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Understanding intra-urban human mobility patterns and their potential driving forces are vital to city planning and commercial site selection. In this paper, we first investigate the functions of urban regions and how different region types dynamically influence people's trip decisions. Furthermore, we characterize urban circadian rhythms by time-vary inter-regional transition probabilities between these regions with different functions, and integrate them into intervening opportunity model to predict human mobility. Public transportation card data in Shanghai are used to demonstrate the effectiveness of the model in terms of station passenger flows, travel time and trip flux. By taking regional function into consideration, the proposed model significantly improved the prediction accuracy. Quantitative analysis ulteriorly indicates that trip intentions and regional features are critical elements in trip flux prediction, especially in the afternoon and evening when people have an abundance of opportunities to travel by their own volition. When the function of a certain region changes, our model is able to make reasonable predictions accordingly. The results indicate the importance of considering individual travel motivation and regional function in modeling human mobility. The proposed model could serve as a guide for popularity and trip flux prediction in urban planning and reconstruction.

Urban commuters and road authorities are interested in knowing how well their city can manage traffic conditions. It is challenging to make a fair comparison among global cities due to the absence of a consistent, publicly accessible and inexpensive framework. This study proposes a methodology to compare travel time and average speed in different cities. Large cities have a central core, in which many of the major activities take place. This core is called downtown or the central business district (CBD). In this study, a comparison is made by simulating the morning commute trips from origins outside to destinations inside the CBD. The proposed framework outlines how the city and the CBD borders are defined. The data are collected by an accessible location service (Google Maps Distance Matrix Application Programming Interface). The framework is conducted on 11 major cities from the five continents, namely Cairo, London, Los Angeles, Melbourne, Moscow, New York, Paris, Singapore, Sydney, Tehran and Toronto. As such Singapore and Cairo had the shortest, while London and Paris had the longest travel times. According to the distribution graphs of average speed and travel time, Asian and African cities experienced a relatively higher average speed and a lower travel time.

In most dense urban environments in emerging markets, retail deliveries are very fragmented to thousands of nanostores. It is not uncommon for a delivery route to include more than 60 stops. Unloading bays are often blocked by regular traffic. Due to the complex urban environment, it is difficult to estimate the benefits of making unloading bays available. In this study, we conduct a field experiment in an urban field lab of one square kilometer in the downtown of Querétaro, Mexico. During the treatment period of one week, we obtain help from the local traffic police to keep the unloading bays available for unloading only. Using advanced GPS devices and extensive manual field observations, we are able to capture the change in driver behavior and the direct efficiency increases. We find a high efficiency gain, not only in travel time (39%) but also – remarkably – in the total time parked (17%). Corrected for other effects, we estimate a gain of about 44% in total time per delivery. Apart from the insights on unloading benefits, we also provide insights into the method of field experimentation in such a complex environment.

We conduct a discrete choice experiment on 1556 solo-driving commuters in Lyon, France to estimate the values of end-to-end travel time (VoTT) of commuting trips in the presence of a HOV-lane for four modes: Solo Driver, Carpool Driver, Carpool Passenger and Public Transport. Using discrete choice models, we find a strong heterogeneity in VoTT across modes and individuals. The analysis of individual heterogeneity distinguishes four behavior patterns: reluctant to mode change (20% of our sample), preferring the three alternative modes over solo driver (35%), preferring public transport (12%) and preferring driver modes whether solo or carpool (32%). We find that current solo drivers are more likely to switch to carpooling as a driver rather than as a passenger. As suggested by our simulations aimed at marginally changing mode shares, carpool passenger will be the scarce resource if one wants to decrease car traffic by stimulating carpooling for commuting trips.

Travelers' behavior is predicted based on their individual preferences. People search for alternatives to maximize their benefit from doing activities, such as increasing the activity time by minimizing the travel time. Traffic congestion and the scarcity of parking spaces in the city center motivate the decision-makers to encourage travelers to use the park-and-ride (P&R) system. An evaluation concerning the impact of using the P&R system on the travel behavior of car users is conducted. Some of the existing P&R facilities are incorporated into the daily activity plans of car travelers to produce new daily activity plans (i.e., P&R facility is considered an activity). By using the Multi-Agent Transport Simulation (MATSim) open-source tool, simulations of the daily activity plans including the P&R system and autonomous vehicles (AVs) are conducted. The study examines three scenarios: (1) a simulation of the existing condition, (2) a simulation of the daily activity plans of the travelers with the P&R system, and (3) a simulation of the daily activity plans of the travelers with the P&R system and AVs. The results show that using the P&R system increases the overall travel time compared with the existing conditions, and the use of AVs as a transport mode impacts the existing modal share as follows: 64 % of the car users switch to AVs, while 15 % of the car users switch to public transport. The output of this study might be used by policy-makers in parking pricing and the location of the P&R facilities.

This study aims to analyze congestion and parking points to construct a behavioral model of congestion, parking, and traffic performance, as well as develop scenarios for projecting the congestion reduction in Makassar City, Indonesia. Three stages were conducted in the study, namely the use of surveys for collecting data on the parking and congestion levels, and the public’s perceptions in developing a behavioral model towards the relationship between parking and congestion. Furthermore, a resolving scenario and projection model for reducing the level of congestion in 2020 to 2050 were compiled. In the first phase, a survey of 67 roads consisting of 78 segments in Makassar was employed to measure the parking and congestion levels. The variables observed were the number of congestion points, vehicle volume, city road capacity, degree of saturation, speed, travel time, and delay. Furthermore, the second stage surveyed the community's perception of the relationship between congestion and parking by distributing questionnaires to 250 respondents. These respondents were selected by incidental sampling in 8 points representing the subdistricts in Makassar. The last stage involved focused group discussions with city managers to formulate resolving scenarios. Base on the scenarios, the projection of the congestion reduction was estimated. The results indicated that the severe congestion incidents, which reduce the travel services in the city, occurred due to crossroads, T junctions, U-turns, parking, and complex occasions. Also, the behavioral model indicated the assessment level and showed that resolving parking issues tend to have more impact in reducing congestion. Therefore, focus group discussions recommend short, medium, and long-term solutions. In addition, projections over 30 years suggest remarkable improvement when resolving parking issues and traffic management are considered in congestion reduction strategies.

