Search

This study introduces a new policy for managing parking scarcity called Parking Allocation and Ride-Sharing System (PARS). In PARS, a centralized algorithm allocates parking spacesto drivers who are willing to participate in a coordinated carpool. The algorithm is used to optimize the creation of carpools going to and returning from a particular venue and simultaneously reserve parking for these carpools at the venue. An efficient mixed integer linear programming (MIP) formulation is presented and two heuristics, namely Ride Decomposition (RD) and Quick Converge (QC), are proposed and compared via internally generated experiments. Experimental results show that a commercial solver is able to solve the MIP with thousands of individuals to optimality in minutes. For larger instances, the RD and QC heuristic algorithms can solve the problem, on average, 42.23% and 86.39% faster than the commercial solver and provide solutions that are 3.61% and 3.49% from optimal, respectively. [ABSTRACT FROM AUTHOR]

This study aims to explore how small and medium-sized platforms in the sharing economy can gain a competitive advantage in a market monopolized by giants. Taking China's ride-hailing industry as an example, the k-means clustering method was employed to compare and analyze the characteristics and differences of 207 small and medium-sized platforms based on the framework of the business model canvas. An empirical typology comprising four representative successful business models of small and medium-sized ride-hailing platforms is extracted from the dimensions of key partners, value propositions, customer segmentation, and cost-revenue structure: high-end business platforms, Minibus-hailing platforms, Intercity carpool platforms, and Aggregation mode platforms. The results show that small and medium-sized platforms in the sharing economy can rely on their own characteristics and advantages to seek new potential development directions and gain development space by constructing value propositions and operating models that are different from industry giants. Specifically, it is necessary to further implement refined market identification and segmentation to continuously develop differentiated competitive advantages. In particular, more effective and open business strategies should be explored and practiced to greatly expand the network effects and business boundaries of small and medium-sized platforms, thereby significantly enhancing their competitiveness in the ride-hailing market. This study provides a new perspective on the reconstruction of market exchange in the sharing economy through the prism of small and medium-sized digital platforms and has certain important theoretical significance for supplementing and advancing existing research. [ABSTRACT FROM AUTHOR]

Since the 1970s, high-occupancy vehicle (HOV) lanes have been a common policy instrument to mitigate traffic congestion. Yet, their effectiveness remains a controversial topic among researchers, policy makers, and the public. In this debate, a key unknown has been the impact of HOV lanes on commuters' carpooling behaviors. This paper brings a new piece of evidence by offering a data-driven assessment of carpooling intent and adoption, using revealed-preferences data. We partner with Waze, a major carpooling platform, and leverage a natural experiment following the introduction of three HOV lanes in Israel in 2019. Using tailored treatment and control groups coupled with econometric analyses, we derive four main findings. First, HOV lanes bring new users to the carpooling platform, which contributes to alleviating the "cold-start" problem in the marketplace. Second, HOV lanes have a positive impact on carpool intent: the number of carpool offers sent by drivers increase manifold following the introduction of the HOV lanes. Third, HOV lanes have a disparate impact on carpool adoption: carpools increase significantly for two out of three HOV lanes. This result underscores the critical impact of HOV lanes design: it seems more beneficial to have round-trip HOV lanes (as opposed to one-way lanes) and two-passenger occupancy requirements (as opposed to three-passenger requirements). Last, HOV lanes have a broader impact, by increasing carpooling on non-HOV routes and shifting the travel behaviors of non-carpoolers. We conclude by discussing policy implications, highlighting collaboration opportunities between policy makers and digital carpooling platforms to enhance the design and operations of HOV lanes. [ABSTRACT FROM AUTHOR]

Where traffic is congested and all the curb spaces are occupied, some drivers are probably cruising for parking. Cities can eliminate this cruising by charging demand-based prices for curb parking to ensure one or two open spaces on every block. Drivers will then usually find convenient places to park within a short walk of their destinations. But if cities charge demand-based prices for curb parking, how will drivers choose where to park, and what will they pay? To answer these questions, I have examined how four variables—parking duration, number of persons in the car, walking speed, and value of saving time spent walking—determine parking choices when prices increase as drivers approach their destinations. Short-term parkers, carpools, slow walkers, and drivers with a high value of saving time will park closer to their destinations. Long-term parkers, solo drivers, fast walkers, and drivers with a low value of saving time will park farther away. This spontaneous, self-organizing pattern of parking choices responding to demand-based parking prices will minimize the collective cost of the time drivers spend walking to and from their destinations. Demand-priced curb parking will also reduce uncertainty about travel times. Drivers delayed by traffic congestion can save time at the end of their trips by paying a higher price to park closer to their destinations. Demand-priced curb parking at the end of a trip can serve as a buffer allowing late-arriving drivers to buy time when they need it most. [ABSTRACT FROM AUTHOR]

