Empty freight car dispatching model under freight car pool concept

In the last few years, growing attention has been given to the cost savings potential of the specialized freight car pool concept. Under this concept, a fleet of single-purpose freight cars are pooled at many loading points, and the cars emptied at unloading terminals can be sent back to any loading point in order to reduce empty car miles and time. As part of a continuing effort to improve the car dispatching method for this concept, this paper offers an improvement to the traditional linear programming transportation problem approach, incorporating daily variations of empty car supply and demand characteristics in the model. The proposed method, therefore, allocates cars between supply and demand points with the dispatching date specified, enabling the dispatcher to make daily car disposition decisions. It can incorporate both the travel distance cost and inventory cost of empty cars at terminals in the objective. If the holding of empty vehicles at the terminals for future dispatch is allowed, the problem is structured as a transshipment problem in which the overnight storage is the transshipment point.     

A study on smart parking guidance algorithm

Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO₂ emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.     

Tailpipe emission from petrol driven passenger cars

Realizing the dominance of petrol-driven passenger cars of MUL over the fleet of cars in India, a case study of different models of petrol-driven passenger cars of Maruti reporting at an authorized service station of M/s R.K.B.K. Automobiles, Gorakhpur was taken up and the tailpipe emissions along with individual vehicle-related parameters were monitored for idle and fast idle test conditions. The outcome of the study relating to the effect of various vehicle-related parameters on CO and HC emissions of petrol-driven passenger cars of Maruti has led to the useful inferences, which can be used not only for predicting the emission of vehicles with respect to vehicle age and mileage, but also for automobile manufacturing sector to help them produce such environmentally benign petrol-driven passenger cars having long-lasting compliance of pollution control systems with respect to vehicle age and mileage of the petrol-driven passenger cars in the country.     

Fuzzy modeling approach to the rail freight car inventory problem

Techniques to improve freight car fleet use are of considerable interest to the railroad industry. In this paper, we present a fuzzy inventory control approach applied to the sizing of empty cars on a rail network. We address the problem of deciding the optimal inventory level and the optimal ordering quantity for a rail freight car fleet system in which demand and travel time are uncertain variables represented as triangular fuzzy numbers. Based on the fuzzy economic order quantity (EOQ) formula, a modified fuzzy EOQ model is set up and the optimal policy is developed using the signed distance method to defuzzify the fuzzy total cost. Computational results made for the Serbian rail network case verify the proposed model as well as the efficiency of the approach.     

Large-scale network distribution of pooled empty freight cars over time,with limited substitution and equitable benefits

A set of models and procedures is described for finding the optimal distribution of empty freight cars owned by the railroads participating in a pooling agreement. A distinction is drawn between a system focus, in which the emphasis is on minimizing total cost, and a company focus, in which the benefits of the agreement to the individual railroads are emphasized. Limited car substitution is accounted for by combining interchange costs with distribution costs, and incorporating interchange possibilities and prohibitions into the network structure. Temporal variations in car supply and demand levels are also taken into account. A large-scale network algorithm is used in conjunction with decomposition to obtain solutions which show for a given time horizon how much equity can be achieved in the balance of savings among the railroads involved and at what cost. Results using actual operating data are reported.     

Autonomous cars and dynamic bottleneck congestion: The effects on capacity,value of time and preference heterogeneity

‘Autonomous cars’ are cars that can drive themselves without human control. Autonomous cars can safely drive closer together than cars driven by humans, thereby possibly increasing road capacity. By allowing drivers to perform other activities in the vehicle, they may reduce the value of travel time losses (VOT). We investigate the effects of autonomous cars using a dynamic equilibrium model of congestion that captures three main elements: the resulting increase in capacity, the decrease in the VOT for those who acquire one and the implications of the resulting changes in the heterogeneity of VOTs. We do so for three market organizations: private monopoly, perfect competition and public supply. Even though an increased share of autonomous cars raises average capacity, it may hurt existing autonomous car users as those who switch to an autonomous car will impose increased congestion externalities due to their altered departure time behaviour. Depending on which effect dominates, switching to an autonomous vehicle may impose a net negative or positive externality. Often public supply leads to 100% autonomous cars, but it may be optimal to have a mix of car types, especially when there is a net negative externality. With a positive (negative) externality, perfect competition leads to an undersupply (oversupply) of autonomous cars, and a public supplier needs to subsidise (tax) autonomous cars to maximise welfare. A monopolist supplier ignores the capacity effect and adds a mark-up to its price.     