Priority to emergency vehicles, buses, high occupancy vehicles (HOVs), and priced low occupancy vehicles (LOVs) is critical to their efficiency and reliability, where multi-functional exclusive lane (MFEL) serves as a salient element with independent operation environment. To enhance MFEL utility and balance the demand between prioritized and non-prioritized vehicles, this research proposes an optimization model for MFEL design and management to comprehensively serve the trip modes with various priority levels and distinct operation patterns, considering the delay from lane access, bus stop dwelling, signalized intersections, and ride-sharing. Case study follows to calibrate and validate the proposed model under varying passenger demand and emergency vehicle frequency, finding that MFEL may reduce total travel time in all scenarios especially under high traffic demand. Sensitivity analyses test the effect of road lane count and bus occupancy on MFEL design and management, where the road with more lanes is more flexible to accommodate increased passenger demand without increasing HOV critical occupancy or LOV price rate. Moreover, higher bus occupancy assists in avoiding significant increase of LOV price rate to promote trip equity. This research may lay foundation to MFEL implementation to mitigate traffic congestion and promote transport sustainability.

This study considers a closed core-suburb city connected by a highway. Two travel modes, namely on-demand and frequency-based autonomous vehicles (AVs), are used for commuting between the suburb and urban core. Each resident attempts to maximize his/her individual utility with consideration to environment quality by choosing a residential location, travel mode, departure time, and non-housing composite consumption good within an expenditure budget. The traffic equilibria are analytically derived for two right-of-way policies, namely (i) the two travel modes sharing the right-of-way and (ii) frequency-based AVs-priority, with consideration of the effect of AVs on travel and urban characteristics. It was found from the analytical results that at any level of AV automation, adopting the frequency-based AVs-priority policy can reduce travel cost for suburban residents while alleviating traffic congestion. Furthermore, an increase in AV automation level results in an increase in expected trip time if the highway capacity is less elastic than the value of travel time for on-demand AVs with respect to the automation level. In addition, if the environment quality depends solely on the residential density, with an increasing level of AV automation, the suburban population and the number of residents using on-demand AVs increase, the land rent in the urban core reduces, the suburb expands, and the utility for all residents increases. These findings help to provide a better understanding of the interactions between AVs, travel and urban characteristics, and serve as a valuable reference to transportation-urban planning in the era of driving automation.

Rail transit agencies have greatly advanced the ability to measure delays to rail system customers and have developed key performance indicators for rail systems based on customer travel time. The ability for operators to link these customer delay metrics to root causes would provide great benefit to agencies, from incident response improvement to capital program prioritization. This paper describes a method for linking late train arrivals to both late customers and incident tickets. Inspired by traffic flow theory, the method identifies impact zones in time and space that can then be linked to a potential root cause by way of incident tickets. This algorithm is currently under development by the Washington Metropolitan Area Transit Authority’s Office of Planning, and its outputs are being integrated into a variety of operations- and capital-related business processes.

This work is motivated by the high rate of private car use by commuters in Australian cities. Considering the various benefits of public transport (PT), it is imperative to analyze the shortcomings of the PT networks in comparison to car travel. For this purpose, this work focuses on analyzing the travel time difference between PT and car journeys. This paper presents a methodology to analyze the relative mobility of a PT network in comparison to car travel. The key component of this methodology is the use of two complementary relative mobility metrics that are developed to determine the portions of PT journeys that are inefficient (time-wise) in comparison to car trips. The first metric is the point-to-point relative mobility used to perform spatial distribution analysis, and the second is the PT line relative mobility that evaluates the performance of the PT routes. A demonstration of the methodology is presented by using a case study from Melbourne (Australia). The results of the case study show some inefficient segments of the PT services in several areas, and within the Port Melbourne area in particular. Therefore, this information can be used to assist decision makers to prioritize PT improvements to encourage mode shifts to PT.

This research analyses the characteristics of travel time reliability for the road network in Kota Bandar Lampung. Therefore, travel time consists of access, wait and interchange time, while its reliability deals with variations of in-passenger/private cars time. Survey of travel time on each road was carried out for 12 hours (from 06.00 to 18.00) for five working days. Furthermore, the buffer time method was used to measure the characteristics of time travel reliability consisting of five measuring tools, namely planning time, planning time index, buffer time, buffer time index and travel time index. This research found that the temporal effects are the main factor that tends to affect travel time, whereas network effects are the second factor that tends to affect travel time. Furthermore, the regression equation was developed to express the effect of planning time (TPlan) and free-flow travel time on average travel time .

In the passenger transportation segment, there is a trend towards door-to-door travel planning. This direction, which is relevant in the world practice of passenger transportation, with a correctly proposed approach, can also be used in the cities of the Russian Federation.The use of a multimodal method of passenger transportation together with MaaS technologies in case of maximum involvement of carrier operators will allow passengers to significantly reduce travel time and find a way to reduce travel costs.Sophisticated logistics of commuter rail transport routes for all time periods will attract additional passenger traffic, increasing the profitability of passenger traffic.The conducted research on the example of the transport-interchange complex of the city of N showed the possibility of organizing a passenger's trip "from door to door" with minimal costs and maximum comfort. The passenger railway company receives direct profit from this service, which makes it possible to recoup the project in a short time. Conclusions are made about the dependence of the profitability of the bus fleet on the number of seats, distance and popularity of the route direction. The organization of additional services on the territory as close as possible to the places of embarkation and disembarkation of passengers will increase the attractiveness of the transport and interchange complex for the passenger traffic of N.

