Commuters’ acceptance of and behavior reactions to license plate restriction policy: A case study of Tianjin,China

License plate restriction (LPR) policies are currently being implemented in major Chinese cities with the aim of mitigating traffic congestions. Meanwhile, much controversy regarding the effectiveness of the LPR policies is arising. To better understand the impact of the LPR policies, this paper studies commuters’ acceptance of and behavior reactions to the policies after their implementation. A theoretical model was proposed as the first step, followed by a questionnaire survey that was conducted in Tianjin, China, where an LPR policy has been in place since March 2014. Car owners frequently commuting within the restricted area were sampled as respondents, and a multi-variable regression method was employed to analyze the collected survey data. The results indicate that it is necessary to promote public’s acceptance of the LPR policy, because lower acceptance will lead to more negative reactions towards the policy, which may weaken its effectiveness. Main factors affecting the level of acceptance of the policy are also found, which may serve as a reference for transportation authorities seeking to increase commuters’ acceptance of the policy. These findings are beneficial to designing and implementing LPR policies.     

Flexing service schedules: Assessing the potential for demand-adaptive hybrid transit via a stated preference approach

This paper assesses the demand for a flexible, demand-adaptive transit service, using the Chicago region as an example. We designed and implemented a stated-preference survey in order to (1) identify potential users of flexible transit, and (2) inform the service design of the flexible transit mode. Multinomial logit, mixed-logit, and panel mixed-logit choice models were estimated using the data obtained from the survey. The survey instrument employed a d_p-efficient design and the Google Maps API to capture precise origins and destinations in order to create realistic choice scenarios. The stated-preference experiments offered respondents a choice between traditional transit, car, and a hypothetical flexible transit mode. Wait time, access time, travel time, service frequency, cost, and number of transfers varied across the choice scenarios. The choice model results indicate mode-specific values of in-vehicle travel time ranging between $16.3 per hour (car) and $21.1 per hour (flexible transit). The estimated value of walking time to transit is $25.9 per hour. The estimated value of waiting time at one’s point of origin for a flexible transit vehicle is $11.3 per hour; this value is significantly lower than the disutility typically associated with waiting at a transit stop/station indicating that the ‘at-home’ pick-up option of flexible transit is a highly desirable feature. The choice model results also indicate that respondents who use active-transport modes or public transit for their current commute trip, or are bikeshare members, were significantly more likely to choose flexible and traditional transit than car commuters in the choice experiments. The implications of these and other relevant model results for the design and delivery of flexible, technology-enabled services are discussed.     

Accounting for systematic heterogeneity across car commuters in response to multiple TDM policies: case study of Tehran

Modeling commuters’ choice behavior in response to transportation demand management (TDM) helps in predicting the consequences of TDM policies. Although research looking at choice behavior has evolved to investigate preference heterogeneity in response to factors influencing mode choice, as far as we know, no study has considered taste variation across commuters in response to multiple TDM policies. This paper investigates the presence of systematic preference heterogeneity across commuters, in response to the TDM policies that can be explained by their socio-economic or commuting-related characteristics. Analysis is based on results of a stated preference survey developed using a Design of Experiments approach. Five policies were assessed in order to study the impact they had on how commuters chose their mode of transportation. These include increasing parking cost, increasing fuel cost, implementing cordon pricing, reducing transit time and improving access to transit facilities. For the sake of assessing both systematic and random preference heterogeneity across car commuters, a form of the Mixed Multinomial Logit (MMNL) model that identifies sources of heterogeneity and consequently makes the choice models less restrictive in considering both systematic and random preference variation across individuals was developed. The sample includes 366 individuals who regularly commute to their workplace in the city center of Tehran, Iran. The likelihood function value of this model shows a significant improvement compared to the base MNL model, using the same variables. The MMNL model shows that taste variation across the studied commuters results in differences in influences estimated for three policies: increasing parking cost, reducing transit time and improving access to transit. The analysis examines several distributions for random parameters to test the impacts of restricting distributions to allow for only normality. The results confirm the potential to improve model fit with alternative distributions.     

