scholarly journals The Influence of Public Transport Delays on Mobility on Demand Services

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 379
Author(s):  
Layla Martin ◽  
Michael Wittmann ◽  
Xinyu Li
Keyword(s):  
Public Transit ◽  
Descriptive Analysis ◽  
Time Of Day ◽  
Public Authorities ◽  
Data Set ◽  
Transportation Services ◽  
Demand Prediction ◽  
On Demand ◽  
Increasing Demand ◽  
The City

Demand for different modes of transportation clearly interacts. If public transit is delayed or out of service, customers might use mobility on demand (MoD), including taxi and carsharing for their trip, or discard the trip altogether, including a first and last mile that might otherwise be covered by MoD. For operators of taxi and carsharing services, as well as dispatching agencies, understanding increasing demand, and changing demand patterns due to outages and delays is important, as a more precise demand prediction allows for them to more profitably operate. For public authorities, it is paramount to understand this interaction when regulating transportation services. We investigate the interaction between public transit delays and demand for carsharing and taxi, as measured by the fraction of demand variance that can be explained by delays and the changing OD-patterns. A descriptive analysis of the public transit data set yields that delays and MoD demand both highly depend on the weekday and time of day, as well as the location within the city, and that delays in the city and in consecutive time intervals are correlated. Thus, demand variations must by corrected for these external influences. We find that demand for taxi and carsharing increases if the delay of public transit increases and this effect is stronger for taxi. Delays can explain at least 4.1% (carsharing) and 18.8% (taxi) of the demand variance, which is a good result when considering that other influencing factors, such as time of day or weather exert stronger influences. Further, planned public transit outages significantly change OD-patterns of taxi and carsharing.

Spatial and Temporal Differences in Weekday Travel Durations Between Private-for-Hire Transportation Services and Transit in the City Center

2021 ◽  
pp. 036119812110197
Author(s):  
Baxter Shandobil ◽  
Ty Lazarchik ◽  
Kelly Clifton
Keyword(s):  
Transportation Network ◽  
Central City ◽  
Temporal Analysis ◽  
Time Of Day ◽  
City Center ◽  
Transportation Services ◽  
Regulatory Frameworks ◽  
Transit Services ◽  
Level Information ◽  
The City

There is increasing evidence that ridehailing and other private-for-hire (PfH) services such as taxis and limousines are diverting trips from transit services. One question that arises is where and when PfH services are filling gaps in transit services and where they are competing with transit services that are publicly subsidized. Using weekday trip-level information for trips originating in or destined for the city center of Portland, OR from PfH transportation services (taxis, transportation network companies, limousines) and transit trip data collected from OpenTripPlanner, this study investigated the temporal and spatial differences in travel durations between actual PfH trips and comparable transit trips (the same origin–destination and time of day). This paper contributes to this question and to a growing body of research about the use of ridehailing and other on-demand services. Specifically, it provides a spatial and temporal analysis of the demand for PfH transportation using an actual census of trips for a given 2 week period. The comparison of trip durations of actual PfH trips to hypothetical transit trips for the same origin–destination pairs into or out of the central city gives insights for policy making around pricing and other regulatory frameworks that could be implemented in time and space.

Who uses Transport Network Companies?: Characterization of Demand and its Relationship with Public Transit in Medellín

2021 ◽  
Author(s):  
Felipe Bedoya-Maya ◽  
Lynn Scholl ◽  
Orlando Sabogal-Cardona ◽  
Daniel Oviedo
Keyword(s):  
Latin American ◽  
Public Transit ◽  
Descriptive Analysis ◽  
Discrete Choice Models ◽  
Transport Network ◽  
Gender Effects ◽  
Transport Systems ◽  
Factors Affecting ◽  
On Demand ◽  
Latin American Region

Transport Network Companies (TNCs) have become a popular alternative for mobility due to their ability to provide on-demand flexible mobility services. By offering smartphone-based, ride-hailing services capable of satisfying specific travel needs, these modes have transformed urban mobility worldwide. However, to-date, few studies have examined the impacts in the Latin American context. This analysis is a critical first step in developing policies to promote efficient and sustainable transport systems in the Latin-American region. This research examines the factors affecting the adoption of on-demand ride services in Medellín, Colombia. It also explores whether these are substituting or competing with public transit. First, it provides a descriptive analysis in which we relate the usage of platform-based services with neighborhood characteristics, socioeconomic information of individuals and families, and trip-level details. Next, factors contributing to the election of platform-based services modeled using discrete choice models. The results show that wealthy and highly educated families with low vehicle availability are more likely to use TNCs compared to other groups in Medellín. Evidence also points at gender effects, with being female significantly increasing the probability of using a TNC service. Finally, we observe both transit complementary and substitution patterns of use, depending on the context and by whom the service is requested.