This paper summarizes the findings from five years of commercial probe data validation conducted in the United States through the I-95 Corridor Coalition Vehicle Probe Project (VPP), focusing specifically on how travel time data quality on arterial facilities has changed since an initial study evaluated it during 2013 and 2014. Thirteen separate arterial validation efforts were conducted from 2014 to 2018 as part of VPP Phase II (VPPII), and data quality from three commercial probe vendors was evaluated through comparison with reference travel time data obtained via re-identification technology. Using two evaluation techniques—a traditional analysis that summarizes the accuracy of precision and bias error metrics, and a slowdown analysis that quantifies each vendor’s ability to capture major slowdown events—the results from VPPII studies are compared with data quality previously observed from nine validation efforts during Phase I (VPPI) from 2013 to 2014. The results show clear improvement in VPPII accuracy levels and suggest that commercial travel time data sets are suitable for many planning and operations applications.

The presence of roundabouts in the central business districts (CBD) of cities can reduce the travel speed of bus rapid transit (BRT) along the radial routes. A throughabout is an unconventional and low-cost design in which the central island is split to provide exclusive lanes for major traffic streams. Although the operation of throughabout has been limitedly investigated for private transport, it has been less considered by designers for public transport and for increasing the speed of the BRT system. The current study aims to evaluate the effects of throughabouts on private and public transports and to compare the design with standard roundabouts and conventional intersections. The calibrated and validated results of the microsimulation tool (AIMSUN) indicated that the throughabout improved the travel time of both public and private transports through better use of the space and kept the traffic flowing at all volume levels. The travel speed of the BRT in the throughabout was remarkably stable in both signal-controlled and unsignalized intersections. The standard roundabout was the second-best design. The throughabout can be very helpful in corridors along which the demand for the bus transit is high and the system needs to receive priority.

Reliability is one of the main metrics of transport system efficiency and quality of service. For both travelers and transport management organizations, the high variance of road travel times has become a problem. Reliability has been identified as one of the main areas of interest of the Strategic Highway Research Plan II. In order to evaluate congestion and unexpected changes in travel time, reliability metrics are increasingly used. GPS devices provide for exact assessment of travel time for each connection along the routes used for this research. (14 Ramadan arterial street, Al-Karada arterial street and Damascus arterial street). A GPS-equipped instrumented car was used to gather 50 test runs at peak and off peak times. At peak and off peak hours, 50 test runs were obtained using a GPS-equipped instrumented car. Raising the buffer time index results in inferior conditions for reliability. A buffer index of AL- Karada street was created about 53% and 30% for Damascus street and finally for 14 Ramadan street which present a 29% buffer index for north direction. As for its southern direction 14 Ramadan street created a buffer index of about 65% and 33% for AL- Karada street and finally for Damascus street which present a 29% buffer index. In addition, travel time index for (14 Ramadan street, AL- Karada street and Damascus street) respectively is about 2.8 %, 3.3% and 2.6% for north direction, as for its southern direction the travel time index is obtained for (14 Ramadan street, AL- Karada street and Damascus street) respectively were a 3%,3.7%, and 2.5%. Finally, the 95% percentile travel time for observed three selected routes in this study, the extra delay was felt on each route (1627, 2212, and 1192) sec. for (14 Ramadan street, AL- Karada street and Damascus street) for north direction, as for its southern direction the extra delay that perceived on each route (2221, 2132, and 975) sec. for (14 Ramadan street, AL- Karada street and Damascus street) respectively.

This type of public transportation BRT mode began to be officially applied in Pontianak City to overcome traffic congestion. The problem is that many travelers prefer to use private vehicles rather than public transportation. This study aims to analyze the sensitivity of the mode selection model which explains the probability of choosing a BRT against aprivate vehicles if a BRT is presented in the Central Business District of Pontianak City. The mode selection method uses the Stated Preferences Technique in the form of a quetionnaire which is analyzed by multiple linear regression to obtain a utility equation. Based on the results of the sensitivity analysis of the mode selection model, the probability value of selecting BRT is 21,7%, if it is in conditions where the difference in the attributes offacilities and comfort (X1) is -10, this means that there are no facilities and conveniences of BRTsuch as private vehicles, thesecond is the difference in thewaiting time attribute (X2) which is 15 minutes, the third condition is the difference in travel costs attribute (X3) namely Rp 0,- and the fourth condition is the difference in travel time attribute (X4), which is 10 minutes To increase the probability of choosing a BRT to 60%, it can be done by increasing the difference between the facilities and comfort attributes to 0 (zero), which means there is no difference in facilities and comfort that BRT has with private vehicles such as the availability of air conditioning, free WIFI, clean, fragrant, having a bag storage area and others. This is because the most sensitive attributes compared to other attributes are facilities and comfort attributes.

Due 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.