Carpool lanes that are not filled to capacity can spell trouble, particularly when deployed on narrow freeways with only 3 lanes in each travel direction. Two alternative treatments for underused carpool lanes were evaluated with this in mind. Both can boost discharge flows by opening a portion of the carpool lane to all freeway traffic in the vicinity of a bottleneck. The simpler of the two alternatives opens the lane segment on a permanent basis. The other does so intermittently. Both alternatives leave the carpool lane intact on segments well upstream of an active bottleneck. Carpools are thus still enabled to bypass slower-moving queues in a freeway's regular-use lanes. Both alternatives have previously been proposed, but were yet to be tested. The present tests entail simulations of a real 3-lane freeway. The simulation model was calibrated to roughly match unfavorable conditions presently triggered by the site's underused carpool lane. Experiments were thereafter performed by varying travel demands parametrically. These tests unveiled why the alternatives are likely to be better options than rescinding the site's carpool restriction and opening the full length of the lane to all traffic. Simulations also show that, unless the carpool lane is nearly filled to capacity, the alternatives perform better than does the traditional practice of running the lane through a bottleneck. The simpler of the two alternatives performed well when the carpool lane operated at less than two-thirds its capacity. The intermittent treatment was found superior when carpool demands were higher. The savings in Vehicle Hours Traveled (VHT) and People Hours Traveled (PHT) generated by the alternatives were often large. Deploying the simpler alternative under the site's present-day conditions, for example, was found to reduce PHT and VHT by more than 1,000 (hours) each, over a 5-h period spanning the afternoon rush. These improvements did not come at great cost to carpools. To the contrary, carpools often benefited from the alternative treatments, despite having at times to traverse the site's bottleneck sans priority. This is because by diminishing regular-lane queues, the alternatives also diminished the deleterious friction effect on carpool-lane speeds. Policy implications for carpool- and other kinds of special-use lanes are discussed. [ABSTRACT FROM AUTHOR]

Car use is critical to improving access to opportunities, especially for low-wage immigrants whose jobs are dispersed and when transit service is minimal. But many states have restricted the ability of undocumented immigrants to obtain drivers licenses, making it potentially difficult for them to improve their economic standing. The effects of these laws have been tested for their association with traffic safety but not on mode choice itself. Using the two most recent versions of the National Household Travel Survey, I fit a series of difference-in-difference models to estimate the effect of permissive immigrant driver licensing on travel outcomes. Permissive licensing increased the rate of giving rides by about 13% and increased the rate of getting a ride by about 6.5%, but changes to driving alone were insignificant. Results suggest permissive licensing has beneficial accessibility impacts for all immigrants in addition to the positive safety and economic externalities documented elsewhere. • This study examines how US driver licensing laws influence immigrant travel. • Permissive licensing increases driving in and taking rides in carpools. • Permissive licensing does not affect VMT or the number of drive alone trips. • Results suggest small but important gains in mobility for immigrant groups. [ABSTRACT FROM AUTHOR]

Carpooling promises benefits to the environment and consumers alike, but research has shown that there are multiple practical challenges to realizing these benefits. One possible solution is the addition of meeting points (hubs) in the design of carpooling systems. Recent studies indicate that introducing hubs increases both carpool participation and system-wide savings. Little to no research has been conducted, however, to understand the origin of these savings, determine their utility in different carpooling models, or detailing how hubs should be introduced (i.e. as a mandate or option). Additionally, we know nothing about the impact of hubs on self-organizing carpools (the primary means of creating carpooling systems). To address these gaps, we studied the impact of meeting points on two types of carpooling models (pick-up/drop-off and to/from), using two solution paradigms (centralized and self-organized), with hubs that were either mandated or optional. Our findings show that adding the option of meeting hubs improves system-wide savings from carpooling. These findings, along with our introduction of a new efficient carpool enumeration technique, have important practical implications for the design of modern carpooling systems in the development of more effective and sustainable uses of transportation resources. [ABSTRACT FROM AUTHOR]

The Dial-a-Ride Problem (DARP) introduced in the early 1980s is the NP-Hard optimization problem of developing the most cost-efficient vehicle schedules for a number of available vehicles that have to start from a depot, pick up and deliver a set of passengers, and return back to the same depot. DARP has been used in many modern applications, including the scheduling of demand-responsive transit and car pooling. This study departs from the original definition of DARP and it extends it by considering an interchange point where vehicles can exchange their picked-up passengers with other vehicles in order to shorten their delivery routes and reduce their running times. In addition to that, this study introduces the concept of generalized passenger travel times in the DARP formulation which translates the increased in-vehicle crowdedness to increased perceived passenger travel times. This addresses a key issue because the perceived in-vehicle travel times of passengers might increase when the vehicle becomes more crowded (i.e., passengers might feel that their travel time is higher when they are not able to find a seat or they are too close to each other increasing the risk of virus transmission or accidents). Given these considerations, this study introduces the Dial-a-Ride Problem with interchange and perceived travel times (DARPi) and models it as a nonlinear programming problem. DARPi is then reformulated to a MILP with the use of linearizations and its search space is tightened with the addition of valid inequalities that are employed when solving the problem to global optimality with Branch-and-Cut. For large problem instances, this study introduces a tabu search-based metaheuristic and performs experiments in benchmark instances used in past literature demonstrating the computation times and solution stability of our approach. The effect of the perceived passenger travel times to the vehicle running costs is also explored in extensive numerical experiments. • Definition and Formulation of the Dial-a-Ride problem with Interchange. • Model reformulation to a mixed-integer linear program. • Incorporation of perceived passenger travel times to the model. • Proof of NP-Hardness and introduction of Valid Inequalities. • Development of problem-specific Tabu search-based approach. [ABSTRACT FROM AUTHOR]

Due to its significant economic and environmental impact, sharing the ride among a number of drivers (i.e., car pooling) has recently gained significant interest from industry and academia. Hence, a number of ride sharing services have appeared along with various algorithms on how to match a rider request to a driver who can provide the ride sharing service. However, existing techniques have several limitations that affect the quality of the ride sharing service, and hence hinder its wide applicability. This paper proposes SHAREK*; a scalable and efficient ride sharing service that overcomes the limitations of existing approaches. SHAREK* allows riders requesting the ride sharing service to indicate the maximum price they are willing to pay for the service, the maximum waiting time before being picked up and the maximum arrival time for arriving the destination. In the mean time, SHAREK* computes the price of the service based on the distance of the rider trip and the detour that the driver will make to offer the service. Then, SHAREK* returns a set of drivers that can make it to the rider within its price and temporal constraints. Since there could be many of such drivers, SHAREK* internally prunes those drivers that are dominated by others, i.e., they provide higher price and higher waiting time (or arrival time) than other drivers. To realize its efficiency and scalability, SHAREK* employs a set of early pruning techniques that minimize the need for any actual shortest path computations. [ABSTRACT FROM AUTHOR]

