Evaluation Results of the Amsterdam, Netherlands, Practical Trial with In-Car Travel and Route Advice

2017 ◽  
Vol 2621 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Isabel Wilmink ◽  
Eline Jonkers ◽  
Maaike Snelder ◽  
Gerdien Klunder
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Large Scale ◽  
User Behavior ◽  
Route Guidance ◽  
Travel Times ◽  
Guidance Services ◽  
Social Navigation ◽  
Total Travel Time ◽  
Message Signs

Travel and route guidance services are widely available. Social navigation services that provide travelers with advice aimed at minimizing driver travel time, while also taking into account the effect on travel times of other travelers, are relatively new. Theoretically, social navigation has been shown to reduce total travel time by 10% to 30%. This paper presents the evaluation results of a large-scale field trial for pretrip and on-trip route advice with load balancing, in which about 20,000 participants were active. The evaluation provided insight into the potential effects of in-car information services, such as effects on user behavior, traffic flow effects, and technical aspects. Participants used mostly the pretrip advisories. Compliance with the on-trip route advice was 50%, which was considered high (compared with compliance with route advice on variable message signs). An effect on traffic flow could not be measured, as penetration rates were (despite thousands of users) still too low. An offline study using measured travel times combined with a traffic model, however, showed that substantial delay reductions can be achieved for the Amsterdam, Netherlands, region. Participants’ appreciation of the service resulted in a mixed picture with positive and negative ratings. The main practical contribution of this paper is that the results can be used to develop social navigation services. Empirical insights about route advice compliance can be seen as the main scientific contribution.

scholarly journals Resilience Assessment of a Twin-Tube Motorway Tunnel in the Event of a Traffic Accident or Fire in a Tube

2022 ◽  
Vol 12 (1) ◽  
pp. 513
Author(s):  
Ciro Caliendo ◽  
Isidoro Russo ◽  
Gianluca Genovese
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Traffic Accident ◽  
Negative Effects ◽  
Passenger Cars ◽  
Support Tool ◽  
Complete Closure ◽  
Closed Tube ◽  
Time Required ◽  
Message Signs

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its partial or complete closure. The functionality of the road infrastructure, in the case of an accident in one of the two tubes (each tube presents two lanes with unidirectional traffic under ordinary conditions), was assumed to be recovered both by using the remaining undisrupted lane of the tube interested by the disruptive event (only one lane is closed) and reorganizing the traffic flow by utilizing the adjacent tube for bi-directional traffic (both lanes are closed). The effects of an alternative itinerary individualized in the corresponding open road network were also examined. The level of functionality of the system during the period in which the tube is partially or completely closed was computed as the ratio between the average travel time required to reach a given destination from a specific origin before and after the occurrence of the disruptive event. The resilience metrics were assumed to be resilience loss, recovery speed, and resilience index. The best scenario was found to be the partial closure of the tube in contrast to the complete one. However, in order to contain the negative effects on the functionality of the motorway section due to the complete closure of the tube, it is worth highlighting how the traffic by-pass before the entrance portal of the closed tube should be open in a very short time by the tunnel management team to allow for the quick use of the adjacent tube for bi-directional traffic. An additional improvement, with reference exclusively to passenger cars traveling through the adjacent unblocked tube, might be obtained by activating the variable message signs, located at a sufficient distance from the motorway junction before the entrance portal of the closed tube, in order to suggest an alternative route to heavy good vehicles (HGVs) only. Whereas, when the alternative itinerary is used by all vehicles traveling towards the blocked tube (i.e., both passenger cars and HGVs), this redirectioning of the motorway traffic flow was found to be characterized by an excessive travel time, with it therefore not being advisable. The results obtained might be useful as a decision-making support tool aimed at improving the resilience of twin-tube tunnels.

Evaluation of Compliance Rates and Travel Time Calculation for Automatic Alternative Route Guidance Systems on Freeways

1996 ◽  
Vol 1554 (1) ◽  
pp. 153-161 ◽  
Author(s):  
Reinhart D. Kühne ◽  
Karin Langbein-Euchner ◽  
Martin Hilliges ◽  
Norbert Koch
Keyword(s):  
Travel Time ◽  
Compliance Rate ◽  
Measurement Data ◽  
High Sensitivity ◽  
Guidance System ◽  
Route Guidance ◽  
Alternative Route ◽  
Travel Times ◽  
Main Road ◽  
Guidance Systems

This study outlines the concept of extending an available simulation model for evaluation of freeway route guidance systems using the compliance rates of drivers with alternative route recommendations based on measurements from the freeway subnetwork near Munich, Germany. The system works with variable direction signs that automatically display routing instructions to prevent congestion on the main road. The effectiveness of the system is assessed by calculating the travel times with and without an alternative route guidance system in operation. The result is a decrease in individual travel times on the main road and overall travel time savings for all traffic participants of the system. The simulation indicates a high sensitivity of diverting portions of traffic that allows an exact validation. The diverted traffic affects not only travel time and the congested area but also the destinations, which permits the use of the compliance rate as an accurate fit parameter for exact description of traffic patterns from measurement data.

