6.4 Traffic engineering and control

Traffic engineering and control are crucial aspects of transportation systems. They focus on optimizing traffic flow, enhancing safety, and improving overall road network efficiency. These techniques help manage congestion, reduce accidents, and create smoother travel experiences for road users.

From traffic signal timing to intelligent transportation systems, this field covers a wide range of strategies. Understanding these concepts is essential for designing and maintaining effective transportation networks that can handle growing traffic demands while prioritizing safety and efficiency.

Traffic Flow Analysis and Capacity

Fundamental Variables and Relationships

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• Traffic flow is characterized by three fundamental variables: flow rate (vehicles per hour), density (vehicles per mile), and speed (miles per hour)
  • Flow rate represents the number of vehicles passing a specific point on a roadway during a given time interval
  • Density is the number of vehicles occupying a certain length of roadway at a particular instant
  • Speed refers to the distance traveled by vehicles per unit of time
• The relationships between these variables are described by fundamental traffic flow diagrams
  • The flow-density diagram shows that as density increases, flow rate initially increases until it reaches a maximum value (capacity) and then decreases as congestion sets in
  • The speed-flow diagram illustrates that as flow rate increases, speed remains relatively constant until capacity is reached, after which it declines sharply
  • The speed-density diagram reveals that speed decreases as density increases, with the relationship being approximately linear in the uncongested regime

Capacity and Level of Service

• Capacity is the maximum sustainable flow rate that can be achieved under prevailing roadway, traffic, and control conditions
  • It represents the upper limit of the traffic volume that a facility can accommodate without experiencing breakdown or unstable flow
  • Capacity is typically expressed in vehicles per hour per lane (vphpl) for uninterrupted flow facilities (freeways) and vehicles per hour (vph) for interrupted flow facilities (urban streets)
• Capacity is a key measure of roadway performance and is used to determine the level of service (LOS) of a facility
  • LOS is a qualitative measure that characterizes the operating conditions on a roadway based on factors such as speed, travel time, freedom to maneuver, comfort, and convenience
  • LOS is typically classified into six categories, ranging from A (best) to F (worst), with each category representing a range of operating conditions and associated delay or density thresholds

Factors Affecting Roadway Capacity

• Roadway capacity is influenced by various factors, including:
  • Lane width: Narrower lanes reduce capacity by constraining lateral movement and increasing the potential for sideswipe collisions
  • Lateral clearance: Insufficient clearance from roadside objects (guardrails, barriers) can reduce capacity by causing drivers to shy away from the edge of the road
  • Number of lanes: Capacity increases with the addition of lanes, but the marginal benefit diminishes as the number of lanes increases due to increased lane changing and weaving maneuvers
  • Grade: Steep upgrades can significantly reduce capacity, particularly for heavy vehicles, as they cause slower speeds and increased headways
  • Heavy vehicles: The presence of trucks, buses, and recreational vehicles reduces capacity due to their larger size, slower acceleration, and increased headways
  • Driver population: Unfamiliar or less skilled drivers can reduce capacity by exhibiting slower speeds, longer headways, and more erratic behavior
• These factors are accounted for using adjustment factors in the Highway Capacity Manual (HCM) methodologies
  • The HCM provides a systematic approach to estimating capacity and LOS based on a set of standard conditions and adjustment factors for various roadway and traffic characteristics
  • For example, the passenger car equivalent (PCE) factor is used to convert heavy vehicles into an equivalent number of passenger cars, accounting for their impact on capacity