scholarly journals Evaluating accessibility of small communities via public transit

2020 ◽  
Vol 56 (4) ◽  
pp. 59-72
Author(s):  
Antonio Danesi ◽  
Simone Tengattini
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Public Transit ◽  
Time Of Day ◽  
Educational Work ◽  
Small Communities ◽  
Schedule Delay ◽  
Total Travel Time ◽  
Travel Impedance ◽  
The City

Accessibility to and from urban centres allows small communities’ dwellers to participate in primary activities and use essential services that are not available on-site, such as educational, work and medical services. Public transport networks are supposed to enhance accessibility and pursue equity principles, overcoming socio-economical differences among people that can exacerbate during crisis. In this paper a methodology is proposed and implemented to assess small communities’ accessibility via public transit. A metric is defined based on the calculation of total travel time, taken as a proxy of travel impedance, with consideration of in-vehicle time, schedule delay and users’ arrival and departure preference curves (i.e. time-of-day functions). A “rooftops” model is specified and implemented under the assumption that travellers cannot accept (scheduled) late arrival or early departure time penalties before and after the participation in their activities in the main urban centre, as many activities rarely admit time-flexibility. Also, a public transport specific impedance factor (PTSIF) is proposed, in order to account for travel impedance determinants, which are a consequence of service scheduling and routing decisions and not due to inherent geographical and infrastructural disadvantages affecting car users too. An application of the methodology for the city of Cesena, Italy, and 90 surrounding small communities is presented. The city is served by train and bus services. Assessment of small communities' accessibility based on both total travel time and PTSIF is presented and discussed. This practice-ready quantitative method can help transport professionals to evaluate impacts on small communities’ accessibility in light of public transport service changes or reduction. Quantitative approach to support strategic decisions is needed, for example, both to assess public transport strengthening politics against depopulation of rural and marginal mountainous areas and to mitigate the effects of possible increasing concentration of services towards high-demand lines, which may follow as a consequence of budget cuts or contingencies, such as vehicle capacity reductions required by sanitary emergencies.

scholarly journals Does an Increase in Population Density Increases Transit Mode Split? Going Beyond the Contemporaneous Correlation Between Built Form and Public Transit Mode Share

2021 ◽  
Author(s):  
Atanaz Dorrani Arab ◽  
Murtaza Haider
Keyword(s):  
Population Density ◽  
Longitudinal Data ◽  
Public Transit ◽  
Data Set ◽  
Built Form ◽  
Transit Ridership ◽  
Mode Share ◽  
The Impact ◽  
The City ◽  
Over Time

This paper explores the relationship between public transit mode share and population density. It critically reviews the long-held belief that an increase in population density (compact built form) will result in an increase in public transit ridership. The research developed a longitudinal data set of travel behavior, transit supply, and proxies of built form for 1996 and 2016 for the City of Toronto. The data set is spatially disaggregated at the Traffic Analysis Zone (TAZ) level such that the TAZs that divide the City into 480 mutually exclusive and collectively exhaustive zones. The paper found that a cross-sectional analysis of population density and transit mode share captures mostly the contemporaneous relationship between the two and does not, by default, lend credence to the argument that if the density increases over time at a place, it will subsequently result in higher public transit ridership. Such a question will require a longitudinal analysis where the impact of a change in public density over time is examined to determine its impact, if any, on transit ridership. Using Linear Mixed Models for longitudinal data, the paper found that the contemporaneous relation between density and transit mode share holds, but the change in population density over time does not automatically correlate with an increase in transit ridership

scholarly journals Does an Increase in Population Density Increases Transit Mode Split? Going Beyond the Contemporaneous Correlation Between Built Form and Public Transit Mode Share

2021 ◽  
Author(s):  
Atanaz Dorrani Arab ◽  
Murtaza Haider
Keyword(s):  
Population Density ◽  
Longitudinal Data ◽  
Public Transit ◽  
Data Set ◽  
Built Form ◽  
Transit Ridership ◽  
Mode Share ◽  
The Impact ◽  
The City ◽  
Over Time

