Vehicle Kilometers Traveled Research Articles

Exploring impacts of on-demand ridesplitting on mobility via real-world ridesourcing data and questionnaires

On-demand ridesplitting is a form of ridesourcing where riders with similar origins and destinations are matched to the same driver and vehicle in real time, and the ride and costs are split among users. With the convenience of all kinds of ridesourcing services, the number of ridesplitting passengers increases, which may have a great impact on the urban mobility. In this paper, we analyze ridesplitting behavior and its impact on multimodal mobility, e.g., vehicle kilometers traveled (VKT) and transportation modal shift, using real-world ridesourcing data extracted from an on-demand ride service platform in Hangzhou, China, and questionnaires filled by on-demand ridesplitting passengers. With the consideration of the VKT shifted from non-passenger/private vehicles, this paper uses the saved VKT of two ridesplitting types, e.g., DiDi Hitch and DiDi Express ridesplitting, to quantify the ridesplitting impact. For the whole ridesourcing ecosystem, ridesplitting is estimated to decrease 58,124 VKT per day in Hangzhou, of which Hitch and Express ridesplitting contribute 2175 km and 55,949 km per day, respectively. The saved VKT of Hitch is much smaller than Express ridesplitting for the following two reasons: (1) Hitch orders are fewer than Express ridesplitting; (2) more than half of the Hitch passengers shift modes from bus/metro transit or other non-passenger/private cars. This paper shines some lights on understanding the emerging on-demand ridesplitting behavior and quantifying its impact on multimodal urban mobility.

Forecasting accident frequency of an urban road network: A comparison of four artificial neural network techniques

AbstractConsiderable effort has been made to determine which of the most common prediction modeling techniques performs best, based on crash‐related data. Accordingly, the present study aims to evaluate how crashes in the urban road network are affected by contributing factors. Therefore, in the present paper, a comparison has been done among four artificial neural network (ANN) techniques: extreme learning machine (ELM), probabilistic neural network (PNN), radial basis function (RBF), and multilayer perceptron (MLP). According to the measures used, including Nash–Sutcliffe (NS), mean absolute error (MAE), and root mean square error (RMSE), ELM was found to be the most successful approach in addressing the objectives defined in the present study. Moreover, not only is ELM the fastest algorithm due to its different structure, but it has also led to the most accurate prediction. In the end, the RReliefF algorithm was utilized to find the importance of variables used, including V/C, speed, vehicle kilometer traveled (VKT), roadway width, existence of median, and allowable/not‐allowable parking. It was proved that VKT is the most influential variable in accident occurrence, followed by two traffic flow characteristics: V/C and speed.

TÜRKİYE’DEKİ KARAYOLU TRAFİK KAZALARINDAKİ EĞİLİMLER, 1980-2016

T he objective of this article is to examine the trends of traffic crashes, deaths and injuries in Turkey from 1980 to 2016. A time-series methodology were used to analyze crash trends per 1000 people, 1000 driver, 1000 vehicle and a million vehicle-kilometer traveled (VKT). Furthermore, the association between economic development of Turkey and traffic crashes were explored. The effectiveness of highway investments and traffic enforcement on traffic crashes, deaths and injuries were also discussed. Results shows that even though a dramatic increase is has observed in income, vehicle ownership and VKT in Turkey, road traffic deaths has decreased by 17% in the last 26 years. However, crashes and injuries has continued to increase, and death rates are still higher than rates in the European Union (EU) countries.

Beijing’s Peak Car Transition: Hope for Emerging Cities in the 1.5 °C Agenda

Peak car has happened in most developed cities, but for the 1.5 °C agenda the world also needs emerging cities to go through this transition. Data on Beijing shows that it has reached peak car over the past decade. Evidence is provided for peak car in Beijing from traffic supply (freeway length per capita and parking bays per private car) and traffic demand (private car ownership, automobile modal split, and Vehicle Kilometres Travelled per capita). Most importantly the data show Beijing has reduced car use absolutely whilst its GDP has continued to grow. Significant growth in electric vehicles and bikes is also happening. Beijing’s transition is explained in terms of changing government policies and emerging cultural trends, with a focus on urban fabrics theory. The implications for other emerging cities are developed out of this case study. Beijing’s on-going issues with the car and oil will remain a challenge but the first important transition is well underway.