Intersection Capacity and Performance Measures

• Intersection capacity is determined by the capacity of each approach and the allocation of green time to each movement
  • Approach capacity is a function of the saturation flow rate (the maximum flow rate that can be achieved during the green phase) and the effective green time (the duration of the green phase minus the lost time due to start-up and clearance)
  • The allocation of green time to each movement is based on the relative traffic volumes and the desired level of service for each approach
• Critical lane group analysis is used to identify the movements with the highest flow ratios (volume-to-capacity ratios), which control the overall intersection capacity
  • The critical lane groups are the movements with the highest flow ratios in each phase, and their sum determines the intersection's overall flow ratio
  • If the critical flow ratio exceeds 1.0, the intersection is considered to be operating over capacity, resulting in excessive delays and queues
• Queue length and delay are important measures of intersection performance
  • Queue length is the number of vehicles waiting at an intersection approach, either at the start of the green phase (initial queue) or at the end of the analysis period (residual queue)
  • Delay is the additional travel time experienced by a driver due to traffic control, geometric conditions, and interactions with other vehicles
  • Delay can be classified into three categories: uniform delay (assuming uniform arrivals), incremental delay (accounting for random arrivals and oversaturation), and initial queue delay (due to residual queues from the previous cycle)
• Other performance measures include stop rate (the number of stops per vehicle), fuel consumption, and emissions, which can be estimated using models that relate these variables to delay and queue length

Traffic Signal Optimization

Signal Timing Parameters

• Traffic signal timing involves determining the appropriate cycle length, green splits, and phase sequence to efficiently serve the competing traffic demands at an intersection while ensuring safety for all users
• Cycle length is the total time required for a signal to complete one full sequence of indications
  • It includes the green, yellow, and all-red intervals for each phase
  • Cycle lengths typically range from 30 to 120 seconds, depending on the intersection size, traffic volumes, and desired level of service
• Green splits refer to the allocation of green time to each phase within a cycle
  • They are determined based on the traffic volumes and the saturation flow rates of each movement
  • The goal is to equalize the volume-to-capacity ratios for all critical lane groups, ensuring that all movements experience similar levels of delay
• Phase sequencing is the order in which the various traffic movements are served within a cycle
  • The most common phase sequences are leading and lagging left-turn phases, which place the left-turn movements before or after the through movements, respectively
  • Overlapping phases allow certain movements to operate concurrently, such as a right-turn phase that overlaps with a complementary left-turn phase

Signal Timing Optimization Methods

• Webster's method is a widely used approach for calculating optimal cycle lengths and green splits
  • It is based on the assumption of uniform arrival rates and the goal of minimizing the total delay at the intersection
  • The optimal cycle length is calculated as a function of the total lost time and the critical flow ratio, while the green splits are proportional to the flow ratios of each phase
• The Highway Capacity Manual (HCM) method is another common approach for signal timing optimization
  • It uses a more detailed model that accounts for the impact of platoon dispersion, queue buildup, and oversaturation on delay and level of service
  • The HCM method involves an iterative process of adjusting the cycle length and green splits until a desired level of service is achieved or the capacity constraints are satisfied
• Other optimization methods include mathematical programming (linear, non-linear, or dynamic programming), simulation-based approaches (using traffic simulation software to evaluate alternative timing plans), and rule-based expert systems (using heuristic rules to generate timing plans based on traffic patterns and operator preferences)

Coordination and Adaptive Control

• Coordination of traffic signals along a corridor involves synchronizing the timing of adjacent intersections to create green waves, minimizing stops and delays for through traffic
  • Coordination is achieved by setting a common cycle length for all intersections and adjusting the offsets (the time difference between the start of green at each intersection) to maintain a constant progression speed
  • Time-space diagrams are used to visualize the progression of platoons along the corridor and identify the optimal offsets for each intersection
• Adaptive traffic control systems use real-time traffic data from sensors (loops, cameras, or radar) to dynamically adjust signal timing parameters in response to changing traffic conditions
  • These systems employ optimization algorithms (such as SCOOT, SCATS, or ACS-Lite) that continuously monitor traffic flows and adjust cycle lengths, green splits, and offsets to minimize delays and stops
  • Adaptive control can improve the efficiency and responsiveness of signal operations, particularly during non-recurrent congestion, incidents, or special events
• Other coordination strategies include transit signal priority (giving preferential treatment to transit vehicles), emergency vehicle preemption (interrupting the normal signal cycle to accommodate emergency vehicles), and freight signal priority (accommodating the unique needs of heavy vehicles in industrial corridors)

