Transportation Planning and Modeling Principles

Posted on Jun 21, 2024 in Other subjects

Trip-End Models

Applied prior to trip distribution, these models work better for cases where there’s no modal competition and no traffic congestion. They cannot include modal level of service attributes (travel time, cost, etc.) since no origin-destination (O-D) flows exist.

Trip-Interchange Models

Applied after trip distribution, these models split O-D flows computed by the trip distribution model. Since O-D demand is known, travel times and costs for competing modes can be computed. These models are applicable to medium and large urban areas and are sensitive to travel time.

Random Utility Theory

This theory assumes people are rational and will choose the alternative that maximizes their utility for a given trip. Utility (Uit) is composed of a systematic component (Vit(systematic)) and a random component (eit(random)).

Uit = Vit(systematic) + eit(random)

Because utility is random, we cannot say with certainty which alternative will be chosen.

Utility Functions

Factors like cost, in-vehicle travel time (IVTT), and out-of-vehicle travel time (OVTT) are generic variables that enter all utility functions with the same parameter values. Alternative-specific constants exist for driving and passenger modes but not for transit. If there are M alternatives, we can only statistically identify M-1 alternative-specific constants.

Direct Elasticity

Direct elasticity refers to the effect of the change of variables directly related to a good on the demand for the same good.

Cross Elasticity

Cross elasticity refers to the effect of the change of variables related to a good on the demand for another good.

Forecasting Mode Choice

These models generate predictions of choice probabilities for individuals using methods such as:

  1. Total enumeration
  2. Sample enumeration
  3. Naive aggregation
  4. Classification with N Aggregation

Aggregation Bias

Consider a scenario where people are identical except for income, and the probability of a person using transit depends only on their income. In this case, aggregation bias (z1) occurs. The more heterogeneous the population, the greater the bias.

Topic 7: Trip Assignments – Choice of Routes

This section addresses three key issues related to route choice:

  1. Differences in Perceptions: Individual perceptions of the best route vary, leading to diverse route choices. This is handled through multiple user classes and generalized costs.
  2. Level of Knowledge: Varying levels of knowledge about alternative routes introduce irrationality in route choice. This is addressed through stochastic effects.
  3. Congestion Effects: Congestion impacts shorter routes first, making their generalized costs comparable to initially less attractive routes. This is addressed through congested assignment and equilibrium.

The concepts of fixed costs (non-congestion) versus variable costs (congestion effects) are also discussed. Volume-Delay Functions, including the Bureau of Public Roads (BPR) function and tangent function, are used to model these effects. The tangent function converges more quickly and provides more realistic results.

Static vs. Dynamic Assignment

  • Static assignment procedures assign trips to all links in the chosen path simultaneously.
  • Dynamic assignment procedures assign trips to each link sequentially, considering the travel time along each link. This approach is more realistic but complex.

Deterministic vs. Stochastic Assignment

  • Deterministic assignment assumes travelers know travel times and make optimal route choices. This approach is simpler, more efficient, and suitable for congested networks where the penalty for choosing a non-optimal route is high.
  • Stochastic assignment acknowledges that travel times are not always known and travelers are not perfect optimizers. This approach is more suitable for lightly congested networks.

Wardrop’s Rules: System Optimization

Wardrop’s first principle aims to minimize total travel time (sum V1Svi). While suitable for freight applications, it doesn’t accurately describe human route choice behavior.

User Equilibrium (UE)

UE is achieved when every traveler uses the best possible route. Volume-Delay Functions (VDF) for links 1 and 2 illustrate this concept.

Topic 8: Institutional Barriers

This section explores various institutional barriers hindering transportation planning:

Organizational Barriers

  • Separate federal and provincial modal authorities
  • Overly prescriptive federal regulations
  • Provincial laws limiting flexibility

Inter-jurisdictional Barriers

  • Reluctance to share power and authority
  • Hesitation to form partnerships
  • Mobility solutions overshadowing mobility needs
  • Poor integration of land use

Resource Barriers

  • Funding shortfalls
  • Lack of evidence/data
  • Absence of comprehensive evaluation tools for comparing mobility projects

Strategies to Overcome Barriers

  1. Inclusive partnerships
  2. Expanded public involvement
  3. Clear project financing identification
  4. Emphasis on evidence-based planning
  5. Focus on system performance optimization
  6. Formal power-sharing among transportation agencies

Models of Decision-Making

  1. Rational actor
  2. Satisficing
  3. Incremental
  4. Organizational process
  5. Political bargaining

The role of planning is to inform the decision-making process by providing credible, understandable, and timely information about available alternatives, trade-offs, and consequences.

Key Transportation Stakeholders

  • Local NGOs: Moving the Economy, Center for Sustainable Transportation, Network of Excellence in Sustainable Transportation, Toronto Atmospheric Fund, GTA Forum
  • International Groups: ASCE, UK Transportation Research Lab
  • Canadian Groups: ITS Canada, Canadian Institute of Planners, Transportation Association of Canada
  • Private Sector: CN, CP, Air Canada, 407/ETR

Topic 9: Values, Goals, Objectives, and Measures of Effectiveness (MOEs)

  • Values: Basic social drives governing human behavior.
  • Goals: Generalized statements connecting the physical environment to values, but without specific tests of fulfillment.
  • Objectives: Specific, measurable statements related to achieving goals.
  • MOEs: Measures of the degree of attainment of particular objectives.

Criteria for Goals and Objectives

  • Objectives must logically follow from goals.
  • Each objective must be measurable by at least one MOE.
  • Goals and objectives must be independent of specific plans and modes.

Criteria for MOEs

  • Unbiased
  • Manageable
  • Sensitive to policies of interest
  • Able to differentiate impacts by interest group

Elements of a Transportation Vision for Toronto

  1. Public transit service that is more competitive with the private automobile.
  2. Efficient goods movement that enhances economic competitiveness.
  3. Reduced need to own or use an automobile.
  4. Protection of the natural environment.

Topic 10: Evaluation

Basis of Evaluation

  • Equity
  • Efficiency
  • Feasibility
  • Adequacy
  • Sensitivity analysis

Steps in Evaluation

  1. Defining
  2. Estimating
  3. Comparing
  4. Understanding

Approaches to Deal with Uncertainty

  • Assume a project’s useful life is less than its economic life.
  • Use scenario planning approaches.
  • Undertake sensitivity analyses of important variables.
  • Build flexibility into the design of the system or facility.