Addressing the \u201cminimum parking\u201d problem for on-demand mobility

Electric vehicles (EVs) are viewed as a key pathway to reducing greenhouse gas emissions. However, their environmental benefits depend on whether their vehicle kilometers traveled (VKT) substitute for travel by internal combustion engine vehicles (ICEVs) rather than generating additional travel demand. This review synthesizes evidence from 34 empirical studies examining VKT by battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), comparing them with ICEVs and identifying the factors that shape EV usage. Across studies, BEVs and PHEVs generally travel fewer kilometers per day than ICEVs, with BEVs showing the lowest VKT levels. Regional differences are evident: BEVs in Europe typically record higher VKTs than those in the US. VKT patterns are influenced by a combination of socio-demographic, spatial, and vehicle-related factors, as well as EV-specific elements such as charging access and ownership type. Leased and company EVs typically travel more kilometers than privately owned vehicles, and greater access to charging is generally associated with higher electric VKT. Most studies included in this review draw on data from the early phases of EV adoption and focus on a limited set of regions. As a result, current findings may not fully capture emerging VKT patterns as EV markets scale and diversify. Future research should incorporate more recent and geographically varied datasets to track evolving travel behaviors and better assess how EVs are reshaping mobility and sustainability outcomes.

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.

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

In the United States, most emissions modeling is done using the MOBILE suite of programs. One of the inputs required is vehicle kilometers of travel (VKT) for each vehicle class as a function of average speed. This information traditionally has been obtained from macroscopic planning models whereby the average speed on a given length of roadway is the same for all vehicle classes. During the past 10 years, however, there has been a definite shift away from macro-level transportation modeling to a more simulation-based approach. In addition to the advances in modeling techniques, the advent of intelligent transportation systems (ITS) has opened numerous possibilities for capturing detailed transportation-related information. The purpose of this paper is to illustrate the trade-offs involved under different aggregation scenarios for estimating vehicular emissions using data sets produced by microsimulation models and ITS. A 22-km section of Interstate 10 in Houston, Texas, was used as the test bed in this study. The VKT and speed data for this corridor were determined using a calibrated TRANSIMS model. This information was then used with the MOBILE5a emission model to compute emission estimates. The vehicular emissions were determined for a broad range of spatial, temporal, and combined spatial and temporal levels of disaggregation. It was found that emission estimates could vary by as much as 20 percent, depending on how the VKT and speed data are determined or depending on the type of ITS data-collection technology used.

Exploring parking choices under the coexistence of autonomous and conventional vehicles

Autonomous Mobility-on-Demand (AMoD) systems hold potential promise for addressing urban mobility challenges. Their key principle is to utilize fleets of shared self-driving vehicles to respond to customer demand on flexible routes in real-time. This research investigates station-based AMoD car-sharing systems and uses scenario analyses to identify plausible future paths for their deployment. A traffic simulation model which implements real-time rebalancing of idle vehicles is developed to evaluate their performance under uncertain travel demands. Unlike other literature which assumed homogeneous demand and resulted in low increases in vehicle kilometers travelled (VKT), this study relied on realistic heterogeneous demand and showed a significant increase in VKT. A case study for Melbourne demonstrated the impacts and showed that while AMoD can meet the demand for travel using only 16% of the current vehicle fleet, they would produce 77% increase in VKT. This would significantly increase congestion in any real-world scenario and goes against the hype of AMoD being the answer to congestion problems.

This article presents an empirical estimation of the effect of fuel prices on vehicle kilometers traveled (VKT) using a panel dataset of 1560 Swiss households over the period 2018–2021. Elasticities are estimated for different segments of households, based on their socio-demographic and vehicle characteristics, as well as on their driving intensity. Our results, based on fixed-effect, instrumental variable, and quantile regression models, indicate relatively large price elasticities and reveal heterogeneity in price sensitivity. Single-member households appear significantly more responsive to price than multiple-member households. Travel-intensive households do respond to changes in gasoline price, while less intensive drivers do not exhibit statistically significant price elasticities. For household segments who do not react to price, tailored non-price measures would be a useful complement to fuel taxes in order to reduce distance traveled and/or avoid imposing too strong a financial burden.

The vehicle kilometers traveled (VKT) is an important factor need to be considered in urban freight transport or logistics planning. At present, some quantitative models have been constructed to estimate the VKT, and study also indicates that the time window of vehicle working hours have great effects on the length of urban distribution trips. But there is no VKT estimate models include the window time factor until now. So we introduced a two dimensional orders density: time dimension and space dimension. Then the density is substituted into the Figliozzi’s model, and after a series mathematic derivation, we get a new VKT estimate model considered the window time of vehicle, which is closer to reality station.

Activity-based travel demand models (ABMs) have the capacity to represent emerging activity dimensions; however, they lack integration of physical and virtual activity spaces. This study introduces a novel ABM framework that captures the dynamic interactions between physical–virtual activity spaces and implements it within an integrated transport, land-use, and emission framework. The study develops information and communication technology (ICT) adoption models, such as internet access and device ownership, into the agent-based structure. Markov chain Monte Carlo (MCMC) and conditional probability algorithms are utilized to schedule activities in physical and virtual environment reflecting factors, such as work arrangements, employment status, mobility and ICT tool ownership. Comprehensive calibration and validation processes are performed to ensure that the model can generate population mimicking real-world conditions. A prototype version of the model is implemented for the Halifax Regional Municipality (HRM), Canada. A scenario simulation is conducted that examines the impacts of ICT tool and virtual work adoption on activity-travel patterns. Results show that increased ICT tool adoption significantly boosts the duration of virtual maintenance and discretionary activities while reducing time spent on mandatory activities. A 10% rise in virtual work reduces vehicle kilometers traveled (VKT) in HRM by 51,800 km/day and lowers carbon dioxide (CO 2 ) emissions by 6.216 metric tons/day. The study confirms the complex, nonlinear impacts of ICT on travel, while showing the potential of virtual-work in reducing peak-hour travel and VKT. The developed tools in this study can aid policymakers in assessing the impacts of virtual activities on transport and land use systems and help achieve regional sustainability goals.