The influence of the built environment on household vehicle travel by the urban typology in Calgary, Canada

Most land use and travel studies have addressed the area-wide impact of land use and transportation policies on vehicle travel, yet few studies have examined the varying impact of those policies on vehicle travel in different spatial settings. The aim of this study is to investigate how land use and transportation factors influence household vehicle travel in Calgary according to the city's urban typology, defined by its development form and functions in Calgary's Municipal Development Plan (MDP). This study employed a segmented regression method, also known as a piecewise regression, to examine the impact of various land use and transportation characteristics on household vehicle kilometers of travel (VKT) in four areas of the city including the center city, inner city, established area, and greenfield sector. The main data sources for the study include the 2011 Calgary and Region Travel and Activity Survey (CARTAS) in conjunction with spatial datasets from the City of Calgary. There is no additional benefit of VKT reduction in the center city found by the intensification efforts tested in this study. However, densification and provision of light rail transit (LRT) may be key to reducing household vehicle travel in the established area and greenfield sector of Calgary. The study results also suggest that households tend to drive significantly more as they live further from the center city, where more than half of the city's employment is clustered. This implies the need to have sub-centers across the city.

How do the effects of local built environment on household vehicle kilometers traveled vary across urban structural zones?

ABSTRACTMany studies have examined the effects of the local built environment (LBE) on household car usage. However, it remains unclear how these effects vary across urban structural zones. This study examines the case of Shenzhen and employs a multigroup structural equation model to reveal the varying LBE effects among car-owning households in inner-city, inner-suburban, and outer-suburban zones. The empirical modeling results indicate that the distance from the residence to the city center and the work-home distance have the greatest influence on household vehicle kilometers traveled (VKT). Average household VKT decreases with the distance from the residence to the city center after it peaks at the threshold radius distance of 8–10 km to the city center. In general, dense, mixed, small-block land use patterns reduce household VKT. However, the magnitude and significance of the LBE effects on household VKT vary across urban structural zones. These findings suggest that land-use policies can be developed specifically for different urban structural zones to effectively decrease household VKT.

The German Vehicle Mileage Survey 2014: Striking the balance between methodological innovation and continuity

Abstract Vehicle kilometers travelled (VKT) directly reflect the extent of spatial interaction within society and economy. VKT is also a key figure to quantify the use of road infrastructure. Consequently, VKT is one of the most important statistical indicators in traffic and transport. For a country with substantial cross-border transport relations such as Germany, VKT must be differentiated in national and domestic VKT: national VKT is the mileage of vehicles registered in Germany while domestic VKT is the mileage on German territory by German and foreign vehicles. This paper presents the most current German VKT survey, Fahrleistungserhebung (FLE) 2014, which comprised two elements: a motor vehicle owner survey to measure national VKT and traffic counts to measure domestic VKT. Vehicle mileage figures with deep stratification of both national and domestic VKT can only be generated through such special empirical studies. The focus of this paper is on the vehicle owner survey and national VKT.

Would the replacement of park-and-ride facilities with transit-oriented development reduce vehicle kilometers traveled in an auto-oriented US region?

One often sees large park-and-ride (P&R) facilities surrounding major transit stations. These parking facilities provide a practical way to increase ridership, but it is less clear how well they serve broader sustainability goals. For example, using scarce station area land for transit-oriented development (TOD) rather than parking may provide a better approach to reducing vehicle kilometers travelled (VKT). This research represents an effort to explore the relative VKT reduction associated with P&R as compared to TOD. A survey of transit users in Charlotte, NC is used to estimate the VKT generated by users of P&R facilities at light rail stations. The estimated VKT is then compared to the VKT that is predicted to occur under hypothetical scenarios in which these parking facilities are replaced with TOD. At four of the seven stations examined in this study, replacing a P&R facility with a moderately dense housing (100 units per hectare) is predicted to result in a net VKT reduction. On the other hand, there is no feasible scenario in which a net VKT reduction can be achieved by replacing the suburban terminal parking structure with TOD. To the degree that VKT reduction is an important outcome of transit provision, the results of this research indicate that conversion of P&R to TOD (or forgoing P&R in the first place) should receive strong consideration at some stations, even in highly auto-oriented contexts such as Charlotte.

