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Understanding the characteristics of passenger vehicle use is the prerequisite for effective urban management. However, it has been challenging in the existing literature due to the lack of continuously observed data on passenger vehicle use. Thanks to the advances in data collection and processing techniques, multi-day vehicle trajectory data generated from volunteered passenger cars provide new opportunities for examining in depth how people travel in regular patterns. In this paper, based on a week's operation data of 6600 passenger cars in Shanghai, we develop a systematic approach for identifying trips and travel purposes, and classify vehicles into four categories using a Gaussian-Mixed-Model. A new method is proposed to identify vehicle travel regularities and we use the Z Test to explore differences in travel time and route choices between four types of vehicles. We find that commercially used vehicles present high travel intensity in temporal and spatial aspects and the use intensity in elevated roads is higher for household-used commuting vehicles than semi-commercially used vehicles. The methodologies and conclusions of this paper may provide not only theoretical support for future urban traffic prediction, but also guidance for employing customized active traffic demand management measures to alleviate traffic congestion. [ABSTRACT FROM AUTHOR]

Enhancing the temporal competitiveness of public transit (PT) over private cars is a crucial strategy for promoting PT mode share and alleviating traffic congestion, especially for commuter trips. However, to our best knowledge, previous studies have rarely considered the impact of time reliability and analyzed the critical stages (e.g., accessing, waiting, transferring) that affect PT competitiveness. To fill these research gaps, we develop a comprehensive set of indicators to evaluate the effect of temporal reliability on the competitiveness of PT compared to private cars for commuter trips. We then conduct a detailed examination of the commuting competitiveness of PT at both the Origin-Destination (OD) and Traffic Analysis Zone (TAZ) levels by combining data from various sources obtained from Hangzhou, China. The results show that the average competitiveness of PT increases after considering reliability. Metro competitiveness rises significantly, and bus competitiveness increases for short trips but decreases for long trips. Furthermore, the bus is far less competitive than the metro, and TAZs near the metro stations could be highly competitive. Moreover, in-bus time affects bus competitiveness primarily, and improving the accessibility of metro stations is essential to enhance metro competitiveness. In conclusion, the proposed methodology presents a comprehensive approach to assess the competitiveness of PT versus cars, including travel time reliability. This methodology enables a more nuanced understanding of the factors influencing PT competitiveness and offers valuable insights for strategically intervening to enhance its performance effectively. • Public transport is more competitive than cars when travel time reliability is considered than when it is not. • Metro is more competitive than the bus, especially considering travel time reliability. • It is not the case that the higher density of the public transit stops, the more competitive the PT is. • Long in-bus and transferring time, low accessibility of station decreases the bus and metro competitiveness, respectively. [ABSTRACT FROM AUTHOR]

Despite decades of research, it is unclear under which circumstances travel is most onerous. While studies have found that some individuals derive positive utility from aspects of commuting, others have shown that traffic congestion can entail important time, monetary, and mental stress costs. Moreover, responses to traffic congestion-related stressors differs by individual characteristics. In response, this research captures how exposure to traffic congestion events, the duration of this exposure, and individual trait susceptibility to congestion affect the utility of commuting. Working through the lens of individual satisfaction with the duration of their commute, we show that not every minute of travel is valued the same by car commuters in Canadian cities. Results suggest a complex relationship between travel time, congestion, and individual predisposition to congestion-related stress. While improvements in travel time matter for increasing commute satisfaction, it is reductions in travel in congested conditions that matter most, particularly among those susceptible to congestion-related stressors. [ABSTRACT FROM AUTHOR]

Purpose – In order to alleviate the impacts of traffic congestion that undermine the mobility and accessibility conditions of the Aristotle University campus, the paper aims at the presentation and description of a complementary network of alternative modes (i.e. pedestrian and bicycle) and the discussion of the appropriate measures for its successful implementation in the campus. Design/methodology/approach – The methodological approach of the paper is twofold: the overview of good practices for implementing cycling and pedestrian networks in European university campuses in an attempt to identify an integrated activity framework compatible to the European approach; and a questionnaire survey for the assessment of the modal split for trips towards and from the campus and the current mobility and accessibility conditions for pedestrians and cyclists in the Aristotle University campus. Findings – The successful implementation of alternative transport networks in university campuses depends on the specific features of each campus in relation to the urban transport network and the commuting characteristics of staff and students. In the case of the Aristotle University campus, the modal split shows that 2/3 of campus-related trips are conducted by motorised transport while the share of bicycle use is very low. In order to promote cycling and walking in the campus, a combined approach must be adopted based on five fields of activity: policy; research; design; support and promotion; and monitoring. Research limitations/implications – The paper derives from the research initiatives of the Aristotle University's Sustainable Mobility Committee, which was founded in order to promote sustainable solutions for the campus's transport system. Originality/value – The paper provides a common and integrated activity framework for the implementation of an alternative transport network in a university campus based on the extensive overview of European experience. Furthermore, it develops for the first time a full proposal for the implementation of a pedestrian and bicycle network in the Aristotle University campus, which is one of the oldest and largest campuses in Greece. [ABSTRACT FROM AUTHOR]