Emissions from mobile sources have become a major concern for health, environmental sustainability and climate change and high-resolution inventories are needed to support the design and assessment of abatement measures in urban areas. This study addresses the development of a traffic emissions inventory for Guayaquil, the second largest city in Ecuador, using the International Vehicle Emissions Model (IVE). Emissions are allocated with a spatial resolution of 1 km × 1 km and a temporal resolution of 1 h using a top-down methodology. This application combines traffic statistics already available in the city with the data from a field campaign to characterize vehicle fleet composition and activity patterns. The estimated annual emissions for the city were 237.1 kt of CO, 46.4 kt of NOx, 28.5 kt of VOC, 7.7 kt of PM10, 0.70 kt of SO2 and 4549.7 kt of CO2. 92.3 % of CO and 85.4 % of VOC were emitted by light gasoline vehicles, including private passenger vehicles and taxis, which represents 68.6 % and 8.8 %, respectively of the total fleet and contributes 52 % and 22 % of the total vehicle kilometer traveled (VKT), respectively. 48.9 % of NOx and 82 % of PM10 were emitted by the bus fleet although buses only represent 7.5 % of the total fleet and contribute 10.6 % of total VKT in the city. 41.1 % and 36.5 % of CO2 were emitted by buses and private vehicles, respectively. Even though, the average age of the fleet is below 10 years, the fleet in Guayaquil presents outdated emission standards and high emission factors. We found the higher emission rates in dense populated areas are associated to secondary roads. There is not much variability of emissions between months, but the typical daily pattern of emissions shows a peak in the morning and another in the afternoon.

Abstract. Volatile organic compound (VOC) species from vehicle exhausts and gas evaporation were investigated by chassis dynamometer and on-road measurements of nine gasoline vehicles, seven diesel vehicles, five motorcycles, and four gas evaporation samples. The secondary organic aerosol (SOA) mass yields of gasoline, diesel, motorcycle exhausts, and gas evaporation were estimated based on the mixing ratio of measured C2–C12 VOC species and inferred carbon number distributions. High aromatic contents were measured in gasoline exhausts and contributed comparatively more SOA yield. A vehicular emission inventory was compiled based on a local survey of on-road traffic in Shanghai and real-world measurements of vehicle emission factors from previous studies in the cities of China. The inventory-based vehicular organic aerosol (OA) productions to total CO emissions were compared with the observed OA to CO concentrations (ΔOA / ΔCO) in the urban atmosphere. The results indicate that vehicles dominate the primary organic aerosol (POA) emissions and OA production, which contributed about 40 and 60 % of OA mass in the urban atmosphere of Shanghai. Diesel vehicles, which accounted for less than 20 % of vehicle kilometers of travel (VKT), contribute more than 90 % of vehicular POA emissions and 80–90 % of OA mass derived by vehicles in urban Shanghai. Gasoline exhaust could be an important source of SOA formation. Tightening the limit of aromatic content in gasoline fuel will be helpful to reduce its SOA contribution. Intermediate-volatile organic compounds (IVOCs) in vehicle exhausts greatly contribute to SOA formation in the urban atmosphere of China. However, more experiments need to be conducted to determine the contributions of IVOCs to OA pollution in China.

In this paper, carbon emissions of a monorail transit are calculated using the method of whole life cycle, which can be divided into four stages: material manufacturing stage, construction stage, operation stage and demolition stage. In the operation phase, the units are PKT (Passenger Kilometers Travelled) and VKT (Vehicle Kilometers Travelled), while in other three stages, the unit is 1 km. The results show that the carbon emissions from the 1km length monorail are 6271.204 tons. In addition, in the operation stage, it is found that the PKT index and VKT index of Chongqing monorail transportation are 0.07468 and 3.31933 respectively, far lower than those of subways in the same city. For PKT indicators of other rail transits, from small to large, they are light rail, tram, subway, APM and maglev. As for VKT indicators, from small to large, they are tram, light rail, subway, APM and maglev. The PKT index of Beijing subway is the lowest compared with that of other cities.

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

A perspective on road fatalities in Jeddah, Saudi Arabia

Measuring the effects of transportation system improvements has long been a challenge. Two estimates—the congestion index method and the travel delay method—are used to produce a range of possible benefits resulting from the implementation of transportation projects and programs. The congestion index method uses the roadway congestion index (RCI), and its relationship with congestion cost per capita, to estimate the benefit derived from operational improvements. The RCI provides an areawide assessment of congestion based on freeway and principal arterial street system daily vehicle kilometers of travel per lane kilometer data. The travel delay method calculates congestion cost by associating the value of time, cost of fuel, and cost of operating commercial vehicles with travel delay estimates. These two methods are used to estimate the effects of three types of transportation system improvement projects/programs—freeway traffic management system, high-occupancy vehicle lanes, and regional computerized traffic signal system— implemented on the freeway and principal arterial street system in Houston, Texas. Although only three operational projects/programs are discussed, it is possible to effectively evaluate the implementation of many other improvements using this methodology.