Nowadays, large cities face numerous problems caused by the rapidly increasing number of vehicles on road. Carpooling has been shown as an efficient solution to ease the traffic pressure. The objective of our carpool scheduling problem is to minimise the number of carpools needed to transport users. Previous research on the similar topic introduces static capacity constraint which limits the carpool size to the vehicle's capacity. However, it is unnecessary since a seat in the vehicle can be occupied by several passengers if their routes are not overlapped. In this paper, we remove this constraint, which allows a vehicle to serve more users than its capacity. We propose a greedy approach based on the iterative matching and merging. Specifically, starting from a set of single-user carpools, the algorithm iteratively checks the merge-ability between carpools, and then applies the maximum matching algorithm to maximise the number of carpools merged. In addition, two methods are proposed to reduce the time complexity of merge-ability checking process. Furthermore, we improve the time efficiency of our algorithms by exploiting geometry properties. Experimental results on synthetic and real-world datasets show that our algorithms have better performances than baseline. [ABSTRACT FROM AUTHOR]

Long-distance carpooling is an emerging mode in France and Europe, but little is known about monetary values of this mode attributes in transport economics. We conducted a discrete choice experiment to identify and measure the values of attributes of long-distance transport modes for a trip as a driver and as a passenger, with a special focus on carpooling. Around 1.700 French individuals have been surveyed. We use discrete mixed logit models to estimate the probability of mode choice. We find that the value of travel time for a driver who carpools is on average 13% higher than the value of travel time when driving alone in his/her car. The average value of travel time for a carpool trip as passenger is around 26 euros per hour, 60% higher than for a train trip and 20% higher than for a bus trip. Moreover, our study confirms a strong preference for driving solo over taking carpoolers in one's car. We also show that individuals traveling as carpool passenger incur a "discomfort" cost of on average 4.5 euros per extra passenger in the same vehicle. Finally, we identify robust socio-economic effects affecting the probability of carpooling, especially gender effects. When they drive a car, females are less likely to carpool than male, but they prefer to carpool two passengers over only one passenger. [ABSTRACT FROM AUTHOR]

Ride sharing has been widely acknowledged as an effective solution for reducing travel costs, congestion, and pollution. This paper considers the ride-sharing problem of the scheduled commuter and business traffic within a closed community of companies that agree to share the calendars of their employees. We propose a formulation in the form of a general integer linear program (ILP) for the aforementioned ride-sharing problem, which incorporates return restrictions to satisfy the business needs, as well as meeting points and the option for riders to transfer between drivers. All the instances with 40 and 60 participants and most of the instances with 80 participants can be solved to optimality within a time limit of two hours. Using instances of up to 100 participants, the ILP can be solved with a gap of no more than 1.8% within the time limit. Because of the high computational complexity, we develop a constructive heuristic that is based on the savings concept. This heuristic is also able to combine ride sharing with the use of an external mobility service provider. Our numerical study shows that ride sharing can be an effective way of reducing the number of trips and vehicle miles. Particularly, ride sharing creates more benefits when the participation is high and when the origins and the destinations of the trips are more spatially concentrated. The results show that ride sharing can create up to 31.3% mileage savings and up to 28.7% reduction in the number of cars needed to fulfill employees' travel schedules. We also illustrate our model using a real-life ride-sharing problem of a Dutch consultancy and research firm. The online appendix is available at https://doi.org/10.1287/trsc.2018.0832. [ABSTRACT FROM AUTHOR]

Carpooling is an environmentally friendly transportation system. It can efficaciously help resolve a variety of societal concerns of the urban areas, ranging from traffic congestion to environmental pollution. In this paper, we propose a new mathematical model to solve the carpooling problem. The model simultaneously minimizes the costs of travel times, the vehicle use, and the vehicle delays. An exact solution method based on Branch-and-Bound (B&B) algorithm is proposed to efficiently obtain the optimal solution of the problem. In order to find the near-optimal solutions for large-scale problems, a heuristic beam search algorithm is introduced, which is based on the partial relaxation of some fathoming criteria applied in our proposed B&B. The computational experiments are conducted, based upon the transportation network of Isfahan city, Iran. The results demonstrate the great capability of the proposed exact solution method in terms of both computational solving time required and the number of the evaluated nodes, in comparison with CPLEX software package. The findings of this research can be applied to solve the carpooling problem compatible to the real-life situations. [ABSTRACT FROM AUTHOR]

Existing carpool optimization techniques based on the centralized approach serve policy-makers' goals, but neglect the realities of participants. Moreover, absent strict enforcement, participants often ignore centralized solutions and maximize their own savings. We present a new heuristic, formulated and tested on real-world, and simulated car pooling problem instances, that mimics a decentralized carpool self-organization process. Our findings reveal system-wide savings similar to centralized models, and a potential strategy for improving carpool utilization. [ABSTRACT FROM AUTHOR]

Carpooling can relieve the traffic congestion, so it has been enforced in many countries. However, little effort has been made to study the impacts of carpooling on the commuting problem from the car-following model. In this paper, we apply a generalized car-following model to study each commuter’s trip cost and the corresponding total cost in a traffic corridor when carpooling is allowed. The numerical result show that carpooling has some prominent positive influences on the commuting problem (i.e., each commuter’s trip cost is reduced) and that the influences are directly dependent on the size of carpooling and each commuter’s time headway at the origin. The results indicate that carpooling can be used to relieve the traffic congestion. [ABSTRACT FROM AUTHOR]