The effect of the competition between cars and trucks on the evolution of the motorway transport system

Motorways, which were devised at the beginning of their history as dedicated roads intended to be traveled by cars only, are at present also traveled by considerable flows of trucks. This fact has deeply changed the motorway transport system with respect to its original conception, owing to the interactions between two categories of vehicles whose characteristics are very different. These interactions greatly increase the transport cost perceived by car drivers with respect to truck drivers. This paper studies the consequences of this cost asymmetry on the evolution of the transport system when the geometric characteristics of a motorway remain unchanged in time, while transport demand increases. By using a theoretical model of competition between cars and trucks, it is shown that, if both the geometric characteristics of a motorway and the increase rate of the activities that feed the transport demand remain unchanged over time, the competition between cars and trucks, as well as the fact that in general passengers have better transport alternatives than freight, make the increase rate of truck traffic greater than that of cars, causing a progressive increase in the proportion of trucks in the time periods in which a motorway is traveled by both the vehicle categories. Since truck traffic on motorways, at least in Europe, is very scarce on weekends and in holiday periods, in which motorways are traveled almost only by cars, these results seem to indicate a tendency to the specialization of motorways, which are likely to be used in the future mostly by only one category of vehicles in different periods of time.     

The effect of the oil crisis on the growth in the ownership and use of cars

Since the oil crisis of 1973, a number of studies have been made in various countries of the effects of the rise in petrol prices on the level of traffic flow, but rather fewer have attempted to delineate the complex chain of reactions within the car market set off by this impulse. We attempt to do this, using data from the UK.Since 1966 during the prediction stage of the first London Transportation Study it became obvious that low income and high income households had different rates of growth of car ownership, mainly because low income households bought cheap, old cars which vary in quantity and price differently from expensive, new cars. The Greater London Council therefore sponsored a study of car prices by age and size, starting from 1957 annually, and since the oil crisis, evaluated monthly. This has enabled us to examine the strong change in trend that had occurred, with large cars depreciating 15% per annum more than the smallest. The quantities of cars of each size registered each month are available from national statistics and this enables us to say that the previous 1% per annum increase in car size was arrested, with new cars becoming substantially smaller.A model of the car market has been developed which relates on the one hand the price distribution of cars by age, and on the other hand the price. distribution of the stock of cars owned at each household income level. Via the expenditure on car purchase at each household income level and the distribution of the length of time between purchase and resale of cars, a fully dynamic model has been developed to relate expenditure flow and stock. This enables us to test the effect of different trends on the dynamic equilibrium in the car market.The implications of the two trends noted above on the prediction of future car ownership growth are discussed, with the standstill since the oil crisis attributed to petrol prices via the split in household expenditure between purchase and use.     

Activity patterns,time use,and travel of millennials: a generation in transition?

Millennials, defined in this study as those born between 1979 and 2000, became the largest population segment in the United States in 2015. Compared to recent previous generations, they have been found to travel less, own fewer cars, have lower driver’s licensure rates, and use alternative modes more. But to what extent will these differences in behaviour persist as millennials move through various phases of the lifecycle? To address this question, this paper presents the results of a longitudinal analysis of the 2003–2013 American Time Use Survey data series. In early adulthood, younger millennials (born 1988–1994) are found to spend significantly more time in-home than older millennials (born 1979–1985), which indicates that there are substantial differences in activity-time use patterns across generations in early adulthood. Older millennials are, however, showing activity-time use patterns similar to their prior generation counterparts as they age, although some differences – particularly in time spent as a car driver – persist. Millennials appear to exhibit a lag in adopting the activity patterns of predecessor generations due to delayed lifecycle milestones (e.g. completing their education, getting jobs, marrying, and having children) and lingering effects of the economic recession, suggesting that travel demand will resume growth in the future.     

Passengers’ activities during short trips on the London Underground

The present study considers underground passengers and investigates the ways in which they spend their time during a trip of average length or shorter. Using a structured procedure that had been refined after a preliminary study, more than 1,700 passengers were observed in London. The results showed that even when the length of travel is very short (2–6 stops), underground passengers engage in several occupations, especially those involving the use of mobile Information and Communication Technologies. These occupations depend on the specific spatial and temporal conditions of the travel, as well as on gender and age. These results should be useful in designing travel services that enhance passengers’ experiences; they also suggest a criterion for comparing trips using different transportation modes (i.e., looking at the time point during the trip at which the ratio of active versus passive occupations changes).     

User preferences regarding autonomous vehicles

This study gains insight into individual motivations for choosing to own and use autonomous vehicles and develops a model for autonomous vehicle long-term choice decisions. A stated preference questionnaire is distributed to 721 individuals living across Israel and North America. Based on the characteristics of their current commutes, individuals are presented with various scenarios and asked to choose the car they would use for their commute. A vehicle choice model which includes three options is estimated:

• (1)Continue to commute using a regular car that you have in your possession.
• (2)Buy and shift to commuting using a privately-owned autonomous vehicle (PAV).
• (3)Shift to using a shared-autonomous vehicle (SAV), from a fleet of on-demand cars for your commute.

