ridesharing and transit. The Los Angeles Metro Red Line in California was considered for a case study because it has recently shown declining ridership trends. For successful implementation of a ridesharing system, strategically selecting locations for individuals to get on and off the rideshare vehicles is crucial, along with an appropriate pricing structure for the rides. The study conducted a parametric analysis of the application of real-time P2P ridesharing to feed the Los Angeles Metro Red Line with simulated demand. A mobile application with an innovative ride-matching algorithm was developed as a decision support tool that suggested transit-rideshare and rideshare routes.

Scalable GEH: A Quality Measure for Comparing Observed and Modeled Single Values in a Travel Demand Model Validation

2019 ◽  
Vol 2673 (4) ◽  
pp. 722-732 ◽  
Author(s):  
Markus Friedrich ◽  
Eric Pestel ◽  
Christian Schiller ◽  
Robert Simon
Keyword(s):  
Normal Distribution ◽  
Travel Demand ◽  
Quality Measures ◽  
Quality Measure ◽  
Specific Reference ◽  
Traffic Planning ◽  
Demand Model ◽  
Trip Purpose ◽  
Traffic Volumes ◽  
Travel Demand Model

For proving the validity of a travel demand model, the deviations between observed values and modeled values must be quantified and evaluated by suitable quality measures. The comparison of observed and modeled values can refer to single values, sets of single values, and distributions of values. The paper focuses on comparing pairs of single values with specific reference to the quality measure GEH (named after Geoffrey E. Havers, who introduced it for traffic planning purposes in the 1970s), which is used in the British guidelines WebTAG. The paper describes desirable and problematic properties of the GEH and examines how it is related to normal distribution. With the objective of overcoming the limitations of the GEH an alternative quality measure was developed, which can be scaled to validate different value ranges representing hourly or daily traffic volumes, daily number of trips per person, or trip distances per trip purpose. The paper concludes with a proposal for validating single values.

Assessing the Role of Modal Shift in Minimizing Transport Energy Consumption, a Case Study of Kathmandu Valley

2020 ◽  
Vol 15 (3) ◽  
pp. 33-41
Author(s):  
Ashim Bajracharya ◽  
Sudha Shrestha
Keyword(s):  
Energy Consumption ◽  
Transport System ◽  
Travel Demand ◽  
Urban Transport ◽  
Kathmandu Valley ◽  
Demand Model ◽  
Modal Shift ◽  
Transit System ◽  
Public Transport System ◽  
Total Transport

With rapid growing economies and population, there is an increasing trend of expansion of urban sprawl and auto-mobilization, in the cities of the Kathmandu Valley. With the rise in travel demand, transport energy is becoming a major concern for planners and policymakers. This paper aims to study the transport energy of daily trips that constitute work and educational trips, in context of the Kathmandu Valley. The study demonstrates the applicability of a 4-step travel demand model for the assessment of energy-saving measures in urban transport system by formulating scenarios. The results show that currently, daily trips consume 3666 TJ annually. Cars and motorcycles contribute to most of the consumption, accounting for over 80% of the total transport energy. As a mitigation measure to reduce transport energy, the introduction of the efficient public transport system in the form of Bus Rapid Transit System (BRTS) along major corridors, could bring down transport energy consumption significantly. The paper concludes with the essence, to address the need for modal shift to the mass transit system, as a step towards the minimization of transport energy.

scholarly journals Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM

2019 ◽  
Vol 11 (19) ◽  
pp. 5525 ◽  
Author(s):  
Jinjun Tang ◽  
Fan Gao ◽  
Fang Liu ◽  
Wenhui Zhang ◽  
Yong Qi
Keyword(s):  
New York ◽  
Travel Demand ◽  
Geographical Area ◽  
Temporal Characteristic ◽  
Temporal Variations ◽  
Road Density ◽  
Transit System ◽  
Factors Affecting ◽  
Urban Travel ◽  
Spatio Temporal

Taxis are an important part of the urban public transit system. Understanding the spatio-temporal variations of taxi travel demand is essential for exploring urban mobility and patterns. The purpose of this study is to use the taxi Global Positioning System (GPS) trajectories collected in New York City to investigate the spatio-temporal characteristic of travel demand and the underlying affecting variables. We analyze the spatial distribution of travel demand in different areas by extracting the locations of pick-ups. The geographically weighted regression (GWR) method is used to capture the spatial heterogeneity in travel demand in different zones, and the generalized linear model (GLM) is applied to further identify key factors affecting travel demand. The results suggest that most taxi trips are concentrated in a fraction of the geographical area. Variables including road density, subway accessibility, Uber vehicle, point of interests (POIs), commercial area, taxi-related accident and commuting time have significant effects on travel demand, but the effects vary from positive to negative across the different zones of the city on weekdays and the weekend. The findings will be helpful to analyze the patterns of urban travel demand, improve efficiency of taxi companies and provide valuable strategies for related polices and managements.

