Impact of high occupancy vehicle lanes on carpooling behavior

High occupancy vehicle lanes have become an integral part of regional transportation planning. Their purpose is to increase ridesharing by offering a travel time advantage to multiple occupant vehicles. This paper examines the extent to which an HOV facility increases ridesharing. Using data from the Route 55 HOV facility in Orange Country, California, changes in the carpooling rate on Route 55 are compared to that of a control group of freeway commuters. The analysis shows that the carpooling rate among peak period commuters, and particularly those who use the entire length of the facility, has increased. However, there has been no significant increase in ridesharing among the entire population of Route 55 commuters. Results suggest that barriers to increased ridesharing are formidable, that travel time savings must be large in order to attract new carpoolers, and that further increases in capooling will likely require development of extensive HOV lane systems.     

Balanced strategy based on environment and user benefit-oriented carpooling service mode for commuting trips

Transportation - Besides saving money and providing convenience, carpooling can result in environmental benefits to society; therefore, it is important to promote and improve daily carpooling...     

Exploring partnership between transit agency and shared mobility company: an incentive program for app-based carpooling

Transportation - How should public transit agencies deliver mobility services in the era of shared mobility? Previous literature recommends that transit agencies actively build partnerships with...     

On the morning commute problem with carpooling behavior under parking space constraint

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.     

The GRAAL of carpooling: GReen And sociAL optimization from crowd-sourced data

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.     

Time-declining risk-adjusted social discount rates for transport infrastructure planning

Transportation - This paper proposes a social discount rate for transport infrastructure project evaluation in Germany that accounts for production efficiency, systematic traffic demand risk, as...     

The marginal social cost of headway for a scheduled service

This brief paper derives the marginal social cost of headway for a scheduled service, i.e. the cost for users of marginal increases to the time interval between departures. In brief we may call it the value of headway in analogy with the value of travel time and the value of reliability. Users have waiting time costs as well as schedule delay costs measured relative to their desired time of arrival at the destination. They may either arrive at the station to choose just the next departure or they may plan for a specific departure in which case they incur also a planning cost. Then planning for a specific departure is costly but becomes more attractive at longer headways. Simple expressions for the user cost result. In particular, the marginal cost of headway is large at short headways and smaller at long headways. The difference in marginal costs is the value of time multiplied by half the headway.     

Egocentric social networks and social interactions in the Greater Tokyo Area

Transportation - This article presents the results of a survey on egocentric social networks in the Greater Tokyo Area. This is, together with our preliminary study, the first study on egocentric...     

沥青拌和设备“油改气”技术

该项目是对沥青混合料拌和设备的加热系统进行改造,用天然气替换重油、柴油为燃料（简称“油改气”项目）。改造的加热系统包括加热石料的燃烧器和加热沥青的燃烧器改造,以及天然气在厂区内的储存设施的建造和天然气供应管道的铺设。该项目对沥青混合料拌和设备的系统改造,能有效地减少二氧化碳的排放,降低二氧化硫和烟尘等有害污染物的排放,无论从节约能源方面还是降低污染方面都有巨大效益。     

混凝土组合搅拌站在隧道施工中的应用

文章结合铁路隧道混凝土施工,叙述并归纳了混凝土组合搅拌站的选型、配置、安装及使用等情况,对铁路施工和其它混凝土施工现场的设备设置具有一定的指导作用.     

A threshold model of social contagion process for evacuation decision making

Individual evacuation decisions are often characterized by the influence of one’s social network. In this paper a threshold model of social contagion, originally proposed in the network science literature, is presented to characterize this social influence in the evacuation decision making process. Initiated by a single agent, the condition of a cascade when a portion of the population decides to evacuate has been derived from the model. Simulation models are also developed to investigate the effects of community mixing patterns and the initial seed on cascade propagation and the effect of previous time-steps considered by the agents and the strength of ties on average cascade size. Insights related to social influence include the significant role of mixing patterns among communities in the network and the role of the initial seed on cascade propagation. Specifically, faster propagation of warning is observed in community networks with greater inter-community connections.     

Correcting for endogeneity in behavioral choice models with social influence variables

While psychologists and behavioral economists emphasize the importance of social influences, an outstanding issue is how to capture such influences in behavioral models used to inform urban planning and policy. In this paper we focus on operational models that do not require explicit knowledge of the individual networks of decision makers. We employ a field effect variable to capture social influences, which is calculated as the percent of population in the peer group that has chosen the specific alternative. We define the peer group based on socio-economic status and spatial proximity of residential location. As in behavioral economics and psychology, the concept is that one is influenced by the choices made by one’s peers. However, using such a social influence variable in a behavioral model causes complications because it is likely endogenous; unobserved factors that impact the peer group also influence the decision maker, yielding correlation between the field effect variable and the error. The contribution of this paper is the use of the Berry, Levinsohn, and Pakes (BLP) method to correct the endogeneity in a choice model. The two-stage BLP introduces constants for each peer group to remove the endogeneity from the choice model (where it is difficult to deal with) and insert it into a linear regression model (where endogeneity is relatively easier to deal with). We test the method using a mode choice data set from the Netherlands and readily available software and find there is an upward bias of the field effect parameter when endogeneity is not corrected. The procedure outlined presents a practical and tractable method for incorporating social influences in choice models.     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

沥青温拌技术在改性沥青混合料中的应用

介绍了温拌技术的特点,总结了温拌沥青混凝土的施工工艺,并对试验路进行了检测,结果表明各项指标都满足规范要求。     

鹤大高速杏复段粉喷桩施工监理

结合鹤大高速宁复段工程中粉喷桩施工的工艺过程和监理要点,简要说明如何加强粉喷桩施工过程的质量监控,确保粉喷桩处理达到应有的加固效果。     

Counting people in the crowd using social media images for crowd management in city events

Transportation - City events are getting popular and are attracting a large number of people. This increase needs for methods and tools to provide stakeholders with crowd size information for crowd...     

The social dimension in action: A multilevel,personal networks model of social activity frequency between individuals

This paper presents a social activity-travel generation model, which explicitly incorporates the individual’s social dimension through the concept of personal networks, modeling the multilevel structure of social relations defined by these networks. The objective of the analysis is to study the relevance of the social dimension as a source of explanation of social activity-travel generation behavior between an individual and each relevant person of their social life. The paper uses a disaggregated perspective of personal networks, explicitly incorporating the characteristics of each network member as well as the characteristics of the overall social structure. Using an ordinal multilevel specification that accounts for the social network in which individuals are embedded, four dimensions are studied: personal characteristics, “with whom” activities are performed, social network composition and structure, and ICT (information and communication technology) interaction. The results show that a proper and complete understanding of social activity generation requires going beyond the individualistic paradigm, explicitly incorporating the role of the social dimension in the study of this decision-making process.