This paper investigates the welfare effect of travelling through congested areas and adverse weather through changes in the speed of individuals' car trips based on the entire commuting trip. Weather measurements are local and time specific (hourly basis). As most commuters travel twice a day between home and work, we are able to employ panel data techniques, which deals with issues related to unobserved heterogeneity and data selection. We find that travelling through congested areas reduces speed by about 7%. For most commuters the welfare effects of adverse weather conditions are negative but small. However, the commuters' welfare costs due to rain are rather substantial during the evening peak in congested areas (and up to 12% of the overall commuting costs). [ABSTRACT FROM AUTHOR]

The purpose of our paper is to generalize the model by Arnott et al. (1990a) to situations with a single origin and destination connected by two routes and to test the analytical results in an experiment with discrete time departure choices. The experimental evidence does not support the theoretical predictions: While the accumulated experience creates significant learning effects which imply a positive evolution of the empirical travel costs towards the equilibrium, the Nash hypothesis is still rejected and the commuting system shows substantial fluctuations until the end of the experiment. [ABSTRACT FROM AUTHOR]

Traffic congestion has caused great concern among policymakers in large cities around the world. In contrast with constantly increasing transport supply, individual-based active travel demand management (ATDM) has been proposed as a more efficient policy alternative for combating congestion. However, how individuals make routing choices during commuting in response to ATDM incentives is still largely unknown, given the lack of individual travel data. Using a desensitized one-week travel trajectory data set involving 5641 personal electric vehicles, we examine the major influencing factors of commuting route stability during working days and make suggestions on targeting the most responsive commuters. We first filter family-used vehicles by clustering vehicle usage patterns through employing the Gaussian mixture model and interpret drivers' route choice behaviors during morning peak hours. To look for factors affecting route stability, we develop a generalized additive model and find that route stability is significantly associated with road network density of origins and destinations, departure time, travel duration, commuting distance, reliability of the expressway, and volatility of the congested sections by which the routes passed. The empirical results may contribute to the understanding of individual route choices, and help urban managers develop more refined ATDM policies to alleviate traffic congestion in the future. [ABSTRACT FROM AUTHOR]

Abstract Commuting is an essential part of urban life. Long commutes have negative impacts on individuals and society, such as stress, loss of productivity, traffic congestion and air pollution. However, researchers often face the challenge of lack of data such as commute distance, duration, departure/arrival time, and origins/destinations in countries such as China. This study uses points of interest (POIs) to estimate employment locations, and implements a gravity-based model to estimate interzonal commuting patterns in central Shanghai, China. The results reveal a "busy corridor" in the west of the central city, especially during the morning peak hours. This pattern corresponds well with reported real-time traffic conditions in Shanghai. Our methodology offers a promising alternative for studying commuting patterns when such data are limited. Highlights • This study uses a gravity-based model to estimate commuting patterns. • It shows that POIs can be used to estimate employment. • Employment in Shanghai has a monocentric structure. • There is a busy commuting corridor in the western part of central Shanghai. • It offers an alternative to study commuting patterns when there are limited data. [ABSTRACT FROM AUTHOR]

Abstract: We introduce the idea of a European-type congestion call option to value commuting to work along a given path for a given departure time selected by automobile drivers who are modeled as Cournot–Nash non-cooperative agents competing for limited roadway capacity when the alternative of telecommuting exists. We show how to compute flow patterns based on congestion call options and contrast these to traditional user optimized flow patterns. In particular, a numerical example is presented that shows congestion options have the potential to lower the network-wide social costs of congestion. [Copyright &y& Elsevier]

