Maximizing net benefits for conventional and flexible bus services

Transit ridership is usually sensitive to fares, travel times, waiting times, and access times, among other factors. Therefore, the elasticities of demand with respect to such factors should be considered in modeling bus transit services and must be considered when maximizing net benefits (i.e. “system welfare” = consumer surplus + producer surplus) rather just minimizing costs. In this paper welfare is maximized with elastic demand relations for both conventional (fixed route) and flexible-route services in systems with multiple dissimilar regions and periods. As maximum welfare formulations are usually too complex for exact solutions, they have only been used in a few studies focused on conventional transit services. This limitation is overcome here for both conventional and flexible transit services by using a Real Coded Genetic Algorithm to solve such mixed integer nonlinear welfare maximization problems with constraints on capacities and subsidies. The optimized variables include service type, zone sizes, headways and fares. We also determine the maximum welfare threshold between optimized conventional and flexible services) and explore the effects of subsidies. The proposed planning models should be useful in selecting the service type and optimizing other service characteristics based on local geographic characteristics and financial constraints.     

Capitalization of BRT network expansions effects into prices of non-expansion areas

A before and after hedonic model is used to determine the property value impacts on properties already served by the transit system caused by extensions to Bogotá’s bus rapid transit system. Asking prices of residential properties belonging to an intervention area (N = 1407 before, 1570 after) or a control area (N = 267 before, 732 after) and offered for sale between 2001 and 2006 are used to determine capitalization of the enhanced regional access provided by the extension. Properties offered during the year the extension was inaugurated and in subsequent years have asking prices that are between 13% and 14% higher than prices for properties in the control area, after adjusting for structural, neighborhood and regional accessibility characteristics of each property. Furthermore, the appreciation is similar for properties within 500 m and properties between 500 m and 1 km of the BRT.     

Carbon emission from urban passenger transportation in Beijing

Urban passenger transport significantly contributes to global greenhouse gas emissions, especially in developing countries owing to the rapid motorization, thus making it an important target for carbon reduction. This article established a method to estimate and analyze carbon emission from urban passenger transport including cars, rail transit, taxis and buses. The scope of research was defined based on car registration area, transport types and modes, the stages of rail transit energy consumption. The data availability and gathering were fully illustrated. A city level emission model for the aforementioned four modes of passenger transport was formulated, and parameters including emission factor of electricity and fuel efficiency were tailored according to local situations such as energy structure and field survey. The results reveal that the emission from Beijing’s urban passenger transport in 2012 stood at 15 million tonnes of CO₂, of which 75.5% was from cars, whereas car trip sharing constitutes only 42.5% of the total residential trips. Bus travel, yielding 28.6 g CO₂, is the most efficient mode of transport under the current situations in terms of per passenger kilometer (PKM) emission, whereas car or taxi trips emit more than 5 times that of bus trips. Although a decrease trend appears, Beijing still has potential for further carbon reduction in passenger transport field in contrast to other cities in developed countries. Development of rail transit and further limitation on cars could assist in reducing 4.39 million tonnes CO₂ emission.     

Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates

Data from connected probe vehicles can be critical in estimating road traffic conditions. Unfortunately, current available data is usually sparse due to the low reporting frequency and the low penetration rate of probe vehicles. To help fill the gaps in data, this paper presents an approach for estimating the maximum likelihood trajectory (MLT) of a probe vehicle in between two data updates on arterial roads. A public data feed from transit buses in the city of San Francisco is used as an example data source. Low frequency updates (at every 200 m or 90 s) leaves much to be inferred. We first estimate travel time statistics along the road and queue patterns at intersections from historical probe data. The path is divided into short segments, and an Expectation Maximization (EM) algorithm is proposed for allocating travel time statistics to each segment. Then the trajectory with the maximum likelihood is generated based on segment travel time statistics. The results are compared with high frequency ground truth data in multiple scenarios, which demonstrate the effectiveness of the proposed approach, in estimating both the trajectory while moving and the stop positions and durations at intersections.     

Inferring patterns in the multi-week activity sequences of public transport users

The public transport networks of dense cities such as London serve passengers with widely different travel patterns. In line with the diverse lives of urban dwellers, activities and journeys are combined within days and across days in diverse sequences. From personalized customer information, to improved travel demand models, understanding this type of heterogeneity among transit users is relevant to a number of applications core to public transport agencies’ function. In this study, passenger heterogeneity is investigated based on a longitudinal representation of each user’s multi-week activity sequence derived from smart card data. We propose a methodology leveraging this representation to identify clusters of users with similar activity sequence structure. The methodology is applied to a large sample (n = 33,026) from London’s public transport network, in which each passenger is represented by a continuous 4-week activity sequence. The application reveals 11 clusters, each characterized by a distinct sequence structure. Socio-demographic information available for a small sample of users (n = 1973) is combined to smart card transactions to analyze associations between the identified patterns and demographic attributes including passenger age, occupation, household composition and income, and vehicle ownership. The analysis reveals that significant connections exist between the demographic attributes of users and activity patterns identified exclusively from fare transactions.     

