Commuters’ Departure Time Decisions in Brussels, Belgium

1997 ◽  
Vol 1607 (1) ◽  
pp. 139-146 ◽  
Author(s):  
André De Palma ◽  
Asad J. Khattak ◽  
Deepak Gupta

Factors that influence commuters’ departure time decisions are explored, especially the trade-off between travel time and schedule delay. Stated and reported behavior data obtained from a survey of commuters in Brussels, Belgium, were used to analyze the influence of socioeconomic and contextual variables. The key findings were as follows. Daily schedules for flextime and fixed-time commuters were quite similar, suggesting that flextime commuters do not extensively use their flexibility to avoid peak-period congestion. When commuters changed their departure times between home and work, their arrival times shifted by a similar amount. This implies that the shortening of travel time is not as critical as other reasons, such as requirements and personal convenience, in motivating departure time changes. Furthermore, 35 to 50 percent of the respondents were unwilling to change their departure times to save 10 min of travel time. Therefore, departure time changes may not be feasible in many cases for the range of travel times encountered in urban areas. Among those willing to make further trade-offs by changing departure times, the values for the early and late schedule delay–travel time trade-off were similar for both the stated and the reported preferences and were broadly consistent with those from other studies. The travel time–schedule delay trade-off values are calculated for the a.m. and p.m. commutes. Commuters who experienced longer travel times were more likely to change their departure times. When changing departure times, females and managers were less likely to depart from home later than usual, and managers were also more likely to depart earlier than usual. To analyze relationships empirically, ordinary-least-squares and tobit models of departure time are estimated. Finally, the implications are discussed.

Author(s):  
Janusz Supernak ◽  
Christine Kaschade ◽  
Duane Steffey

Selected results are presented of the Traffic Study, one of 12 studies conducted by San Diego State University for the I-15 Congestion (Value) Pricing Project in San Diego, a 3-year demonstration. The focus is on the project's impact on travel times and their distribution on both the main lanes and the express lanes of I-15 for both ExpressPass and FasTrak phases of the project. Specifically addressed is the issue of reliability of on-time arrival enjoyed by the FasTrak subscribers and the high variability of travel times for the I-15 travelers who use only main lanes of I-15 for their commute. Examination of the ramp and freeway delays shows that in the worst-case scenario, FasTrak subscribers who use express lanes can save up to 20 min avoiding delay on the I-15 main lanes. This finding agrees with the drivers’ perceptions about their time savings when using FasTrak. Travel-time changes during the duration of the project also are examined. There were substantial year-to-year changes in travel times along the I-15 main lanes and the I-8 lanes used as control. The travel-time profile along the I-15 main lanes differed significantly from the profile along I-8, the control corridor, in both a.m. and p.m. peak periods.


Author(s):  
Luong H. Vu ◽  
Benjamin N. Passow ◽  
Daniel Paluszczyszyn ◽  
Lipika Deka ◽  
Eric Goodyer

Author(s):  
Khatun Zannat ◽  
Charisma Farheen Choudhury ◽  
Stephane Hess

Dhaka, one of the fastest-growing megacities in the world, faces severe traffic congestion leading to a loss of 3.2 million business hours per day. While peak-spreading policies hold the promise to reduce the traffic congestion levels, the absence of comprehensive data sources makes it extremely challenging to develop econometric models of departure time choices for Dhaka. This motivates this paper, which develops advanced discrete choice models of departure time choice of car commuters using secondary data sources and quantifies how level-of-service attributes (e.g., travel time), socio-demographic characteristics (e.g., type of job, income, etc.), and situational constraints (e.g., schedule delay) affect their choices. The trip diary data of commuters making home-to-work and work-to-home trips by personal car/ride-hailing services (957 and 934 respectively) have been used in this regard. Given the discrepancy between the stated travel times and those extracted using the Google Directions API, a sub-model is developed first to derive more reliable estimates of travel time throughout the day. A mixed multinomial logit model and a simple multinomial logit model are developed for outbound and return trip, respectively, to capture the heterogeneity associated with different departure time choice of car commuters. Estimation results indicate that the choices are significantly affected by travel time, schedule delay, and socio-demographic factors. The influence of type of job on preferred departure time (PDT) has been estimated using two different distributions of PDT for office employees and self-employed people (Johnson’s SB distribution and truncated normal respectively). The proposed framework could be useful in other developing countries with similar data issues.


2020 ◽  
Author(s):  
Florian Dandl ◽  
Gabriel Tilg ◽  
Majid Rostami-Shahrbabaki ◽  
Klaus Bogenberger

The growing popularity of mobility-on-demand fleets increases the importance to understand the impact of mobility-on-demand fleets on transportation networks and how to regulate them. For this purpose, transportation network simulations are required to contain corresponding routing methods. We study the trade-off between computational efficiency and routing accuracy of different approaches to routing fleets in a dynamic network simulation with endogenous edge travel times: a computationally cheap but less accurate Network Fundamental Diagram (NFD) based method and a more typical Dynamic Traffic Assignment (DTA) based method. The NFD-based approach models network dynamics with a network travel time factor that is determined by the current average network speed and scales free-flow travel times. We analyze the different computational costs of the approaches in a case study for 10,000 origin-destination (OD) pairs in a network of the city of Munich, Germany that reveals speedup factors in the range of 100. The trade-off for this is less accurate travel time estimations for individual OD pairs. Results indicate that the NFD-based approach overestimates the DTA-based travel times, especially when the network is congested. Adjusting the network travel time factor based on pre-processed DTA results, the NFD-based routing approach represents a computationally very efficient methodology that also captures traffic dynamics in an aggregated way.


