Exploring the correlation between ride-hailing and multimodal transit ridership in toronto

Transportation - Ride-hailing (RH) services have been growing rapidly and gaining popularity worldwide. However, many transit agencies are experiencing ridership stagnation or even decline....     

The spatial distribution of journey-to-work trips in Greater London

Although a great deal is known about the distribution of homes and the distribution of workplaces in Greater London, the spatial relationship between them is less well understood. Using 1966 census data, the authors try to give a simple visual picture of this relationship, and to assess the relative travel intensities which would arise at different points in London from commuter trips, assuming straight line routing.The results show firstly that a large proportion of the population work quite close to their homes, with radial travel towards the city centre being only slightly more prominent than other directions of movement. The remainder tend to work near the city centre and to travel much longer distances. Secondly, relative to various annuli at 2 km increments centred on Charing Cross, the amounts of through traffic expressed as a proportion of the totals are roughly constant for radii between 4 and 14 km. Thirdly, people's choice of home in relation to their workplace is, on the whole, quite efficient, since it gives rise to a total amount of travel which is much closer to the theoretical minimum than it is to the amount corresponding to a random choice of homes from the available stock.     

Forecasting ridership for a metropolitan transit authority

The recent volatility in gasoline prices and the economic downturn have made the management of public transportation systems particularly challenging. Accurate forecasts of ridership are necessary for the planning and operation of transit services. In this paper, monthly ridership of the Metropolitan Tulsa Transit Authority is analyzed to identify the relevant factors that influence transit use. Alternative forecasting models are also developed and evaluated based on these factors—using regression analysis (with autoregressive error correction), neural networks, and ARIMA models—to predict transit ridership. It is found that a simple combination of these forecasting methodologies yields greater forecast accuracy than the individual models separately. Finally, a scenario analysis is conducted to assess the impact of transit policies on long-term ridership.     

GIS-based transit trip allocation methods converting stop-level boarding and alighting trips into TAZ trips

ABSTRACT

This study introduces a framework to improve the utilization of new data sources such as automated vehicle location (AVL) and automated passenger counting (APC) systems in transit ridership forecasting models. The direct application of AVL/APC data to travel forecasting requires an important intermediary step that links stops and activities – boarding and alighting – to the actual locations (at the traffic analysis zone (TAZ) level) that generated/attracted these trips. GIS-based transit trip allocation methods are developed with a focus on considering the case when the access shed spans multiple TAZs. The proposed methods improve practical applicability with easily obtained data. The performance of the proposed allocation methods is further evaluated using transit on-board survey data. The results show that the methods can effectively handle various conditions, particularly for major activity generators. The average errors between observed data and the proposed method are about 8% for alighting trips and 18% for boarding trips.     

Impact of pricing and transit disruptions on bikeshare ridership and revenue

Transportation - Bikeshare operators routinely explore options to improve ridership and revenue by studying interaction among pricing, service and operations. The objective of this research is to...     

A time series analysis of monthly ridership for an urban rail rapid transit line

This paper presents two time series regression models, one in linear form and the other in logarithmic form, to estimate the monthly ridership of a single urban rail rapid transit line. The model was calibrated for a time period of about six and a half years (from 1978–1984) based on ridership data provided by a transit authority, gasoline prices provided by a state energy department, and other data.The major findings from these models are: (1) seasonal variations of ridership are –6.26%, or –6.20% for the summer period, and 4.77%, or 4.62% for the October period; (2) ridership loss due to a station closure is 2.46% or 2.41%; and (3) elasticities of monthly ridership are –0.233 or –0.245 with respect to real fare, 0.113 or 0.112 with respect to real gasoline price, and 0.167 or 0.185 with respect to real bridge tolls for the competing automobile trips. Such route specific application results of this inexpensive approach provide significant implications for policymaking of individual programs in pricing, train operation, budgeting, system changes, etc., as they are in the case reported herein and would be in many other cities.     

The effects of ozone action day public advisories on train ridership in Chicago

Ground level ozone is a criteria pollutant that is significantly affected by transportation patterns. Ozone action day advisories represent one type of voluntary ozone-abating program operating in urban areas where ozone pollution is concentrated. When forecasts predict that ground level ozone will exceed healthy levels, public advisories urge citizens to voluntarily choose public transportation as a means of eliminating automobile trips and reducing mobile emissions. To obtain credit for emission reductions spurred by voluntary programs, states must provide verifiable reduction estimates. This paper applies a fixed effects regression model to a panel of hourly Chicago Transit Authority train ridership data to evaluate the potential effects of Ozone Action Day advisories in Chicago from 2002 to 2003. Findings show that while the overall effect of ozone action days on ridership is not significant, there are statistically significant changes in hourly ridership patterns that indicate a more complex relationship between the public advisories and travel behavior.     

