Modeling park 'n ride and kiss 'n ride as submodal choices

The logit modeling methodology is applied to include transit access mode choices in conjunction with the automobile vs. transit travel choice decision. The practical problems that arise when the choice set expands beyond two alternatives are identified and addressed. In particular, the complexities that must be resolved in order to use ULOGIT or a similar program include the definition of independent choices (the Independence of Irrelevant Alternatives Property (IIA)), a sequential binary or multinomial logit model (MNL) structure, specification and testing of variables, and the potential for transferring the model to new areas for transportation planning purposes. It was found that the available options cannot be reduced to a single modeling strategy. However, the analysis showed certain concepts which can reduce the uncertainties in related applications of the logit model. It was determined that as many independent choices as possible should be hypothesized and tested for inclusion in the model, but the IIA must be carefully considered because it limits the number of choices that can be represented. Although binary calibration techniques are conceptually appealing, the large number of calibrations for studies involving more than three alternatives suggests that the MNL approach is most practical. Application of the MNL model requires that not only must variables be selected that best explain choice, but they must also be placed in the disutility function of the specific mode or modes to which they are most unique. Finally, it was shown that if choice sets and homogeneous market segments are properly defined, the models can be transferred among different urban areas even though the urban areas exhibit different aggregate characteristics. All observations lead to the general conclusion that the logit modeling methodology can now best be advanced with implementation experience.     

Bus ride times of exceptional school children

This paper examines bus ride times of exceptional school children in North Carolina. It uses levels of service data, which show excessive ride times for exceptional school children, to form clusters of local education agencies. From these clusters short term objectives or standards for maximum ride times are determined for each cluster. Among the findings are three distinct clusters of local education agencies (clusters 1, 2 and 3) whose maximum ride times are respectively 170 minutes, 105 minutes and 62 minutes.

The maximum ride times show that only one cluster (cluster 3) provides a service whose maximum ride time is comparable to the ideal maximum ride time (long term objective) of one hour revealed by the literature and also by responses of school superintendents and transportation directors. Methods of achieving these standards are examined. A comparison of the levels of service of regular and exceptional children transportation is also provided.

     

Park and ride facilities on light rail transit systems

There is now considerable interest in exploring the idea of strategic park and ride as a means of promoting the use of rail transit and encouraging a transfer of commuters from car to public transport. This is especially evident in North America, where extensive park and ride facilities have been installed on a number of light and heavy urban rail systems. There is a general consensus about the most suitable types of location for facilities, but less agreement on the development of a reliable method of forecasting demand and also on the required size of sites. Experience in practice indicates that although park and ride is attractive to commuters, schemes do not generally result in lasting reductions in highway congestion, due to rising car ownership and use and the phenomenon of generated traffic.Abbreviations Centro West Midlands Passenger Transport Executive - K&R Kiss and ride - LRT Light Rail Transit - PT Public Transport - RT Rapid Transit - TRRL Transport & Road Research Laboratory, UK     

A model to assess cost and fuel savings from ride sharing

A model based on geometric probability concepts is developed to assess the performance of carpooling and vanpooling strategies. Fuel consumption and operating cost issues are treated in the paper, and the model can be extended to treat travel time and air quality issues also. It is shown that simple calculations of the fuel saved through carpool programs can overstate the savings by a factor of two. The operating costs of vanpools and carpools are also compared.     

Utilization patterns of park and ride facilities among Kuala Lumpur commuters

A parking utilization survey was undertaken with the main objective of analyzing and comparing the daily workday utilization patterns of two main park and ride stations within the Kuala Lumpur conurbation. This study also aimed to gauge the level of usage of the park and ride facilities. The findings showed that the overall utilization pattern of the facilities was very high with a utilization rate of between 80 and 95%. The stations, however, recorded a contrasting accumulation pattern. The study further revealed that most of the rail-based suburban park and ride users were long term parkers. The results of this study are comparable to results of similar studies in Seoul, Calgary, Tyne and Wear and others. Since parking availability is an important factor that has influence on the behavior of a park and ride user, more accurate information relating to the supply and demand of the park and ride facility will assist in planning new transport infrastructure.

Accommodating user preferences in ad hoc shared ride trip planning using GIS

Ad hoc shared ride trip planning (SRTP) utilizes mobile devices, geo-sensors and wireless networks to match on-the-fly individual travel demand with transport supply. It represents one of many alternatives to single occupancy vehicle use. This paper outlines a SRTP approach via a two-phase algorithm based on user preferences in a time-dependent routing. Whereas current algorithms use minimization of travel time as the only optimization criterion in trip planning, in the framework presented here, the user can specify multiple trip preferences including travel time, walking time, number of transfers between cars and trip length. Various scenarios are simulated in the city of Tehran (Iran) to demonstrate how preference settings affect the routes of ad hoc shared journeys.     