A factor analysis determined five relevant latent variables describing the individuals’ attitudes: technology interest, environmental concern, enjoy driving, public transit attitude, and pro-AV sentiments. The effects that the characteristics of the individual and the autonomous vehicle have on use and acceptance are quantified through random utility models including logit kernel model taking into account panel effects.Currently, large overall hesitations towards autonomous vehicle adoption exist, with 44% of choice decisions remaining regular vehicles. Early AV adopters will likely be young, students, more educated, and spend more time in vehicles. Even if the SAV service were to be completely free, only 75% of individuals would currently be willing to use SAVs. The study also found various differences regarding the preferences of individuals in Israel and North America, namely that Israelis are overall more likely to shift to autonomous vehicles.Methods to encourage SAV use include increasing the costs for regular cars as well as educating the public about the benefits of shared autonomous vehicles.     

Distributed algorithm for empty vehicles management in personal rapid transit (PRT) network

In this paper, an original heuristic algorithm of empty vehicles management in personal rapid transit network is presented. The algorithm is used for the delivery of empty vehicles for waiting passengers, for balancing the distribution of empty vehicles within the network, and for providing an empty space for vehicles approaching a station. Each of these tasks involves a decision on the trip that has to be done by a selected empty vehicle from its actual location to some determined destination. The decisions are based on a multi‐parameter function involving a set of factors and thresholds. An important feature of the algorithm is that it does not use any central database of passenger input (demand) and locations of free vehicles. Instead, it is based on the local exchange of data between stations: on their states and on the vehicles they expect. Therefore, it seems well‐tailored for a distributed implementation. The algorithm is uniform, meaning that the same basic procedure is used for multiple tasks using a task‐specific set of parameters. Copyright © 2016 John Wiley & Sons, Ltd.     

A heuristic algorithm for the multi-vehicle advance request dial-a-ride problem with time windows

A heuristic algorithm is described for a time-constrained version of the advance-request, multi-vehicle, many-to-many Dial-A-Ride Problem (DARP). The time constraints consist of upper bounds on: (1) the amount of time by which the pick-up or delivery of a customer can deviate from the desired pick-up or delivery time; (2) the time that a customer can spend riding in a vehicle. The algorithm uses a sequential insertion procedure to assign customers to vehicles and to determine a time schedule of pick-ups and deliveries for each vehicle. A flexible objective function balances the cost of providing service with the customers' preferences for pick-up and delivery times close to those requested, and for short ride times. Computational experience with the algorithm is described, including a run with a real database of 2600 customers and some 20 simultaneously active vehicles. The scenario for the application of the algorithm is also discussed in detail.     

Using connected vehicle technology to improve the efficiency of intersections

Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control.Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.     

Accounting for travel time variability in the optimal pricing of cars and buses

A number of studies have shown that in addition to travel time and cost as the common influences on mode, route and departure time choices, travel time variability plays an increasingly important role, especially in the presence of traffic congestion on roads and crowding on public transport. The dominant focus of modelling and implementation of optimal pricing that incorporates trip time variability has been in the context of road pricing for cars. The main objective of this paper is to introduce a non-trivial extension to the existing literature on optimal pricing in a multimodal setting, building in the role of travel time variability as a source of disutility for car and bus users. We estimate the effect of variability in travel time and bus headway on optimal prices (i.e., tolls for cars and fares for buses) and optimal bus capacity (i.e., frequencies and size) accounting for crowding on buses, under a social welfare maximisation framework. Travel time variability is included by adopting the well-known mean–variance model, using an empirical relationship between the mean and standard deviation of travel times. We illustrate our model with an application to a highly congested corridor with cars, buses and walking as travel alternatives in Sydney, Australia. There are three main findings that have immediate policy implications: (i) including travel time variability results in higher optimal car tolls and substantial increases in toll revenue, while optimal bus fares remain almost unchanged; (ii) when bus headways are variable, the inclusion of travel time variability as a source of disutility for users yields higher optimal bus frequencies; and (iii) including both travel time variability and crowding discomfort leads to higher optimal bus sizes.     