Intelligent Transportation Systems

Overview and Benefits

• Intelligent Transportation Systems (ITS) encompass a wide range of advanced technologies and strategies aimed at improving transportation safety, mobility, and environmental sustainability through the integration of communication, control, and information processing technologies
• ITS applications can benefit various aspects of transportation systems, including:
  • Reducing congestion and delays by optimizing traffic flow and providing real-time information to users
  • Enhancing safety by preventing collisions, mitigating the severity of incidents, and improving emergency response times
  • Improving efficiency and reliability of transit services by providing priority treatment, real-time tracking, and dynamic scheduling
  • Reducing environmental impacts by smoothing traffic flow, promoting eco-driving behaviors, and supporting alternative modes of transportation
  • Enhancing traveler experience by providing personalized and timely information, simplifying payment and ticketing processes, and offering multimodal integration

Advanced Traffic Management Systems (ATMS)

• ATMS include a range of strategies and technologies designed to optimize traffic flow, improve safety, and enhance the operational efficiency of transportation networks
• Adaptive traffic control systems use real-time traffic data from sensors to dynamically adjust signal timing parameters in response to changing traffic conditions
  • Examples include SCOOT (Split Cycle Offset Optimization Technique), SCATS (Sydney Coordinated Adaptive Traffic System), and ACS-Lite (Adaptive Control Software Lite)
• Incident management systems use a combination of detection, verification, response, and clearance strategies to minimize the impact of incidents on traffic flow and safety
  • Components include traffic monitoring cameras, dynamic message signs, emergency response vehicles, and traffic management centers
• Traveler information systems provide real-time information to users about traffic conditions, travel times, incidents, and alternative routes through various media, such as dynamic message signs, websites, mobile apps, and social media
  • Examples include 511 systems, which provide phone and web-based access to traffic, transit, and travel information for a specific region

Advanced Traveler Information Systems (ATIS)

• ATIS provide real-time, multimodal information to travelers to help them make informed decisions about their trips, such as mode choice, route selection, and departure time
• Pre-trip information systems allow users to access travel information before beginning their journey, typically through websites, mobile apps, or interactive voice response systems
  • Information may include real-time traffic conditions, transit schedules and delays, parking availability, and weather forecasts
• En-route information systems provide dynamic, location-specific information to travelers while they are on their trip, using technologies such as dynamic message signs, in-vehicle navigation systems, and mobile alerts
  • Examples include real-time transit arrival information, parking guidance systems, and congestion pricing information
• Multimodal trip planning tools allow users to compare travel options across different modes (e.g., driving, transit, biking, walking) based on factors such as travel time, cost, and environmental impact
  • These tools often integrate real-time data from multiple sources and provide personalized recommendations based on user preferences and constraints

Electronic Payment and Pricing Systems

• Electronic Toll Collection (ETC) systems use vehicle-mounted transponders and roadside readers to automatically collect tolls without requiring vehicles to stop
  • Examples include E-ZPass in the northeastern United States and FasTrak in California
  • ETC systems improve throughput, reduce congestion, and minimize emissions at toll plazas by eliminating the need for manual toll collection
• Congestion pricing systems use variable tolls to manage demand and optimize traffic flow on congested facilities, such as urban highways or city centers
  • Prices are typically higher during peak periods to discourage discretionary trips and encourage shifts to alternative modes or routes
  • Examples include the London Congestion Charge, Singapore's Electronic Road Pricing, and the I-15 Express Lanes in San Diego
• Integrated payment systems allow users to pay for multiple transportation services (e.g., transit fares, parking fees, bike-share rentals) using a single smartcard or mobile app
  • These systems provide convenience for users, reduce transaction costs for operators, and enable the implementation of multimodal pricing strategies
  • Examples include the Octopus card in Hong Kong, the Oyster card in London, and the Ventra system in Chicago

Connected and Autonomous Vehicles

• Connected Vehicle (CV) technology enables wireless communication between vehicles, infrastructure, and personal devices, allowing for the exchange of real-time data and enabling a range of safety, mobility, and environmental applications
  • Vehicle-to-Vehicle (V2V) communication allows vehicles to share information about their location, speed, and trajectory, enabling applications such as collision avoidance, platooning, and cooperative adaptive cruise control
  • Vehicle-to-Infrastructure (V2I) communication enables vehicles to receive information from roadside units about traffic conditions, signal timing, and road hazards, enabling applications such as speed harmonization, red light violation warning, and curve speed warning
  • Vehicle-to-Pedestrian (V2P) communication allows vehicles to detect and communicate with pedestrians and cyclists, enabling applications such as pedestrian collision warning and bicycle detection
• Autonomous Vehicles (AVs) are equipped with sensors, cameras, and advanced control systems that enable them to navigate and operate with little or no human input
  • AVs have the potential to significantly reduce crashes, congestion, and emissions by eliminating human error, optimizing traffic flow, and enabling shared mobility services
  • Examples of AV technology include Google's Waymo, Tesla's Autopilot, and GM's Super Cruise
  • Challenges to widespread AV adoption include legal and regulatory issues, public acceptance, and the need for extensive testing and validation to ensure safety and reliability