A clustering algorithm for urban taxi carpooling based on data field energy and point spacing is proposed to solve the clustering problem of taxi carpooling on urban roads. The data field energy function is used to calculate the field energy of each data point in the passenger taxi offpoint dataset. To realize the clustering of taxis, the central point, outlier, and data points of each cluster subset are discriminated according to the threshold value determined by the product of each data point field values and point spacing. The classical algorithm and proposed algorithm are compared and analyzed by using the compactness, separation, and Dunn validity index. The clustering results of the proposed algorithm are better than those of the classical clustering algorithm. In the case of cluster numbers 25, 249, 409, and 599, the algorithm has good clustering results for the taxi trajectory dataset with certain regularity in space distribution and irregular distribution in time distribution. This algorithm is suitable for the clustering of vehicles in urban traffic roads, which can provide new ideas and methods for the cluster study of urban traffic vehicles. [ABSTRACT FROM AUTHOR]

Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS. [ABSTRACT FROM AUTHOR]

Using data of attitudes in the Puget Sound region we first identify predispositions in favor of car use (car loving persons and households) and distinguish them from other predispositions favoring other modes (transit and carsharing lovers). Then we explore if like-minded people (homophily) live together and examine heterogeneity within their households. To do this we analyze attitudinal data using multilevel latent class clustering that allows identification of groups of persons and groups of households jointly. Our analysis identifies distinct groups of people with different attitudes towards modes and we do not find strong homophily in attitudes within households. The distinction of attitudes among persons transfers well to the household level giving us the opportunity to identify and test differences among the different attitudinal groups using longitudinal records. We then move to a longitudinal analysis using a small sample of households that participated in more than ten years of the Puget Sound panel survey to explore the sequence of their residential location characteristics, car ownership, and travel. We find in descriptive statistics and in a second application of multilevel cluster models that carpool and transit loyalty persists over time by a portion of car pool and transit lovers. We also find sustained use of cars by car loving households, sustained car use of a neutral in attitudes group, a group of younger households with positive attitudes towards carsharing and sustained car sharing over time, and a possibly disenfranchised older household group lacking access to opportunities. The inclusion in the analysis of the two residential location characteristics (evolution of density and diversity around the household residence) enabled a more complete analysis and a clearer description of household context for both attitudes and behavior. [ABSTRACT FROM AUTHOR]

Carpooling can be understood as an informal agreement between several individuals to share a privately owned car for a trip and to contribute to its expenses. It represents one of the most appealing strategies for reducing car use since it could reduce the number of kilometres driven by car, save money, and contribute to lowering CO 2 emissions. Despite these advantages, and even if accepted and somewhat practiced, carpooling is still underused. The aims of this study are to investigate for which type of everyday trips French drivers use carpooling, to analyze their characteristics, and determine whether the motivations for carpooling are different for each type of trip, as well as to find out whether the motivation changes according to the number of carpooled trips. 634 carpool drivers and/or passengers (aged 19–75 years, M  = 43.85, SD  = 12.05, 42.7% men) were recruited to answer an online survey. Factual data (socio-demographics, transportation accessibility) and motivational factors (attitudes regarding car use, public transportation, environment) were used to describe and explain carpooling for four types of trips (work, children, leisure, and shopping). Carpooling was most frequently used for leisure trips, followed by shopping, and then by work and children trips. Among the motivations underlying carpooling, most notable were the following: perceived pressure from family and peers (for all types of trips) and public transportation attitudes. Finally, motivations for carpooling use differed according to whether participants carpool for one, two, three or four trips, regardless of the type of trip. [ABSTRACT FROM AUTHOR]

Nowadays, ride-hailing services have been established as a part of the urban transportation. Their arrival has remade the profit structure and resulted in the unbalance of interest in taxi market. Here, we establish the service models of taxis, carpooling, and car-hailing under “Internet +” from the perspective of profit margins, to perform a comparative analysis among the different services. Results: First, Profit margins are generally higher for short trips than for long trips, though empty cruise fee to a certain degree make up for the driver’s decreased profit margins. Second, the profit margin for carpooling is roughly 1.85 times that of ride-hailing, and 1.75 times that of taxis. This shows that the sharing economy has a certain advantage. Third, Profit margins are higher and fluctuations are lower on non-work days than on work days. At last, Profit margins are roughly 1.3 times higher on non-congested roads than on congested roads. The reduced profitability on congested roads makes it even harder to catch a ride during rush hours and on congested roads. We suggest that the relevant departments make appropriate efforts to make it more attractive for drivers to take on passengers during rush hours and on congested roads, and promote the sharing in the taxi market. [ABSTRACT FROM AUTHOR]

This paper examines how commuter motivations to drive relate to propensities to carpool, using two sequential studies: Study 1 determines the key dimensions of commuters’ motivations for driving using secondary data ( N  = 432) from staff and postgraduate student commuters at a United Kingdom university. We code the contents of the respondents’ self-reported reasons for driving (i.e. the instrumental rationalities attributed to driving with respect to varying purposes) to identify keywords representing motivation to drive; we then analyse the keyword data using multidimensional scaling ( MDS ). Study 2 examines how the dimensions discovered through study 1 relate to propensity to carpool, using structural equation modelling ( SEM ). Data for Study 2 are the survey responses of commuters ( N  = 1028) based in the United States. The MDS reveals four key dimensions of motivation to drive. These capture instrumental rationalities for driving within four situational domains which we term: (1) Family ; (2) Public transport impractical changes ; (3) Rigid schedule ; and (4) Non-urban areas . The SEM results show that the regression coefficients on propensity to carpool of Public transport impractical changes and Rigid schedule are significant and negative; the Family domain has a positive but non-significant regression coefficient. Regarding demographics, men’s mean values on all four domain variables are significantly higher than those for women, except for the Family domain where the mean value for women is higher; meanwhile, age predicts decreasing propensity to carpool. Additionally, the situational domains of Public transport impractical changes , Rigid schedule and Non-urban areas significantly positively correlate. Consequently, overall, the results imply that addressing commuters’ instrumental rationalities for driving, namely increasing schedule flexibility and providing more direct or quicker public transport, could indirectly encourage commuters to carpool. The study makes an original contribution by estimating the causal relationship between commuters’ motivation to drive and propensity to carpool. [ABSTRACT FROM AUTHOR]