Transit user perceptions of driverless buses

This paper reports the results of a stated preference survey of regular transit users’ willingness to ride and concerns about driverless buses in the Philadelphia region. As automated technologies advance, driverless buses may offer significant efficiency, safety, and operational improvements over traditional bus services. However, unfamiliarity with automated vehicle technology may challenge its acceptance among the general public and slow the adoption of new technologies. Using a mixed logit modeling framework, this research examines which types of transit users are most willing to ride in driverless buses and whether having a transit employee on board to monitor the vehicle operations and/or provide customer service matters. Of the 891 surveyed members of University of Pennsylvania’s transit pass benefit program, two-thirds express a willingness to ride in a driverless bus when a transit employee is on board to monitor vehicle operations and provide customer service. By contrast, only 13% would agree to ride a bus without an employee on board. Males and those in younger age groups (18–34) are more willing to ride in driverless buses than females and those in older age groups. Findings suggest that, so long as a transit employee is onboard, many transit passengers will willingly board early generation automated buses. An abrupt shift to buses without employees on board, by contrast, will likely alienate many transit users.

     

Carpooling: Who,how and why

Carpooling is the commuting mode of 18 to 20% of American workers, but relatively little definitive information has been available on who carpools, how and why. Based on data from the 1977–1978 Nationwide Personal Transportation Survey, this paper analyzes the characteristics of carpoolers, distinguishes among different types of carpoolers, identifies the key differences between carpoolers and drive alone and transit commuters, describes how commuters carpool, and offers explanations of why commuters carpool. The paper also addresses the issue of the feasibility of a substantial increase in carpool mode share.     

Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology,application and impact evaluation

This paper illustrates a ride matching method for commuting trips based on clustering trajectories, and a modeling and simulation framework with ride-sharing behaviors to illustrate its potential impact. It proposes data mining solutions to reduce traffic demand and encourage more environment-friendly behaviors. The main contribution is a new data-driven ride-matching method, which tracks personal preferences of road choices and travel patterns to identify potential ride-sharing routes for carpool commuters. Compared with prevalent carpooling algorithms, which allow users to enter departure and destination information for on-demand trips, the proposed method focuses more on regular commuting trips. The potential effectiveness of the approach is evaluated using a traffic simulation-assignment framework with ride-sharing participation using the routes suggested by our algorithm. Two types of ride-sharing participation scenarios, with and without carpooling information, are considered. A case study with the Chicago tested is conducted to demonstrate the proposed framework’s ability to support better decision-making for carpool commuters. The results indicate that with ride-matching recommendations using shared vehicle trajectory data, carpool programs for commuters contribute to a less congested traffic state and environment-friendly travel patterns.     

Identifying transit deserts for low-income commuters in Wuhan Metropolitan Area,China

The rapid expansion of many Chinese cities has put increasing pressure on existing urban transportation systems. Using Baidu users’ location data, this research analyzes the spatial patterns of the transit systems and commuter flows in Wuhan Metropolitan Area, China, and identifies transit deserts affecting low-income commuters. The results show that, first, most transit demand are generated by trips between neighboring communities, while large transit supply tends to occur between distant communities in the region. Second, about 11.21% of low-income commuters are affected by transit deserts in Wuhan Metropolitan Area. In detail, 61.30% of them commute within the city centers and 36.06% of them commute within the suburbs. Only about 2.64% of them actually travel between city centers and suburbs. Third, for low-income suburban commuters, transit deserts occur when they are surrounded by low-density transit infrastructure and low-frequency transit services, which makes it very difficult for them to connect to rest of the region. However, for low-income commuters residing in the city centers, transit deserts are mainly caused by the large numbers of transit-dependent people competing for limited transit supply in the areas. This research explores the relationship between transit systems and commuting demand in a major Chinese metropolitan area. The findings could help guide future transit system planning in China and beyond.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

A novel permit scheme for managing parking competition and bottleneck congestion

Morning commuters may have to depart from home earlier to secure a parking space when parking supply in the city center is insufficient. Recent studies show that parking reservations can reduce highway congestion and deadweight loss of parking competition simultaneously. This study develops a novel tradable parking permit scheme to realize or implement parking reservations when commuters are either homogeneous or heterogeneous in their values of time. It is found that an expirable parking permit scheme with an infinite number of steps, i.e., the ideal-scheme, is superior to a time-varying pricing scheme in the sense that designing a permit scheme does not require commuters’ value of time information and the performance of the scheme is robust to the variation of commuters’ value of time. Although it is impractical to implement the ideal-scheme with an infinite number of steps, the efficiency loss of a permit scheme with finite steps can be bounded in both cases of homogeneous and heterogeneous commuters. Moreover, considering the permit scheme may lead to an undesirable benefit distribution among commuters, we propose an equal cost-reduction distribution of parking permits where auto commuters with higher value of time will receive fewer permits.     