The correct estimation of ambulance travel time is an extremely important issue from the perspective of healthcare and the security of citizens. In some events, the threat to the health or life of an injured person increases with each minute of waiting for an ambulance. The authors of this article analyzed how ambulances travel throughout the entire Lesser Poland voivodeship in southern Poland. Based on the analysis of 300 million GPS records that were collected over several years from 300 ambulances, real ambulance speed characteristics were compiled for the most important cities in the region. The obtained results regarding ambulance speed characteristics were used to understand the correlation between ambulance speed, the density of the road network, and the built-up areas of a given city. Furthermore, the impact on the speed of ambulances of traffic, time of day, day of the week, or the season was also examined. The influence of the use of ambulances’ lights/sirens on travel time was also examined. The culmination of the research was the presentation of the theoretical foundations of coverage maps and a method of implementing them based on the determined speed characteristics. The presented studies show that the speed at which ambulances move is a very local phenomenon. Also, a relatively constant average speed of ambulances throughout the whole week was found. Moreover, a difference in speed between signaled and non-signaled ambulance trips was observed. The speed characteristics that were obtained were used as input data for the development of dynamic coverage maps, which are an invaluable tool for supporting the decisions of ambulance dispatchers.

This study proposes using intelligent transportation systems (ITS) and open-data sources to evaluate the impact of transportation network companies (TNCs) on ground access to airports. The unexpected interruption of the TNCs services in Austin, Texas, U.S., in 2016, is used as a natural experiment to provide a before-and-after analysis of the changes in the traffic conditions of the access area to the Austin-Bergstrom International Airport (ABIA). An analysis of variance (ANOVA) is implemented to determine whether the difference in speeds across periods is statistically significant, and the value of time for TNC-induced delay is estimated, using values of passengers’ willingness to pay for airport access travel time savings. Furthermore, a speed linear model is developed to assess the impact of TNC demand on ground access areas using trip information from an Austin-based TNC service. The main results suggest that airport ground access speeds were higher during the period that the TNCs were out of the city. The re-introduction of the services resulted in a speed reduction of 9% for the airport morning and 18% for the afternoon peak hours, translating to a total passenger cost of approximately $150+ (morning) and $400+ (afternoon) per hour. Furthermore, it was found that the number of TNC pick-up trips is a predictor of airport access speed and that the flight schedule can potentially be used to develop predictive speed models.

With the rapid development of high-speed rail (HSR) systems in China, the evaluation of the accessibility of HSR has become an important issue, especially for daily accessibility, or daytime round-trip travel (one-way journeys taking within 4 h), as this form of travel has significantly redefined the concept of the business trips are. This paper presents an improved approach to measuring potential-based accessibility by adding train frequency as an important weight and distinguishing the travel time into different intervals to measure accessibility. With a case study of Shandong Province, China, the paper verifies that the improved approach is more suitable for evaluating the daily accessibility and more practical for regional and transport planning than the original approach. First, the method is more effective in analyzing the differences in accessibility between cities and revealing more detailed changes or improvements in accessibility resulting from HSR. Second, there is a stronger correlation between the accessibility of different time intervals and the local economic level (GDP). Third, the method is more in line with the actual conditions in explaining the improved accessibility and corresponding spatial structures of a region. As a result, the improved approach provides an improved ability to better characterize the impacts of accessibility on regional development and will play an important role in regional planning and transportation planning. Finally, the paper also notes that the proposed approach is primarily suited for the middle-or macrolevel accessibility studies.

The 6th edition of the Highway Capacity Manual (HCM6) introduced a methodology for estimating and forecasting arterial travel time (TT) distributions (TTD) and their associated travel time reliability (TTR) metrics. Recently, it was shown that the HCM6 severely underestimated both the TTD and the TTR metrics for a test network in Lincoln, NE, U.S. Subsequently, it was shown that the underestimation issue could be eliminated through a proposed calibration methodology. Because this validation and calibration work was done on a single, relatively short section of arterial roadway there is an open research question on whether this finding applies to longer and more congested arterial roadways. The goal of this paper is to validate and calibrate the HCM6 TTR methodology on five arterial roadway testbeds that are longer and more congested than the original testbed. Empirical data from the National Performance Management Research Data Set (NPMRDS) which is managed by INRIX was used to represent the ground truth. Similar to the original study, it was found that the HCM6 TTR methodology severely underestimated the TTDs, and their respective TTR metrics, on all five testbeds. This is problematic, because the HCM6 methodology indicates that the corridors had more reliable TT than the empirical data would suggest. It was also shown that the calibration methodology eliminated this underestimation. It is recommended that users of the HCM6 TTR methodology validate and, if necessary, calibrate the model using local empirical travel data.

Automated vehicles (AVs) are expected to change personal mobility in the near future. Most studies on the mobility impacts of AVs focus on fully automated (SAE L5) vehicles, but the gradual development of the technology will probably bring AVs with more limited capabilities to begin with. This stated-preference study focused on the potential mobility impacts of conditionally automated (L3) and highly automated cars (L4). We investigated personal mobility impacts among 59 participants who experienced automated driving repeatedly in a driving simulator. Half of them drove with an L3 and half with an L4 motorway function. After the first and final drive they answered questions on their travel experience and how automated vehicles could change their mobility. After the drives, participants in both groups were willing to accept 30–50% longer travel times for a 30 min trip if they did not need to drive the whole trip themselves. This translates into savings of around 30% for the perceived value of travel time on routes where automation is available. There were no statistically significant differences between L3 and L4 in the accepted travel times. Most participants did not expect to make more trips with automated cars, but around half of them anticipated making longer trips. The amount of car travel may increase more with L4 than with L3 automation, possibly due somewhat to changes in the experienced travel quality. The results suggest that the mobility impacts of automated driving may increase with a higher level of automation.