Motivators and deterrents of bicycling: comparing influences on decisions to ride

In a survey of 1,402 current and potential cyclists in Metro Vancouver, 73 motivators and deterrents of cycling were evaluated. The top motivators, consistent among regular, frequent, occasional and potential cyclists, were: routes away from traffic noise and pollution; routes with beautiful scenery; and paths separated from traffic. In factor analysis, the 73 survey items were grouped into 15 factors. The following factors had the most influence on likelihood of cycling: safety; ease of cycling; weather conditions; route conditions; and interactions with motor vehicles. These results indicate the importance of the location and design of bicycle routes to promote cycling.     

Travel behaviour change impacts of a major ride to work day event

While there is increasing interest in the field of travel behaviour change, relatively little attention has been given to the behaviour change potential of major events. ‘Ride to Work Day’ is an annual event which attracts thousands of participants and actively promotes riding to and from work throughout Victoria in Australia. The methodology used to assess the impact of the event on travel behaviour has evolved from a monthly panel survey of event participants to a single follow-up survey five months after the event which focuses on travel behaviour and measurement of the stage of engagement in the behaviour change process. About one in five of those participating in the event are riding to work for the first time. More than one in four (27%) of those who rode to work for the first time as part of the event were still riding to work five months after the event. Over 80% of first-timers indicated that the event had a positive impact on their readiness to ride to work with 57% indicating that it influenced their decision to ride. The event was found to have a greater impact on influencing behaviour change for female than male riders.     

Development of location-based services for recommending departure stations to park and ride users

More and more commuters are beginning to favour public transportation. Fast and convenient park and ride (PnR) services provided by public transportation authorities are the result of changes of household demographics and household, increasing fuel prices and a focus on environmental sustainability. However, lack of parking spaces in PnR facilities creates a major bottleneck to this service. The aim of this research is to develop a location-based service (LBS) application to help PnR users choose the best train station to use to reach their destination using a multicriteria decision making model. A fuzzy logic method is used to estimate parking availability when a user is estimated to arrive at a PnR facility. Two surveys are conducted to collect traffic flow, travel behaviour and service quality data at four selected Perth Western Australia train stations. With the proposed approach and survey data, a prototype of LBS application, Station Finder, was developed using the Android SDK 4.0 and Google API 16. This application is a useful and practical tool to save travel cost and time of PnR users’.     

I want to ride it where I like: measuring design preferences in cycling infrastructure

Transportation - Sidewalk cyclists are a major concern to planners in many cities around the world: they are considerable in numbers, and increase the risk of injury not only to pedestrians but...     

Modeling travel mode choice of young people with differentiated E-hailing ride services in Nanjing China

E-hailing ride service (ERS) has become increasingly popular globally and is changing the urban mobility landscape. There is insufficient research effort in understanding the impact of ERS on travel behavior, in particular among young people. This paper aims to start filling that research gap by first collecting mode choice preference data through a stated preference survey in City of Nanjing, China and then applying nested logit (NL) models and a series of post-estimation analysis to address a number of key research questions of mode choice behavior without and with ERS. Three ERS modes are considered in the Chinese context: DiDi Taxi (D-Taxi), DiDi Express (D-Express), and DiDi Premier (D-Premier), all provided by DiDi Chuxing, the dominant ERS service provider in China. The study finds that age makes little difference in mode choice preference when ERS is introduced between the two age groups considered (18–30 and 31–45). The study results also suggest that young travelers are naturally drawn to ERS for what it represents (a technology innovation) and its business (pricing) model. ERS appears to be a competitive alternative to the conventional modes especially when they are under performed. The study also finds that ERS will likely increase vehicle kilometers traveled (VKT) considerably, which will lead to increase in on-road vehicular emissions, unless some mechanism to switch users to ridesharing is in place.     

Where do cyclists ride? A route choice model developed with revealed preference GPS data

To better understand bicyclists’ preferences for facility types, GPS units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.     

Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC

This study analyzes the potential benefits and drawbacks of taxi sharing using agent-based modeling. New York City (NYC) taxis are examined as a case study to evaluate the advantages and disadvantages of ride sharing using both traditional taxis (with shifts) and shared autonomous taxis. Compared to existing studies analyzing ride sharing using NYC taxi data, our contributions are that (1) we proposed a model that incorporates individual heterogeneous preferences; (2) we compared traditional taxis to autonomous taxis; and (3) we examined the spatial change of service coverage due to ride sharing. Our results show that switching from traditional taxis to shared autonomous taxis can potentially reduce the fleet size by 59% while maintaining the service level and without significant increase in wait time for the riders. The benefit of ride sharing is significant with increased occupancy rate (from 1.2 to 3), decreased total travel distance (up to 55%), and reduced carbon emissions (up to 866 metric tonnes per day). Dynamic ride sharing, wich allows shared trips to be formed among many groups of riders, up to the taxi capacity, increases system flexibility. Constraining the sharing to be only between two groups limits the sharing participation to be at the 50–75% level. However, the reduced fleet from ride sharing and autonomous driving may cause taxis to focus on areas of higher demands and lower the service levels in the suburban regions of the city.     