The main reason for contemporary transport problems related to traffic congestion in urban transport networks is the excessive number of passenger cars used by people commuting to work (i.e., to places where they carry out their work duties). During the COVID-19 pandemic, a significant reduction in traffic flow was observed due to the implementation of remote work. Currently, transport problems are similar to those observed before the pandemic period. This article presents the results of research and a discussion on various factors, the recognition and analysis of which enable the virtualization of activities related to work duties. Contribution to the development of science and knowledge in the field of transport, and in particular in urban mobility planning, justifies the need for in-depth research taking into account, among other matters, objective and subjective personal factors in the assessment of social generation preferences to carry out activities in a virtual form (e.g., remote work). Proper recognition of these factors enables the development of mobility plans that can significantly reduce traffic congestion. [ABSTRACT FROM AUTHOR]

• Employs quantitative research and analysis methods. • Explores traffic congestion in light of CSR ratings and its translation to real-world outcomes. • An innovative idea on sustainable transportation and policy in CSR. • Enhancing CSR policy in mitigating traffic congestion is an area where private entities can have a significant local impact on a social issue affecting people, plant, and profit. Traffic congestion (TC) is a complex issue that has an adverse impact on the environment, business operations, livability, and health of a community. Supply-side TC mitigation measures increase transportation capacities while demand-side measures attempt to modify travel behavior so that the travel demand is reduced. As part of the demand-side, some corporations are investing in TC reduction through actions that contribute to improved walkability, reduced peak travel demand, and active commuting. While beneficial for their local communities, TC reduction efforts are not specifically tagged as a part of corporate social responsibility (CSR) endeavors. CSR involves reporting of a company's stewardship towards its community and environmental impact. Research reflecting on the impact of CSR on TC has not been conducted. This study aims to fill this gap. Using corporations headquartered in the top traffic-congested cities in the United States, this study examines the relationship between TC and CSR. This research employed a hierarchical linear model with two datasets, Travel Time Index (TTI) and CSRHub ratings. Of the four CSR categories studied, community, employees, and environment ratings are significantly related to TTI, with employees and environment ratings having an inverse relationship to TTI. This shows that congestion has a strong impact on the environment and that companies, through their employee policies, can impact TC. The results also highlight the opportunities that companies have in potentially reducing their environmental impact by incorporating congestion reduction strategies as part of their CSR, either as a separate measure or as part of their environmental or employee CSR ratings. Our results are also a starting point for new tools/strategies that transportation policymakers and analysts can use to engage companies to help mitigate TC. A further study on other cities with major traffic problems may shed more light on CSR and TC. [ABSTRACT FROM AUTHOR]

Various government laws have recently been enacted to alleviate the environmental deterioration of transportation systems. Environmental constraint is a valid means to explicitly reflect various environmental protection requirements imposed by the government. In this paper, we examine the environmentally constrained traffic equilibrium problem (EC-TEP), which is a fundamental tool for modeling and evaluating environmental protection requirements. Specifically, we provide an equivalent reformulation for the EC-TEP. The proposed reformulation adapts the concept ofgap functionto simultaneously reformulate the nonlinear complementarity conditions associated with the generalized user equilibrium conditions, environmental constraints, and conservation constraints as an equivalent unconstrained optimization problem. This gap function reformulation has two desirable features: (1) it can handle a generalenvironmental constraintstructure (linear or nonlinear; link-based or area-based) and a generallink and route coststructure, enhancing the modeling adaptability and flexibility; (2) it is smooth and unconstrained, permitting a number of existing efficient algorithms for its solution. A gradient-based solution algorithm with a self-regulated averaging stepsize scheme is customized to solve the reformulated unconstrained optimization problem. Numerical examples are also provided to demonstrate the modeling flexibility of the proposed EC-TEP reformulation. [ABSTRACT FROM AUTHOR]

This paper examines the design and efficiency of a highway use reservation system where commuters need reservations to access a highway facility at specific times. We show that, by accommodating reservation requests to the level that the highway capacity allows, traffic congestion can be relieved. Generally, a more differentiated design of the reservation system yields a higher reduction of travel cost and thus achieves a higher efficiency. The efficiency bound of the system is established. We also show that braking or tactical waiting behaviors of drivers would cause a loss of efficiency, which thus need be proactively accommodated. Given that user heterogeneity cause further loss of efficiency, we explore how two specific types of user heterogeneity affect the system efficiency. Auction-based reservation is then proposed to mitigate the efficiency loss. [ABSTRACT FROM AUTHOR]