Traffic Safety Evaluation and Mitigation

Crash Data Analysis

• Crash data analysis involves the systematic examination of crash records to identify patterns, trends, and contributing factors associated with traffic accidents
  • This process helps prioritize safety improvements, allocate resources effectively, and evaluate the effectiveness of implemented countermeasures
• Key steps in crash data analysis include:
  • Data collection: Gathering crash reports from police departments, insurance companies, and other sources, and compiling them into a standardized database
  • Data quality control: Checking for errors, inconsistencies, and missing values in the crash data, and applying appropriate data cleaning and imputation techniques
  • Data integration: Combining crash data with other relevant datasets, such as roadway inventory, traffic volumes, and weather data, to enable more comprehensive analysis
  • Descriptive analysis: Summarizing crash patterns and characteristics using statistical measures and data visualization techniques, such as frequency tables, cross-tabulations, and heat maps
  • Spatial analysis: Identifying high-crash locations or "hotspots" using geographic information systems (GIS) tools and spatial statistical methods, such as kernel density estimation and local indicators of spatial association (LISA)
  • Causal analysis: Investigating the underlying factors that contribute to crashes using methods such as collision diagrams, fault tree analysis, and root cause analysis

Safety Performance Measures

• Crash frequency, rate, and severity are key metrics used to quantify safety performance and compare the relative risk of different locations or facilities
• Crash frequency is the total number of crashes occurring at a specific location or along a particular roadway segment during a given time period
  • Crash frequency can be further disaggregated by crash type (e.g., rear-end, angle, sideswipe), severity level (e.g., fatal, injury, property damage only), or contributing factor (e.g., speeding, distracted driving, impaired driving)
• Crash rate accounts for exposure by normalizing crash frequency with a measure of traffic volume, such as vehicle miles traveled (VMT) or average annual daily traffic (AADT)
  • Crash rates are typically expressed as crashes per million VMT or crashes per million entering vehicles (MEV) for intersections
  • Crash rates allow for the comparison of safety performance across locations with different traffic levels and are used to identify locations with higher-than-expected crash risk
• Crash severity is a measure of the degree of injury or property damage resulting from a crash
  • Severity levels are typically classified as fatal, serious injury, minor injury, possible injury, or property damage only, based on the most severe outcome for any individual involved in the crash
  • Crash severity can be quantified using metrics such as the fatality rate (fatalities per 100 million VMT), the injury rate (injuries per 100 million VMT), or the severity index (a weighted average of crash severity levels)

Collision Diagrams and Countermeasures

• Collision diagrams are graphical representations of crash patterns at a specific location, providing a visual summary of the types, locations, and movements involved in crashes
  • They are typically created using a standard set of symbols and conventions to represent different crash types, vehicle movements, and contributing factors
  • Collision diagrams are useful for identifying high-risk locations, understanding the predominant crash patterns, and selecting appropriate countermeasures
• Crash modification factors (CMFs) are used to estimate the expected change in crash frequency or severity resulting from the implementation of a specific countermeasure
  • CMFs are derived from empirical studies that compare crash outcomes before and after the implementation of a countermeasure, while controlling for other factors that may influence safety performance
  • CMFs are expressed as a decimal value, with a value less than 1.0 indicating a reduction in crashes and a value greater than 1.0 indicating an increase in crashes
  • For example, a CMF of 0.8 for the installation of a roundabout at an intersection would indicate an expected 20% reduction in crashes compared to a conventional intersection design
• Engineering countermeasures for improving traffic safety can be broadly categorized as:
  • Geometric design improvements: Modifying the physical layout or