Analytic, Microscopic Model of Traffic Flow and Travel Time

2002 ◽  
Vol 1802 (1) ◽  
pp. 233-238
Author(s):  
Fabien M. Leurent
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Safety Margin ◽  
Mean Value ◽  
Microscopic Model ◽  
Travel Times ◽  
Kinematic Parameters ◽  
Acceleration Rate ◽  
The Mean

A model of disaggregate interactions between individual vehicles was developed that makes explicit the vehicle classes, the class trip rates, and their kinematic parameters (free speed, acceleration rate, length, safety margin). Assuming exponential gaps between vehicles, analytic formulas were derived for the mean value and the variance of the path travel times within each class. The model was successively applied to one-lane roads; two-way, two-lane roads; one-way, two-lane roads; and two-way, three-lane roads.

Strategic Evacuation for Hurricanes and Regional Events with and without Autonomous Vehicles

2021 ◽  
pp. 036119812110074
Author(s):  
Jooyong Lee ◽  
Kara M. Kockelman
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Autonomous Vehicle ◽  
Time Span ◽  
Network Congestion ◽  
Travel Times ◽  
Total Delay ◽  
Evacuation Time ◽  
Conflicting Objectives

A scheduling algorithm is developed for optimal planning of large-scale, complex evacuations to minimize total delay plus travel time across residents. The algorithm is applied to the eight-county Houston-Galveston region and land use setting under the 2017 Hurricane Harvey scenario with multiple destinations. Autonomous vehicle (AV) use under central guidance is also tested, to demonstrate the evacuation time benefits of AVs. Higher share of AVs delivers more efficient evacuation performance, thanks to greater reliability on evacuation order compliance, lower headways, and higher road capacity. Furthermore, 100% AV use delivers lower overall evacuation costs and network clearance times and less uncertainty in travel times (via lower standard deviation in). Based on evaluations of different evacuation schedules, a 50% compressed evacuation time span resulted in longer travel times and network congestion. A 50% longer evacuation time span reduced residents' total travel time and network congestion, but increased the evacuation cost. As expected, evacuation efficiency falls when evacuees do not comply with evaucation schedules. Large shares of AVs will not be possible in the near future, so methods to enhance evacuees' compliance behavior (e.g., enforced and prioritized evacuation orders) should be considered until a meaningful level of AV technical maturity and penetration rate is available. This paper demonstrates the benefits of scheduled departure times, AV use, and evacuation order compliance, which help balance conflicting objectives during emergencies.

scholarly journals Review, Experimental Evaluation and Policy Considerations of a Directional Time of Day Truck Restriction on Highways

2015 ◽  
Author(s):  
Shy Bassan
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Time Of Day ◽  
Truck Traffic ◽  
Passenger Cars ◽  
Traffic Efficiency ◽  
Flow Parameters ◽  
Time Period ◽  
Traffic Stream ◽  
Total Travel Time

The paper reviews several strategies of restricting or separating trucks from the regular traffic stream. Typical truck restriction policies focus on leftmost lanes restriction, which has been shown by several studies to have some advantages. However, those studies clearly show that vehicle queue lengths in the vicinity of critical merging areas increase significantly as the percentage of trucks increases. Therefore, this study examines a different policy—one which investigates traffic efficiency gained by restricting heavy truck traffic in one direction—in this case, westbound on Highway 1 in Israel—during afternoon peak hours. Similar policies of utilizing a specific vehicle category (e.g. passenger cars or trucks) in different daily time periods or physical separation of homogenous traffic of passenger cars in the inner lanes and mixed traffic in the outer lanes, were recommended in Italian motorways and in New Jersey Turnpike dual-dual freeways respectively.Highway 1 is a freeway connecting Jerusalem and Tel Aviv that passes by Ben-Gurion International Airport. The major objective of this study is to estimate the benefit of restricting truck traffic in the traffic stream according to three traffic-flow parameters: average travel time, total travel time, and average traffic speed. Analysis of the results, which consider the significant differences of 30-minute time period samples (“before-after” truck restriction), shows that prohibiting trucks in all lanes in one direction during the peak afternoon period of 16:00-18:00 improved all three traffic flow parameters by 8%-12%. Generally a steep grade from which truck traffic is banned is correlated with an improvement in traffic flow. In our case, Highway 1 road segments 1 and 2 and 4, which have steep grades (longitudinal grades), incorporated the most significant improvements in the traffic stream parameters examined.