THE INTERPLAY OF SPATIAL POLICY, TRAVEL BEHAVIOUR AND AIR QUALITY IN ISKANDAR MALAYSIA

Iskandar Malaysia has been emerging as a centre of economic growth in the southern corridor of Malaysia. While the present spatial policy has emboldened the growth centre that inspires the urban development in the region to flourish, the spatial development has brought a substantial environmental consequence to urban areas. With the support of travel behaviour of the citizens as a catalyst, the interplay between spatial policy and urban air quality in the region becomes a major concern. This study began by undertaking spatial policy analysis at local and federal levels. Then, an origin-destination study was carried out to assess the travel behaviour of citizens and the concentricity or poly-centricity of the region as an eventual reflection of spatial policy. Based on the information on travel behaviour and number of vehicles in Iskandar Malaysia, the vehicle-kilometre travelled (VKT) was estimated as well as the carbon emission from the transport sector. An ethnographic survey was also conducted to understand the nonmotorized travel behaviour of the citizens i.e. willingness to walk. This survey was to crosscheck and confirm the willingness to walk of the citizens resulting from questionnaire survey. Results of the study reveal that the spatial policies of Iskandar Malaysia along with the travel behaviour of the citizens have strongly shaped the present spatial structure of Iskandar Malaysia region, and ultimately lead to ever increasing air pollution in the region.

THE INTERPLAY OF SPATIAL POLICY, TRAVEL BEHAVIOUR AND AIR QUALITY IN ISKANDAR MALAYSIA

Iskandar Malaysia has been emerging as a centre of economic growth in the southern corridor of Malaysia. While the present spatial policy has emboldened the growth centre that inspires the urban development in the region to flourish, the spatial development has brought a substantial environmental consequence to urban areas. With the support of travel behaviour of the citizens as a catalyst, the interplay between spatial policy and urban air quality in the region becomes a major concern. This study began by undertaking spatial policy analysis at local and federal levels. Then, an origin-destination study was carried out to assess the travel behaviour of citizens and the concentricity or poly-centricity of the region as an eventual reflection of spatial policy. Based on the information on travel behaviour and number of vehicles in Iskandar Malaysia, the vehicle-kilometre travelled (VKT) was estimated as well as the carbon emission from the transport sector. An ethnographic survey was also conducted to understand the nonmotorized travel behaviour of the citizens i.e. willingness to walk. This survey was to crosscheck and confirm the willingness to walk of the citizens resulting from questionnaire survey. Results of the study reveal that the spatial policies of Iskandar Malaysia along with the travel behaviour of the citizens have strongly shaped the present spatial structure of Iskandar Malaysia region, and ultimately lead to ever increasing air pollution in the region.

Effects of additional capacity on vehicle kilometers of travel in the U.S.: Evidence from National Household Travel Surveys

Adding capacity is one policy mechanism to alleviate congestion. However, the empirical evidence strongly suggests that additional capacity only makes congestion worse. This study analyzes the differential effects of additional freeway capacity versus additional arterial capacity on vehicle kilometers of travel (VKT) in metropolitan areas across the U.S. The analysis uses vehicle data and household data from the 2001 and the 2009 National Household Travel Surveys (NHTS) and includes stock and flow measures of road capacity, road congestion, commuter demand, and economic growth for metropolitan areas. Taking into account differences between metropolitan areas on each measure, the study adopts a novel multilevel model approach to estimate how additional capacity affects VKT. Results indicate that adding more arterial capacity slightly decreases VKT over a lag period from six years (1995 to 2001) to eight years (2001 to 2009), probably because adding arterials shortens routes between origins and destinations more so than adding freeways. Consistent with expectations, VKT is lower in more congested metropolitan areas, and in metropolitan areas that got more congested. Results also indicate that rebound effects (higher fuel-economy vehicles are driven much more than lower fuel-economy vehicles) will at least partially offset the demand management benefits of (gasoline) price sensitivity (higher gasoline prices decrease VKT).