A bi-level model for single-line rail timetable design with consideration of demand and capacity

This paper proposes a bi-level model to solve the timetable design problem for an urban rail line. The upper level model aims at determining the headways between trains to minimize total passenger cost, which includes not only the usual perceived travel time cost, but also penalties during travel. With the headways given by the upper level model, passengers’ arrival times at their origin stops are determined by the lower level model, in which the cost-minimizing behavior of each passenger is taken into account. To make the model more realistic, explicit capacity constraints of individual trains are considered. With these constraints, passengers cannot board a full train, but wait in queues for the next coming train. A two-stage genetic algorithm incorporating the method of successive averages is introduced to solve the bi-level model. Two hypothetical examples and a real world case are employed to evaluate the effectiveness of the proposed bi-level model and algorithm. Results show that the bi-level model performs well in reducing total passenger cost, especially in reducing waiting time cost and penalties. And the section loading-rates of trains in the optimized timetable are more balanced than the even-headway timetable. The sensitivity analyses show that passenger’s desired arrival time interval at destination and crowding penalty factor have a high influence on the optimal solution. And with the dispersing of passengers' desired arrival time intervals or the increase of crowding penalty factor, the section loading-rates of trains become more balanced.     

Using the built environment to oversample walk,transit, and bicycle travel

Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a ¼ mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle.     

Wireless charging in California: Range,recharge, and vehicle electrification

This research evaluated the potential for wireless dynamic charging (charging while moving) to address range and recharge issues of modern electric vehicles by considering travel to regional destinations in California. A 200-mile electric vehicle with a real range of 160 miles plus 40 miles reserve was assumed to be used by consumers in concert with static and dynamic charging as a strict substitute for gasoline vehicle travel. Different combinations of wireless charging power (20–120 kW) and vehicle range (100–300 miles) were evaluated. One of the results highlighted in the research indicated that travel between popular destinations could be accomplished with a 200-mile EV and a 40 kW dynamic wireless charging system at a cost of about $2.5 billion. System cost for a 200-mile EV could be reduced to less than $1 billion if wireless vehicle charging power levels were increased to 100 kW or greater. For vehicles consuming 138 kWh of dynamic energy per year on a 40 kW dynamic system, the capital cost of $2.5 billion plus yearly energy costs could be recouped over a 20-year period at an average cost to each vehicle owner of $512 per year at a volume of 300,000 vehicles or $168 per year at a volume of 1,000,000 vehicles. Cost comparisons of dynamic charging, increased battery capacity, and gasoline refueling were presented. Dynamic charging, coupled with strategic wayside static charging, was shown to be more cost effective to the consumer over a 10-year period than gasoline refueling at $2.50 or $4.00 per gallon. Notably, even at very low battery prices of $100 per kWh, the research showed that dynamic charging can be a more cost effective approach to extending range than increasing battery capacity.     

Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.     

Dynamic travel time prediction using data clustering and genetic programming

The current state-of-practice for predicting travel times assumes that the speeds along the various roadway segments remain constant over the duration of the trip. This approach produces large prediction errors, especially when the segment speeds vary temporally. In this paper, we develop a data clustering and genetic programming approach for modeling and predicting the expected, lower, and upper bounds of dynamic travel times along freeways. The models obtained from the genetic programming approach are algebraic expressions that provide insights into the spatiotemporal interactions. The use of an algebraic equation also means that the approach is computationally efficient and suitable for real-time applications. Our algorithm is tested on a 37-mile freeway section encompassing several bottlenecks. The prediction error is demonstrated to be significantly lower than that produced by the instantaneous algorithm and the historical average averaged over seven weekdays (p-value <0.0001). Specifically, the proposed algorithm achieves more than a 25% and 76% reduction in the prediction error over the instantaneous and historical average, respectively on congested days. When bagging is used in addition to the genetic programming, the results show that the mean width of the travel time interval is less than 5 min for the 60–80 min trip.     

Effects of e-bikes on bicycle use and mode share

In Norway, as in many countries, a political goal is to increase bicycle use, and the e-bike is promising in this respect. However, concerns have been raised about mode-share effects. It has been argued that if the e-bike’s only function is in cycling becoming cycling with electric assistance, there would be no benefit to either the environment or public health. Little is yet known about the use of the e-bike, or of its potential in reducing motorized travel. In the current study, 66 randomly selected participants were given an e-bike to use for a limited period of time and the results compared with those of a control group (N = 160). E-bike cycling trips increased from 0.9 to 1.4 per day, distance from 4.8 km to 10.3 km and, as a share of all transport, from 28% to 48%, whereas with the control group there was no increase in cycling. The effect of the e-bike increased with time, indicating a learning effect among users, and was greater for female than for male cyclists. There were no differences with age. Overall, the results suggest that the e-bike is indeed practical for everyday travel.     