Route guidance during evacuations integrated with perimeter control strategy in large-scale mixed traffic flow networks

2018 ◽  
Vol 29 (11) ◽  
pp. 1850112 ◽  
Author(s):  
Mianfang Liu ◽  
Dongchu Han ◽  
Dongmei Li ◽  
Ming Wang
Keyword(s):  
Traffic Flow ◽  
Control Strategy ◽  
Traffic Management ◽  
Large Scale ◽  
Route Choice ◽  
Heterogeneous Traffic ◽  
Route Guidance ◽  
Traffic Networks ◽  
Mixed Traffic ◽  
Mixed Flow

Recent efficient monitoring and traffic management of large-scale mixed traffic networks still remain a challenge for both traffic researchers and practitioners. The difficulty in modeling route guidance evacuation of pedestrian-vehicle mixed flow lies in mixed flow and uneven or heterogeneous network flow. Existing studies have demonstrated that multi-region control can display different layers of traffic state measurement and control, and incorporate heterogeneity effect in the large-scale network dynamics. The optimal perimeter control can manipulate the percentages of flows that transfer between two regions, offering real-time traffic management strategies to improve the network performance. However, the effect of route guidance evacuation integrated with perimeter control strategies in case of heterogeneous traffic networks is still unexplored. The paper advances in this direction by firstly extending route choice behavior aggregation with perimeter control. For an evacuation study, we consider a campus and its surrounding traffic network that can be classified into two types of networks: the first includes emergency areas that involve a large number of evacuees, and the second includes roads that lead to different destinations. The second network consists of some regions with different evacuation directions. Based on the configuration, this paper proposes a route evacuation guidance control strategy that addresses traffic flow first assignment between regions by controlling perimeter flow with the help of Macroscopic fundamental diagram (MFD) representation and to guide evacuates’ route choice at intersections by LOGIT model in regions. In addition, comparison results show that the proposed route guidance strategy has considerable potential to improve performances and equilibrium conditions (i.e. system optimum and user equilibrium) on the overall network.

Appraising relative earthquake location errors

1992 ◽  
Vol 82 (2) ◽  
pp. 836-859 ◽  
Author(s):  
Gary L. Pavlis
Keyword(s):  
Travel Time ◽  
Upper Bound ◽  
Large Scale ◽  
Velocity Structure ◽  
Order Approximation ◽  
Earthquake Location ◽  
Travel Times ◽  
Spatial Error ◽  
Location Errors ◽  
Error Terms

Abstract Earthquake location estimates suffer from two types of errors: (1) systematic offsets caused by large scale earth structure, and (2) scatter of locations of different earthquakes relative to each other. I show that relative location errors are controlled by four separate error terms: (1) scatter caused by random, measurement error; (2) nonlinear effects; (3) mislocations caused by interaction of errors in modeling travel times with variations in the number and quality of arrivals recorded by different events; and (4) mislocations caused by variations in how errors in modeling travel times vary with position inside the real Earth. The first can be handled by conventional statistical methods. The second can be bounded using a second-order approximation, provided one can provide a reasonable estimate for an upper bound on the total spatial error that might be present in the location estimate. I demonstrate that the size of each of the two error terms related to inadequate knowledge of the Earth's velocity structure can be bounded provided we can determine an upper bound on travel-time errors as a function of distance. I describe an empirical approach for determining such a bound using differences between the sum of squared residuals of earthquakes located with all available data and the same event located with a single arrival deleted. This calculation is repeated for all arrivals and used to construct an upper bound on travel-time errors as a function of distance. The concepts developed are applied to bound errors in locations of earthquakes in the Garm region of central Asia, and they demonstrate the utility of these ideas in sorting out events with minimal relative error.

Forecasting Multiple-Period Freeway Link Travel Times Using Modular Neural Networks

1998 ◽  
Vol 1617 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Dongjoo Park ◽  
Laurence R. Rilett
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Transportation Systems ◽  
Time Profile ◽  
Identification System ◽  
Route Guidance ◽  
Travel Times ◽  
Test Bed ◽  
Link Travel Time ◽  
Time Information

With the advent of route guidance systems (RGS), the prediction of short-term link travel times has become increasingly important. For RGS to be successful, the calculated routes should be based on not only historical and real-time link travel time information but also anticipatory link travel time information. An examination is conducted on how realtime information gathered as part of intelligent transportation systems can be used to predict link travel times for one through five time periods (of 5 minutes’ duration). The methodology developed consists of two steps. First, the historical link travel times are classified based on an unsupervised clustering technique. Second, an individual or modular artificial neural network (ANN) is calibrated for each class, and each modular ANN is then used to predict link travel times. Actual link travel times from Houston, Texas, collected as part of the automatic vehicle identification system of the Houston Transtar system were used as a test bed. It was found that the modular ANN outperformed a conventional singular ANN. The results of the best modular ANN were compared with existing link travel time techniques, including a Kalman filtering model, an exponential smoothing model, a historical profile, and a real-time profile, and it was found that the modular ANN gave the best overall results.