TEM Journal ◽  
2020 ◽  
pp. 951-958
Author(s):  
Fatmah Yousef Assiri

Traffic congestion impacts economics, health, and productivity. Traffic congestion is increasing in the urban areas and negatively impacts people in these areas due to air pollution, accidents, delays in travel time, and more. In Saudi Arabia, more than 500,000 people have died or been injured because of traffic. To improve this problem, we developed a rewarding system that encourages people to drive during off-peak hours. In addition, the system provides recommendations for a preferred departure time in order to avoid traffic congestion. Recommended departure time is based on historical data. This system will be used to create dataset of drivers and traffic information in order to build an intelligent recommendation system


2021 ◽  
Author(s):  
Joel Hansson ◽  
Fredrik Pettersson-Löfstedt ◽  
Helena Svensson ◽  
Anders Wretstrand

AbstractDue to relatively low patronage levels, rural bus stops are sometimes questioned in order to improve travel time and reliability on regional bus services. Previous research into stop spacing has focused on urban areas, which means that there is a lack of knowledge regarding the effects of bus stops in regional networks, with longer distances, higher speeds, and lower passenger volumes, in general. The present study addresses this knowledge gap by analysing the effects of bus stops on a regional bus service regarding average travel times, travel time variability, and on-time performance. This is done by statistical analysis of automatic vehicle location (AVL) data, using a combination of methods previously used for analysis of rail traffic and urban bus operations. The results reveal that bus stops that are only used sporadically have a limited impact on average travel times, in general. In contrast, they are all the more influential on travel time variability, and, in turn, on on-time performance. On the studied bus service, the number of stops made have a far greater impact on travel time variability than any of the other included variables, such as the weather or traffic conditions during peak hours. However, the results suggest that rural bus stops have a much lower impact than what we define as secondary bus stops in urban areas. Consequently, by primarily focusing on bus stop consolidation in urban areas, it is possible to significantly improve service reliability without impairing rural coverage.


2020 ◽  
Author(s):  
Florian Dandl ◽  
Gabriel Tilg ◽  
Majid Rostami-Shahrbabaki ◽  
Klaus Bogenberger

The growing popularity of mobility-on-demand fleets increases the importance to understand the impact of mobility-on-demand fleets on transportation networks and how to regulate them. For this purpose, transportation network simulations are required to contain corresponding routing methods. We study the trade-off between computational efficiency and routing accuracy of different approaches to routing fleets in a dynamic network simulation with endogenous edge travel times: a computationally cheap but less accurate Network Fundamental Diagram (NFD) based method and a more typical Dynamic Traffic Assignment (DTA) based method. The NFD-based approach models network dynamics with a network travel time factor that is determined by the current average network speed and scales free-flow travel times. We analyze the different computational costs of the approaches in a case study for 10,000 origin-destination (OD) pairs in a network of the city of Munich, Germany that reveals speedup factors in the range of 100. The trade-off for this is less accurate travel time estimations for individual OD pairs. Results indicate that the NFD-based approach overestimates the DTA-based travel times, especially when the network is congested. Adjusting the network travel time factor based on pre-processed DTA results, the NFD-based routing approach represents a computationally very efficient methodology that also captures traffic dynamics in an aggregated way.


1981 ◽  
Vol 71 (6) ◽  
pp. 1903-1927
Author(s):  
R. W. Clymer ◽  
T. V. McEvilly

Abstract The general failure of searches for precursory seismic travel-time variations associated with strike-slip earthquakes in California has led to this investigation into the feasibility of using a controlled-source seismic method to improve significantly the precision of travel-time measurements, and to investigate the nature of any detected travel-time changes. Travel times have been measured over a period of several years at sites south of Hollister, California, along the seismically active creeping zone of the San Andreas fault, using a single-channel VIBROSEIS system with real-time on-site data processing. At a site near Bear Valley, 7 km from the fault, no variations in the travel time of a deep crustal reflection were observed that could be associated with local earthquakes. However, significant variations (0.5 to 2.5 msec) of first arrival travel times observed near the Cienega Winery may have been associated with a series of nearby earthquakes and with a creep event. Major sources of measurement error have been identified in source variations and in rainfall-induced variations in near-surface properties. The former limits the precision of the deep reflection measurements to about 0.05 per cent of the travel time and the first arrival measurements to about 0.1 per cent of the travel time. The second effect is apparent as seasonal oscillations in travel time of as much as 15 to 20 msec, and also in wavelet amplitude and waveform, giving an implied travel-time accuracy of about 0.2 per cent for the deep reflection measurements and about 1 per cent for first arrivals. While these noise levels are disappointing, they can be reduced significantly by improved field procedures. Ongoing experiments are testing such procedures.


1997 ◽  
Vol 1607 (1) ◽  
pp. 178-184 ◽  
Author(s):  
André De Palma ◽  
Fabrice Marchal ◽  
Yurii Nesterov

METROPOLIS proposes an interactive environment that simulates automobile traffic in large urban areas. The core of the system is a dynamic simulator that integrates commuters’ departure time and route choice behaviors over large networks: Drivers are assumed to minimize a generalized travel cost function that depends on travel time and schedule delay. This simulator is based on a behavioral driver information process. It allows real-time and off-line simulations. The system also includes a scenario builder and a graphical results viewer. The main ideas underlying METROPOLIS are presented, and preliminary computer simulation experiments are discussed for Geneva, Switzerland.


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