Exploring car ownership and car use in neighborhoods near metro stations in Beijing: Does the neighborhood built environment matter?

Public transport services are believed to play an important role in constraining car use. However, it has been found that cars are still used at high rates near many metro stations. This paper aims to explore car ownership and car use in people living close to metro stations. Taking Beijing, China, as a case study, this study shows that the likelihood of owning a car, and the number of work and non-work vehicle kilometers traveled (VKT), is lower in areas with higher mixed land use. Residents’ income and family structure both affect VKT. People with an awareness of sustainable land use and transportation modes use fewer VKT. The study also has some interesting new findings in the Chinese context. It found that residential density was not significantly related to VKT. Interestingly, neighborhood type was firmly associated with car ownership and use: those who live in Danwei neighborhoods generated more work VKT, and those living in indemnificatory neighborhoods used more non-work VKT. Additionally, renters were less likely to own cars than house owners, and people with Beijing hukou generated more VKT. People preferring to live in close proximity to the metro system and travel by foot were more likely to own cars in the future than other people. The results suggest that increasing land use diversity and the accessibility of living amenities in neighborhoods near metro stations could enhance the performance of transport systems by reducing dependence on cars. Housing and transport policies, along with behavior-education programs, could strengthen this effect.

Vehicle kilometers traveled reduction impacts of Transit-Oriented Development: Evidence from Shanghai City

The role of residential self-selection has become a major subject in the debate over the relationships between the built environment and travel behavior. Numerous previous empirical studies on this subject have provided valuable insights into the associations between the built environment and travel behavior. However, the vast majority of the studies were conducted in North American and European cities; yet this research is still in its infancy in most developing countries, including China, where residential and transport choices are likely to be more constrained and travel-related attitudes quite different from those in the developed world. Using the data collected from 2038 residents currently living in TOD neighborhoods and non-TOD neighborhoods in Shanghai City, this paper aims to partly fill the gaps by investigating the causal relationship between the built environment and travel behavior in the Chinese context. More specifically, this paper employs Heckman’s sample selection model to examine the reduction impacts of TOD on personal vehicle kilometers traveled (VKT), controlling for self-selection. The results show that whilst the effects of residential self-selection are apparent; the built environment exhibits the most significant impacts on travel behavior, playing the dominant role. These findings produce a sound basis for local policymakers to better understand the nature and magnitude toward the impacts of the built environment on travel behavior. Providing the government department with reassurance that effective interventions and policies on land use aimed toward altering the built environment would actually lead to meaningful changes in travel behavior.

Refined 2013-based vehicle emission inventory and its spatial and temporal characteristics in Zhengzhou, China

Vehicle emission is becoming one of the most important pollution sources because of the increase in vehicle population and activity in China. A more reasonable and complete vehicle emission inventory in Zhengzhou for the year 2013 was developed in this study. This inventory is suitable for local emission factors and vehicle kilometers of travel. Estimates show that the total carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOX), particulate matter (PM2.5 and PM10) and sulfur dioxide (SO2) emissions were 291Gg, 35Gg, 106Gg, 6Gg, 7Gg, and 3Gg, respectively. Approximately 55% of CO and HC emissions were from light duty gasoline vehicles and normal gasoline motorcycles, whereas approximately 60% of NOX, PM2.5, PM10 and SO2 were from heavy duty diesel vehicles, heavy duty diesel trucks, and medium duty diesel trucks. The spatial distribution of emissions was allocated in grid cells based on a road network and traffic flows with a resolution of 1km×1km at different road types and locations, which shows that the six aforementioned air pollutants have similar characteristics in administrative districts. Emissions are mainly concentrated on the central grid cells of each part and in good agreement with line sources. The spatial characteristics were compared at a resolution of 3km×3km and in a population-based approach. The network approach yields better level estimates in this study. Meanwhile, the preliminary temporal profiles were also established for on-road mobile source.

