scholarly journals ANALYSIS ON MARGINAL COST OF TRAFFIC CONGESTION CONSIDERING DEPARTURE TIME CHOICE

2006 ◽  
Vol 62 (1) ◽  
pp. 96-112
Author(s):  
Takamasa IRYO ◽  
Yasuo ASAKURA
Keyword(s):  
Traffic Congestion ◽  
Marginal Cost ◽  
Departure Time ◽  
Departure Time Choice

scholarly journals Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays

2020 ◽  
Vol 12 (24) ◽  
pp. 10470
Author(s):  
Haiyan Zhu ◽  
Hongzhi Guan ◽  
Yan Han ◽  
Wanying Li
Keyword(s):  
Traffic Congestion ◽  
Choice Behavior ◽  
Road Traffic ◽  
Stated Preference ◽  
Revealed Preference ◽  
The Road ◽  
Departure Time ◽  
Departure Time Choice ◽  
Mnl Model ◽  
Peak Travel

The adjustment of road toll is an important measure that can alleviate road traffic congestion by convincing car travelers to travel during off-peak times. In order to reduce congestion on the expressway on the first day of a holiday, factors that affect the departure times of holiday travelers must be comprehensively understood to determine the best strategy to persuade car travelers to avoid peak travel times. This paper takes holiday car travelers as the research object and explores the characteristics and rules of departure time choice behavior for different holiday lengths. Based on Utility Maximization Theory, a multinomial logit (MNL) model of departure time choice for a three-day short holiday and a seven-day long holiday was established. Model calibration and elastic analysis were carried out using Revealed Preference/Stated Preference (RP/SP) survey data. Additionally, the influence of the highway toll policy on departure times for long and short holidays was analyzed. The results show that the rate of first-day departures is much higher than that of other departure times for both short and long vacations under the current policy of free holiday passage on highways. Factors such as trip duration, size of the tourist group, the number of visits, travel range, travel time, monthly income, occupation, age and road toll have a significant influence on the departure time decisions of holiday car travelers, and the effect and degree of influence are markedly different for different holiday lengths. The effects of tolls for each departure time and different pricing scenarios on the choice behavior of travelers are different between long and short holidays. Furthermore, the effectiveness of the road toll policy also varies for travelers with different travel distances. This study can provide useful information for the guidance of holiday travelers, the management of holiday tolls on expressways and the formulation of holiday leave time.

scholarly journals Modeling Departure Time Choice of Car Commuters in Dhaka, Bangladesh

2021 ◽  
pp. 036119812110398
Author(s):  
Khatun Zannat ◽  
Charisma Farheen Choudhury ◽  
Stephane Hess
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Logit Model ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Data Sources ◽  
Similar Data ◽  
Schedule Delay ◽  
Departure Time ◽  
Departure Time Choice

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.

scholarly journals Departure Time Choice (DTC) Behavior for Intercity Travel during a Long-Holiday in Bangkok, Thailand

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Bhawat Chaichannawatik ◽  
Kunnawee Kanitpong ◽  
Thirayoot Limanond
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Multinomial Logit Model ◽  
Time Of Day ◽  
Travel Patterns ◽  
Peak Period ◽  
Intercity Travel ◽  
Departure Time ◽  
Departure Time Choice

Time-of-day (TOD) or departure time choice (DTC) has become an interesting issue over two decades. Many researches have intensely focused on time-of-day or departure time choice study, especially workday departures. However, the travel behavior during long-holiday/intercity travel has received relatively little attention in previous studies. This paper shows the characteristics of long-holiday intercity travel patterns based on 2012 New Year data collected in Thailand with a specific focus on departure time choice of car commuters due to traffic congestion occurring during the beginning of festivals. 590 interview data were analyzed to provide more understanding of general characteristics of DTC behavior for intercity travel at the beginning of a Bangkok long-holiday. Moreover, the Multinomial Logit Model (MNL) was used to find the car-based DTC model. The results showed that travelers tend to travel at the peak period when the parameters of personal and household are not so significant, in contrast to the trip-related characteristics and holiday variables that play important roles in traveler decision on departure time choice. Finally, some policies to distribute travel demand and reduce the repeatable traffic congestion at the beginning of festivals are recommended.

Departure and travel time model for the temporal distribution of morning rush-hour traffic congestion

2019 ◽  
Vol 31 (02) ◽  
pp. 2050023
Author(s):  
Sida Luo
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Temporal Distribution ◽  
Time Estimation ◽  
Wave Model ◽  
Model Parameters ◽  
Travel Time Estimation ◽  
Time Model ◽  
Departure Time ◽  
Departure Time Choice

The chronic traffic congestion undermines the level of satisfaction within a society. This study proposes a departure time model for estimating the temporal distribution of morning rush-hour traffic congestion over urban road networks. The departure time model is developed based on the point queue model that is used for estimating travel time. First, we prove the effectiveness of the travel time model (i.e. point queue), showing that it gives the same travel time estimation as the kinematic wave model does for a road with successive bottlenecks. Then, a variant of the bottleneck model is developed accordingly, aiming to capture travelers’ departure time choice for commute trips. The proposed departure time model relaxes a traditional assumption that the last commuter experiences the free flow travel time and considers travelers’ unwillingness of late arrivals for work. Numerical experiments show that the morning rush-hour generally starts at 7:29 am and ends at 8:46 am with a traffic congestion delay index (TCDI) of 2.164 for Beijing, China. Furthermore, the estimation of rush-hour start and end time is insensitive to most model parameters including the proportion of travelers who tend to arrive at work earlier than their schedules.

scholarly journals Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

2014 ◽  
Vol 2014 ◽  
pp. 1-16
Author(s):  
Qinmu Xie ◽  
Shoufeng Ma ◽  
Ning Jia ◽  
Yang Gao
Keyword(s):  
Traffic Congestion ◽  
Evolutionary Dynamics ◽  
Mass Transit ◽  
Urban Traffic ◽  
Peak Period ◽  
Transit System ◽  
Departure Time ◽  
Departure Time Choice ◽  
Multiagent Modeling ◽  
Formation And Evolution

With the growing problem of urban traffic congestion, departure time choice is becoming a more important factor to commuters. By using multiagent modeling and the Bush-Mosteller reinforcement learning model, we simulated the day-to-day evolution of commuters’ departure time choice on a many-to-one mass transit system during the morning peak period. To start with, we verified the model by comparison with traditional analytical methods. Then the formation process of departure time equilibrium is investigated additionally. Seeing the validity of the model, some initial assumptions were relaxed and two groups of experiments were carried out considering commuters’ heterogeneity and memory limitations. The results showed that heterogeneous commuters’ departure time distribution is broader and has a lower peak at equilibrium and different people behave in different pattern. When each commuter has a limited memory, some fluctuations exist in the evolutionary dynamics of the system, and hence an ideal equilibrium can hardly be reached. This research is helpful in acquiring a better understanding of commuter’s departure time choice and commuting equilibrium of the peak period; the approach also provides an effective way to explore the formation and evolution of complicated traffic phenomena.

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