Objectives of determining and forecasting travel demand
Travel Demand Forecasting allows the engineer to predict the volume of traffic that will use a given transportation element in the future, whether that element is an existing highway or a potential light-rail route.
Like many other ‘predictive’ sciences, Travel Demand Forecasting is continually growing. Special refinements based on experience and researches are proposed each year, but the general ideology behind Travel Demand Forecasting has remained relatively untouched. The travel demand forecasting process can be confusing.
Objectives of determining and forecasting travel demand
Modern societies experience a growing demand for passenger and freight movement. Accurate forecasting of the total passenger and freight demand and the competitive (or substitutive) and complementary relationships among transport modes are necessary inputs in planning, designing, evaluating, and regulating transport and supply chain systems. Transport investment, especially investment in highway, rail, airport, and seaport infrastructure require long-term financial commitments, and the sunk costs can be very high if the investment projects fail to fulfill their design capacities. Therefore, accurate prediction of the long-term demand for using transport or some other public capital (e.g., water supply, electricity, fuel, information, and communication) infrastructure often forms an important part of the overall project appraisal. Also, the prediction of the transport demand and competition relationships can support the marketing and strategic planning of the transport firms, and the efforts for decoupling economic growth from transport intensity and promoting more energy-efficient and environment-friendly means of transport. From the perspective of firms, estimates of expected consumer demand constitute a crucial element in all scheduling and planning activities to improve business profitability. Thus, public transport operators and logistics firms have a major interest in developing and interpreting the results of accurate and reliable demand forecasting models.
Models
Generally, a four-step process is used for transportation planning analysis. This process has four phases. Don't use plagiarised sources.Get your custom essay just from $11/page
1: Trip Generation
2: Trip distribution
3: Mode choice
4: The trip assignment
Trip generation
Trip generation means how many trips are going to be made by the people of that area. This all depends on the factors like number and size of households, automobile ownership, and activity type (residential or commercial). What will be traffic density in that area. Trip generation rates are created by using a geographic unit called the transportation analysis zone (TAZ).
Trip distribution
Once a model has generated a certain number of trips from each TAZ, it needs to determine to which zone each trip goes. This is called trip distribution, and the analysis involves a sophisticated process for weighting the “attractiveness” of each TAZ based on the number of attractions it has and the travel time from other TAZs. This step leads to a picture of origin and destination points within the region and how many trips are going between each pair of TAZs.
Mode choice
This shows what people used to travel from one to another place like people are using local transport for going to their workplace, or they are using their cars for this purpose is. A sub-model system is present to determine the mode choice, which helps to understand how many people are using their car and how many people are traveling by bus.
Trip assignment
This model determines what route people are using to reach their destination. Generally, people choose the shortest or quickest route to reach their destination. For measuring route selection, all kinds of information regarding actual or predicted congestion levels, road conditions, transit schedules, and fares, traffic signal systems, is required.
These models are helpful for decision-makers to make transportation planning decisions. The result from each model varies depending on the ideas and information used and the sophistication of the particular model. Small models generally provide users with forecasted highway volumes for roadways with functional classes of minor arterial and above. Large model regions generally provide users with everything included in small models and transit forecasts. Some more sophisticated models also provide users with information on truck forecasts, college/university travel, HOV travel, and the effects of toll strategies on travel behavior.