Waiting time perceptions at transit stops and stations: Effects of basic amenities,gender, and security

Waiting time in transit travel is often perceived negatively and high-amenity stops and stations are becoming increasingly popular as strategies for mitigating transit riders’ aversion to waiting. However, beyond recent evidence that realtime transit arrival information reduces perceived waiting time, there is limited empirical evidence as to which other specific station and stop amenities can effectively influence user perceptions of waiting time. To address this knowledge gap, the authors conducted a passenger survey and video-recorded waiting passengers at different types of transit stops and stations to investigate differences between survey-reported waiting time and video-recorded actual waiting time. Results from the survey and video observations show that the reported wait time on average is about 1.21 times longer than the observed wait time. Regression analysis was employed to explain the variation in riders’ reported waiting time as a function of their objectively observed waiting time, as well as station and stop amenities, weather, time of the day, personal demographics, and trip characteristics. Based on the regression results, most waits at stops with no amenities are perceived at least 1.3 times as long as they actually are. Basic amenities including benches and shelters significantly reduce perceived waiting times. Women waiting for more than 10 min in perceived insecure surroundings report waits as dramatically longer than they really are, and longer than do men in the same situation. The authors recommend a focus on providing basic amenities at stations and stops as broadly as possible in transit systems, and a particular focus on stops on low-frequency routes and in less safe areas for security measures.     

The evening commute with cars and transit: Duality results and user equilibrium for the combined morning and evening peaks

This paper extends Vickrey’s (1969) commute problem for commuters wishing to pass a bottleneck for both cars and transit that share finite road capacity. In addition to this more general framework considering two modes, the paper focuses on the evening rush, when commuters travel from work to home. Commuters choose which mode to use and when to travel in order to minimize the generalized cost of their own trips, including queueing delay and penalties for deviation from a preferred schedule of arrival and departure to and from work. The user equilibrium for the isolated morning and evening commutes are shown to be asymmetric because the schedule penalty in the morning is the difference between the departure and wished curves, and the schedule penalty in the evening is the difference between the arrival and wished curves. It is shown that the system optimum in the morning and evening peaks are symmetric because queueing delay is eliminated and the optimal arrival curves are the same as the departure curves.The paper then considers both the morning and evening peaks together for a single mode bottleneck (all cars) with identical travelers that share the same wished times. For a schedule penalty function of the morning departure and evening arrival times that is positive definite and has certain properties, a user equilibrium is shown to exist in which commuters travel in the same order in both peaks. The result is used to illustrate the user equilibrium for two cases: (i) commuters have decoupled schedule preferences in the morning and evening and (ii) commuters must work a fixed shift length but have flexibility when to start. Finally, a special case is considered with cars and transit: commuters have the same wished order in the morning and evening peaks. Commuters must use the same mode in both directions, and the complete user equilibrium solution reveals the number of commuters using cars and transit and the period in the middle of each rush when transit is used.     

Transportation serviceability analysis for metropolitan commuting corridors based on modal choice modeling

Major commuting corridors in metropolitan areas generally comprise multiple transportation modes for commuters, such as transit (subways or buses), private vehicles, or park-and-ride combinations. During the morning peak hour, the commuters would choose one of the available transportation modes to travel through the corridors from rural/suburban living areas to urban working areas. This paper introduces a concept of transportation serviceability to evaluate a transportation mode’s service status in a specific link, route, road, or network during a certain period. The serviceability can be measured by the possibility that travelers choose a specific type of transportation service at a certain travel cost. The commuters’ modal-choice possibilities are calculated using a stochastic equilibrium model based on general travel cost. The modeling results illustrate how transportation serviceability is influenced by background traffic flow in a corridor, value of comfort for railway mode, and parking fee distribution.     