The impact of urban rail transit on commercial property value: New evidence from Wuhan,China

The interaction between rail transit and the urban property market is a vital foundation for planning transit-based policy such as Value Capture and Transit Oriented Development (TOD). Yet only few studies have reported the impact of transit access on commercial property value. This paper presents empirical evidence from Wuhan, China, to enrich the knowledge in the subject area. Spatial autoregressive models were employed to estimate the commercial value capture, based on 676 observations along Wuhan’s metro rail line through the main business districts. Value appreciation was discovered within the 400 m radius of road network distance from Metro stations. The transit access premiums present as two tiers: 16.7% for the 0–100 m core area and approximately 8.0% within the 100–400 m radius. The result demonstrates the potential benefit of adopting value capture and optimising TOD planning to support sustainable urban rail transit investment. Amid rapid urbanisation in China, the evidence reported here could help better inform cities, across the developing world and beyond, of the benefits of adopting rail transit-based policy.     

A study of feasibility and potential benefits of organised car sharing in Ireland

In this study, the market potential of car sharing has been evaluated using multiple alternative scenarios which examine the geographic, financial and environmental factors influencing car sharing adoption. The scenarios are applied to the available and collected travel information of the Irish population to estimate the potential impact of introducing car sharing in Ireland. The analysis identified that car owners who travel predominantly on alternative modes, could make significant cost and CO₂ savings through car sharing. A reduction of yearly CO₂ emissions of 86 kt is readily achievable through car sharing, with reductions up to 895 kt possible with appropriate policy and financial support. These figures are comparable to other measures proposed under the Irish National Climate Change Strategy.     

Using nonparametrics to specify a model to measure the value of travel time

Using a range of nonparametric methods, the paper examines the specification of a model to evaluate the willingness-to-pay (WTP) for travel time changes from binomial choice data from a simple time–cost trading experiment. The analysis favours a model with random WTP as the only source of randomness over a model with fixed WTP which is linear in time and cost and has an additive random error term. Results further indicate that the distribution of log WTP can be described as a sum of a linear index fixing the location of the log WTP distribution and an independent random variable representing unobserved heterogeneity. This formulation is useful for parametric modelling. The index indicates that the WTP varies systematically with income and other individual characteristics. The WTP varies also with the time difference presented in the experiment which is in contradiction of standard utility theory.     

Can rail/sail compete with air travel to Cyprus? A comparison of emissions

Rail and sea voyage journeys to Cyprus from a variety of origins are constructed to derive the travel emissions and travel time per person to compare popular aviation routes. The hypothetical ‘slow travel’ routes are approximately eight to ten times longer than flying. Emissions are lower from certain origins by about 100 kg CO₂ per person per round trip under reasonably high occupancy conditions when compared to current direct air services. Emissions from the sea voyages are derived from a sample of 162 marine vessels using the energy efficiency design index for European ships running at 20 knots.     

Would personal carbon trading reduce travel emissions more effectively than a carbon tax?

The application of personal carbon trading (PCT) to transport choices has recently been considered in the literature as a means of reducing CO₂ emissions. Its potential effectiveness in changing car travel behavior is compared to the conventional carbon tax (CT) by means of a stated preferences survey conducted among French drivers (N ∼ 300). We show evidence that PCT could effectively change travel behavior and hence reduce transport emissions from personal travel. There is however a definite reluctance to reduce car travel. We were unable to demonstrate any significant difference between the effectiveness of PCT and the CT with regard to changing travel behavior. However, in the experiment, the PCT scheme provided consistent results while this was not the case for the CT scheme. Further research is needed into the “social norm” conveyed by a personal emissions allowance.     

The cost of convenience; Air pollution and noise on freeway and arterial light rail station platforms in Los Angeles

Light rail transit (LRT) systems constitute one of the most sustainable public transportation modes and transit agencies have increasingly constructed LRT lines along the median of roadways to reduce land acquisition costs and traffic conflicts. Despite these conveniences, few studies have examined the air pollution and noise exposures for passengers on LRT station platforms within freeway or arterial medians. In response, we monitored particle number count (PNC) concentrations and noise levels on 17 station platforms in the Los Angeles metro system in summer 2012 and assessed differences between freeway and arterial platforms. We visited each station on average 7 times for approximately 19 min with two teams carrying a full set of instruments. As expected, impacts were higher on green line platforms in the center of a grade-separated freeway compared to blue line platforms in the center of an arterial due to being in close proximity to greater traffic volumes. Overall, freeway-arterial platform differences were 35,100 versus 20,000 particles/cm³ for PNC and 83 versus 62 dBA for noise. This average noise intensity on green line platforms was four times that on blue line stations. We also found that PNC concentrations were significantly higher at open air monitoring platform positions compared to standing under a shade canopy (about 2000 particles/cm³ higher), but that noise levels were significantly lower at open air positions compared to under canopy positions (about 3.2 dBA lower). Results identify important factors for transport planners to consider when locating and designing in-roadway LRT platforms.     