This paper explores the relationship between public transit mode share and population density. It critically reviews the long-held belief that an increase in population density (compact built form) will result in an increase in public transit ridership. The research developed a longitudinal data set of travel behavior, transit supply, and proxies of built form for 1996 and 2016 for the City of Toronto. The data set is spatially disaggregated at the Traffic Analysis Zone (TAZ) level such that the TAZs that divide the City into 480 mutually exclusive and collectively exhaustive zones. The paper found that a cross-sectional analysis of population density and transit mode share captures mostly the contemporaneous relationship between the two and does not, by default, lend credence to the argument that if the density increases over time at a place, it will subsequently result in higher public transit ridership. Such a question will require a longitudinal analysis where the impact of a change in public density over time is examined to determine its impact, if any, on transit ridership. Using Linear Mixed Models for longitudinal data, the paper found that the contemporaneous relation between density and transit mode share holds, but the change in population density over time does not automatically correlate with an increase in transit ridership

Simulation of Potential Use Cases for Shared Mobility Services in the City of Ann Arbor

2021 ◽  
pp. 036119812110045
Author(s):  
Richard Twumasi-Boakye ◽  
Xiaolin Cai ◽  
James Fishelson ◽  
Andrea Broaddus
Keyword(s):  
Motor Vehicle ◽  
Simulation Software ◽  
Use Cases ◽  
Transportation Services ◽  
On Demand ◽  
Park And Ride ◽  
Mobility Service ◽  
Shared Mobility ◽  
Ann Arbor ◽  
The City

In this paper, we model and simulate special use cases of on-demand shared mobility services for the City of Ann Arbor, MI. We define shared mobility as any motor-vehicle-served transportation option between private vehicles and public transit, such as taxis, demand-responsive transit, and dynamic shuttles. Here, we present and evaluate a suite of four different service types that could potentially complement existing transportation services in Ann Arbor. A novel aspect of this study is that it tests scenarios that were developed in consultation with city planners looking for insights into real-world problems. This study used fleet simulation software to test four service configuration scenarios for a hypothetical on-demand shared mobility service: citywide shuttle, a corridor-based downtown shuttle, a park and ride shuttle, and a transit-complementary service. Three levels of demand were tested for each scenario: 3%, 9%, and 15% of all private vehicle trips in the city. Findings indicated that citywide on-demand shared mobility services struggled to achieve higher vehicle occupancies than private vehicles at approximately 1.4. Service configurations with aggregated trip density resulted in slightly improved occupancies, as found in downtown- and park and ride shuttle scenarios. More impactful was aggregating demand by moving from “many-to-many” routing as with citywide floating services to “many-to-one” routing as with downtown- or park and ride shuttle services, which increased vehicle occupancy from 1.4 to almost 2. Lastly, we also discuss the potential benefits of reduced congestion and parking needs.

Pengaruh Kotbah, Musik Gereja Dan Fasilitas Gereja Terhadap Tingkat Kehadiran Jemaat

2016 ◽  
Vol 1 (1) ◽  
pp. 1-15
Author(s):  
Frederich Oscar Lontoh
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Church Music ◽  
Pearson Correlation ◽  
Descriptive Analysis ◽  
Target Population ◽  
The Other ◽  
Pearson Correlation Coefficient ◽  
Christian Church ◽  
The City

This research is titled " The influence of sermon, church music and church facilities on the level of attendance”. The purpose of research is to identify and analyze whether sermon, church music and church facilities have influence on the the level of attendance. The target population in this study is a Christian church members who live in the city of Surabaya.. Sample required is equal to 47 respondents. Through sampling stratified Random techniques.These influence was measured using Pearson correlation coefficient and multiple regression analysis, t-test and analysis of variance. Descriptive  analysis  were taken to analyze the level of attendance according to demographic groups.The hypothesis in this study are the sermon, church music and church facilities have positive and significant on the level of attendance. The results showed that collectively, there are positive and significant correlation among the sermon, church music and church facilities on the level of attendance  96,2%. It means that 96,2 % of level of attendance influenced by sermon, church music and church facilities and the other 28,9% by others. All of the variable partially have significant correlation to level of attendance.