For the problem of taxi carpooling detour, this paper studies driver strategy choice with carpooling detour. The model of taxi driver strategy evolution with carpooling detour is built based on prospect theory and evolution game theory. Driver stable strategies are analyzed under the conditions of complaint mechanism and absence of mechanism, respectively. The results show that passenger’s complaint mechanism can effectively decrease the phenomenon of driver refusing passengers with carpooling detour. When probability of passenger complaint reaches a certain level, the stable strategy of driver is to take carpooling detour passengers. Meanwhile, limiting detour distance and easing traffic congestion can decrease the possibility of refusing passengers. These conclusions have a certain guiding significance to formulating taxi policy. [ABSTRACT FROM AUTHOR]

We address a novel decentralized supply chain with one supplier and multiple independent retailers based on the practice of several supply chains in the real world. Coordination of such a supply chain has rarely been studied. Despite overcoming the well-known double marginalization, the supplier’s route selection can obstruct supply chain coordination. We present a wholesale-price-and-carpooling contract to coordinate such a supply chain. We demonstrate supply chain coordination under such a contract and show that the profit along the supply chain can be arbitrarily allocated. We show that the popular revenue-sharing contract may lose flexibility in profit allocations. [ABSTRACT FROM AUTHOR]

Carpooling, i.e. the sharing of vehicles to reach common destinations, is often performed to reduce costs and pollution. Recent work on carpooling takes into account, besides mobility matches, also social aspects and, more generally, non-monetary incentives. In line with this, we present GRAAL, a data-driven methodology for GReen And sociAL carpooling. GRAAL optimizes a carpooling system not only by minimizing the number of cars needed at the city level, but also by maximizing the enjoyability of people sharing a trip. We introduce a measure of enjoyability based on people’s interests, social links, and tendency to connect to people with similar or dissimilar interests. GRAAL computes the enjoyability within a set of users from crowd-sourced data, and then uses it on real world datasets to optimize a weighted linear combination of number of cars and enjoyability. To tune this weight, and to investigate the users’ interest on the social aspects of carpooling, we conducted an online survey on potential carpooling users. We present the results of applying GRAAL on real world crowd-sourced data from the cities of Rome and San Francisco. Computational results are presented from both the city and the user perspective. Using the crowd-sourced weight, GRAAL is able to significantly reduce the number of cars needed, while keeping a high level of enjoyability on the tested data-set. From the user perspective, we show how the entire per-car distribution of enjoyability is increased with respect to the baselines. [ABSTRACT FROM AUTHOR]

Smart city relies on the smart transportation. And the smart savings on private car pooling based on internet of vehicles will greatly facilitate the expansion of smart transportation. The paper puts forward the smart savings scheme for private car pooling, establishes the dynamic relationship of human - vehicle - road during carpooling process basing on internet of vehicles. We applied the route recommendation technology, information matching technology, information notification technology, dynamic information searching technology and collaborative route optimization technology to the carpooling system to improve the real-time, accuracy and efficiency of carpooling process in uncertain dynamic demand market and realize the smart savings on private car pooling. Finally, we take an area of Huai'an as example to verify the feasibility of the program and technologies. The experimental results show that the carpooling program (TCP) increased 40% on the private car seat utilization, saved 30.7% on the total travel cost and 38.4% on total travel time than the other existing carpooling program (TECP). [ABSTRACT FROM AUTHOR]

For the purpose of alleviating traffic congestion, this paper proposes a scheme to encourage travelers to carpool by traffic restriction. By a variational inequity we describe travelers’ mode (solo driving and carpooling) and route choice under user equilibrium principle in the context of fixed demand and detect the performance of a simple network with various restriction links, restriction proportions, and carpooling costs. Then the optimal traffic restriction scheme aiming at minimal total travel cost is designed through a bilevel program and applied to a Sioux Fall network example with genetic algorithm. According to various requirements, optimal restriction regions and proportions for restricted automobiles are captured. From the results it is found that traffic restriction scheme is possible to enhance carpooling and alleviate congestion. However, higher carpooling demand is not always helpful to the whole network. The topology of network, OD demand, and carpooling cost are included in the factors influencing the performance of the traffic system. [ABSTRACT FROM AUTHOR]

The implications of racial residential segregation on travel behavior have remained understudied, despite the persistent existence of segregation. Using the 2009 National Household Travel Survey, I investigate whether residence in a co-ethnic neighborhood affects the likelihood that ethnic minorities will form inter-household carpools, and if so, how such effects differ across race or ethnic groups. Inter-household carpooling requires arrangements and interactions between people living in geographical proximity, so it will likely reflect the social networks of a neighborhood. The results show that Hispanics and Asians who reside in their co-ethnic neighborhoods, regardless of immigrant status, are more likely to use inter-household carpools for non-work purposes than their counterparts living outside co-ethnic neighborhoods. In contrast, black neighborhood residency is not associated with the likelihood that African Americans will do inter-household carpooling, regardless of trip purpose. These differences across racial/ethnic groups suggest that the role of neighborhoods in promoting social ties as reflected by activities such as external carpooling is complex. Residence in a black neighborhood may be less of a choice than residence in a Hispanic or Asian neighborhood due to the long history of black segregation in the US. With less residential choice, the propensity to develop local social ties may be weaker. [ABSTRACT FROM AUTHOR]