scholarly journals Speeding and Traffic-Related Injuries and Fatalities during the 2020 COVID-19 Pandemic: The Cases of Seattle and New York City

2021 ◽  
Author(s):  
Haifeng Liao ◽  
Michael Lowry
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Travel Demand ◽  
Motor Vehicle ◽  
Weather Conditions ◽  
Incidence Rates ◽  
Severe Injuries ◽  
Police Data ◽  
Traffic Volumes

Despite fewer cars on roads during the COVID-19 pandemic, deaths associated with motor vehicle collisions in New York City and Seattle remained largely unchanged in 2020. Using police data on weekly counts of collisions, we compared trends in 2020 with those of 2019, while controlling for the reduction of traffic volumes and seasonal weather conditions. Results of difference-in-differences estimation suggest that during the early months of the pandemic, or March-May, the incidence rates of severe or fatal injury crashes related to speeding increased by nearly 8 times in Seattle and more than 4 times in New York City. In the rest of 2020, they were still significantly higher than what would be expected in the absence of the pandemic. This research suggests that in similar situations that depress travel demand (e.g., another pandemic), policymakers should formulate plans to reduce speeding which may prevent an upswing in severe injuries and fatalities.

scholarly journals Bus passenger flow congestion risk evaluation model based on the Pressure-State-Response framework: A case study in Beijing

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041988356 ◽  
Author(s):  
Siyong Ma ◽  
Jiancheng Weng ◽  
Chang Wang ◽  
Dimitrios Alivanistos ◽  
Pengfei Lin
Keyword(s):  
Network Flow ◽  
Risk Evaluation ◽  
Travel Demand ◽  
Evaluation Model ◽  
Risk Identification ◽  
Risk Level ◽  
Transit System ◽  
State Response ◽  
Passenger Flow ◽  
Pressure State

Urban public transport is a very essential mode for urban residents’ commute travel; however, the unbalanced spatial and temporal distribution of travel demand usually leads to passenger flow congestion risk at certain section and time. Meanwhile, the risk is short of quantified description. Based on the Pressure-State-Response framework, the study puts forward three bus passenger flow congestion risk evaluation indexes including the alternative pressure, the congestion intensity, and the transport efficiency. Then, the evaluation model is proposed based on the entropy method, and the risk is divided into four levels by K-means clustering. The article considers the 3rd Ring Road corridor in Beijing as a case to identify the risk level. The results show that the risk in the peak hours of weekdays is generally about 1.5 times higher than the risk in the weekends. The congestion risk is stable in level 3 during the majority time of morning peak hours. The duration intensity of level 4 risk is less than 0.1 during weekdays, indicating that the highest flow congestion can be quickly evacuated in a short time. The integrated passenger risk identification and evaluation model was proposed to identify the passenger flow risk level and induce the network flow distribution more reasonable. The study also provides technical support for ensuring the public transit system safety.

scholarly journals Integrasi Layanan Trans Koetaradja dengan Feeder Angkutan Labi-Labi di Kota Banda Aceh

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Winiko Afriza ◽  
Okto Risdianto Manullang
Keyword(s):  
Traffic Congestion ◽  
Travel Demand ◽  
Descriptive Analysis ◽  
Provincial Government ◽  
Transit System ◽  
Traffic Jam ◽  
Time Required ◽  
The Cost ◽  
Operational Integration ◽  
Banda Aceh

The Aceh Provincial Government through the department of transportation in 2016 began operating Bus Rapid Transit (BRT) in Banda Aceh city. The presence of Trans Koetaradja is expected to be able to implement a mass transit system that is capable of maintaining order, traffic congestion and traffic jam in Banda Aceh City. However, the existence of BRT Trans Koetaradja poses a threat to the existence of drivers and businessmen of transporting labi-labi in Banda Aceh City. Starting from the problem, this research aims to create the form of integration of BRT Trans Koetaradja service with feeder of labi-labi transportation in Banda Aceh City. The research method used is descriptive analysis of kunatitatif which will describe the potential of travel demand and condition of existing road network. In addition, it uses a spatial descriptive analysis method to formulate the form of feeder transport routes of labi-labi and analyze the operational integration of routes, time and rates. The result of the research shows that there are 6 feeder routes that will serve the corridor I Keudah-Darussalam namely Prada area route, Zainal Abidin General Hospital route, Simpang Keramat route, Unsyiah campus route and UIN Ar-Raniry route, Aceh Governor Office and route of Simpang Mesra area. Operationally, the integration of Trans Koetaradja transport service time with feeder transport of labi-labi is at 07.00-18.00 wib. The required headway of each feeding route is 4-9 minutes. The travel time required for each feeder route is 10-15 minutes with the number of fleets used by 32 units to serve 6 (six) feeder routes. In terms of tariff integration, the cost to be spent per passenger to use labi-labi transportation on each feeder route is between Rp.1.000 - Rp. 1,500.

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