Total cost minimizing transit route structures considering trips towards CBD and periphery

The total cost minimizing approach to design transit systems is extended here beyond the usual dimensions of fleet (frequency) and vehicle size in order to examine the most appropriate spatial setting of transit lines as well. Motivated by the case of large cities in Latin America, characterized by high volumes of relatively long urban trips, we analyze the best ways to provide public transport services in a simplified urban setting represented by an extended cross-shaped network, where short trips (periphery–center) and long trips (periphery–periphery) coexist, generating economies of density. Three families of strategic lines structures are compared: mostly direct, feeder–trunk and hub and spoke. For each structure fleet and vehicle sizes are optimized, considering total (users’ and operators’) costs. The best structure is found parametrically in total passenger volume, the proportion of long trips and the value of the transfer penalty. The advantages of each dominating structure are explained in terms of factors like idle capacity, waiting or in-vehicle times and number of transfers.     

The impact of fare and gasoline price changes on monthly transit ridership: Empirical evidence from seven U.S. transit authorities

This paper presents eight empirical models of monthly ridership for seven U.S. Transit Authorities. Within the framework of these models, the impacts upon monthly ridership from changes in the real fare and gasoline prices are examined. Important findings are: (1) the elasticities of monthly transit ridership with respect to the real fare are negative and inelastic, ranging from 0.042 to 0.62; and (2) the elasticities of monthly transit ridership with respect to the real gasoline price are positive and inelastic, ranging from 0.08 to 0.80. Such results have important policy implications for decisions based on the relationships of price, revenue, and ridership; and for assessing the impacts of changing gasoline prices upon urban modal choice.     

Demand and welfare effects in recreational travel models: Accounting for substitution between number of trips and days to stay

In this paper we present a non-linear demand system for households’ joint choice of number of trips and days to spend at a destination. The approach, which facilitates welfare analysis of exogenous policy and price changes, is used empirically to study the effects of an increased CO₂ tax. In particular, we focus on the effect of including substitution between households choice of the number of trips and days to spend at a destination in the welfare analysis. The analysis reveals that the equivalent variation (EV) measure, for the count data demand system, can be seen as an upper bound for the households welfare loss. Approximating the welfare loss by the change in consumer surplus, accounting for the positive effect from longer stays, imposes a lower bound on the households welfare loss. The difference in the estimated loss measures, from the considered CO₂ tax reform, is about 20%. This emphasizes the importance of accounting for substitutions toward longer stays in travel demand policy evaluations.     

Comparison on travel scheduling between driving and walking trips by habitual car users

Research on walking behavior has become increasingly more important in the field of transportation in the past decades. However, the study of the factors influencing the scheduling decisions related to walking trips and the exploration of the differences between travel modes has not been conducted yet. This paper presents a comparison of the scheduling and rescheduling decisions associated with car driving trips and walking trips by habitual car users using a data set collected in Valencia (Spain) in 2010. Bivariate probit models with sample selection are used to accommodate the influence of pre-planning on the decision to execute a travel as pre-planned or not. The explicative variables considered are: socio-economic characteristics of respondents, travel characteristics, and facets of the activity executed at origin and at destination including the scheduling decisions associated with them. The results demonstrate that a significant correlation exists between the choices of pre-planning and rescheduling for both types of trips. Whether for car driving or walking trips, the scheduling decisions associated with the activity at origin and at destination are the most important explicative factors of the trip scheduling and rescheduling decisions. However, the rescheduling of trips is mainly influenced by modifications in the activity at destination. Some interesting differences arise regarding the rescheduling decision processes between travel modes: if pre-planned, walking trips are less likely to be modified than car driving trips, showing a more rigid rescheduling behavior.     