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a largescale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics).We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the trade-off between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ~3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems. [ABSTRACT FROM AUTHOR]

Morning commuters choose their departure times and travel modes based on a combinational evaluation of factors associated with the chances of running into bottleneck congestion, likely schedule delays, parking space availability as well as monetary costs of traveling and parking. This study investigates a morning commute problem with carpooling behavior under parking space constraint at destination. We consider such a scenario that as a competing mode of the transit line, the highway contains a carpool lane only used by carpoolers while all solo drivers are forced to use a general purpose (GP) lane. Unlike the standard bottleneck model, the rush-hour dynamic departure patterns with a binding parking supply vary with the relative proportion of the two lanes’ capacities. The possible departure pattern domain with different parking supply and lane capacity allocation is explored in terms of the relative extra carpool cost and distinguished between the bi-mode and multi-mode equilibria. It is found that compared with solo drivers, carpoolers have shorter rush hour in order to smooth the extra carpool cost. With the decrease of parking spots, the number of solo drivers cuts down gradually, whilst the number of carpoolers climbs up firstly and then declines in the multi-mode system. Under mild assumptions, the best system performance can be realized with the joint consideration of total travel cost and vehicle emission cost through optimizing the lane capacity allocation and the parking supply. [ABSTRACT FROM AUTHOR]

Same-sex partnered individuals are far more likely to use transit, walk, and cycle, and to a lesser extent, use carpools than are people in straight couples. As society becomes more tolerant, gay and lesbian populations are an increasingly visible social group, yet they have received scant attention by transportation scholars. This paper builds on this nascent literature by documenting and attempting to explain these dramatic differences by controlling for factors known to influence mode choice. We perform two separate analyses employing two distinct datasets. The first analysis examines journey-to-work data from the American Community Survey. The second analysis focuses in specifically on non-motorized (walking, biking) travel using use self-reported walk and bike frequency from the 2009 National Household Travel Survey. In both, we find that characteristics of the neighborhoods in which gays and lesbians live, as well characteristics of the individuals themselves, only explain part of the increased propensity to use “alternative” modes of transportation; a strong residual effect remains. [ABSTRACT FROM AUTHOR]

The paper contains a brief description of analysis done in literature addressing the problem of using carpooling systems. Significant economic, technical and legal aspects have been discussed. It may be observed that certain possibilities and financial profits lead to the fact that carpooling solutions are commonly used, especially by young people. After a short introduction into the subject, examples of carpooling systems such as BlaBlaCar, Inonecar, Autem.pl, JedziemyRazem.pl have been characterized and analyzed. The next part consists of a presentation of the economic aspects. Part three consists of the technical aspects. In part four there is a description of the legal situation of the passenger and of the driver from the corporate, civil, insurance, tax and criminal law perspectives. Finally, a case study has been presented. The authors have used a selected system to travel to conferences in countries in Europe: Poland, Slovakia, Hungary, Serbia, Bulgaria, Romania, Germany, Sweden. Brief conclusions end the paper. The main method used in this research was case study. In addition, the work contains assumptions regarding the further development of carpooling systems, both among individuals and business people. Carpooling systems may be used by individuals and business people to save money and time, however the disadvantages should be taken into consideration as well. [ABSTRACT FROM AUTHOR]

In a traffic system with HOV lanes, considering two modes of driving alone and carpooling, we proposed three kinds of travel cost functions for potential commuters such as carpoolers in HOV lanes, driving alone users and carpoolers in general purpose lanes. Assume that all commuters will experience a random travel time with discrete distribution during their trip, this paper compared the commuters' equilibrium choices of travel mode and travel route under the framework of cumulative prospect theory and expected utility theory. In addition, the sensitivity analysis on the proportion of driving alone users, the individual preference such as the reference point were conducted. The resultant observations show that the individuals' risk preference and reference dependence definitely affect the commuters' choices on the travel mode and travel route. When the proportion of driving alone users exceeds a critical value, the carpooling users will be better than driving alone users since they have higher cumulative prospect value. However, this critical value will be slightly overestimated under the framework of expected utility theory. [ABSTRACT FROM AUTHOR]

We investigate the role of social influence in the commute to work. Using instruments to address the endogeneity of commute decisions and a dataset of U.S. military commuters on 100 military bases over the period 2006–2013, we show that workplace peers positively influence one another's decisions to drive alone to work and carpool to work. All else equal, an increase in the fraction of peers who drive alone of 10 percentage points increases the probability of driving alone by 6.05 percentage points. An increase in the fraction of peers who carpool of 10 percentage points increases the probability of carpooling by 5.14 percentage points. To examine whether conventional measures of social status and seniority predict who exerts the strongest influence on others, we disaggregate the dataset into subgroups and identify which subgroups have the greatest influence and which are most susceptible to influence. Results show that in commute decisions, intra-group influence can be more important than inter-group influence. This suggests that workplace travel interventions that seek to shift employees away from driving alone or toward carpooling may be most effective if communicated by one's own peer group. [ABSTRACT FROM AUTHOR]

This paper analyzes the passenger-carpooling potential among undergraduate students using a model for estimating choice based on combined revealed and stated preference data. The data are obtained from a survey performed at four campuses of Istanbul Technical University. The case in focus is carpooling as a passenger; carpooling as a driver is deliberately left out because of students' lack of familiarity with it. The hypothetical passenger-carpooling scenarios lead to enquiries about the fee students are willing to pay and the distance they are willing to walk to a designated pick-up location. The estimation results show that females and frequent campus travelers are more likely to prefer passenger carpooling. The scenario analysis included in the paper reveals the prioritization of carpool fee over walking distance to pick-up locations among undergraduate students. [ABSTRACT FROM AUTHOR]

