•Exploring the real-time ramp crash occurrences using various parameters.•Real-time safety analysis used trip Generation and socio-demographic predictors.•The percentage of home-based-work production ...had positive impact on crash risk.•Support Vector Machines model with all variables might have an overfitting problem.
There have been numerous studies on real-time crash prediction seeking to link real-time crash likelihood with traffic and environmental predictors. Nevertheless, none has explored the impact of socio-demographic and trip generation parameters on real-time crash risk. This study analyzed the real-time crash risk for expressway ramps using traffic, geometric, socio-demographic, and trip generation predictors. Two Bayesian logistic regression models were utilized to identify crash precursors and their impact on ramp crash risk. Meanwhile, four Support Vector Machines (SVM) were applied to predict crash occurrence. Bayesian logistic regression models and SVMs commonly showed that the models with the socio-demographic and trip generation variables outperform their counterparts without those parameters. It indicates that the socio-demographic and trip generation parameters have significant impact on the real-time crash risk. The Bayesian logistic regression model results showed that the logarithm of vehicle count, speed, and percentage of home-based-work production had positive impact on crash risk. Meanwhile, off-ramps or non-diamond-ramps experienced higher crash potential than on-ramps or diamond-ramps, respectively. Though the SVMs provided good model performance, the SVM model with all variables (i.e., all traffic, geometric, socio-demographic, and trip generation variables) had an overfitting problem. Therefore, it is recommended to build SVM models based on significant variables identified by other models, such as logistic regression.
The subsidy level of public transport systems varies considerably among systems worldwide. While limited-scale free-fare public transport (FFPT) services such as limited campaigns and fare evasion ...for special groups or specific services are prevalent, there is only limited evidence on the consequences of introducing a full-fledged FFPT. The case of Tallinn, Estonia offers a full-scale experiment that provides a unique opportunity to investigate the impacts of FFPT. This study examines travel pattern changes based on individual travel habit survey shortly before and almost 1 year after the introduction of FFPT policy in Tallinn based on interviews and travel diaries of a random sample of 1500 household. We analyse modal shift effects and whether they are driven by trip generation or trip substitution, travel attitudes and satisfactions as well as impacts on equity, employment prospects, and trip destination choices. Almost a year after the introduction of FFPT, public transport usage increased by 14 % and there is evidence that the mobility of low-income residents has improved. The effect of FFPT on ridership is substantially lower than those reported in previous studies due to the good level of service provision, high public transport usage and low public transport fees that existed already prior to the FFPT.
This paper investigates the spatial demand for bikesharing through the application of a series of trip generation models for the London Bicycle Sharing Scheme (LBSS). The production of trips from and ...the arrival of trips at scheme stations are evaluated in reference to how they connect with features of the built environment, demographics of the resident and workplace populations, and attributes of the scheme's structure. A spatial econometrics approach is taken to specify the models, with four different time windows considered throughout the day for all trips taken during 2016. The built environment features show a consistent pattern of results in the model, indicating that proximity to cycling infrastructure, rail stations, parks, university facilities, as well as the density of shops and conventional roads in the vicinity of stations is linked with trip generation rates. The presence of males and Caucasians are associated with higher station demand, aligning with other work on the introduction of new mobility solutions elsewhere, though we do find that greater distances to work tend to depress use. Trip generation is also reduced at the minority of stations located south of the River Thames, indicating that the presence of natural barriers can affect the operation of schemes. The results carry implications for scheme integration in other cities.
•Spatial demand for bikeshare exhibits clear spatial clustering in demand levels.•Proximity to cycling infrastructure is linked with higher trip rates.•Co-locating stations near attractors (e.g. rail and retail) can boost demand.•Male resident and white (ethnic) resident populations more inclined to use the scheme.•Natural barriers such as rivers can inhibit scheme demand.
•The paper analyses the implications of data aggregation on freight trip generation.•Constant estimations (on activity and activity-workforce categories) are provided.•Functional form models on ...activity categories are also assessed.•Functional form models are in general more accurate than only constant FTG rates.•The choice of the functional form is more relevant than that of the categorization.•Results have important impacts in data collection and FTG estimation in practice.
This paper analyzes the impacts of aggregation level and category construction on the relevance and quality of freight trip generation (FTG) models. More precisely, constant generations and functional form models are compared, as well as activity and activity-workforce categories. The paper proposes a method to compare constant generation and functional form models on different category classifications based on MAPE estimations. Functional forms are assessed via linear regression and compared using Pearson coefficient. Results show that the aggregation level has not always a positive impact on the model’s accuracy and the choice of suitable functional form leads to more accurate models.
Purpose
This paper assesses the parking needs of freight and service related commercial activities and identifies the role of demand management in mitigating these needs.
Methods
To provide a context ...for the analyses, the authors selected two small commercial areas of about the same number of commercial establishments—one in Troy, NY, and the other in New York City—and applied freight and service trip generation models to estimate the total freight and service traffic generated at these sites. Then, using different assumptions of the amount of time these vehicles spend at a parking location, the authors estimated the number of parking spaces required by time of day under different assumptions of demand management.