There is increasing evidence that ridehailing and other private-for-hire (PfH) services such as taxis and limousines are diverting trips from transit services. One question that arises is where and when PfH services are filling gaps in transit services and where they are competing with transit services that are publicly subsidized. Using weekday trip-level information for trips originating in or destined for the city center of Portland, OR from PfH transportation services (taxis, transportation network companies, limousines) and transit trip data collected from OpenTripPlanner, this study investigated the temporal and spatial differences in travel durations between actual PfH trips and comparable transit trips (the same origin–destination and time of day). This paper contributes to this question and to a growing body of research about the use of ridehailing and other on-demand services. Specifically, it provides a spatial and temporal analysis of the demand for PfH transportation using an actual census of trips for a given 2 week period. The comparison of trip durations of actual PfH trips to hypothetical transit trips for the same origin–destination pairs into or out of the central city gives insights for policy making around pricing and other regulatory frameworks that could be implemented in time and space.

Recently, ridesharing has been noticed as an effective and sustainable mode of transport. In which, each passenger carries out a journey that benefits travelers and society greatly, such as reducing travel costs, reducing journey times, relieving road traffic congestions, preserving fuel and reducing air pollution. While the importance and efficiency of ridesharing, ridesharing among travelers has not been commonly utilized. This paper introduces an upgraded disaggregated utility model for a mode choice step in the four-step traffic demand model for transport of passengers in Tanta city - Gharbiya governorate. For the first time, the analysis in this paper includes ridesharing mode in addition to other three common modes; private vehicle, bus, and taxi . The aim of this research is to involve the ridesharing mode and new parameters in the mode choice analysis of the case study. This is done by including additional parameters such as travel cost and comfortable in addition to travel time. Based on surveys, the developed Multinomial logit utility models have been assessed using the McFadden pseudo R2 values. The values demonstrated high compatibility of results with real data as pseudo R2 values ranges between 0.2 and 0.4. In addition, all utility models developed for modes are found to have P-values less than 0.05 indicating the significance of the considered utility characteristics.

With the rise of urban sprawl, urban railways extend out further to the city’s outer district, installing additional stations. Passengers who travel from the outer district to the center of the city therefore experience long travel times. Although skip-stop strategy helps save total travel time, deviation of travel time among all origin–destination pairs may be increased, leading to equity problems. This study aims to minimize the inequity and total travel time through train stop planning and train scheduling. A coefficient of variation is adopted as a measure of inequity. The problem is formulated as a multi-objective mixed integer nonlinear programming model. Origin–destination demand is extracted from smartcard data and a case study of four urban railway lines in Seoul is conducted. The results indicate that the number of transfer stations for equity-oriented skip-stop strategy is smaller than that for total-travel-time-oriented skip-stop strategy. We also discover that as the number of transfer stations rises, inequity increases and total travel time is reduced. For skip-stop strategy considering total travel time and equity simultaneously, average total travel time and the average deviation are reduced by up to 10.3% and 10.6%, respectively, compared with those of all-stop strategy. We analyze the gradient of Pareto optimal sets to find out which factors (equity or total travel time) are more significant. Skip-stop strategy on lines 5 and 9 can be designed based on equity, while line 4 can be planned based on total travel time.

The metropolitan area experiences disaster due to large population density, urbanization and heterogeneous demands at different time periods and places, like accidents, sudden vehicle breakdowns, congestions, lane blockages, earthquakes, flood and hurricanes. These disasters cause severe property damages, economic losses and losses of life. Therefore, in order to reduce the effects of disasters an effective evacuation management of victims from disaster zone is necessary. The evacuation during and after the disaster is difficult due to several unforeseen hurdles. We need a dynamic and adaptive transport management scheme to suite the requirements. In this paper, we propose Emergent Intelligence (EI) technique based transport management for evacuation of victims from disaster zone to safe zone. The EI technique makes static agent (resided at depot in a disaster zone) to logically divide disaster zones into multiple zones and sub-zones. Static agent creates and dispatches mobile agents to these zones and sub-zones, and EI technique makes group communication among mobile agents and static agent, during group communication they collect, analyze and share estimated victims density, resources availability, resources allocated, relevant routes availability, and boundary of disaster. The static agent at a depot estimates guaranteed routes, evacuation exit points, fraction of victims arrive at each exit points, average travel time to exit evacuees from disaster location to exit points. A case study is presented to test the proposed system transport allocation to different routes depending upon population of victims for evacuation management in a disaster zone. The proposed system reduces average delay propagation (i.e., 4 sec.) of disaster information compared to the traditional system (i.e., 30 sec.), minimizes the average evacuation time (i.e., at max. 10 minutes) required for evacuating victims from disaster zone to safe zone, and also uniformly distributes victim among evacuation exit points.

Travel time reliability quantifies variability in travel times and has become a critical aspect for evaluating transportation network performance. The empirical travel time cumulative distribution function (CDF) has been used as a tool to preserve inherent information on the variability and distribution of travel times. With advances in data collection technology, probe vehicle data has been frequently used to measure highway system performance. One challenge with using CDFs when handling large amounts of probe vehicle data is deciding how many different CDFs are necessary to fully characterize experienced travel times. This paper explores statistical methods for clustering CDFs of travel times at segment level into an optimal number of homogeneous clusters that retain all relevant distributional information. Two clustering methods were tested, one based on classic hierarchical clustering and the other used model-based functional data clustering, to find out their performance on clustering distributions using travel time data from Interstate 64 in Virginia. Freeway segments and those within interchange areas were clustered separately. To find the proper data format as clustering input, both scaled and original travel times were considered. In addition, a non-data-driven method based on geometric features was included for comparison. The results showed that for freeway segments, clustering using travel times and the Anderson–Darling dissimilarity matrix and Ward’s linkage had the best performance. For interchange segments, model-based clustering provided the best clusters. By clustering segments into homogenous groups, the results of this study could improve the efficiency of further travel time reliability modeling.