scholarly journals Spatiotemporal Partitioning of Transportation Network Using Travel Time Data

2017 ◽  
Vol 2623 (1) ◽  
pp. 98-107 ◽  
Author(s):  
Clélia Lopez ◽  
Panchamy Krishnakumari ◽  
Ludovic Leclercq ◽  
Nicolas Chiabaut ◽  
Hans van Lint
Keyword(s):  
Travel Time ◽  
Urban Areas ◽  
Large Scale ◽  
Spatial Clustering ◽  
Transportation Network ◽  
Route Guidance ◽  
Time Data ◽  
Normalized Cut ◽  
Urban Network ◽  
Travel Time Data

Today, the deployment of sensing technology permits the collection of massive amounts of spatiotemporal data in urban areas. These data can provide comprehensive traffic state conditions for an urban network and for a particular day. However, data are often too numerous and too detailed to be of direct use, particularly for applications such as delivery tour planning, trip advisors, and dynamic route guidance. A rough estimate of travel times and their variability may be sufficient if the information is available at the full city scale. The concept of the spatiotemporal speed cluster map is a promising avenue for these applications. However, the data preparation for creating these maps is challenging and rarely discussed. In this study, that challenge is addressed by introducing generic methodologies for mapping the data to a geographic information system network, coarsening the network to reduce the network complexity at the city scale, and estimating the speed from the travel time data, including missing data. This methodology is demonstrated on the large-scale urban network of Amsterdam, Netherlands, with real travel time data. The preprocessed data are used to build the spatiotemporal speed cluster by using three partitioning techniques: normalized cut, density-based spatial clustering of applications with noise, and growing neural gas (GNG). A new posttreatment methodology is introduced for density-based spatial clustering and GNG, which are based on data point clustering, to generate connected zones. A preliminary cross comparison of the clustering techniques shows that GNG performs best in generating zones with minimum internal variance, the normalized cut computes three-dimensional zones with the best intercluster dissimilarity, and GNG has the fastest computation time.

scholarly journals “In cities, it’s not far, but it takes long”: comparing estimated and replicated travel times to reach life-saving obstetric care in Lagos, Nigeria

2021 ◽  
Vol 6 (1) ◽  
pp. e004318
Author(s):  
Aduragbemi Banke-Thomas ◽  
Kerry L M Wong ◽  
Francis Ifeanyi Ayomoh ◽  
Rokibat Olabisi Giwa-Ayedun ◽  
Lenka Benova
Keyword(s):  
Travel Time ◽  
Friction Surface ◽  
Obstetric Care ◽  
Travel Times ◽  
Night Time ◽  
Google Maps ◽  
Surface Approach ◽  
Low Resource ◽  
Life Saving ◽  
The Cost

BackgroundTravel time to comprehensive emergency obstetric care (CEmOC) facilities in low-resource settings is commonly estimated using modelling approaches. Our objective was to derive and compare estimates of travel time to reach CEmOC in an African megacity using models and web-based platforms against actual replication of travel.MethodsWe extracted data from patient files of all 732 pregnant women who presented in emergency in the four publicly owned tertiary CEmOC facilities in Lagos, Nigeria, between August 2018 and August 2019. For a systematically selected subsample of 385, we estimated travel time from their homes to the facility using the cost-friction surface approach, Open Source Routing Machine (OSRM) and Google Maps, and compared them to travel time by two independent drivers replicating women’s journeys. We estimated the percentage of women who reached the facilities within 60 and 120 min.ResultsThe median travel time for 385 women from the cost-friction surface approach, OSRM and Google Maps was 5, 11 and 40 min, respectively. The median actual drive time was 50–52 min. The mean errors were >45 min for the cost-friction surface approach and OSRM, and 14 min for Google Maps. The smallest differences between replicated and estimated travel times were seen for night-time journeys at weekends; largest errors were found for night-time journeys at weekdays and journeys above 120 min. Modelled estimates indicated that all participants were within 60 min of the destination CEmOC facility, yet journey replication showed that only 57% were, and 92% were within 120 min.ConclusionsExisting modelling methods underestimate actual travel time in low-resource megacities. Significant gaps in geographical access to life-saving health services like CEmOC must be urgently addressed, including in urban areas. Leveraging tools that generate ‘closer-to-reality’ estimates will be vital for service planning if universal health coverage targets are to be realised by 2030.

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