Effects of a tradable credits scheme on mobility management: A household utility based approach incorporating travel money and travel time budgets

We investigate the influence of a new mobility management measure, the tradable credits scheme (TCS), on the daily travel mode choices of individuals. Generally, we assume the individuals’ travel consists of different modes, e.g. private car mode and mass transit mode. In order to control the rapid increase in use of the private car mode in an area, policy makers may wish to implement a TCS basing on the vehicle kilometre travelled (VKT). The effects of the TCS are investigated in this paper based on a utility-theory travel demand model proposed by Golob et al. (1981), a household utility based model incorporating proposed travel money and travel time budgets. The empirical investigation is based on comparison studies of the short-term response and long-term effects with and without TCS. It finds that the implementation of TCS has not a clear impact to the value of time of household in the short-term, and the presence of TCS does not affect the linear relationship between travel time budget and travel money budget over long term. Numerical results demonstrate that the TCS will affect the travel distance of the available transport modes differentially, according to different levels of annual household income.

On the distribution of individual daily driving distances

Plug-in electric vehicles (PEV) can reduce greenhouse gas emissions. However, the utility of PEVs, as well as reduction of emissions is highly dependent on daily vehicle kilometres travelled (VKT). Further, the daily VKT by individual passenger cars vary strongly between days. A common method to analyse individual daily VKT is to fit distribution functions and to further analyse these fits. However, several distributions for individual daily VKT have been discussed in the literature without conclusive decision on the best distribution. Here we analyse three two-parameter distribution functions for the variation in daily VKT with four sets of travel data covering a total of 190,000 driving days and 9.5 million VKT. Specifically, we look at overall performance of the distributions on the data using four goodness of fit measures, as well as the consequence of choosing one distribution over the others for two common PEV applications: the days requiring adaptation for battery electric vehicles and the utility factor for plug-in hybrid electric vehicles. We find the Weibull distribution to fit most vehicles well but not all and at the same time yielding good predictions for PEV related attributes. Furthermore, the choice of distribution impacts PEV usage factors. Here, the Weibull distribution yields reliable estimates for electric vehicle applications whereas the log-normal distribution yields more conservative estimates for PEV usage factors. Our results help to guide the choice of distribution for a specific research question utilising driving data and provide a methodological advancement in the application of distribution functions to longitudinal driving data.

Joint charging mode and location choice model for battery electric vehicle users

This paper aims to investigate the choice for charging mode and location with the revealed preference data of battery electric vehicle (BEV) users in Japan. Three alternatives including the normal charging at home (for private BEVs)/company premise (for commercial BEVs), normal charging at public charging stations and fast charging at public charging stations are defined. A mixed logit model is developed to investigate what and how factors influence BEV users’ choice of charging mode (normal or fast) and location (home/company or public stations), by identifying an appropriate instrumental variable to correct the serious endogeneity problem caused by the midnight indicator. The parameters estimation and results interpretation are conducted for private and commercial BEVs respectively. They suggest that the battery capacity, midnight indicator, initial state of charge (SOC) and number of past fast charging events are the main predictors for users’ choice of charging mode and location, that the day interval between current charging and next trip positively affects the normal charging at home/company. In addition, with the increasing of vehicle-kilometres of travel (VKT)/travel duration on former/next travel day, the probability of normal charging at home/company is increased for commercial BEVs, while is decreased for private BEVs. The findings obtained herein have provided new insights into the realization of power peak-load shifting and operation strategy for public charging stations, as well as inspired the development and application of new models and methodologies to determine the density and deployment of public charging stations.