The trade-off between trips and distance traveled in analyzing the emissions impacts of center-based telecommuting

Several travel indicators were compared between telecommuting (TC) days and non-telecommuting days for a sample of 72 center-based telecommuters in California. Distance traveled decreased significantly on TC days, with average reductions of 51 person-miles (58%) and 35 vehicle-miles (53%). When weighted by telecommuting frequency, average reductions of 11.9% in PMT and 11.5% in VMT were found over a five-day work week. Person-trips and vehicle-trips increased slightly (but not significantly) on TC days. This was due to statistically significant increases in commute trips by telecommuters (who more often went home for lunch on their TC days), partly counteracted by decreases in non-commute travel. The drive-alone mode share increased on TC days, both for all trips, and for commute trips in particular. Walking and biking shares also increased modestly on TC days, whereas shares of transit and ridesharing declined. Despite the increase in trip rates, TC-day reductions were found for all pollutants analyzed: 15% for total organic gas emissions, 21% for carbon monoxide, 35% for oxides of nitrogen, and 51% for particulate matter. The reduction in VMT more than compensated for the marginal increase in number of trips (and consequently, cold starts) on telecommuting days.     

The propensity for motorists to walk for short trips: Evidence from West Edinburgh

The trade-offs individuals make between the motor car and walking for short trips are investigated, using data from a West Edinburgh household survey. Propensity to walk discrete choice models are estimated from a stated preference experiment within the survey questionnaire. This includes segmented models using socio-economic, spatial and attitudinal variables. The relative importance of the three attributes of journey time, petrol cost and parking cost are examined; value of time estimates are also generated. With all other factors remaining constant, for short trips motorists are more likely to walk in response to an increase in parking costs than a rise in petrol prices. The use of parking as a transport policy tool is discussed.     

A simultaneous destination and mode choice model for shopping trips

This paper describes a disaggregate simultaneous destination and mode choice model for shopping trips. Following an introduction to the model structure and a review of the data, the results of five different model specifications are discussed. The models were estimated using data from two communities adjacent to Eindhoven, the Netherlands and utilise the multinomial logit model.     

Modeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon

Transportation - This study investigates the current and potential uptake of ridesourcing services, such as Uber and Careem, by the students of the American University of Beirut, Lebanon. A hybrid...     

A model of daily time allocation to discretionary out-of-home activities and trips

This paper presents a model of discrete activity choice and continuous resource allocation which is based on the premise of random utility maximization and which can be conveniently estimated using existing statistical software packages. The model derivation involves virtually no approximations and adheres strictly to the utility maximization concept. The empirical analysis applies the model to the participation choice and resource (time) allocation to nonwork, out-of-home activities by workers. The statistical results show that activity choice and time allocation are governed by the same mechanism as the utilitarian assumptions indicate and support the theoretical framework employed in the model development.     

Influencing factors and heterogeneity in ridership of traditional and app-based taxi systems

The growth of app-based taxi services has disrupted the urban taxi market. It has seen significant demand shift between the traditional and emerging app-based taxi services. This study explores the influencing factors for determining the ridership distribution of taxi services. Considering the spatial, temporal, and modal heterogeneity, we propose a mixture modeling structure of spatial lag and simultaneous equation model. A case study is designed with 6-month trip records of two traditional taxi services and one app-based taxi service in New York City. The case study provides insights on not only the influencing factors for taxi daily ridership but also the appropriate settings for model estimation. In specific, the hypothesis testing demonstrates a method for determining the spatial weight matrix, estimation strategies for heterogeneous spatial and temporal units, and the minimum sample size required for reliable parameter estimates. Moreover, the study identifies that daily ridership is mainly influenced by number of employees, vehicle ownership, density of developed area, density of transit stations, density of parking space, bike-rack density, day of the week, and gasoline price. The empirical analyses are expected to be useful not only for researchers while developing and estimating models of taxi ridership but also for policy makers while understanding interactions between the traditional and emerging app-based taxi services.

     

Express guideway transit: A case for further development in transit automation

Safe and reliable coupling and decoupling of cars from a moving train is feasible with further developments in linear motor propulsion and control of transit vehicles. This allows the last car of a train to decouple and stop at a station for a relative long dwell time, before it accelerates and is coupled to a following train. Controlled doors in front and rear of the transit vehicle permit passengers to walk through the train to the car which stops at their destination. A proposed transit system using these features is described and compared to Bombardier's Advanced Rapid Transit. Potential advantages are high schedule speed, uncrowded trains, smaller and more stations, low energy requirements and a smaller vehicle fleet.     

北京市轨道交通建设尚需深入研究的课题

目前,北京市在同时建设多条轨道交通线路,建设规模大、工期紧、工法多、周围环境复杂,工程难度大.为了配合新线建设,推进科技创新,提高新线工程建设的施工质量、技术水平和科技含量,一些技术难点问题需要进行研究攻关.文章重点就北京地铁4号、5号、10号线正在研究和有待研究的一些课题的必要性和关键技术问题进行阐述并提出建议,可供参考.