Analisis Wilayah Kecamatan Potensial Melalui Pendekatan Tipologi Klassen di Kabupaten Ende

Analisis ◽  
2020 ◽  
Vol 19 (1) ◽  
pp. 39-49
Author(s):  
Estherlina Sagajoka
Keyword(s):  
Economic Development ◽  
Descriptive Analysis ◽  
Population Data ◽  
Spatial Inequality ◽  
Theil Index ◽  
Time Data ◽  
Entropy Index ◽  
Quantitative Descriptive Analysis ◽  
Index Analysis ◽  
The City

This study aims to determine the comparison of the results of the inequality analysis of economic development between districts / cities in the province of East Nusa Tenggara for the period of 2013-2018. The method used in this research is quantitative descriptive analysis using the Williamson index, and Theil Entropy Index, using time data per capita PDRB series and population data for each district / city in 2013-2018. The Williamson Index analysis results show that the economic development sector inequality in 21 districts in NTT province is very evenly distributed (low inequality) except for the city of Kupang, which has an Williamson Index value of 1.49 other than districts in NTT province in the period 2013-2018. The Intra Index Analysis Results show spatial inequality within the regency. The city of Nusa Tenggara Timur province is fairly evenly distributed within the regency except the city of Kupang  shows an unequal inequality compared to 21 other districts. Through the Theil Entropy Index calculation of development inequality between 21 regencies and Kupang  tend to widen (divergence) which has Theil  Index of 798,15, while the other 21 districts in the 2013-2018 period have the Theil Entropy Index Index 211,26 for Regencies and  TTS 201,11, while other districts have an index numberbelow 200.

scholarly journals INDIKATOR MAKROEKONOMI DAN PEMBANGUNAN KOTA BANDUNG

2019 ◽  
pp. 622
Author(s):  
Teguh Santoso ◽  
Bayu Kharisma
Keyword(s):  
Economic Growth ◽  
Poverty Reduction ◽  
Moving Average ◽  
Descriptive Analysis ◽  
High Rate ◽  
Purchasing Power ◽  
Autoregressive Moving Average Model ◽  
Food Commodities ◽  
The City ◽  
Poverty Levels

The high rate of inflation has the potential to increase poverty because it can reduce people's purchasing power, where if inflation rises significantly it can shift the people who are categorized as not poor, become vulnerable to poverty, almost poor and even poor. The aims of this study are to analyze the development of macroeconomic indicators, namely inflation and economic growth that are associated with poverty levels in the city of Bandung. The methodology used in this study is descriptive analysis and the ARMA (autoregressive moving average) model. The results showed that the high inflation in the city of Bandung compared to national and West Java inflation carries its own burden for the economy of the community, where purchasing power will decrease when inflation rises significantly and will have an impact on people's welfare. Inflation in the city of Bandung is often due to the price of food commodities (volatile food inflation). In addition, the high economic growth in the city of Bandung is not directly proportional to the decline in poverty levels. This shows that the quality of economic growth in the city of Bandung has problems that need attention. Therefore, local government in their efforts to encourage economic growth must prioritize poverty reduction and inequality.

scholarly journals On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2789 ◽  
Author(s):  
Hang Qi ◽  
Hao Huang ◽  
Zhiqun Hu ◽  
Xiangming Wen ◽  
Zhaoming Lu
Keyword(s):  
Reinforcement Learning ◽  
Transmission Rate ◽  
Single Agent ◽  
Time Of Day ◽  
Action Space ◽  
Traffic Load ◽  
Traffic Demand ◽  
Channel Bonding ◽  
On Demand ◽  
Multi Agent

In order to meet the ever-increasing traffic demand of Wireless Local Area Networks (WLANs), channel bonding is introduced in IEEE 802.11 standards. Although channel bonding effectively increases the transmission rate, the wider channel reduces the number of non-overlapping channels and is more susceptible to interference. Meanwhile, the traffic load differs from one access point (AP) to another and changes significantly depending on the time of day. Therefore, the primary channel and channel bonding bandwidth should be carefully selected to meet traffic demand and guarantee the performance gain. In this paper, we proposed an On-Demand Channel Bonding (O-DCB) algorithm based on Deep Reinforcement Learning (DRL) for heterogeneous WLANs to reduce transmission delay, where the APs have different channel bonding capabilities. In this problem, the state space is continuous and the action space is discrete. However, the size of action space increases exponentially with the number of APs by using single-agent DRL, which severely affects the learning rate. To accelerate learning, Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is used to train O-DCB. Real traffic traces collected from a campus WLAN are used to train and test O-DCB. Simulation results reveal that the proposed algorithm has good convergence and lower delay than other algorithms.

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