As the share of public transport increases, the express strategy of the urban railway is regarded as one of the solutions that allow the public transportation system to operate efficiently. It is crucial to express the urban railway’s express strategy to balance a passenger load between the two types of trains, that is, local and express trains. This research aims to estimate passengers’ preference between local and express trains based on a machine learning technique. Extreme gradient boosting (XGBoost) is trained to model express train preference using smart card and train log data. The passengers are categorized into four types according to their preference for the local and express trains. The smart card data and train log data of Metro Line 9 in Seoul are combined to generate the individual trip chain alternatives for each passenger. With the dataset, the train preference is estimated by XGBoost, and Shapley additive explanations (SHAP) is used to interpret and analyze the importance of individual features. The overall F1 score of the model is estimated to be 0.982. The results of feature analysis show that the total travel time of the local train feature is found to substantially affect the probability of express train preference with a 1.871 SHAP value. As a result, the probability of the express train preference increases with longer total travel time, shorter in-vehicle time, shorter waiting time, and few transfers on the passenger’s route. The model shows notable performance in accuracy and provided an understanding of the estimation results.

We investigate the effects of autonomous vehicles (AVs) on highway congestion. AVs have the potential to significantly reduce highway congestion, since these vehicles are able to maintain smaller inter-vehicle gaps and travel together in larger platoons (or batches) than human-driven vehicles (HVs). Various policies have been proposed to regulate AVs on highways, yet no in-depth comparison of these policies exists. To address this shortcoming, we develop a queueing model for a multi-lane highway, and analyze two policies for a mixed fleet of HVs and AVs: the designated-lane policy (“D policy”) under which one lane is designated to AVs, and the integrated policy (“I policy”) under which AVs travel together with HVs in all lanes. Our analysis connects the service rate of the queueing system to congestion on the highway, as well as inter-vehicle gaps using a Markovian arrival process (MAP). We measure the performance of these policies using mean travel time and throughput as metrics. We show that although the I policy performs at least as well as a benchmark case with no AVs, the D policy outperforms the benchmark only when the highway is heavily congested and AVs constitute the majority of vehicles; in such a case this policy may outperform the I policy as well. These findings caution against recent industry and government proposals that the D policy should be employed at the beginning of the mass appearance of AVs. Finally, we calibrate our model to data; our numerical analysis shows that for highly congested highways, a moderate number of AVs can make substantial improvement (e.g., 22% AVs can improve throughput by 30%), and when all vehicles are AVs, throughput can be increased over 400%.

Research describes the effect of the on-street parking to the travel time of vehicle in crossing the road. The case study from this research is in the Jalan H. Agus Salim Jakarta Pusat, where the location is using the on street parking as the type of the parking system. Research method that we used is license plate method for travel time and parking characteristic survey. We used Manual Kapasitas Jalan Indonesia (MKJI) 1997 and linear regression as the based to calculate all the datas. To get the correlation between travel time and on-street parking, we used Correlation Test. With the value of R more than 0,8 it means the relationship between travel time and on-street parking is very strong. And for the result of the relationship between travel time, flow and capacity we get Y = 186,24 + 215,71 X, with a = 0,733. The conclusion from this research is on street parking has strong influence on the travel time of the vehicle to get through to Jalan H. Agus Salim.

The need for reliable performance measures of urban arterial corridors is increasing because of the rise in traffic congestion and the high value of users’ travel time. Consequently, travel time reliability (TTR), which attempts to capture the day-to-day variability in travel times, has recently received considerable research interest. The basis of all TTR metrics is the underlying travel time distribution (TTD) along the given link or corridor. Estimating and forecasting arterial corridor TTDs for TTR analysis is the focus of this paper. This paper proposes a TTR methodology that addresses some of the limitations of the current U.S. state-of-the-art methodology which was published in the 6th edition of the Highway Capacity Manual (HCM6). Specifically, HCM6 can only estimate average TTD and not the population TTD. However, the population TTD is needed for accurate trip decision-making by individual drivers and logistics companies. In addition, HCM6 cannot be used to analyze the effect of new technologies, such as connected and automated vehicles, nor can it be used easily for long corridors or networks. The proposed TTR methodology, which is traffic-microsimulation based, was applied on a 1.16 mi arterial testbed in Lincoln, Nebraska, U.S. It was shown that the proposed TTR methodology, when calibrated, could replicate the empirical population TTD at a 5% significance level. The population TTD could also be transformed into an average TTD that also replicated the corresponding empirical average TTD at a 5% significance level.

A feasibility study has been made of the planned railway connection to the mainland Russian Federation and Sakhalin Island based on a comparative analysis of currently available data and calculated characteristics obtained in the course of this study. The research was carried out in the following areas: comparative analysis of cargo transportation along the Vladivostok–Kholmsk route, calculation of payback based on the most modern reporting data, and a comparative analysis of historical projects, recent government documents and existing technical projects. Data of a comparative analysis of cargo transportation in terms of three parameters (distance, travel time, and volume of cargo transportation) of the existing railway-ferry service and the planned railway connection along the Vladivostok–Kholmsk route, taking the characteristics of the ferry service into account, were obtained and used as a basis to draw economic-geographical conclusions. A calculation of the recoupment of the planned railway connection was done according to average statistical information. A comparative analysis was made of the historical projects beginning in 1875, as well as an analysis of recent state documents (plans, strategies, and programs). A comparative analysis was made of the current modern technical projects from the bridge-tunnel alternative and their advantages and disadvantages; on its basis, a technical conclusion was made about the possibility and prospects of construction.