Characteristics of air pollutants at near and far field regions of a national highway located at an industrial complex

This paper presents the characterization of air quality monitored at near field region (NFR) and far field region (FFR) of a national highway located at an industrial complex. The pollutants such as PM₁₀, SO₂ and NO₂ were monitored in two campaigns (11th September to 18th October 2012 and 18th January to 17th February 2013). The 24 h average PM₁₀ concentration at NFR and FFR were found to be 86.69 ± 18.56 μg/m³; 73.16 ± 16.21 μg/m³ and 89.44 ± 18.69 μg/m³; 81.91 ± 16.42 μg/m³, respectively during first and second campaign. In both the campaigns PM₁₀, SO₂ and NO₂ concentration at NFR was higher than FFR. The chemical characterization of PM₁₀ at NFR and FFR indicated the abundance of major elements such as Na (NFR = 30% and FFR = 32%), Ca (NFR = 12% and FFR = 14%) and ions namely NO₃⁻ (NFR = 71% and FFR = 68%) and NH₃⁺ (NFR = 15% and FFR = 19%). Further, at FFR, SO₄²⁻ and NO₃⁻ were found to be 18% and 35% higher than NFR indicating the conversions of SO₂ and NO₂ concentration into secondary particles. The measured SO₂ and NO₂ concentrations were 23 and 21% lower at FFR when compared to NFR confirms the secondary formation.The CALPUFF, EPA regulatory model was set up to understand the dynamics of air pollutants at the industrial complex. The predicted PM₁₀, SO₂ and NO₂ concentrations at NFR and FFR were found to be 32.31 ± 1.56 μg/m³ and 31.35 ± 1.27 μg/m³; 0.37 ± 0.21 μg/m³ and 0.06 ± 0.04 μg/m³; 12.83 ± 6.55 μg/m³ and 4.67 ± 2.77 μg/m³, respectively. The model showed moderate predictions for PM₁₀ (R² = 0.44–0.52), SO₂ (R² = 0.41–0.51) and NO₂ (R² = 0.45–0.61) concentrations.     

Volume and GHG emissions of long-distance travelling by Western Europeans

It is generally recognised that long distance travelling accounts for a significant part of the mileage of person travel. However, estimates have been hardly made. The paper estimates volume and GHG emissions of long-distance travel by Western Europeans. The analysis is predominantly based on data of the DATELINE project, the only EU-wide survey on long-distance travelling, conducted in 2001 and 2002. Some studies demonstrate that DATELINE suffers from serious underreporting of journeys. We analysed the causes for underreporting and developed expansion factors that correct for that. These gave the opportunity to estimate long-distance travel volumes and related GHG emissions in 2001/2002. Next an update to 2013 is made using statistics on the development of tourist travel and patronage of long-distance modes. Defining long distance ⩾100 km crow-fly, the estimates per capita in the Western European countries in 2013 are 7.5 journeys (defined as round-trips), 8600 km, and 1300 kg greenhouse gasses. The estimated total GHG emissions of long-distance travelling is 520 megaton. In the Netherlands and Flanders, countries where data on short-distance travelling were available, long-distance travelling accounts for 45% of the mileage and nearly 50% of the GHG emissions of all person transport. Long-distance travelling is growing and is expected to continue to grow, particularly by air. The GHG emissions are expected to grow as well, though to a smaller extent. Because short-distance travelling is stagnating, the shares of long distance travelling in both mileage and GHG emissions are likely to increase.     

Integrated transit services for minimum cost operation considering heterogeneous demand

Abstract

In large metropolitan areas, public transit is a major mode choice of commuters for their daily travel, which has an important role in relieving congestion on transportation corridors. The purpose of this study is to develop a model which optimizes service patterns (SPs) and frequencies that yield minimum cost transit operation. Considering a general transit route with given stops and origin-destination demand, the proposed model consists of an objective total cost function and a set of constraints to ensure frequency conservation and sufficient capacity subject to operable fleet size. A numerical example is provided to demonstrate the effectiveness of the developed model, in which the demand and facility data of a rail transit route were given. Results show that the proposed model can be applied to optimize integrated SPs and headways that significantly reduce the total cost, while the resulting performance indicators are generated.