This study examines the potential for a social network peer-to-peer-based carpooling system called FacePorter for the University of Calgary staff and students. In this study, a survey that combined both revealed and stated preferences was designed and distributed randomly among students and staff. The survey consisted of a sample of 210 responses, which were divided into two groups of stated preference respondents: (i) auto drivers, who were given the choice between driving alone and carpooling as drivers; and (ii) transit riders, who were given the choice between public transport and carpooling as passengers. A binomial logit model and two ordinal logit models (one for ride offerors and one for ride seekers) were calibrated to examine the impacts of various examined socio-economic, psychological, and travel characteristic variables on the propensity to participate in the hypothetical carpooling program. The results of the models clearly demonstrated that many factors have significant impacts on FacePorter demand: occupation, income, marital status, working schedule flexibility, trip characteristics (i.e., distance, travel time, and number of required transfers when riding transit), weather condition, carpooling fee, perceived rider and driver profiles, and carpooling fee would significantly influence the market demand of the examined carpooling system. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Carpooling is an effective solution to major environmental problems but it is insufficiently used, particularly in France. In order to increase carpooling, it is important to understand why people do or not carpool. This study, carried out a large sample of drivers, was aimed at (1) identifying whether or not people carpool, (2) investigating the factual data (e.g. socio-demographics, transportation accessibility) and motivational factors (e.g. attitudes regarding car use, public transportation, environment) upon which carpoolers and non-carpoolers differ, and (3) highlighting the main determinants of the practice of carpooling. An online survey was administered to 1207 French drivers (48% men, ages 19–87) recruited by means of a random-quota method. In our sample, 52.5% of the participants said they were using carpooling. Carpoolers and non-carpoolers were similar in terms of kilometers driven per year, distance to their workplace or schools/universities, and public transportation accessibility. Compared to non-carpoolers, carpoolers were more likely to be women, have children, have positive attitudes toward public transport, and be more environmentally aware. These results suggest various different strategies for increasing the number of carpoolers and the frequency of carpooling use by taking into account the gender of road users. [ABSTRACT FROM AUTHOR]

Few controlled evaluations of Safe Routes to School (SRTS) initiatives have been conducted. The Texas Childhood Obesity Prevention Policy Evaluation (T-COPPE) study included three conditions: schools awarded infrastructure (I) projects (n = 23), schools awarded noninfrastructure (NI) projects (n = 21), and matched comparison (C) schools (n = 34). Fourth-grade children completed tallies to determine transport to/from schools. Serial cross-sectional surveys were collected from students and parents at baseline (2009) and follow-up (2012). Data were analyzed using mixed linear regression and growth curve models. Morning percent active commuting to school (ACS) in I and NI schools were higher than C schools (p = .024, p = .013, respectively). Afternoon percent ACS in NI schools decreased more over time compared with C schools (p = .009). I and NI school students had higher ACS self-efficacy; similar results were noted for parents in I schools. Policies that provide cost-reimbursement funding for SRTS achieve modest short-term ACS outcomes, with few differences between types of funding allocations. [ABSTRACT FROM AUTHOR]

Most special-use freeway lanes in the US, whether reserved for carpools, toll-paying commuters or both, are physically separated from the adjacent regular-use lanes by some form of barrier. Vehicle movements in and out of a special lane of this type are permitted only at select access points along the route. The barrier at each select point might open for a distance of 400 m or so. Limiting access in this way is said to reduce the “turbulence” that might otherwise occur were the special lane not to have a barrier, such that vehicles could instead enter or exit that lane anywhere along its length. Yet, real freeway traffic studied in spatiotemporal fashion shows that access points are prone to become bottlenecks. The problem occurs when traffic in the regular lanes becomes dense, as commonly happens during a rush. Drivers then seek refuge in the special lane in greater numbers. Since the vehicular maneuvers through the access point are focused within a limited physical space, they can become disruptive and further degrade traffic. Degradation can occur both in the special lane and in the adjacent regular ones. The damage can be worse than when there is no barrier to limit special-lane ingress and egress. The problem is shown to be reproducible across sites and across days at each site. Policy implications are discussed. Select designs and policies to address the problem are thereafter explored in Part II of the paper using traffic simulation. [ABSTRACT FROM AUTHOR]

Carpooling is an effective means of reducing traffic. A carpool team shares a vehicle for their commute, which reduces the number of vehicles on the road during rush hour periods. Carpooling is officially sanctioned by most governments, and is supported by the construction of high-occupancy vehicle lanes. A number of carpooling services have been designed in order to match commuters into carpool teams, but it known that the determination of optimal carpool teams is a combinatorially complex problem, and therefore technological solutions are difficult to achieve. In this paper, a model for carpool matching services is proposed, and both optimal and heuristic approaches are tested to find solutions for that model. The results show that different solution approaches are preferred over different ranges of problem instances. Most importantly, it is demonstrated that a new formulation and associated solution procedures can permit the determination of optimal carpool teams and routes. An instantiation of the model is presented (using the street network of Guangzhou city, China) to demonstrate how carpool teams can be determined. [ABSTRACT FROM AUTHOR]

Carpooling for commuting can save cost and helps in reducing pollution. An automatic Web based Global CarPooling Matching Service (GCPMS) for matching commuting trips has been designed. The service supports carpooling candidates by supplying advice during their exploration for potential partners. Such services collect data about the candidates, and base their advice for each pair of trips to be combined, on an estimate of the probability for successful negotiation between the candidates to carpool. The probability values are calculated by a learning mechanism using, on one hand, the registered person and trip characteristics, and on the other hand, the negotiation feedback. The problem of maximizing the expected value of carpooling negotiation success was formulated and was proved to be NP-hard. In addition, the network characteristics for a realistic case have been analyzed. The carpooling network was established using results predicted by the operational FEATHERS activity based model for Flanders (Belgium). [ABSTRACT FROM AUTHOR]