Drivers experience variations in travel time due to congestion and delays associated with road construction projects on existing transportation facilities. The effect on the travel time of a link decreases as its distance from the road construction project increases. In addition, the effect could extend to the connecting arterial street links within the vicinity of the road construction project. Therefore, the focus of this research is to model the effect of a road construction project on the freeway and connecting arterial street link-level travel times. Data pertaining to a resurfacing construction project, which lasted for six months, was gathered from the traffic incident management systems (TIMS). The travel time data was collected and processed, for each selected freeway and connecting arterial street link, for six months before the start of the resurfacing construction project and six months during the construction of the resurfacing project. Generalized linear models (GLM) were developed and validated for before and during the construction project periods with the average travel time on a link as the dependent variable. Data such as time-of-the-day, day-of-the-week, the distance of a link from the work zone, subject link characteristics, and upstream and downstream link characteristics were collected and used as the predictor variables. The results indicate that the subject link, upstream link and downstream link characteristics have a significant effect on the freeway and connecting arterial street link-level travel times due to the resurfacing construction project.

This paper consists of a study conducted to quantify the traffic congestion problem. The quantification is made in terms of congestion cost and index. To study the effect of congestion, a road stretch of Thiruvananthapuram city in Kerala state was selected. A traffic congestion index was assessed based on travel time model. Congestion index helps to rank the road segments which will be useful for prioritizing the traffic management measures effectively. Another tool used for quantifying the congestion was the congestion cost. From the study, it was inferred that the congestion cost for the study stretch was about 0.03% of GSDP of Kerala and about 25% of the expenditure allocated for the road transport sector during the Kerala state Budget 2020–21. The economic analysis of traffic delay cost will inform the policymakers in monetary terms the actual impact of the traffic congestion and delays that the society bears and helps to allocate the resources efficiently.

In December 2016, the first bus rapid transit (BRT) service in Vietnam was introduced in an urban area of Hanoi, the capital, with a 14.7-km route. This study empirically investigates the impacts of introducing the Hanoi BRT service on the travel behaviors of commuters using public transportation services. A quasi-experimental approach is employed with difference-in-differences and propensity score matching to identify the impacts on commuters’ travel time, acceptable walking distance to the nearest stop, and modal share of public transportation. Interviews with public transportation users were conducted to collect data in June 2018, and 501 valid responses were obtained. Respondents were asked about their travel behaviors and perceptions regarding public transportation before and after the BRT introduction. The study assumes a treatment group containing commuters currently using the BRT service and a control group containing those currently using standard bus services. The estimation results reveal that the introduction of the Hanoi BRT service had significantly positive impacts on improving travel time efficiency, increasing the acceptable walking distance to the nearest stop, and encouraging commuters to use more public transportation in their daily journeys.

An analysis of methods for determining the number and passenger capacity of rolling stock on urban routes of passenger traffic. Coordinated growth of efficiency and quality of urban passenger transport allows to increase the level of satisfaction of passenger transportation needs, reduce transport stress on the urban passenger transport system, improve the environmental situation, reduce road accidents and the number of road accidents, ensure unprofitable work of carriers. Improving the functioning of the production system of urban passenger transport should ensure a minimum travel time of passengers, regular movement of vehicles along the route, rational use of rolling stock and quality passenger service at minimal cost. Managing the number and passenger capacity of rolling stock on the route is an important task that affects both the quality of passenger transport services and the economic efficiency of carriers. These factors are opposite, ie, by improving the quality of passenger transport services, the carrier is usually forced to reduce the efficiency of vehicles. The tasks of local authorities are to ensure the number and passenger capacity of vehicles on the route and the quality of passenger transport services that would ensure maximum efficiency of the urban passenger transport system, taking into account the interests of all parties, ie carriers, passengers and the community. Despite the presence of a significant amount of research, the task of choosing the number and passenger capacity of buses on regular routes in city traffic, which would ensure an improvement in the quality of services, remains urgent.

Autonomous Vehicles (AVs) have been designed to make changes in the travel behaviour of travellers. These changes can be interpreted using transport models and simulation tools. In this study, the daily activity plans were used to study the possibility of increasing the utility of travellers through minimizing the travel time by using AVs. Three groups of travellers were selected based on the benefits that they can obtain when AVs are on the market. The groups are (a) long-trip travellers (b) public transport riders, and (c) travellers with specified characteristics. Each group is divided into one or more scenarios based on the definition of each group and the collected data. A total of seven scenarios were derived from the collected data and simulated twice to include the existing transport modes and the presence of AVs. The simulations were conducted using Multi-Agents Transport Simulation (MATSim) that applies the concept of a co-evolutionary algorithm. MATSim simulates the current plans and the ones where AVs replace all or part of the existing conventional transport modes in the daily activity plans. The results have shown a reduction in the trip time: 13% to 42% for group (a), 33% for group (b), and 16% to 28% for group (c) compared with the original trip times. In conclusion, it can be claimed that AVs could reduce the travel time in all cases, which provides benefits for people to increase their utilities.

This paper presents an optimization procedure to choose a parking facility according to different criteria: total travel time including transfers, parking fee and a factor depending on the risk of ...

This paper evaluates the effectiveness of toll roads in reducing congestion and improving travel time reliability on streets within its vicinity, over time. The data, from the year 2013 to 2017, for the Triangle Expressway in the city of Raleigh, North Carolina was used in the systemic evaluation process. The spatial and temporal variations in the travel time distributions on the toll road, parallel route, and near-vicinity cross-streets (in a 2-mile buffer) were evaluated. The average travel time (ATT), the 95th percentile travel time (or planning time, PT), the buffer time (BT), and the buffer time index (BTI) were computed for each link by the day-of-the-week and the time-of-the-day. Though there was an improvement in travel time after the speed limit change in the year 2014, the travel time reliability got reduced on the Triangle Expressway. Over time, there was a gradual improvement in BT and BTI. The parallel route reliability decreased significantly over time, whereas the travel time reliability of cross-streets showed a consistent trend. The stabilization of travel time distributions and the reliability measures in the year 2017 indicate that further reduction in performance measures may not be expected in the next few years on the near-vicinity links.