Commuters’ willingness-to-pay for improvement of transfer facilities in and around metro stations – A case study in Kolkata

Although several cities in India are developing the metro system, there are lacunas associated with transfer facilities in and around metro stations. The present work aims to investigate the perception of commuters of Kolkata city, India in terms of their willingness-to-pay (WTP) for improvement of transfer facilities. A stated preference survey instrument was designed to collect choice responses from metro commuters and the database was analysed by developing random parameter logit (RPL) models. The decomposition effects of various socioeconomic and trip characteristics on mean estimates were also investigated in random parameter logit models with heterogeneity. The work indicates significantly high WTP of metro commuters as compared to the average metro fare for improvement of various qualitative attributes of transfer facility such as ‘facility for level change’, ‘visual communication’, ‘pedestrian crossing’, and ‘pedestrian environment’. The WTP values are also found to vary across different groups of commuter formed on the basis of ‘trip purpose’, ‘monthly household income’, ‘station type’ and ‘metro fare’. ‘Work trip’ commuters are found to have higher WTP for improvement of access time, pedestrian environment and use of an escalator over the elevator. On the other hand, ‘high-income group’ commuters have shown higher WTP for improvement of access time, pedestrian crossing, and pedestrian environment. While ‘high fare group’ commuters have higher WTP for access time and pedestrian environment, heterogeneity is also observed in WTP for facility for level change, pedestrian crossing, and pedestrian environment across commuters using different ‘station type’ (underground, at-grade, and elevated). The findings from the study provide a basis for formulating policies for the improvement of transfer facilities in and around metro stations giving due attention to the preference of commuters having different socioeconomic and trip characteristics.     

Integrating commuter information needs in the design of a motorist information system

This paper presents the results of a large sample survey designed to investigate the response of commuters to the delivery of traffic information. The main purpose of the survey was to investigate the impact of traffic information on commuters route choices, mode choices, and departure times in order to provide functional requirements for the design of a real-time motorist information system. The surveyed population consisted of 3,893 freeway motorists who routinely commuted to a central business district. The results of the survey indicated that four distinct commuter subgroups existed with respect to their traffic information needs: These groups were: (1) route changers, those willing to change route, or mode before entering the freeway (20.6%), (2) nonchangers, those unwilling to change time, route, or mode (23.4%), (3) time and route changers, (40.1%), and (4) pretrip changers, those willing to change time, mode, or route before leaving the house (15.9%). In terms of receiving traffic information, commercial radio was rated as the most useful and preferred medium both before and while driving. However, only a small, discrete group of commuters were likely to be influenced to change transportation mode. Implication of the survey results for the design of a real-time motorist information system are discussed.     

Social Media Use during Unplanned Transit Network Disruptions: A Review of Literature

Abstract

This paper explores social media's role in managing unplanned transit networks disruptions. Although literature exists more broadly on the use of social media in transit, this paper presents the first literature review in this setting. When disruptions occur, commuters require reliable, up-to-date information. Its provision reduces anxiety and allows informed choices. Social media is beneficial given it provides real-time information but it can only supplement (not replace) conventional approaches. Information reliability was critical. Research in the field of disaster management illustrates the importance of publicly contributed information. Known as “crowdsourcing”, it is part of the emerging field of crisis informatics which for the first time was linked to unplanned transit disruption management. The results highlight that social media's real-time nature can reduce disrupted travel demand; however, its utilisation can be resource-intensive. A framework presented illustrates how social media utilisation varies according to the operational characteristics of a disrupted network. Social media use as an information delivery tool is still in its infancy and an unwillingness to embrace it is an impediment to sustained growth. Crowdsourcing is one approach that could resolve the issue of transit agency resourcing whilst satisfying the increased demand and expectation for real-time information.     

An analysis of the commuter departure time decision

Transportation planners and transit operators alike have become increasingly aware of the need to diffuse the concentration of peak period travel in an effort to improve gasoline economy and reduce peak load requirements. An evaluation of the potential effectiveness of strategies directed to achieve this end requires an understanding of factors which affect commuter trip timing decisions. The research discussed in this article addresses this particular problem through the development and estimation of a commuter departure time (to work) choice model.A number of conclusions were drawn based on the departure time model results and related analyses. It was found that work schedule flexibility, mode, occupation, income, age, and transportation level of service all influence departure time choice. The uncertainty in work arrival time and the consequences of various work arrival times may also be determinants of commuter departure time choice.The estimated model represents improvements over previous work in that it more explicitly considers work arrival time uncertainty and travelers' perceived loss associated with varying work arrival times, and additional socio-demographic factors which can potentially affect departure time choice. Furthermore, the estimated model includes consideration of transit commuters, in addition to single occupant auto and carpool work travelers. The inclusion of transit commuters represents a particularly important contribution for policy analysis, since the model could potentially be used to study the effect of service and employment policies on transit system peak load requirements.     