With the rising fuel costs, ride sharing is becoming a common mode of transportation. Sharing taxis which has been prominent in several developing countries is also becoming common in several cities around the world. Sharing taxis presents several advantages as it minimizes vacant seats in cars thus reducing costs on taxi operators which results in significantly lower taxi fares for passengers. Besides the economical advantages, taxi sharing is highly important for reducing congestion on the roads and for minimizing the impact of transportation on the environment. In this paper, we formulate the problem of assigning passengers to taxis and computing the optimal routes of taxis as a mixed integer program. To solve the proposed model, we present a Lagrangian decomposition approach which exploits the structure of the problem leading to smaller problems that are solved separately. Furthermore, we propose two heuristics that are used to obtain good quality feasible solutions. The Lagrangian approach along with the heuristics are implemented and compared to solving the full problem using CPLEX. The computational results indicate the efficiency of the methodology in providing tighter bounds than CPLEX in shorter computational time. [ABSTRACT FROM AUTHOR]

Immigrants are more likely to travel by carpool than the US-born. Strong ethnic ties within immigrant communities may contribute to immigrants’ propensity to carpool, enabling residents to find carpool partners more easily and increasing the likelihood that residents will travel to and from common destinations. Drawing on data from the 2000 US census and a 2001 regional travel survey, this paper examines whether residents of ethnic neighbourhoods in Southern California are more likely to carpool than other residents. A strong positive relationship is found between the percentage foreign-born in a census tract and carpooling rates. Analysis of individual data shows that this relationship is strongest for immigrants who live in immigrant neighbourhoods; immigrants living in non-immigrant neighbourhoods are less likely to carpool. These findings suggest an important role for social networks in travel behaviour and the potential benefits of linking land use to the specific needs of local residents. [ABSTRACT FROM PUBLISHER]

This article evaluates the willingness to accept (WTA) carpooling with binary logistic regression using the methodology of contingent valuation method. This study, a practical application of the work outlined in the previous empirical research ventures, measures how much Weber State University students are willing to accept the introduction of a car-sharing system with a detailed survey. To demonstrate the amount of WTA car-sharing, 5 different levels of compensation ($0, $25, $50, $75, and $250) were offered respondents (n = 181) enrolling for the current semester. The mean WTA was $56.55, and the marginal effect of a main interested predictor, price, was 0.0013, meaning as one dollar increases, there is an increase in the possibility for a respondent to participate in car-sharing by 0.13%. [ABSTRACT FROM AUTHOR]

Abstract: Carsharing is growing rapidly in popularity, often backed by government and private partners, such as universities and developers. While reduced parking demand is frequently cited as a reason to promote carsharing, virtually no quantitative analysis has been done on the impact of carsharing on parking demand. Instead, prior studies focus on vehicle ownership, which has an implied connection to parking demand. This paper analyzes the impact of carsharing on parking demand in a university setting (with just over 1000 carsharing users) using a member survey and parking permit sales data. Changes in parking demand are broken down by geographic area and parking type. Members report the vast majority (over 76%) of forgone vehicles would be parked in the same area as the member's household on most weekdays, nights, and weekends. Roughly 30% would be parked on the street at most times, with the percentage parked in personal driveways and garages peaking at roughly 40% on nights and weekends and dropping to 26% on weekdays. Members reported an increase in shopping trips made by car or truck (statistically significant at 1% level), leading to a small increase in parking demand at stores, but this increase was much smaller than the reductions seen elsewhere. The paper also assesses other impacts which have so far been nearly exclusively measured in relatively large cities. For example, the survey revealed a reduction of 15.3 personal vehicles for every carsharing vehicle, roughly equivalent to findings from major cities. [Copyright &y& Elsevier]

Current rapid technological improvement in optical radiometric instrumentation provides an opportunity to develop innovative measurements protocols where the remote quantification of the plant physiological status can be determined with higher accuracy. In this study, the leaf and canopy reflectance variability in the PRI spectral region (i.e., 500–600 nm) is quantified using different laboratory protocols that consider both instrumental and experimental set-up aspects, as well as canopy structural effects and vegetation photoprotection dynamics. First, we studied how an incorrect characterization of the at-target incoming radiance translated into an erroneous vegetation reflectance spectrum and consequently in an incorrect quantification of reflectance indices such as PRI. The erroneous characterization of the at-target incoming radiance translated into a 2% overestimation and a 31% underestimation of estimated chlorophyll content and PRI-related vegetation indexes, respectively. Second, we investigated the dynamic xanthophyll pool and intrinsic Chl vs. Car long-term pool changes affecting the entire 500–600 nm spectral region. Consistent spectral behaviors were observed for leaf and canopy experiments. Sun-adapted plants showed a larger optical change in the PRI range and a higher capacity for photoprotection during the light transient time when compared to shade-adapted plants. Outcomes of this work highlight the importance of well-established spectroscopy sampling protocols to detect the subtle photochemical features which need to be disentangled from the structural and biological effects. [ABSTRACT FROM AUTHOR]

A utility function U is said to be invariant with respect to a family of transformations Γ provided, for every member γ of Γ, U and U oγ represent the same preference relation over lotteries. An invariance with respect to a wide class of transformations can be reduced to an invariance with respect to the shift transformations. We give a complete answer to the following question: given a nonempty set T of shifts determine all utility functions invariant with respect to the shift transformations by every element of T. As a consequence of our results we obtain the forms of utility functions invariant with respect to the families of commuting transformations. [ABSTRACT FROM AUTHOR]