This study evaluates the Dynamic Message Signs (DMSs) use to dissipate incident information on the freeways in Las Vegas, Nevada. It focuses on the DMSs message timing, extent, and content, from the operators’ and drivers’ perspectives, considering the variability in drivers’ freeway experience. Two-week incidents data with fifty-nine incidents, DMS log data, and responses from a survey questionnaire were used. The descriptive analysis of the incidents revealed that about 54% of the incidents had their information posted on the DMSs; however, information of only 18.6% of the incidents was posted on time. The posted information covered the incident type (54.2%), location (49.2%), and lane blockage (45.8%), while the expected delay or the time the incident has lasted are rarely posted. Further, the standard DMSs are the most preferred sources of traffic information on the freeway compared to the travel time only DMSs, and the graphical map boards. The logistic regression applied to the survey responses revealed that regular freeway users are less likely to take an alternative route when they run into congestion, given no other information is available. Conversely, when given accurate information through DMSs, regular freeway users are about 2.9 times more likely to detour. Furthermore, regular freeway users perceive that the DMSs show clear information about the incident location. Upon improving the DMSs usage, 73% of respondents suggested that the information be provided earlier, and 54% requested improvements on congestion duration and length information. These findings can be used by the DMSs operators in Nevada and worldwide to improve freeway operations.

A road construction project has a significant effect on traffic congestion and operational performance of the project corridor and connecting street links. However, not many researchers focused on travel time performance-based measures to assess the effect of a road construction project on the project corridor and connecting street links. Therefore, travel time data for a freeway road resurfacing project on 100 links within its vicinity were gathered and processed to assess the effect on freeway and connecting arterial street links. A paired t-test was used to examine the differences in means between the before and during road resurfacing project period travel time performance-based measures. There is a significant difference in travel time performance-based measures before and during the road resurfacing project period on freeway links and connecting arterial links. Their significance varied by the time-of-the-day and day-of-the-week on the freeway and connecting arterial links. The average travel time, planning time, and travel time index can consistently explain the effect of a road resurfacing (construction) project on transportation system performance when compared to buffer time and buffer time index. The findings can be used to enhance temporary traffic control practices in the vicinity of road construction projects.

Urban rail transit has become an important traffic mode in large cities and has brought great conveniences to urban residents, however traffic accidents often occur in daily operations, therefore the safety and robustness must be paid more attention. In this paper, the network utilization of urban rail transit networks (URTNs) is expressed by the travel time difference between user equilibrium and optimal system, and the travel time difference is considered as the assessment indicator of robustness. Meanwhile, Shanghai metro network is taken as the example to analyze the robustness of URTNs under different disturbances, such as node attack, link-demand attack and overall-demand attack. The results show that URTNs have better robustness subjected to the random link-demand attack than node attack, and the robustness decreases with the increase of the attack intensity when the network suffers overall-demand attack. Moreover, we find that the critical stations and links can be identified, and URTNs can be paralyzed when the attack intensity exceeds the critical threshold.

Shared Autonomous Vehicle (SAV) services hold potential for disruptive impacts on urban transport systems. The value of travel time savings (VTTS) for these new services is assumed to be both significantly different from that of regular services and to have a strong impact on mobility behaviors. In this study, an agent-based transport simulation for Berlin, Germany, is used to investigate the sensitivity of the urban transport system to different VTTS for shared autonomous vehicle services. Simulation experiments are carried out for a range of plausible VTTS suggested by the literature. The simulation results indicate a strong impact of the VTTS on the modal split. Overall, further research is needed to further investigate behavioral parameters as well as the resulting impact on the urban transport system.

The increase in the North Barito district's economy also affects increasing the volume of people and goods transporting into and out of the North Barito district. Providing reliable transportation needs to be done, one of which is by providing alternative transportation services by train. To obtain information on the extent of public interest in trains, it is necessary to choose existing and new transportation modes, namely between airplanes, minibusses, and trains. The route analyzed is from MuaraTeweh-Palangkaraya. The analytical method used is the Multi NomialLogit approach. Based on the results obtained, the attributes include personal characteristics that influence the mode choice, gender, and the traveler's income level. The characteristics of traffic movements that affect the model are travel time, travel cost, and transportation services level. The probability of a balance between the three modes of transportation under study is obtained because the train's cost is IDR. 250,000, -, minibus cost IDR. 200,000, - and an airplane cost IDR. 295,000, -. Keywords: mode choice, sensitivity, travel cost, travel time

Gunay, Gurkan/0000-0003-0597-1511; GOKASAR, ILGIN/0000-0001-9896-9220 Mode choice of airport ground access has been covered by several studies, but there is a lack of research in the case of airport ground egress; that is, mode choices of inbound passengers for ground trips from the airport to the city center. This study aimed to cover this gap by modeling the ground egress mode choice of passengers, employing mixed logit and comparing it with the multinomial logit model. The data for this research was collected at Istanbul's Sabiha Gokcen International Airport (SAW) in 2015. Analyses included six modes, namely automobile, pick-up, public transit, taxi, shuttle and public transit (SP), and shuttle and taxi (ST). An important outcome was that a mixed logit model with error components outperformed the multinomial logit model. Results showed that significant variables affecting the ground egress mode choice included the income of the passenger, the cost of a ground trip from the airport, auto ownership status, number of luggage and trip purpose. Passengers are less constrained by ground travel time in their airport egress trips than in their airport access trips. By this, a significant finding was that prioritizing egress trip cost over travel time affected the mode choice.