Results
The results show that parking needs are proportional to the average parking durations. Essentially, the longer the duration the higher the parking needs. In terms of impacts on demand management, the results show that the 100% Off-Hour Deliveries (OHD) program is expected to be the most impactful as it reduces the parking needs by 70–80% during peak hours. In second place, Staggered Deliveries reduces parking needs by about 60% during the peak hours. The third place is occupied by the 30% OHD Scenario and the Receiver-Led Consolidation programs, which are virtually tied, offering about 10–25% reduction.
Conclusions
The initial analysis revealed the importance of parking duration as it was shown to be proportional to parking needs; the longer the duration the higher the need for parking. The delivery simulation further bolstered this finding by showing that the optimal case occurs (i.e. minimizing parking duration) the closer the parking location is to the establishment. The further away the vehicle is parked the longer the walking time to the establishment, hence increasing the time the vehicle occupies the parking spot. The strategies applied to the case studies showed that Transportation Demand Management (TDM) strategies are effective in decreasing the number of parking spots needed during peak periods.
When a disturbance acts on a fiber it induces a change in the local refractive index that influences the fiber backscattering trace. If a chirped pulse Formula Omitted-OTDR setup is used to ...interrogate the fiber, this refractive index change appears as a local shift of the received trace, linear to the acting perturbation. However, the refractive index change influences the round trip time of all the backscattering components generated by further fiber sections as well. Due to the high sensitivity of chirped pulse Formula Omitted-OTDR, the change in the round trip time of the backscattering components, which is usually negligible, may appear as a virtual perturbation in certain conditions. In this letter we derive a mathematical model for the virtual perturbation induced by a disturbance acting on the fiber, when the measurement is performed by a chirped pulse Formula Omitted-OTDR. We experimentally validate the model by inducing a temperature change on a known span of fiber while monitoring its effects in a further fiber section kept at rest. The experimental results are then analyzed and compared with the theoretical ones.
The travel accessibility problems resulted from the lack of transportation facilities and socioeconomic opportunities. These are often called travel impedances. At remote locations, the travel ...impedances severely affect the decision-making processes of households to satisfy basic needs. Thus, this study aims to highlight the impedance factors of rural households, using the trip generation regression model as an optimum accessibility measure. The study area was selected as Badin, the deprived subregion of southern Pakistan. Pakistan is the 5th most populous country in the world recently beating Brazil. More than 60% of Pakistan’s total population is living in rural areas without essential transportation services. The truancy of a rural transport policy can be said as one of the reasons behind the vulnerability of rural Pakistan. Hence, the household’s trip purposes were anticipated to the income, size, distance, and travel time. With the help of cluster sampling, the questionnaire survey was performed from a random sample of 100 households. The model, regional household trips by purpose (RT
p
), revealed strong-positive correlation values of
R
= 0.998 and
R
2
= 0.997. The larger household size and lower household income were found as acute impedances compared to travel time and distance. In other words, the higher population size and lack of economic opportunities were reported as the main findings of this study. This research deliberated the concept of a trip generation that is rarely executed to underline impedances of rural households. The study's findings can assist transport planners to formulate policy proposals for not only rural subregions but also urban centers of developing and developed countries.
Time-dependent patterns in freight trip generation Holguín-Veras, José; Ramirez-Rios, Diana; Pérez-Guzmán, Sofía
Transportation research. Part A, Policy and practice,
06/2021, Volume:
148
Journal Article
Peer reviewed
This paper summarizes the research conducted by the authors to investigate time-dependent patterns in Freight Trip Generation (FTG). As part of the research, the authors estimated econometric FTG ...models as a function of establishment attributes and temporal variables, using multi-year establishment-level data collected during the period 2005–2014. These unique data—encompassing the period of economic turmoil around the 2008 collapse of Wall Street, and the period of recovery that followed—were collected in New York City from commercial establishments in various industry sectors. The comprehensive modeling effort undertaken considered four different functional forms, two combinations of establishment characteristics, two different metrics of time, and eleven different industry sectors defined by two-digits North-America Industry Classification System (NAICS). The resulting models were analyzed to assess the extent and magnitude of the time-dependent effects on FTG for the industry sectors in the sample. In its final sections, the paper discusses the implications for transportation planning and policy and summarizes the chief findings of the effort.
City governments and planners alike commonly seek to increase pedestrian activity on city streets as part of broader sustainability, community building, and economic development strategies. Though ...walkability has received ample attention in planning literature, most planners still lack practical methods for predicting how development proposals could affect pedestrian activity on specific streets or public spaces at different times of the day. Cities typically require traffic impact assessments (TIAs) but not pedestrian impact assessments. In this study I present a methodology for estimating pedestrian trip generation and distribution between detailed origins and destinations in both existing and proposed built environments. Using the betweenness index from network analysis, I introduce a number of methodological improvements that allow the index to model pedestrian trips with parameters and constraints to account for pedestrian behavior in different settings. I demonstrate its application in the Kendall Square area of Cambridge (MA), where estimated foot traffic is compared during lunch and evening peak periods with observed pedestrian counts.
The proposed approach can be particularly useful for TIAs, neighborhood plans, and large-scale development projects, where pedestrian flow estimates can be used to guide pedestrian infrastructure and safety improvements and public space investments or for locating pedestrian priority streets during the COVID-19 pandemic.
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