Influence of composition,amount and life span of passenger cars on end-of-life vehicles waste in Belgium: A system dynamics approach

The increasing worldwide production of passenger cars depletes natural resources and increases the number of end-of-life vehicles (ELVs) to be processed. Lack of landfill capacity and a growing scarcity of natural resources have lead to severe ELV reuse and recovery targets in the European Union (EU). This paper examines the main influencing parameters affecting the amount and composition of ELV waste originating from passenger cars to be treated in Authorized Treatment Facilities (ATFs). Moreover the effect of a changing number, composition and life span of passenger cars on the ability to meet the ambitious EU ELV Directive 2000/53/EC targets in 2015 is examined for Belgium. Using system dynamics, the aforementioned changing parameters are studied from 1990 and projected to 2030. The model results show that the total annual weight of ELV waste to be reused and recycled in Belgium is expected to grow over the coming years despite the economic downturn of 2008 and its effect on GDP growth. Moreover it shows that Belgium can sustainably achieve the ambitious EU ELV Directive 2000/53/EC targets in 2015 and thereafter if it continues to invest in waste treatment of ELV plastics. The availability of higher amounts of ELV plastics proves to be favourable to trigger investments in their reusing and recycling. We demonstrate that this can be realized by reducing export of discarded passenger cars, shortening the life span of passenger cars or shortening the time for investing in additional plastic recovery.     

Ex-post analysis of impacts of the car registration fee in the Czech Republic

Currently, the influence of transportation and its impact on environmental indicators throughout the world are increasing; however, governments of particular countries try to implement new economic instruments with the expectations of changing people’s behaviour or at least environmental parameters of the motor vehicle fleet. The Government of the Czech Republic introduced a new economic instrument, which came into force on 1 January 2009 and was inspired by similar environmental taxes in Member States of the European Union – the car registration fee, which is based on emission parameters of cars. The main target of this fee has been to change the structure of the passenger car fleet in the Czech Republic, particularly to support new registrations of new passenger cars with better environmental characteristics and to decrease the share of new registrations of used passenger cars. This article focuses on an ex-post analysis of impacts of the car registration fee on the structure of the passenger car fleet in the Czech Republic and its environmental characteristics in the first 3 years after the legal mandate of the fee. The case study is based on a correlation analysis and an analysis of statistical data from official sources in the Czech Republic. The impacts of the car registration fee on both the structure of the passenger car fleet in the Czech Republic and the environmental characteristics of new registrations are significant. For the first time since 2004, the number of new registrations of new cars was higher in the period 2009–2011 than the number of new registrations of used cars. Moreover, the share of alternative fuel cars in the passenger car market is increasing and the emissions from private car transport are decreasing.     

Changes in fuel economy: An analysis of the Spanish car market

This paper estimates the role that technological change and car characteristics have played in the rate of fuel consumption of vehicles over time. Using data from the Spanish car market from 1988 to 2013, we estimate a reduced form equation that relates fuel consumption with a set of car characteristics. The results for the sales-weighted sample of vehicles show that energy efficiency would have improved by 30% and 42% for petrol and diesel cars respectively had car characteristics been held constant at 1988 values. However, the shift to bigger and more fuel-consuming cars reduced the gains from technological progress. Additionally, using the results of the fuel equation we show that, besides a natural growth rate of 1.1%, technological progress is affected by both the international price of oil and the adoption of mandatory emission standards. Moreover, according to our estimations, a 1% growth in GDP would modify car characteristics in such a way that fuel consumption would increase by around 0.23% for petrol cars and 0.35% for diesel cars.     

The market valuation of new car quality

The study examines the question of whether the new car market values put a premium on superior quality cars while penalizing those cars that are of relatively inferior quality. The results suggest that the market does value cars that ex post have a much better than average or better than average reliability rating based on the criteria used in Consumer Reports. Moreover, cars that perform relatively poorly in terms of reliability ratings have a lower associated price, all other things equal. Finally, the results show that the market does value safety as a quality characteristic.     

Determining optimal frequency and vehicle capacity for public transit routes: A generalized newsvendor model

The level of service on public transit routes is very much affected by the frequency and vehicle capacity. The combined values of these variables contribute to the costs associated with route operations as well as the costs associated with passenger comfort, such as waiting and overcrowding. The new approach to the problem that we introduce combines both passenger and operator costs within a generalized newsvendor model. From the passenger perspective, waiting and overcrowding costs are used; from the operator’s perspective, the costs are related to vehicle size, empty seats, and lost sales. Maximal passenger average waiting time as well as maximal vehicle capacity are considered as constraints that are imposed by the regulator to assure a minimal public transit service level or in order to comply with other regulatory considerations. The advantages of the newsvendor model are that (a) costs are treated as shortages (overcrowding) and surpluses (empty seats); (b) the model presents simultaneous optimal results for both frequency and vehicle size; (c) an efficient and fast algorithm is developed; and (d) the model assumes stochastic demand, and is not restricted to a specific distribution. We demonstrate the usefulness of the model through a case study and sensitivity analysis.