01702386

Component

https://doi.org/10.1177/0361198119839981

Improved traffic management techniques are needed to reduce congestion on road networks, especially as “driving” is made easier, through self-driving vehicles. In this paper, reactive congestion pricing varies toll rates based on recent congestion levels, and automated vehicles are added to the conventional traffic mix for evaluation of evolving travel conditions. As expected, drivers with higher values of travel time (VOTT) are more likely to use the tolled route than drivers with lower VOTT, and tolled-route speeds rose (about 4%) while speeds on non-tolled road segments fell (about 15%). Thanks to traveler sorting, net benefits exceeded $600 per hour in all scenarios, using a very small (toy) network. Toll revenues can be distributed uniformly among travelers (resulting in credit-based congestion pricing) or invested in improving bottlenecks and alternative modes. Rising shares of automated vehicles (from 0% to 50% and 100%) also improved outcomes.

19-03774

English

pp 536-547

2019-6

Transportation Research Record: Journal of the Transportation Research Board

Digital/other

Figures (3) ; References (27) ; Tables (4)

Autonomous vehicles; Congestion pricing; Drivers; Forecasting; Route choice; Simulation; Traffic flow; Travel time; Value of time; Variable tolls

Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment

TRIS, TRB, ATRI

Mar 8 2019 10:07AM

• Analysis of Bicycle Headway Distribution, Saturation Flow and Capacity at a Signalized Intersection using Empirical Trajectory Data
• Analyzing Transit User Behavior with 51 Weeks of Smart Card Data
• Approximative Network Partitioning for MFDs from Stationary Sensor Data
• Arterial Traffic Flow Estimation Based on Vehicle-to-Cloud Vehicle Trajectory Data Considering Multi-Intersection Interaction and Coordination
• Assessment of Contributing Factors to Air Service Loss in Small Communities
• Automatic Ground Points Identification Method for Roadside LiDAR Data
• Automatic Vehicle Classification using Roadside LiDAR Data
• Bicyclist Crash Types on National, State, and Local Levels: A New Look
• Bikeability in Basel
• Bus Arrival Time Modeling Based on Auckland Data
• Comparative Analysis between Modern-Era Retrospective Analysis for Research and Applications and Updated Mechanistic-Empirical Pavement Design Guide Climate Database in the State of Tennessee
• Data-Driven Methodology for Prioritizing Traffic Signal Retiming Operations
• Designing a Comprehensive Procedure for Flagging Archived Traffic Data: A Case Study
• Development of a Performance-Volumetric Relationship for Asphalt Mixtures
• Does One Bicycle Facility Type Fit All? Evaluating the Stated Usage of Different Types of Bicycle Facilities among Cyclists in Quebec City, Canada
• Driver Back-Tracing Based on Automated Vehicle Identification Data
• Driving Style Clustering using Naturalistic Driving Data
• Empirical Estimation of Effects of Flexible Working on Mobility and Congestion in the Netherlands 2000 to 2016
• Engineering Properties of Asphalt Binders from Different Sources and Their Influence on Stiffness of Asphalt Concrete Mixtures
• Evaluation of Degradation of SBS Modified Asphalt Binder Because of RTFO, PAV, and UV Aging using a Novel Extensional Deformation Test
• Evaluation of Laboratory Performance and Structural Contribution of Cold Recycled Versus Hot Mixed Intermediate and Base Course Asphalt Layers in New Hampshire
• Familiar versus Unfamiliar Drivers on Curves: Naturalistic Data Study
• Field Evaluation of Different Pre-Wetting Ratios for Sustainable Salting
• Framing the Bicyclist: A Qualitative Study of Media Discourse about Fatal Bicycle Crashes
• Fusing Multiple Sources of Data to Understand Ride-Hailing Use
• Impact of Aging on the Viscoelastic Properties and Cracking Behavior of Asphalt Mixtures
• Impermeable Asphalt Concrete Layer to Protect and Seal Concrete Bridge Decks
• Investigating Effect of Driver-, Vehicle-, and Road-Related Factors on Location-Specific Crashes with Naturalistic Driving Data
• Investigation into the Oxidative Aging of Asphalt Binders
• Investigation of Bimodal Macroscopic Fundamental Diagrams in Large-Scale Urban Networks: Empirical Study with GPS Data for Shenzhen City
• Joint Optimization Scheme for the Planning and Operations of Shared Autonomous Electric Vehicle Fleets Serving Mobility on Demand
• New Method for Detecting Oil Contaminants in Asphalt Mixtures through Chemical Testing
• New Test Method for Measuring Reflective Cracking in Hot-Mix Asphalt Overlay Pavements
• Non-Intrusive Detection of Drowsy Driving Based on Eye Tracking Data
• Novel Divide and Combine-Based Approach to Estimating Mixture Markov Model for Large Categorical Time Series Data: Application to Study of Clusters using Multiyear Travel Survey Data
• Optimal Design of Bus Routes for Different Vehicle Types Considering Various Driving Regimes and Environmental Factors
• Pattern Identification from Older Bicyclist Fatal Crashes
• Real-Time Pedestrian Detection Approach with an Efficient Data Communication Bandwidth Strategy
• Relationship between Asphalt Binder Parameters and Asphalt Mixture Rutting
• Safety in Numbers for Bicyclists at Urban Intersections
• Seasonal and Long-Term Changes to Pavement Life Caused by Rising Temperatures from Climate Change
• Signal Timing Parameters Estimation for Intersections using Floating Car Data
• Understanding the Illinois Flexibility Index Test (I-FIT) using Indiana Asphalt Mixtures
• Using Smart Farecard Data to Support Transit Network Restructuring: Findings from Los Angeles
• Validating the Adaptability of Travel Time Reliability Measurements using Probe Data
• Volume Estimation using Traffic Signal Event-Based Data from Video-Based Sensors