Emission inventory of trace gases from road transport in India

In India, road transport sector is one of the major anthropogenic contributor of GHGs and other pollutants into the atmosphere which have significant adverse human health effects. National and state level pollutants’ emissions from road transport in India have been estimated by using VKT approach for the period of 2001–2013 which includes the values of average vehicle kilometres travelled (VKT) by different vehicle types and emission factors (EF) for different vehicle types. The results revealed a Compound Annual Growth Rate (CAGR) of 8.5%, 8.5%, 8.1%, 8.3%, 8.4%, 8.2% and 9% respectively of carbon dioxide (CO2), methane (CH4), nitrogen oxides (NOx), carbon monoxide (CO), sulphur dioxide (SO2), particulate matters (PM) & hydrocarbon (HC) emissions from vehicles in road transport sector during the periods 2001–2013 due to increase of vehicle population. The study also showed a negative temporal trend in the CO2 emissions per unit of GDP indicating reduced CO2 emission intensities in transport sector. Statewise emission estimates from different vehicle categories confirmed that states like Maharashtra, Gujarat, Tamil Nadu, Kerala, Uttar Pradesh, Rajasthan, Andhra Pradesh, Karnataka and Delhi are responsible for about 68% of total emissions of CO2, CO, CH4, NOx, SO2, HC and PM.

Does the Use of Smartphone Influence Travel Outcome? An Investigation on the Determinants of the Impact of Smartphone Use on Vehicle Kilometres Travelled

Abstract This paper investigates the impact of smartphone on travel outcome that uses data from a web-based survey conducted in Halifax Regional Municipality, Nova Scotia in 2015. Following a Latent Class Modelling (LCM) Approach, the study analyses the change in vehicle kilometres travelled (VKT) as an influence of smartphone use and how this change differentiates among different socio-demographic groups, residential locations and life-style strata.Vehicle kilometres travelled has been examined on three choice contexts: smartphone use had i) reduced VKT ii) no impact on VKT and iii) increased VKT. The model identifies two classes based on socio-demographic characteristics where Class 1 can be characterized as student and young professionals, whose annual income is less than CAD 15K, female population with part-time or full-time employment and who are not full-time student. To facilitate the discussion, Class 1 has been branded as ‘Tech-Savvy’ and Class 2 of the model as ‘Non Tech-Savvy’. Results suggest that variation exists between Tech-Savvy and Non Tech-Savvy group. For example, in the Tech-Savvy group, the novice smartphone users have less probability of reduction in kilometres travelled compared to the other group, whereas in the Non Tech-Savvy group, the probability of substitution increases for the novice users. Determinants that can reduce VKT because of smartphone use are: higher use of smartphones for online shopping, active transportation as primary mode, home to work/school distance, pro-environment attitude, etc. This study offers important insights and could be useful for transport policy making.

Improved Binning of Operating Modes in EPA Simulator Program for Transit Buses: Case Study in Beijing

The Motor Vehicle Emissions Simulator (MOVES) quantifies emissions as a function of the operating mode (opmode) and emissions rates. The opmode, the determinant parameter in estimating emissions, is defined by two critical parameters: speed and scaled tractive power (STP). Activity characteristics of transit buses are commonly recognized as being quite different from those of other vehicles, and this study found the values of the two parameters for transit buses to be much smaller than those for other vehicles. However, the MOVES program uses an identical opmode binning method for transit buses and other vehicles, a method that likely leads to errors in emissions estimations for transit buses. This paper developed a binning method based on massive field data collected in Beijing to improve the opmode binning for transit buses. To this end, STP fractions, vehicle kilometers traveled (VKT) fractions, and emissions contributions were first investigated. The STP values were grouped into nine bins on the basis of analysis of emissions rates and emissions contributions. Three speed bins were then determined with the hierarchical clustering method and the averaging of VKT fractions. As a result, 29 opmode bins were defined for transit buses. Finally, the proposed method was applied to real-world emissions data in Beijing. The results indicated that the proposed binning method could reduce errors in emissions estimation errors. On average, the relative errors in estimating carbon dioxide, carbon monoxide, nitrogen oxide, and hydrocarbon emissions by the proposed method were 2.0%, 5.9%, 1.6%, and 1.5% lower, respectively, than errors made by the MOVES method.