Understanding the Relationship Between Physical and Virtual Representations of Transit Agencies

Abstract

This study examines whether physical attributes of transit agencies, such as agency size, make a difference in how transit websites are designed, and how transit information is distributed. The objective of this study is to see if there is a relationship between physical and virtual representations of transit agencies. A rating instrument is developed for evaluating the quality of transit websites. Our findings suggest that transit agency size plays a key role in determining website quality: When the size of transit system is large, the information about the agency is too complex to be effectively presented on web pages. Thus, the quality of the large agencies’ websites is lower than medium-sized agencies. Instead, we find that large agencies attempt to design more user-friendly sites, and provide advanced information searching tools to compensate for low information quality. Policy implications for transit agencies are discussed.     

Policy Simulation for New BRT and Area Pricing Alternatives Using an Opinion Survey in Jakarta

Abstract

An area pricing scheme for Jakarta, Indonesia, is currently under review as a transportation control measure along with the operation of new bus rapid transit (BRT) system. While this scheme may be effective for congestion reduction in the central business district (CBD), provision of alternative means of transportation for auto users that are ‘pushed-out’ is of great importance to obtain public acceptance. Hence, it is necessary to simulate simultaneously the area pricing scheme and the BRT development which may serve as an alternative for assumed ‘pushed-out’ auto users. Utilizing data from an opinion survey, this paper studies how BRT and auto ridership are likely to vary as a function of traveler and system attributes. Additionally, the study attempts to evaluate the way this new travel mode is distinguished from other existing conventional transportation alternatives in Jakarta. The survey data contains socioeconomic information of over 1000 respondents as well as details of to-work/school trips to the CBD including mode, travel cost, time, etc. Respondents were asked about their willingness to shift from their current mode to BRT to make the same travel for different BRT fare levels. Modeling efforts suggest that a mixed logit model performs better in explaining choice behavior. Therefore, this model was used for policy simulation. The simulation results brought about many implications as to the tested policies. While the developed models may be applied only to future BRT corridors in which the survey was conducted, they capture the key variables that are significant in explaining mode choice behavior and present great potential for practical use in policy simulation and analysis in a large metropolitan area of the developing world.     

Improving travel efficiency by parking permits distribution and trading

In this paper, we study various parking management schemes in a many-to-one network, where each origin is connected to the destination by a highway with a bottleneck and a parallel transit line. First, we derive a model to compute the morning commuting pattern when the destination has inadequate parking space to accommodate potential private cars. Second, we propose and compare the following three schemes of distributing parking permits to commuters residing in different origins: uniform, Pareto improving, and system optimum distribution of parking permits. Third, free trading of parking permits among commuters in a free market is introduced to better cater for commuters’ parking needs. Numerical examples show that parking permits distribution and trading are very efficient in traffic management.     

The effects of attitudes and personality traits on mode choice

We hypothesise that differences in people’s attitudes and personality traits lead them to attribute varying importance to environmental considerations, safety, comfort, convenience and flexibility. Differences in personality traits can be revealed not only in the individuals’ choice of transport, but also in other actions of their everyday lives—such as how much they recycle, whether they take precautions or avoid dangerous pursuits. Conditioning on a set of exogenous individual characteristics, we use indicators of attitudes and personality traits to form latent variables for inclusion in an, otherwise standard, discrete mode choice model. With a sample of Swedish commuters, we find that both attitudes towards flexibility and comfort, as well as being pro-environmentally inclined, influence the individual’s choice of mode. Although modal time and cost still are important, it follows that there are other ways, apart from economic incentives, to attract individuals to the, from society’s perspective, desirable public modes of transport. Our results should provide useful information to policy-makers and transportation planners developing sustainable transportation systems.