Shared ride services in North America: definitions,impacts, and the future of pooling

ABSTRACT

Shared ride services allow riders to share a ride to a common destination. They include ridesharing (carpooling and vanpooling); ridesplitting (a pooled version of ridesourcing/transportation network companies); taxi sharing; and microtransit. In recent years, growth of Internet-enabled wireless technologies, global satellite systems, and cloud computing - coupled with data sharing – are causing people to increase their use of mobile applications to share a ride. Some shared ride services, such as carpooling and vanpooling, can provide transportation, infrastructure, environmental, and social benefits. This paper reviews common shared ride service models, definitions, and summarises existing North American impact studies. Additionally, we explore the convergence of shared mobility; electrification; and automation, including the potential impacts of shared automated vehicle (SAV) systems. While SAV impacts remain uncertain, many practitioners and academic research predict higher efficiency, affordability, and lower greenhouse gas emissions. The impacts of SAVs will likely depend on the number of personally owned automated vehicles; types of sharing (concurrent or sequential); and the future modal split among public transit, shared fleets, and pooled rides. We conclude the paper with recommendations for local governments and public agencies to help in managing the transition to highly automated vehicles and encouraging higher occupancy modes.     

Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use

Fluctuating fuel prices, rising congestion, longer commutes, and related environmental and human health effects have combined to once more draw the interest of governments, commuters, and firms toward the concept of travel demand management (TDM). While TDM is not new, the proliferation of mobile telephony, fixed Internet, and associated applications has created fresh prospects for the implementation of commuter focused TDM strategies. One recent example is Carpool Zone, an on-line carpool-matching tool deployed and managed by the TDM group at Metrolinx, the regional transportation planning agency within Canada’s largest metropolitan region, the Greater Toronto and Hamilton Area. Using data provided by Metrolinx, this paper broadens current thinking on carpool formation and use. The main hypothesis guiding this work is that the carpool formation and use process is sensitive to personal and household characteristics, space, time, travel cost, and workplace TDM policies. Results from a logistic regression analysis suggest that geographical proximity to other users; workplace TDM policies; the scheduling of work; and commuter role preference increase the odds of successfully carpooling. Importantly, findings regarding the positive influence of workplace TDM policies suggest that Internet based TDM tools will likely require critically important investment in human capital at the back-end to ensure program participation.     

Improved modeling of park‐and‐ride transfer time: Capturing the within‐day dynamics

An important factor that affects park‐and‐ride demand is transfer time. However, conventional park‐and‐ride demand models treat transfer time as a single value, without considering the time‐of‐day effect. Since early comers usually occupy spots closer to the entrance, their transfer times are shorter. Hence, there is a relationship between arrival time and transfer time. To analyze this relationship, a micro‐simulation model is developed. The model simulates the queuing system at the entrance and the pattern that parking spots are occupied in the parking lot over time. As expected, the model output illustrates an increasing relationship between arrival time and transfer time. This relationship has significant implication in mode choice models because it means that the attractiveness of park‐and‐ride depends on the time of arrival at the park‐and‐ride lot. This model of park‐and‐ride transfer time can potentially improve travel demand forecasting, as well as facilitate the operation and design of park‐and‐ride facilities.     

A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost

Developing demand responsive transit systems are important with regard to meeting the travel needs for elderly people. Although Dial‐a‐ride Problems (DARP) have been discussed for several decades, most researchers have worked to develop algorithms with low computational cost under the minimal total travel costs, and fewer studies have considered how changes in travel time might affect the vehicle routes and service sequences. Ignoring such variations in travel time when design vehicle routes and schedules might lead to the production of inefficient vehicle routes, as well as incorrect actual vehicle arrival times at the related nodes. The purpose of this paper is to construct a DARP formulation with consideration of time‐dependent travel times and utilizes the traffic simulation software, DynaTAIWAN, to simulate the real traffic conditions in order to obtain the time‐dependent travel time matrices. The branch‐and‐price approach is introduced for the time‐dependent DARP and tested by examining the sub‐network of Kaohsiung City, Taiwan. The numerical results reveal that the length of the time window can significantly affect the vehicle routes and quantitative measurements. As the length of the time window increases, the objective value and the number of vehicles will reduce significantly. However, the CPU time, the average pickup delay time, the average delivery delay time and the average actual ride time (ART)/direct ride time (DRT) will increase significantly as the length of the time window increases. Designing the vehicle routes to reduce operating costs and satisfy the requirements of customers is a difficult task, and a trade‐off must be made between these goals. Copyright © 2014 John Wiley & Sons, Ltd.